Identification and characterization of

aryl hydrocarbon receptor (AHR) as a suppressor

of non-small-cell lung cancer metastasis

Inaugural-Dissertation

zur

Erlangung des Doktorgrades

Dr. rer. nat.

der Fakultät für Biologie

an der Universität Duisburg-Essen

vorgelegt von

Silke Nothdurft

aus Aschaffenburg

Oktober 2019

Die der vorliegenden Arbeit zugrunde liegenden Experimente wurden im Labor für

Molekulare Onkologie der Inneren Klinik (Tumorforschung) am Universitätsklinikum

Essen durchgeführt.

1. Gutachter: Prof. Dr. med. Martin Schuler

2. Gutachter: Prof. Dr. rer. nat. Markus Kaiser

3. Gutachter: Prof. Dr. med. Guido Reifenberger

Vorsitzender des Prüfungsausschusses: Prof. Dr. rer. nat. Ralf Küppers

Tag der mündlichen Prüfung: 23.03.2020

Diese Dissertation wird via DuEPublico, dem Dokumenten- und Publikationsserver derUniversität Duisburg-Essen, zur Verfügung gestellt und liegt auch als Print-Version vor.

DOI:URN:

10.17185/duepublico/71562urn:nbn:de:hbz:464-20210817-104321-6

Alle Rechte vorbehalten.

3

Table of contents

A part of the results in this thesis have been included

in a manuscript to be submitted for publication.

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Table of contents

TABLE OF CONTENTS

Table of contents ........................................................................................................... 4

1 Abstract ...................................................................................................................... 8

1.1 English .................................................................................................................. 8

1.2 German ................................................................................................................. 9

2 Introduction ............................................................................................................. 11

2.1 Lung cancer: clinical features and treatment options .......................................... 11

2.1.1 Staging and survival rates ...................................................................... 11

2.1.2 Current treatment modalities .................................................................. 12

2.2 Factors governing cancer metastasis and the role of the epithelial-mesenchymal

transition (EMT) ......................................................................................................... 16

2.2.1 Transitions between epithelial and mesenchymal phenotypes (EMT/MET)

............................................................................................................... 19

2.2.2 Emerging roles of the microenvironment in cancer metastasis .............. 22

2.2.3 Metabolic dependencies and reprogramming ......................................... 23

2.3 Aryl hydrocarbon receptor: a sensor of xenobiotics and its potential role in tumor

progression ................................................................................................................ 24

3 Aim of the study ...................................................................................................... 25

4 Methods .................................................................................................................... 26

4.1 Cell Biology Methods .......................................................................................... 26

4.1.1 Cell culture ............................................................................................. 26

4.1.2 Freezing and thawing of cells ................................................................. 26

4.1.3 Spheroid formation assay ....................................................................... 26

4.2 Generation of stable transgenic cell models ....................................................... 26

4.2.1 Generation of lentiviral and retroviral particles ....................................... 26

4.2.2 Lentiviral and retroviral transduction of lung adenocarcinoma cell lines . 27

4.2.3 Small hairpin ribonucleic acid (shRNA)-mediated knockdown ................ 27

4.2.4 Reintroduction of shRNA-resistant AHR into AHR knockdown cell lines 28

4.3 siRNA mediated knockdown ............................................................................... 30

4.4 Proliferation assays ............................................................................................. 30

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4.5 Cell competition assay ........................................................................................ 30

4.6 Transwell migration invasion assay..................................................................... 31

4.7 T-HUVEC adhesion assay .................................................................................. 31

4.8 Biochemical methods .......................................................................................... 31

4.8.1 Preparation of whole cell extracts ........................................................... 31

4.8.2 Measurement of protein concentrations ................................................. 32

4.8.3 SDS-PAGE, protein transfer and staining............................................... 32

4.8.4 Gelatine zymography ............................................................................. 33

4.9 Molecular Biology Methods ................................................................................. 33

4.9.1 Plasmid isolation from bacterial cultures ................................................ 33

4.9.2 Transformation of competent bacteria .................................................... 33

4.9.3 Site-directed mutagenesis ...................................................................... 33

4.9.4 Agarose gel electrophoresis and gel extraction ...................................... 34

4.9.5 Restriction digest .................................................................................... 34

4.9.6 RNA isolation and cDNA synthesis ........................................................ 34

4.9.7 Quantitative real-time PCR (qRT-PCR) .................................................. 35

4.10 Flow cytometry .................................................................................................. 35

4.11 RNA-Sequencing .............................................................................................. 36

4.12 Gene set enrichment analysis (GSEA) ............................................................. 36

4.13 In vivo experiments ........................................................................................... 36

4.13.1 Orthotopic lung xenografts ..................................................................... 36

4.13.2 In vivo and ex vivo bioluminescence imaging ......................................... 37

4.13.3 In vivo shRNA screen using orthotopic lung cancer model..................... 37

4.13.4 In vivo stress assay ................................................................................ 38

4.14 Statistics ........................................................................................................... 38

5 Results ..................................................................................................................... 39

5.1 Unbiased shRNA screen in an orthotopic mouse model of lung cancer reveals

potential metastasis genes ........................................................................................ 39

5.2 Suppression of endogenous AHR increases metastatic potential of H1975 cells

in vitro ........................................................................................................................ 41

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5.3 Reconstitution of AHR expression by introduction of shAHR-resistant AHR in

H1975 AHR-knockdown cells partially reverses the pro-metastatic phenotype ......... 44

5.4 Depletion of AHR favors metastatic spread in vivo ............................................. 47

5.5 RNA sequencing experiment identifies candidate targets of AHR involved in

stress responses and metastasis .............................................................................. 49

5.5.1 AHR activation and expression negatively correlates with genes

associated with matrix remodeling and EMT .................................................... 54

5.5.2 AHR activation regulates cellular stress responses in H1975 ................ 56

5.5.3 ASNS and ATF4 are confirmed AHR targets in colorectal cancer cells .. 59

5.6 AHR is involved in metabolic reprogramming ..................................................... 60

5.7 In vivo stress assay ............................................................................................. 66

6 Discussion ............................................................................................................... 70

6.1 AHR as a suppressor of lung cancer metastasis ................................................ 70

6.2 Mechanistic insights to AHR-regulated metastatic pathways .............................. 72

6.3 AHR-regulated pathways as a target in anti-metastatic therapy of lung cancer .. 78

6.4 Conclusion and outlook ....................................................................................... 80

7 References ............................................................................................................... 81

8 Appendix ................................................................................................................ 101

8.1 Supplementary figures ...................................................................................... 101

8.2 Materials and reagents ...................................................................................... 102

8.2.1 Eukaryotic cell lines .............................................................................. 102

8.2.2 Plasmids and primers ........................................................................... 104

8.2.3 Antibodies ............................................................................................. 106

8.2.4 Commercial kits .................................................................................... 106

8.2.5 Chemicals ............................................................................................. 107

8.2.6 Media, reagents and commercial buffers ............................................. 108

8.2.7 Buffers and solutions ............................................................................ 109

8.2.8 Restriction enzymes and buffers .......................................................... 111

8.2.9 Consumables ....................................................................................... 111

8.2.10 Technical equipment ............................................................................ 112

8.2.11 Software ............................................................................................... 113

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8.3 List of figures ..................................................................................................... 113

8.4 List of tables ...................................................................................................... 115

8.5 List of abbreviations .......................................................................................... 116

9 Acknowledgements ............................................................................................... 120

10 Curriculum Vitae .................................................................................................... 122

11 Declarations ........................................................................................................... 124

8

Abstract

1 ABSTRACT

1.1 English

Lung cancer is the leading cause of cancer-related deaths worldwide. Lung cancer mor-

tality is mainly caused from metastatic progression. The majority of patients presents with

metastatic disease at primary diagnosis. In addition, a substantial fraction of patients

comes down with metastatic relapse despite potentially curative treatment of localized

disease. Lung cancers are histologically classified as small cell (SCLC) and non-small-

cell lung cancers (NSCLC). Adenocarcinomas and squamous cell carcinomas are the

largest subgroups of NSCLC. Current strategies to reduce the risk of metastatic relapse

in early stage NSCLC rely on adjuvant cisplatin-based chemotherapy and radiation though

having only modest activity. There are no therapeutic or preventive approaches

specifically tailored to modulation of metastasis. This is in part due to still limited

understanding of the metastatic process itself and the lack of defined molecular targets

for anti-metastatic interventions.

Against this background, we used an in vivo shRNA screening platform in an orthotopic

mouse model of lung cancer to identify candidate metastasis-modulators. Among these,

aryl hydrocarbon receptor (AHR), a ligand-regulated transcription factor and sensor of

xenobiotics, was prioritized and subjected to functional and mechanistic validation in this

thesis.

In the NCI-H1975 lung adenocarcinoma model, shRNA-mediated suppression of AHR

expression increased metastatic potential in vitro and promoted metastases formation in

an orthotopic lung cancer model in vivo. Importantly, low intratumoral AHR expression

correlated with inferior survival and decreased time to progression in patients with locally

or locally advanced lung cancer. Analysis of constitutive and AHR-ligand activated RNA

expression profiles revealed a negative correlation of AHR expression and EMT signa-

tures including several genes encoding matrix-metalloproteases. Activation of AHR by its

ligand omeprazole induced expression of ASNS and ATF4, both encoding gene products

that are involved in the cellular stress response. Interestingly, ASNS induction was ATF4-

dependent and attenuated in AHR-deficient NCI-H1975 exhibiting increased metastatic

9

Abstract

potential. Moreover, AHR knockdown conferred increased resistance to glutamine-

depleted growth conditions.

These findings identify AHR and AHR-regulated pathways as promising targets for

rational anti-metastatic interventions in NSCLC.

1.2 German

Lungenkarzinome sind weltweit die Hauptursache der Krebs-assoziierten Todesfälle. Die

hohe Mortalität bei Lungenkrebs wird hauptsächlich durch metastasierendes Fortschrei-

ten der Krankheit verursacht. Die Mehrheit der Patienten weist bei der Erstdiagnose

bereits ein Krankheitsstadium mit ausgebildeten Metastasen auf. Des Weiteren erleidet

ein erheblicher Teil der Patienten mit lokalisiertem Tumor trotz potenziell kurativer

Behandlung ein Rezidiv durch das Auftreten von Metastasen. Histologisch wird

Lungenkrebs in das kleinzellige (SCLC) und das nicht-kleinzellige Lungenkarzinom

(NSCLC) eingeteilt. Adenokarzinome und Plattenepithelkarzinome sind die größten

Untergruppen des NSCLC. Gegenwärtige Strategien, um das Risiko eines Rezidivs durch

Metastasierung bei Patienten in einem frühem Krankheitsstadium zu verringern, beruhen

auf adjuvanter Cisplatin-basierter Chemotherapie und Strahlentherapie, welche

dahingehend aber nur moderate Wirksamkeit aufweisen. Es gibt keine therapeutischen

oder präventiven Ansätze, die speziell auf die Modulation der Metastasierung abzielen.

Dies ist teilweise auf das noch immer eingeschränkte Verständnis des

Metastasierungsprozesses sowie das Fehlen von spezifischen molekularen

Ansatzpunkten für anti-metastatische Interventionen zurückzuführen.

Vor diesem Hintergrund haben wir eine in vivo shRNA-Screening-Plattform in einem

orthotopen Mausmodell des Lungenkarzinoms genutzt, um potentielle Metastasierungs-

modulatoren zu identifizieren. Von diesen wurde der Aryl-Hydrocarbon-Rezeptor (AHR),

ein Liganden-regulierter Transkriptionsfaktor und Sensor von Xenobiotika, priorisiert und

im Zuge dieser Arbeit einer funktionellen und mechanistischen Validierung unterzogen.

In dem Lungenadenokarzinom-Modell NCI-H1975 erhöhte die shRNA-vermittelte

Suppression der AHR-Expression das Metastasierungspotential in vitro und förderte die

Metastasenbildung in einem orthotopen Lungenkrebs-Modell in vivo. Bei Patienten mit

lokalem oder lokal fortgeschrittenem Lungenkrebs korreliert eine niedrige

10

Abstract

AHR-Expression im Tumorgewebe mit einer verkürzten Zeit bis zur Progression. Die Ana-

lyse von konstitutiven und AHR-Liganden-aktivierten RNA-Expressionsprofilen ergab eine

negative Korrelation zwischen AHR-Expression und EMT-Gensignaturen. Darunter

befanden sich mehrere Gene, die für Matrix-Metalloproteasen kodieren. Die Aktivierung

von AHR durch seinen Liganden Omeprazol induzierte die Expression von ASNS und

ATF4, welche für Genprodukte codieren, die an der zellulären Stressantwort beteiligt sind.

Interessanterweise war die ASNS-Induktion abhängig von ATF4 und war in AHR-

defizienten NCI-H1975, die ein erhöhtes metastatisches Potential aufwiesen, vermindert.

Darüber hinaus vermittelte die Herabregulation von AHR eine erhöhte Resistenz

hinsichtlich Wachstum unter Glutaminentzug.

Diese Ergebnisse identifizieren AHR und AHR-regulierte Signalwege als vielverspre-

chende Ansatzpunkte für zielgerichtete, anti-metastatische Interventionen bei NSCLC.

11

Introduction

2 INTRODUCTION

2.1 Lung cancer: clinical features and treatment options

Lung cancer is the most commonly diagnosed cancer type worldwide and leading cause

of cancer-related deaths accounting for 1.8 million deaths estimated in 2018 (American

Cancer Society 2019, Bray et al. 2018). Besides smoking being the main risk factor for

lung cancer, several other causal components including asbestos, radon and genetic pre-

disposition have been described (Field et al. 2000 , Hodgson, Darnton 2000 , Matakidou

et al. 2005, McGuire 2016). As more than 80 % of lung cancer cases in Western

populations are attributed to smoking, prevention of cigarette smoke exposure is of utmost

importance (Bray et al. 2018 , Goeckenjan et al. 2011). Nevertheless, never smokers

should not be neglected. Further, inhalation of environmental pollutants such as

carcinogenic particles, volatile substances and xenobiotic chemicals is much more

challenging to avoid and its role in lung cancer prevention is less understood.

Based on histological and clinical characteristics, lung cancer is divided into small-cell

lung cancer (SCLC) and non-small-cell lung cancer (NSCLC). With approximately 85 %,

the majority of lung cancer patients is diagnosed with NSCLC, which comprises adeno-

carcinoma, squamous carcinoma, large cell carcinoma, mixed types and lung cancer not

otherwise specified. Adenocarcinomas are the most common form of lung cancer

amounting approximately 50 % of all cases (American Cancer Society 2019 , Zappa,

Mousa 2016).

2.1.1 Staging and survival rates

Anatomical staging of lung cancer is based on the size and invasion of neighboring struc-

tures of the primary tumor, lymph node involvement and distant metastasis. This is sum-

marized by the TNM staging system, which determines assignment to four UICC/IASCL

stages (Detterbeck et al. 2017). Stage I comprises locally (IA) and locally advanced

tumors (IB) with lymph nodes being unaffected. In stages II and III patients show large

and/or locally invasive primary tumors, ipsilateral lung metastases and/or local and medi-

astinal lymph node metastases. Stage IV is defined by the occurrence of distant metasta-

ses either in the contralateral lung, pleura or single extrathoracic site (IVA) or multiple

metastatic sites (IVB). Importantly, both clinical prognosis and treatment decisions are

12

Introduction

highly dependent on the stage at diagnosis (American Cancer Society 2019 , Detterbeck

et al. 2017, Goeckenjan et al. 2011 , Zappa, Mousa 2016).

Today, lung cancer is still among the cancer types with the lowest survival rates with an

estimated 5-year survival rate of 18 % for all stages. In NSCLC, 5-year survival estimates

show immense differences with regard to TNM staging ranging from 73 % in stage IA to

13 % in stage IV (American Cancer Society 2019 , Woodard et al. 2016). Despite improve-

ment of clinical detection methods, the majority of patients (about 40 %) is diagnosed with

stage IV lung cancer and therefore facing a very poor prognosis. Approximately 16 % of

lung cancers are detected at a non-metastatic stage (IA and IB) with a 5-year survival rate

of 56 % (American Cancer Society 2019 , Zappa, Mousa 2016). Further, screening by low-

dose computed tomography (CT) scanning has recently led to improved outcomes in high-

risk populations due to early detection of lung cancers. Its implementation effectively pre-

vented deaths in high-risk populations (Aberle et al. 2011). Therefore, increasing numbers

of lung cancer patients with localized disease are expected from national screening pro-

grams using this technology. Hence, there is a high need in developing treatment options

effectively reducing the risk of metastasis in this patient group to improve clinical

outcomes.

2.1.2 Current treatment modalities

In early stages of NSCLC (I, II and IIIA), patients amenable to surgery usually undergo

surgical resection of tumors and systemic lymph node dissection. For stages II and III,

adjuvant therapy including chemotherapy and in case of mediastinal lymph node involve-

ment radiotherapy aims to reduce the risk of lung cancer relapse (Zappa, Mousa 2016).

For patients with inoperable tumors or refusing surgery, radiation or combined chemo-

radiotherapy is currently the recommended treatment option (Lemjabbar-Alaoui

et al. 2015). In advanced NSCLC, including stage III patients with severe comorbidities

and stage IV patients, the standard of care is palliative treatment with systemic

chemotherapy and local radiotherapy (Goeckenjan et al. 2011 , Ramalingam,

Belani 2008). More recently, chemotherapy is combined with antibodies targeting the

programmed cell death-1 (PD-1) and programmed cell death ligand-1 (PD-L1) immune

checkpoint molecules (Zappa, Mousa 2016). Moreover, genomically defined subgroups

of stage IV NSCLC receive targeted therapies with small molecules inhibiting oncogenic

13

Introduction

kinases, such as epidermal growth factor receptor (EGFR), anaplastic lymphoma kinase

(ALK), proto-oncogene tyrosine-protein kinase ROS (ROS1), serine/threonine-protein

kinase B-raf (BRAF), proto-oncogene tyrosine-protein kinase receptor Ret (RET),

neurothrophic tropomyosin receptor kinases (NTRK) or hepatocyte growth factor receptor

(Boolell et al. 2015, The Cancer Genome Atlas Research Network 2014).

Radiotherapy is applied to a large part of lung cancer patients upon their treatment course

either as first-line therapy or combination therapy in adjuvant, neoadjuvant or palliative

settings (Goeckenjan et al. 2011, Mohiuddin, Choi 2005). In general, radiotherapy applies

high-energy radiation to induce cell death in tumor cells by directly damaging the deoxy-

ribonucleic acid (DNA) and by indirect effects conferred by free radicals deriving from

ionization (Baskar et al. 2012 , Baskar et al. 2014). During conventional radiotherapy,

fractionated regimes are used to deliver the highest possible dose while limiting

detrimental effects to adjacent non-tumorous tissue (Baskar et al. 2014). Optimal dosing

and scheduling have been intensively studied and are depending on disease stage and

the physical condition of the patient (Goeckenjan et al. 2011 , Lindblom et al. 2015 , Roach

et al. 2018, Saunders et al. 1999). Improvement in imaging modalities and implementation

of software-supported approaches such as intensity modulated radiation therapy (IMRT)

or cone-beam computed tomography (CBCT) has highly improved localized application of

radiation (Baskar et al. 2012 , Jaksic et al. 2018 , Wang-Chesebro et al. 2006). In non-

resected early stage NSCLC, stereotactic body radiation therapy (SBRT) has been shown

to confer superior survival benefits compared to conventionally fractionated radiation

therapy (CFRT) (Abel et al. 2019 , Baumann et al. 2009 , Nyman et al. 2006) and suggested

to result in potentially comparable clinical outcomes as after resection (Chang et al. 2015 ,

Onishi et al. 2011). Radiosensitizers such as platin-based chemotherapy are commonly

applied in combination with radiation to improve treatment effects by sensitizing the tumor

(Sause et al. 1995 , Schaake-Koning et al. 1992). More recently, the integration of targeted

approaches in radiotherapy has been subject to intense research aiming to further

increase radiation efficacy and precision (Dumont et al. 2009 , Wang et al. 2017 , Zhuang

et al. 2014).

In the past 15 years, identification of several oncogenic drivers including EGFR and ALK

has led to the development of targeted therapy approaches exploiting these molecular

14

Introduction

dependencies in respective patient subgroups (Boolell et al. 2015 , The Cancer Genome

Atlas Research Network 2014 , Zappa, Mousa 2016). The use of targeted therapies is

clinically active by inducing remission, delaying cancer progression, and improving sur-

vival (Camidge et al. 2012 , Maemondo et al. 2010 , Mok et al. 2009). Further, these drivers

or their mutational status were successfully used as biomarkers to predict therapy

responses of certain patient cohorts (Lynch et al. 2004 , Mok et al. 2009 , Paez et al. 2004).

One prime example routinely being used in treatment of lung cancer is EGFR. Activating

mutations in EGFR lead to uncontrolled cancer cell proliferation and survival and can be

detected in up to 10-15 % of NSCLC patients. Most commonly these are deletions in

exon 19 or a single point mutation giving rise to the L858R variant in exon 21 (Lynch

et al. 2004, Pao et al. 2004 , The Cancer Genome Atlas Research Network 2014 , Zappa,

Mousa 2016). Targeting of EGFR with tyrosine kinase inhibitors (TKIs) improves the clin-

ical outcome and quality of life also in late stage disease (Mok et al. 2009 , Zhou

et al. 2011). First generation TKIs, namely gefitinib and erlotinib, are small molecules

reversibly binding to EGFR and are approved for EGFR-mutated NSCLC stage IV patients

(Morgillo et al. 2016). Unfortunately, the majority of patients acquire resistance upon TKI

treatment leading to recurrent disease. The emergence of secondary resistance mutations

such as T790M occurring in about 60 % of NSCLC patients has further guided the devel-

opment of second and third generation TKIs (Balak et al. 2006 , Socinski et al. 2013 , Yu

et al. 2013). Afatinib, a second generation EGFR TKI covalently binding to EGFR, human

epidermal growth factor 2 (HER2) and 4 (HER4), significantly improved clinical outcome

compared to gefitinib and chemotherapy in EGFR-mutant patient cohorts (Park

et al. 2016, Sequist et al. 2013). Specifically designed to target mutant EGFR T790M, the

third-generation TKI osimertinib exhibited improved activity in T790M-positive NSCLC

patients progressing upon or after EGFR-TKI therapy (Cross et al. 2014). Further,

osimertinib demonstrated superior clinical outcomes and superior central nervous system

(CNS) efficacy as compared to chemotherapy (Mok et al. 2016) and to first generation

EGFR-TKIs (Soria et al. 2018). Despite being clinically effective, the absence of clinically

targetable oncogenic driver mutations in the majority of lung cancer patients limits the

applicability of tailored therapies to certain patient subgroups. Further, acquisition of

resistance commonly occurs along therapy leading to cancer recurrence or metastatic

15

Introduction

relapse also in initially responding patients (Balak et al. 2006, Morgillo et al. 2016 , Zappa,

Mousa 2016).

More recently, immunotherapy has been implemented in lung cancer treatment (reviewed

in (Zappa, Mousa 2016)). Here, different approaches are used to target immuno-

modulating mechanisms aiming to accelerate the immune system’s anti-tumor activity.

Previous approaches used cytokines such as interleukin-2 (IL-2) or interferon (IFN) to

systemically activate the host’s immune system with modest effect (reviewed in

(Berraondo et al. 2019)). For lung cancer, immunostimulating cytokines failed to

consistently improve clinical outcomes while causing partially severe side effects (Ridolfi

et al. 2011, Yang et al. 2016). Recently developed strategies comprise the blockade of

tumor-mediated immune suppression and thereby enhancing immunosurveillance of the

tumor. Here, the inhibition of immune checkpoints by monoclonal antibodies has shown

promising results (Pardoll 2012 , Zappa, Mousa 2016). Mechanistically, tumor cells are

able to avoid immune clearance by expressing immune-suppressive surface markers

such as PD-L1. Binding of PD-L1 to PD-1 expressed on T-cells leads to suppression of

T-cell proliferation and activity (Keir et al. 2006 , Santini, Hellmann 2018 , Yang et al. 2016).

This negative feedback can be abrogated by antibody-mediated blockade of the

PD-1/PD-L1 interaction. In lung cancer, antibodies targeting PD-1 or PD-L1 were superior

to second-line chemotherapy (Borghaei et al. 2015 , Carbone et al. 2017 , Herbst

et al. 2016). In NSCLC patients with high PD-L1 expression, pembrolizumab alone was

more efficacious than platinum-based first-line chemotherapy (Reck et al. 2016). In

NSCLC patients with low or absent PD-L1 expression, anti-PD-1/PD-L1 antibodies are

combined with platinum-based chemotherapy (Gandhi et al. 2018 , Paz-Ares et al. 2018 ,

West et al. 2019).

Currently, two anti-PD-1 antibodies (nivolumab and pembrolizumab) and two anti-PD-L1

antibodies (atezolizumab and durvalumab) are globally approved for second-line treat-

ment of recurrent NSCLC (Lu, Su 2019). Further, combination treatment with anti-PD-1

and anti-CTLA4 (cytotoxic T-lymphocyte antigen-4) antibodies has been suggested to

increase clinical activity and improve survival rates (Hellmann et al. 2017 , Ready

et al. 2019). An additional field of research has led to the application of acellular or cellular

vaccines designed to prime tumor cells for tumor-associated antigens (TAA) which are

16

Introduction

currently under clinical investigation (García et al. 2008 , Gonzalez et al. 2003 , Lu,

Su 2019, Parikh et al. 2011 , Ramalingam et al. 2013 , Yang et al. 2013 , 2013, Yang

et al. 2016).

Despite improvement among NSCLC treatment modalities, metastatic relapse remains

the foremost cause of cancer-related death displaying a great challenge in the treatment

of lung cancer (Anderson et al. 2019 , Herbst et al. 2018 , Lambert et al. 2017). Intense

research on the mechanistic principles of cancer metastasis during the last decades could

not yet overcome the lack of therapies specifically targeting metastatic spread which

largely determines the clinical outcome of cancer patients. Although adjuvant chemo-

therapy (Arriagada et al. 2004 , Douillard et al. 2006 , Winton et al. 2005) or chemoradio-

therapy (Douillard et al. 2008 , Eberhardt et al. 2015) was shown to improve survival of

patients with localized lung cancer, curative treatments are not available for the majority

of NSCLC patients. Recently, durvalumab has been demonstrated to increase overall

survival and decrease the risk of metastatic progression in stage III NSCLC patients

treated with simultaneous radiochemotherapy (Antonia et al. 2018). However, its impact

in resected lung cancer has not yet been evaluated.

The development of anti-metastatic drugs has several obstacles to overcome due to the

complexity of the metastatic process, the biological difference of primary tumors and

metastatic cells and the translation of preclinical data into clinical application (Anderson

et al. 2019). Valid preclinical models and molecular dissection of metastasis are the

prerequisite for clinically active therapies capable of delaying or even preventing

metastatic progression.

2.2 Factors governing cancer metastasis and the role of the epithelial-

mesenchymal transition (EMT)

Cancer metastasis is a multistep cascade (Figure 1) including the invasion of cancer cells

from a locally growing primary tumor and dissemination via the circulatory system to form

secondary lesions at distant sites (Brabletz 2012 , Chaffer, Weinberg 2011 , Lambert

et al. 2017). Given the small proportion of disseminated tumor cells (DTCs) successfully

forming metastases, cancer metastasis can be considered a highly ineffective process

upon which many metastasizing cells die (Luzzi et al. 1998). Still, metastatic relapse

commonly occurs among all tumor types and remains the major challenge in the curative

17

Introduction

treatment of cancer patients (Anderson et al. 2019 , Lambert et al. 2017). However, the

biological obstacles that tumor cells have to overcome during metastasis might constitute

promising targets for anti-metastatic therapies (Anderson et al. 2019). Intensive research

in evaluating the biological and molecular mechanisms of cancer metastasis has led to a

better but still incomplete understanding of this complex process.

Figure 1: Overview of the metastatic cascade. The multistep process of cancer metastasis comprises tumor cell

invasion into the adjacent microenvironment to enable intravasation into blood or lymphatic vessels and transit of tumor cells through the circulation before extravasation in order to form metastasis. Tumor-derived factors secreted from the primary tumor lead to the formation of pre-metastatic niches which facilitate survival and growth of micrometastases at the secondary site which is required for metastatic colonization. Acquisition of dormant phenotypes in disseminated tumor cells or micrometastases enables escape from cell death. MDSC: myeoloid-derived suppressor cells (Anderson et al. 2019).

In the initial step of metastasis, primary tumor cells need to acquire an invasive phenotype

in order to locally invade the adjacent tumor microenvironment and to intravasate into

blood or lymphatic circulation (Chaffer, Weinberg 2011). Epithelial tumors such as adeno-

carcinomas are mainly consisting of highly differentiated cells with strong intercellular

junctions and are bordered by basement membranes (Brabletz 2012 , Chaffer,

18

Introduction

Weinberg 2011). Upon tumor progression, accumulation of genetic and epigenetic

alterations increase tumor heterogeneity which leads to locally invasive and metastatic

tumors characterized by increased dedifferentiation especially at the invasive front

(Brabletz 2012, Marusyk et al. 2012). Hallmarks of epithelial-mesenchymal transition

(EMT) including activation of EMT transcription factors (EMT-TF), notably Snail, Slug,

Twist and Zeb1, and loss of epithelial markers such as E-cadherin are commonly

associated with this dedifferentiation (Lambert et al. 2017 , Nieto et al. 2016 , Polyak,

Weinberg 2009). Furthermore, invasive tumor cells show increased secretion of matrix-

metalloproteases (MMPs) and thus induce the degradation of the surrounding

extracellular matrix (ECM) facilitating tumor cell invasion (Conlon, Murray 2019 , Radisky,

Radisky 2010). Certain MMPs including MMP2, MMP9 and MMP28 were implicated in

promotion of EMT pathways and phenotype (Illman et al. 2006 , Radisky, Radisky 2010).

Generally, induction of EMT or EMT-like processes is considered to be highly

advantageous for cancer cell invasion and dissemination (Chaffer, Weinberg 2011 ,

Lambert et al. 2017 , Spaderna et al. 2008). Mechanistically, mesenchymal-like cells show

increased invasiveness, anchorage-independent growth and stemness-like character-

istics, all of which support cancer metastasis (Guadamillas et al. 2011 , Mani et al. 2008 ,

Polyak, Weinberg 2009 , Singla et al. 2018). However, the necessity of EMT induction for

metastasis is recently controversially discussed as the importance of re-differentiation of

disseminated tumor cells by mesenchymal-epithelial transition (MET) is increasingly

recognized as a crucial step for outgrowth of metastatic lesions (Brabletz et al. 2018 ,

Chaffer et al. 2006 , Chu et al. 2013).

Traditional models of tumorigenesis claim metastatic spread to occur as a late event of

tumor progression, though there now has been experimental evidence demonstrating the

occurrence of early dissemination (Harper et al. 2016, Hüsemann et al. 2008 , Rhim

et al. 2012, Talmadge, Fidler 2010). Further, different forms of dissemination have been

described so far. Besides the classical view of single disseminating cells that have gained

invasive capacity and spread from the tumor, recent studies using intravital microscopy or

tumor spheroid models have demonstrated the collective migration of tumor cell clusters

(Friedl et al. 2012 , Konen et al. 2017 , Lambert et al. 2017).

19

Introduction

Notably, trans-endothelial migration (TEM) during intra- and extravasation requires the

tumor cells to endure mechanical deformation. Here, low cellular stiffness has been

suggested to be advantageous for metastatic cells (Cross et al. 2007 , Wirtz et al. 2011).

After entry into the circulation, immunogenicity as well as mechanical and oxidative stress

display major challenges for the survival of circulating tumor cells (CTCs) or multicellular

CTC clusters (Headley et al. 2016 , Lambert et al. 2017 , Wirtz et al. 2011). Importantly, the

generation of a viable metastatic niche is considered the critical if not rate-limiting step of

metastasis in order for the disseminated tumor cells to survive and regain proliferative

functions (Chambers et al. 1995 , Luzzi et al. 1998). As the microenvironment of the

secondary site is markedly different from the primary tumor site, the translocated tumor

cells have to substantially adapt to the new environment to allow for metastatic coloni-

zation (Anderson et al. 2019 , Lambert et al. 2017). Acquisition of temporary dormant

states are described to facilitate survival of DTCs until cellular pathways are sufficiently

remodeled to cope with the conditions at the secondary site (Lambert et al. 2017 , Senft,

Ronai 2016). Furthermore, dormancy of DTCs potentially explains the clinical occurrence

of metastatic relapse after a period of latency with no clinical manifestation of residual

disease (Meng et al. 2004 , Senft, Ronai 2016). Accumulating evidence suggests a com-

bination of EMT characteristics and stemness features as prerequisite for metastasis in a

concept of migrating cancer stem cells (Brabletz et al. 2005). Cancer stem cells (CSCs)

endow the ability to regain a proliferative state and give rise to differentiated cell types,

thus being qualified to represent the founders of metastatic colonies (Ayob,

Ramasamy 2018, Lambert et al. 2017 , Mani et al. 2008). However, preservation of a

mesenchymal cell state has been shown to limit tumor cell proliferation and thereby inhibit

metastatic colonization (Brabletz et al. 2001 , Tsai et al. 2012 , Vega et al. 2004). Thus,

re-differentiation via MET after dissemination is frequently observed in metastases that

recapitulate the main histological and genetic characteristics of the primary tumor at dif-

ferent secondary sites (Brabletz 2012, Liu et al. 2017 , Tsai et al. 2012).

2.2.1 Transitions between epithelial and mesenchymal phenotypes (EMT/MET)

EMT has first been described in physiological conditions occurring successively upon the

formation of embryonic layers and the generation of internal organs during embryonic

development (Acloque et al. 2009). During tumor progression, tumor cells appear to hijack

20

Introduction

parts of these transcriptomic programs to gain metastatic capacity (Brabletz et al. 2018 ,

Lambert et al. 2017 , Nieto et al. 2016). EMT and MET have therefore been object of

numerous investigations revealing molecular mediators and signaling pathways.

EMT can be induced by various external triggers including soluble factors, such as

transforming growth factor-β (TGF-β), hepatocyte growth factor (HGF), fibroblast growth

factor (FGF) as well as Wnt, Notch and hedgehog proteins (Thiery, Sleeman 2006 , Xiao,

He 2010). Furthermore, hypoxic conditions and interactions with components of the ECM,

such as collagen and hyaluronic acid, are described to induce EMT in cancer cells (Choi

et al. 2017, Yang et al. 2008 , Zoltan-Jones et al. 2003). Subsequent activation of signaling

cascades orchestrated by a network of EMT-TFs provoke alterations in proteins regulating

cell polarity, adhesion, cytoskeleton and ECM degradation (Polyak, Weinberg 2009 ,

Puisieux et al. 2014 , Thiery, Sleeman 2006). Generally, EMT activation leads to

decreased abundance of epithelial and increased abundance or activation of mesen-

chymal markers (Lee et al. 2006). Loss of E-cadherin as epithelial marker is regarded to

be crucial for EMT induction and commonly described to be downregulated during tumor

progression (Polyak, Weinberg 2009 , Puisieux et al. 2014 , Wirtz et al. 2011). However,

recent studies showed controversial results in which E-cadherin is required for the for-

mation of metastases (Chu et al. 2013). Still, loss in adhesion appears necessary for

adenocarcinoma cells in order to dissociate from the primary tumor (Cavallaro,

Christofori 2004, Nieto et al. 2016 , Puisieux et al. 2014). Several mesenchymal markers

including Zeb1, Zeb2, Snail, Slug, and Twist are either direct or indirect repressors of

E-cadherin (Polyak, Weinberg 2009). In many epithelial cancer types, loss of E-cadherin

is accompanied by induction of mesenchymal cadherins including N-cadherin and

cadherin-11 (Cavallaro, Christofori 2004). Moreover, β-catenin, usually part of adherens

junctions when binding cadherins, is translocating into the nucleus as a transcriptional co-

activator of EMT-related genes (Lee et al. 2006).

21

Introduction

Figure 2: Model of cellular plasticity through transitional EMT/MET states. During tumor progression, transition

between epithelial (E) and mesenchymal (M) phenotypes is considered as a continuum with several intermediate (EM) cell states. Upon transition, cells sequentially lose their polarity and cell-adhesions (TJ - tight junction, AJ - adherens junction, DS - desmosome). Several transcription factors (SNAI1/2, ZEB, TWIST1, GRHL2, OVOL1/2 and PRRX1), miRNAs and epigenetic factors have been described to be involved in a regulatory network conferring this phenotypic plasticity. The existence of stable and metastable EM states is predicted but not yet proven. ECM: extracellular matrix (Nieto et al. 2016).

During developmental programs, complete transitions from epithelial to mesenchymal cell

states occur, whereas cancer cells rather show transient and partial EMT upon metastatic

progression (Brabletz 2012 , Lambert et al. 2017). Multiple intermediate cell states

exhibiting some mesenchymal traits while retaining other epithelial features were demon-

strated to exist during the course of the metastatic cascade (Figure 2) (Lambert

et al. 2017, Nieto et al. 2016 , Pastushenko et al. 2018). Here, reciprocal feedback loops

between classical EMT-TFs and microRNAs (miRs) such as miR-200 as well as epi-

genetic regulations are suggested to allow for reversible and transient molecular changes

and phenotypic plasticity (Brabletz 2012, Nieto et al. 2016 , Wellner et al. 2009). Further,

this model of cellular plasticity is able to explain the switch to re-differentiation via MET in

order to form macrometastases (Chaffer et al. 2006 , Nieto et al. 2016).

Additionally, EMT-TFs are discussed to affect stemness, DNA repair and survival path-

ways, which are advantageous for metastatic cells by increasing therapy resistance and

cell survival (Brabletz et al. 2018 , Puisieux et al. 2014 , Shibue, Weinberg 2017).

22

Introduction

2.2.2 Emerging roles of the microenvironment in cancer metastasis

Recently, the tumor microenvironment (TME) has been increasingly recognized as an

important factor for cancer metastasis as well as a potential therapeutic target for the

suppression of metastatic progression (Altorki et al. 2019 , Anderson et al. 2019 , Hanahan,

Coussens 2012, Hanahan, Weinberg 2011 , 2011). Because of its close proximity and

reciprocal interaction with tumor and host cells, the TME highly influences the survival and

signaling pathways of tumor cells (Peng et al. 2017). Thus, the TME has been considered

as an emerging hallmark of cancer (Hanahan, Weinberg 2011).

A supportive microenvironment is both important for primary tumor growth and metastasis

to establish viable premalignant and metastatic niches (Zhang, Xiang 2019). This com-

prises recruitment of associated stromal cells, ECM remodeling including stimulation of

angiogenesis, induction of malignant features such as invasion and EMT, immuno-

suppression as well as alteration in metabolism (De Palma et al. 2017 , Hanahan,

Coussens 2012, Liu et al. 2014). In order to improve blood supply of the tumor, tumor cells

initiate secretion of vascular endothelial growth factor (VEGF) under hypoxic conditions

thus inducing angiogenesis by engaging VEGF receptor 2 (VEGFR2) on endothelial cells

(LaGory, Giaccia 2016 , Potente et al. 2011). Moreover, direct interaction of tumor cells

with ECM proteins such as collagen I via integrins leads to activation of internal signaling

pathways and has been demonstrated to promote tumor growth as well as establishment

of metastatic niches (Navab et al. 2016 , Peng et al. 2017 , Wu et al. 2019b). Further, the

development of pre-metastatic niches is suggested to occur even prior to tumor cell dis-

semination. Here, the microenvironment at prospective metastatic sites is actively modi-

fied by systemic secretion of regulating factors from the primary tumor (Liu et al. 2014 ,

Peinado et al. 2017, Zhang, Xiang 2019). Moreover, homing of disseminated cancer cells

appears in an organ-specific manner as many cancer types display preferred secondary

sites (Langley, Fidler 2011). Common metastatic sites for lung cancer are the contralateral

lung, lymph nodes, liver, adrenal glands, bones, and brain (Milovanovic et al. 2017).

Several therapeutic strategies targeting the tumor or metastatic microenvironment are

currently under clinical investigation. With regard to immunotherapy and angiogenesis,

various approaches have already been approved and implemented in cancer treatment

(Lu, Su 2019, Potente et al. 2011).

23

Introduction

2.2.3 Metabolic dependencies and reprogramming

Major remodeling of the primary metabolism in cancer cells has been defined as one of

the emerging cancer hallmarks (Hanahan, Weinberg 2011). During tumor initiation and

metastatic colonization, the survival and sustained proliferation of cancer cells at hypoxic

and nutrient-poor environments demand for alternative routes of nutrient supply. In the

absence of sufficient supply with metabolites, micro- and macropinocytosis of extracellular

proteins, entosis of living cells or phagocytosis of apoptotic bodies have been described

to fuel tumor cell metabolism (Krajcovic et al. 2013 , Pavlova, Thompson 2016 , Stolzing,

Grune 2004). Besides opportunistic routes of nutrient utilization, the rewiring of intrinsic

metabolic pathways leads to alterations in metabolite dependencies enabling uncontrolled

cell proliferation under limiting growth conditions (Hanahan, Weinberg 2011).

Glucose and glutamine are two principal nutrients supporting proliferation and bio-

synthesis of cells. Their catabolism provides cells with essential components including

carbon intermediates, source of reducing agents nicotinamide adenine dinucleotide

hydrogen (NADH) and flavin adenine dinucleotide dihydrogen (FADH2) as well as equiva-

lents such as adenosine triphosphate (ATP) (Pavlova, Thompson 2016). Various cancer

cells exhibit high levels of glycolysis also in presence of oxygen (aerobic glycolysis, also

termed Warburg effect) thus generating ATP at a lower efficiency compared to oxidative

phosphorylation on which normal cells rely for energy production (Fouad, Aanei 2017 ,

WARBURG 1956). Further, upregulation of glucose transporters such as GLUT1 has

been demonstrated in many cancer types as means to enhance cellular glucose uptake

(Gonzalez-Menendez et al. 2018 , Hanahan, Weinberg 2011). Glutamine is the most abun-

dant amino acid and constitutes not only a source of carbon but also of nitrogen for

de novo biosynthesis (Altman et al. 2016 , Pavlova, Thompson 2016). Due to the increased

catabolism in tumor cells, glutamine and glucose are commonly used as isotope-labeled

clinical tracers during tumor imaging and suggested as therapeutic target to exhaust tumor

metabolism (Almuhaideb et al. 2011 , Altman et al. 2016 , Hamanaka, Chandel 2012 ,

Lieberman et al. 2011 , Venneti et al. 2015). More recently, the availability of other amino

acids such as asparagine and aspartate has been controversially discussed to affect

tumor growth under limited nutrient and oxygen conditions (Garcia-Bermudez et al. 2018 ,

Pavlova et al. 2018 , Sullivan et al. 2018). Although much of metabolic reprogramming is

24

Introduction

considered cell intrinsic, increasing evidence indicates reciprocal feedback from the

microenvironment (Pavlova, Thompson 2016). Upon metastatic progression, DTCs need

to adapt their metabolic pathways according to the nutrient environment at a specific

metastatic site leading to altered metabolism also between primary tumor and metastases

(Christen et al. 2016 , Elia et al. 2018). Further, CTCs rely on antioxidant metabolism

during loss of adhesion and transit in circulation in order to circumvent reactive oxygen

species (ROS)-mediated cell death (Elia et al. 2018 , Hawk, Schafer 2018 , Piskounova

et al. 2015).

2.3 Aryl hydrocarbon receptor: a sensor of xenobiotics and its potential role in

tumor progression

Aryl hydrocarbon receptor (AHR) is a ligand-regulated transcription factor sensing xeno-

biotic and endogenous factors leading to the modulation of highly complex regulation pat-

terns (Esser et al. 2018 , Murray et al. 2014). Here, a variety of exogenous factors including

2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) and benzo[a]pyrene (BaP) as well as some

endogenous ligands such as kynurenine and indoxyl sulfate have been identified as acti-

vating ligands of AHR (Murray et al. 2014). Upon ligand binding, AHR translocates into

the nucleus, dissociates from its cytosolic complex and regulates target genes of xeno-

biotic responsive elements (XRE) upon heterodimerization with aryl hydrocarbon receptor

nuclear translocator (ARNT). In response to xenobiotic stimuli, AHR induces the transcrip-

tion of several cytochrome P450 (CYP) enzymes that are important in the metabolism and

bioactivation of carcinogens (Li et al. 1998 , Murray et al. 2014 , Whitlock 1999). Besides

its transcriptional activity, ligand-independent regulation of AHR was suggested to be

mediated by nucleo-cytoplasmatic shuttling in AHR high expressing cells (Chang

et al. 2007, Ikuta et al. 2000 , Murray et al. 2014).

As a transcription factor, AHR modulates a variety of physiological as well as pathological

pathways and processes (Esser et al. 2018 , Larigot et al. 2018). Important roles of AHR

in embryonic development and homeostasis of organs such as heart, liver and skin as

well as in the function of the immune system were demonstrated by the developmental

defects observed in transgenic mouse models (Fernandez-Salguero et al. 1997 , Schmidt

et al. 1996). However, AHR-deficient mice are viable and fertile. With regard to patho-

logical processes, AHR-mediated activity has been linked to response to environmental

25

Aim of the study

factors, autoimmunity, imbalance in metabolism and carcinogenesis (Esser et al. 2018 ,

Fingerhut et al. 1991 , Rothhammer, Quintana 2019 , Whitlock 1999).

First, AHR was discovered as the receptor of TCDD, a high-affinity ligand that mediated

immunosuppression and tumor promotion by sustained activation of its receptor (Knerr,

Schrenk 2006, Rothhammer, Quintana 2019). Further, pro-tumorigenic functions of AHR

were demonstrated in numerous other studies (D'Amato et al. 2015 , Murray et al. 2014 ,

Opitz et al. 2011). However, AHR displayed tumor and metastasis suppressive activity in

certain entities including Ewing sarcoma, neuroblastoma as well as lung and breast

cancer (Jin et al. 2014 , Mutz et al. 2016, Wu et al. 2019a). Hence, the controversial results

of AHR functions in tumor initiation and progression suggests a ligand- and tissue-specific

role that might be depending on disease stage.

3 AIM OF THE STUDY

This work was based on the hypothesis that a better understanding of the molecular

mechanisms of cancer metastasis will guide the development of treatment options specif-

ically targeting metastatic progression in lung cancer patients. In order to identify factors

crucial in the metastatic cascade, a shRNA screen in an orthotopic lung cancer mouse

model has been conducted in a collaborative project of our group and the group of

Dr. Trever G. Bivona at the Department of Medicine of the UCSF Cancer Center prior to

this work.

This thesis aimed to validate and characterize AHR as a putative metastasis-modulating

factor and identify novel insights into the metastatic process in lung cancer. NCI-H1975

cells with stable shRNA-mediated AHR suppression were generated to provide reliable

cell models to investigate the impact of AHR on the metastatic potential of adeno-

carcinomas. Those were used for validation of AHR as a suppressor of lung cancer

metastasis using the established orthotopic mouse model recapitulating the complete

metastatic cascade. Mechanistic studies of AHR-regulated pathways could then provide

promising targets to develop pharmacological strategies to prevent metastatic progres-

sion. Further, publicly available databases were mined to correlate the expression of AHR

with clinical outcomes in lung cancer patients.

26

Methods

4 METHODS

4.1 Cell Biology Methods

4.1.1 Cell culture

HEK293FT, Phoenix (FNX), SW480 and SW620 cells were cultivated in DMEM,

NCI-H1975 (hereinafter referred to as H1975), A549 and NCI-H1299 (hereinafter referred

to as H1299) cells in RMPI 1640, each supplemented with 10 % heat-inactivated FBS,

100 U/ml penicillin, 100 μg/ml streptomycin, and 2 mM L-glutamine, in a humidified

atmosphere at 37 °C and 5 % CO2. Passaging of cells was performed at 80-90 % conflu-

ency using 0.05 % trypsin-EDTA. Cells were discarded at passages higher than 30. If not

stated otherwise, cells were pelleted by centrifugation at room temperature (RT) and

300 x g for 5 min. Treatment with omeprazole (Sigma-Aldrich) was conducted for 48-72 h.

All cell lines were authenticated using short tandem repeat (STR) analysis and absence

of mycoplasma contamination was confirmed by regular testing.

4.1.2 Freezing and thawing of cells

All cell lines were frozen in early passages using FBS supplemented with 10 % DMSO

and stored short-term at -80 °C and long-term in liquid nitrogen. Frozen cells were shortly

thawed at 37 °C, centrifuged and transferred to culture dishes with warm culture medium.

Cells were passaged at least once after thawing before being used for experiments.

4.1.3 Spheroid formation assay

In order to initiate formation of spheroids, cells were seeded into commercially available

cell culture plates with cell-repellent surface. Spheroids were grown for up to 72 h and

pictures taken every 24 h using Primovert microscope (Zeiss).

4.2 Generation of stable transgenic cell models

Note that viral particles are handled at BSL-2.

4.2.1 Generation of lentiviral and retroviral particles

For generation of lentiviral particles, HEK293FT cells were transfected at 50 % confluency

in fibronectin-coated 10 cm dishes with lentiviral packaging plasmids pMD2, pSPAX and

the plasmid of interest (1.5, 3 and 3 µg, respectively) using FuGENE HD transfection

reagent (Promega) according to the manufacturer’s recommendations. Fresh medium

27

Methods

was added after 24 h and viral supernatants collected 72 h post transfection. Remaining

packaging cells were removed from the supernatants using 0.45 µm filters to avoid cross-

contamination. For generation of retroviral particles, FNX cells were transfected as

described above only that retroviral packaging plasmids Hit60 (MLV gag-pol) and

pCMV.VSV-G were used.

4.2.2 Lentiviral and retroviral transduction of lung adenocarcinoma cell lines

Human cell lines were infected with lentiviral or retroviral constructs by addition of viral

supernatant from packaging cells diluted 1:2 in culture medium and 1 µg/ml polybrene for

24 h. After 48 h, H1975 cells were selected with 0.5 µg/ml puromycin and A549 as well as

H1299 were selected with 1 µg/ml puromycin for 7 days. In the rescue approach, selection

of H1975 cell clones expressing shAHR or control shRNA (shScr) was carried out in the

presence of 1 mg/ml neomycin.

4.2.3 Small hairpin ribonucleic acid (shRNA)-mediated knockdown

Lentiviral shRNA targeting AHR (shAHR) and retroviral shRNAs targeting ASNS

(shASNS) were purchased as bacterial stocks from Sigma-Aldrich and OriGene,

respectively (Table 1). Plasmid DNA was prepared as described in chapter 4.9.1. Viral

supernatants were generated (4.2.1) and used to stably integrate shRNAs into human

adenocarcinoma cell lines by viral transduction (4.2.2).

Table 1: Sequences for shRNAs targeting AHR or ASNS.

target sequence (5’ - 3’)

lentiviral (pLKO.1 backbone)

non-mammalian

target (Scr)

CCGGCAACAAGATGAAGAGCACCAACTCGAGTTGGTGCTCT

TCATCTTGTTGTTTTT

AHR CCGGCGGCATAGAGACCGACTTAATCTCGAGATTAAGTCGG

TCTCTATGCCGTTTTT

retroviral (pGFP-V-RS backbone)

scrambled negative

control n/a

ASNS A) AAGGTCTTGTTACATTGAAGCACTCCGCG

B) ATTCGGAAGAACACAGATAGCGTGGTGAT

28

Methods

In order to enhance stability of target gene suppression, clonal cell lines were established

from the transgenic cell lines using limiting dilution after antibiotic selection. Briefly, cells

were seeded at 0.5 cells/well in a 96-well plate and proliferating colonies from single cells

were expanded for experiments and long-term storage in liquid nitrogen.

4.2.4 Reintroduction of shRNA-resistant AHR into AHR knockdown cell lines

In order to reconstitute AHR expression in the shAHR harboring H1975 cell lines, rescue

vectors encoding for shRNA-resistant AHR were established.

As the shRNA carrying cells were already puromycin resistant due to stable integration of

the pLKO.1-shRNA vector, a retroviral MSCV backbone mediating neomycin resistance

was chosen for rescue vector generation. MSCV-tdTomato-PGK-Neo was kindly provided

by Dr. Barbara M. Grüner, which was used by Dr. Sophie Kalmbach to generate a

tdTomate-truncated MSCV backbone (hereinafter referred to as MSCV vector).

The full-length coding sequence (CDS) of AHR was generated in a single polymerase

chain reaction (PCR) (Table 2) using high fidelity AccuPrime Polymerase (invitrogen)

according to the manufacturer’s guidelines. cDNA transcribed from 2 µg of RNA from

parental H1975 was diluted 1:5 and used as a template.

Table 2: PCR program for generation of full-length CDS of AHR.

procedure period [min] temperature [°C] # of cycles

initialization 2:00 95 1x

denaturation 0:15 95 35x

annealing 0:30 64

elongation 3:00 68

final elongation 2:00 68 1x

cooling ∞ 4 1x

Primers were designed to result in a PCR product consisting of the CDS of AHR flanked

by restriction sites for FspAI at the 5’ end and BglII at the 3’ end (Table 3).

29

Methods

Table 3: Primer sequences for cloning of rescue vector.

primer sequence (5’ - 3’)

AHR FspAI For ATTGTGCGCATCCACCATGAACAGCAGCAGCGCC

AHR BglII Rev CGGCGAGATCTCCGTTACAGGAATCCACTGGATGTCAA

After purification of the PCR product using PCR Purification Kit (Qiagen) according to the

manufacturer’s manual, the PCR product as well as the MSCV vector were digested with

FspAI and BglII restriction enzymes for 3 h at 37 °C (Table 4).

Table 4: Reaction mixes for restriction digest of MSCV backbone and AHR PCR product.

procedure MSCV PCR product

amount DNA 4 µg total amount from

purification

restriction

enzyme

15 U FspAI

20 U BglII

15 U FspAI

20 U BglII

10x O puffer 5 µl 5 µl

aqua ad 50 µl

DNA fragments of interest were separated using agarose gel electrophoresis and isolated

from the gel with QIAquick Gel Extraction Kit (Qiagen) according to the manufacturer’s

protocol (4.9.4). DNA was eluted in 30 µl A. dest.

Backbone and insert were used for ligation at a molar ratio of 1:6 using T4 DNA ligase

(New England Biolabs) overnight at 16 °C in a total volume of 10 µl. All steps were

conducted referring to the manufacturer’s recommendations.

Ligation products (3 µl of reaction mix) were introduced into One ShotTM Stbl3TM E. coli

(invitrogen) by transformation according to the manufacturer’s protocol. Integration of the

CDS of AHR into the MSCV backbone was confirmed by PCR and Sanger sequencing

(Microsynth Seqlab) using AHR Primers (Table 3). Plasmid DNA was isolated from bac-

terial cultures (4.9.1). Silent point mutations were introduced into the shRNA-binding site

of the CDS using site-directed mutagenesis (4.9.3) in order to confer resistance to shAHR.

30

Methods

The sequence of the resulting vector (AHR rescue vector) was again confirmed using

Sanger sequencing. Finally, the AHR rescue vector was introduced into H1975 expressing

shAHR (K1-K3) or shScr by retroviral transduction as described before (4.2.2). Further,

respective cell lines transduced with the empty MSCV vector were generated to serve as

controls.

4.3 siRNA mediated knockdown

Transient introduction of siRNA into adenocarcinoma cell lines was conducted using

Lipofectamine® RNAiMAX reagent (Thermo Fischer Scientific) according to the manufac-

turer’s protocol. 30 pmol and 150 pmol of siRNA were used for transfection of 6-well or

10 cm dish, respectively. During siRNA studies, treatment with omeprazole was started

24 h post transfection to ensure suppression of target mRNA at the time of treatment.

MISSION® esiRNA targeting human ATF4 as well as MISSION® siRNA Universal

Negative Control were purchased from Sigma-Aldrich.

4.4 Proliferation assays

Cell proliferation was analyzed using 3-(4,5-Dimethylthiazole-2-yl)-2,5-diphenyl-2H-

tetrazolium bromide (MTT) in 96-well plates after 48-72 h. Briefly, 10 µl of MTT solution

was added per well. After 4 h of incubation, cells were lysed with 100 µl MTT solubilization

buffer overnight. The absorption was measured with a spectrophotometer plate reader at

570-595 nm and at 655 nm as reference wavelength. For L-glutamine and serum

starvation studies, cells were directly seeded into different starvation media and incubated

for 72 h before addition of MTT. Omeprazole treatment was conducted by addition of

treatment as a twofold concentrated solution to cells seeded in culture medium 4 h before.

For all assays, 5 x 104 cells were seeded per well.

4.5 Cell competition assay

H1975 cells expressing AHR-specific or control shRNAs were mixed in equal ratios and

co-cultivated in culture medium with or without addition of L-glutamine. H1975 shScr

control cells or H1975 shAHR-K2 expressing green fluorescent protein (GFP) were mixed

with their non-labeled counterparts and vice versa. The proportion of fluorescent cells in

the cell mixtures was determined by flow cytometry at the day of seeding and after two

weeks of culture. Cells were passaged every 3-5 days.

31

Methods

4.6 Transwell migration invasion assay

The transwell migration invasion assay was conducted using BioCoatTM GFR Matrigel and

control inserts for 24-well plate (Corning) according to the manufacturer’s protocol. Briefly,

cells were seeded at 6 x 105 on 10 cm dishes. The next day, cells were starved with low-

serum (0.5 % FBS) medium for 4 h and then seeded at 1.5 x 104 cells/insert using low-

serum medium. Full-serum (10 % FBS) medium was added to the lower compartment to

serve as chemoattractant. Cells were incubated for 24 h in a humidified incubator at 37 °C

and 5 % CO2. After mechanical removal of cells remaining on the apical side of inserts,

migrated/invaded cells were fixed with 70 % ethanol and stained using 0.1 % crystal violet

solution. Membranes were then cut from the inserts and embedded with entellan. Four

representative pictures were taken per insert using the BIOREVO BZ-9000 microscope

(Keyence). The mean cell number of triplicates was used to calculate the number of

migrated or invaded cell as well as the relative invasion as described in the manual for the

transwell inserts.

4.7 T-HUVEC adhesion assay

hTERT-immortalized HUVEC (human umbilicial vein endothelial cells, hereinafter referred

to as T-HUVECs) were kindly provided by Dr. Barbara M. Grüner and seeded in 24-well

plates to form confluent monolayers. H1975 cells expressing AHR-specific or control

shRNAs were treated with omeprazole or DMSO for 48 h. Treated cells were harvested

using trypsin, washed twice with PBS and resuspended in culture medium. Cell suspen-

sions with 5 x 105 cells/ml were prepared for each treatment group and 5 x 104 cells/well

added to T-HUVECs in duplicates. After incubation for 20 min with agitation, unbound

cells were washed off with PBS twice before remaining cells were harvested and analyzed

by flow cytometry for proportion of GFP-positive (GFP+) cells.

4.8 Biochemical methods

4.8.1 Preparation of whole cell extracts

According to the cellular localization of the target protein, NP40 or RIPA lysis buffer were

applied for cell lysis. RIPA buffer was used for mainly nuclear localized and membrane

proteins whereas NP40 buffer was used for cytosolic proteins.

32

Methods

Cells were harvested using trypsin followed by washing with PBS. Cell pellets were

resuspended in appropriate volumes of cold lysis buffer supplemented with cOmplete

protease inhibitor cocktail (Roche) and phosphatase inhibitors cocktails 2 and 3 (Sigma-

Aldrich). For treatment studies and detection of phosphorylated proteins, cells were

directly scraped off the culture dish on ice after washing with PBS and addition of cold

supplemented lysis buffer. Cell lysis was carried out for 20 min on ice with regular

vortexing. Finally, lysates were snap frozen with liquid nitrogen, thawed on ice and cleared

of cell debris by centrifugation at 18,400 x g at 4 °C for 10 min. Total protein

concentrations were determined as described in 4.8.2 and protein extracts were stored

at -80 °C.

4.8.2 Measurement of protein concentrations

For all protein extracts, total protein concentrations were determined using Bio-Rad

Protein Assay Dye Reagent Concentrate (Bio-Rad). Briefly, Bradford reagent was diluted

1:5 in A. dest and samples were added at a ratio of 1:500. Absorbance was detected at a

wavelength of 595 nm using the Gene Quant Photometer (Amersham). Protein concen-

tration was determined by comparison to a blank value with lysis buffer as reference.

4.8.3 SDS-PAGE, protein transfer and staining

Equal amounts of proteins (range = 20-50 µg) were supplemented with 5X SDS-PAGE

loading buffer, denatured at 95 °C for 5 min and separated at 95-110 V using the Mini-

PROTEAN electrophoresis system (Bio-Rad). Proteins were transferred to nitrocellulose

membranes with the Trans-Blot® TurboTM system (Bio-Rad) and Mini Nitrocellulose

Transfer Kit (Bio-Rad). Membranes were incubated in blocking buffer for at least 1 h and

blotted with primary antibodies overnight at 4 °C (Table 10). After incubation with horse-

radish peroxidase (HRP)-conjugated secondary antibodies (Pierce Antibodies, 1:4000) for

1-3 h at RT, signals were detected with the Super Signal West Pico/Femto system

(Thermo Fisher Scientific) on the ChemiSmart Imaging System (VILBER LOURMAT

Deutschland GmbH). For reprobing with different antibodies, membranes were incubated

in Restore™ Western Blot Stripping Buffer (Thermo Fisher Scientific) according to the

manufacturer’s protocol to remove primary and secondary antibodies prior to blocking and

blotting with the next antibody.

33

Methods

4.8.4 Gelatine zymography

Gelatine zymography to assess activity of MMP2 and MMP9 was adapted from Kleiner

and Stetler-Stevenson (Kleiner, Stetler-Stevenson 1994). Briefly, cells were seeded at

3.5 x 105 in 6-well plates. After adhesion of the cells to the surface, culture medium was

replaced by medium containing 0.5 % FBS. Conditioned medium (CM) was harvested

after 16 h of incubation and centrifuged to remove floating cells. Equal volumes of CM

were supplemented with 5X non-reducing zymography sample buffer, incubated for

15 min at RT and subjected to separation by SDS-PAGE (4.8.3). Subsequently, gels were

successively incubated for 1 h each in 2.5 % triton X-100 and zymography enzyme buffer.

Fresh enzyme buffer was added before the gels were incubated 18-48 h at 37 °C in an

incubator under atmospheric conditions. Staining with 0.5 % coomassie blue in 30 %

methanol and 10 % acetic acid for 1 h and destaining with 30 % methanol and 10 % acetic

acid for 0.5 h plus 1 h were conducted at RT on a rotary shaker. Areas of digestion

displayed as non-stained bands.

4.9 Molecular Biology Methods

4.9.1 Plasmid isolation from bacterial cultures

Bacterial glycerol stocks or bacterial colonies from agar plates were used to inoculate

bacterial cultures in Circlegrow® medium containing 50 µg/ml ampicillin or 25 µl/ml

kanamycin. Bacterial cultures were grown at 37 °C and 225 rpm overnight. For viral

packaging plasmids temperature was reduced to 32 °C. Plasmid DNA from bacteria was

isolated with QIAGEN Plasmid Plus Maxi Kit (Qiagen) or QIAprep Spin Miniprep Kit

(Qiagen) according to the manufacturer’s protocol. DNA concentrations were determined

using the NanoDrop photometer (Peqlab) and DNA samples were stored at -20 °C.

4.9.2 Transformation of competent bacteria

Plasmid DNA was transformed into One Shot® Stbl3TM chemically competent E. coli

(invitrogen) according to the manufacturer`s protocol.

4.9.3 Site-directed mutagenesis

In order to inhibit shRNA-mediated degradation of the ectopically expressed AHR

messenger RNA (mRNA) in H1975 shAHR, five silent point mutations were introduced

into the rescue vector at the shRNA binding site using GeneArt™ Site-Directed

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Methods

Mutagenesis System Kit (Thermo Fisher Scientific) according to the manufacturer’s

instructions.

The forward primer was designed to be complementary to the binding site of the AHR-

targeting shRNA with the exception of five single bases each on the third position of the

codon (Table 5).

Table 5: Primer sequences for AHR mutagenesis. Yellow: shRNA binding site. Red: silent point mutations.

primer sequence (5’ - 3’)

silMut AHR

For ATCCTTCCAAGCGGCACAGGGATCGTCTCAATACAGAGTTGGACC

silMut AHR

Rev GGTCCAACTCTGTATTGAGACGATCCCTGTGCCGCTTGGAAGGAT

4.9.4 Agarose gel electrophoresis and gel extraction

Agarose gels were prepared using 1-2 % agarose in TAE buffer and 0.5 µg/ml ethidium

bromide. Separation of DNA fragments supplemented with 6X DNA loading dye was

achieved by applying 100-120 V for 1-2 h. Isolation of DNA fragments from TAE agarose

gels was achieved using QIAquick Gel Extraction Kit (Qiagen) according to the

manufacturer’s protocol.

4.9.5 Restriction digest

Digestion of plasmid DNA or purified PCR product was carried out using restriction en-

zymes as indicated according to the manufacturer’s protocol. Undigested DNA was used

as negative control and samples were analyzed using agarose gel electrophoresis (4.9.4).

4.9.6 RNA isolation and cDNA synthesis

For qRT-PCR, RNA was isolated and purified using High Pure RNA Isolation Kit (Roche)

and reversely transcribed by Transcriptor High Fidelity cDNA Synthesis Kit (Roche) as per

the manufacturer’s protocols. For mRNA sequencing, RNeasy Mini Kit (Qiagen) was used

to obtain highly enriched mRNA-fractions (4.11).

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Methods

4.9.7 Quantitative real-time PCR (qRT-PCR)

qRT-PCR was conducted using LightCycler® 480 SYBR Green I Master Kit (Roche

Molecular Systems, Inc.) according to the manufacturer’s manual. If not stated otherwise,

primers were designed using Primer3 software and purchased from Thermo Fisher

Scientific, Qiagen or Integrated DNA Technologies (Table 9) and applied at 2 µM final

concentration.

Table 6: Standard protocol for qRT-PCR at LightCycler®480.

procedure period [min] temperature [°C] # of cycles

initialization 5:00 95 1x

denaturation 0:10 95 45x

annealing 0:10 s 57

elongation 0:10s 72

melting curve

0:05 s 95 1x

1:00 65

continuous 97

cooling 0:10 40 1x

Target expression was quantified in duplicates or triplicates on a LightCycler®480 System

(Roche) using the 2-ΔΔCt method and actin beta (ACTB), glyceraldehyde-3-phosphate

dehydrogenase (GAPDH) and hypoxanthine phosphoribosyltransferase 1 (HPRT1) as

internal controls. For a detailed run protocol see Table 6.

4.10 Flow cytometry

Detection of fluorescently labeled cells and analysis of cell viability was conducted using

flow cytometry. If not indicated otherwise, cells were harvested using trypsin, centrifuged

at 300 x g for 5 min and resuspended in FACS buffer. DAPI (5 ng/ml) was supplemented

to allow for discrimination of viable cells.

FACSCelestaTM and FACSDiva™ software (BD Biosciences) were used for all analyses.

Data from the in vivo stress experiment were re-analyzed using FlowJo software due to

file sizes.

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Methods

4.11 RNA-Sequencing

RNA was isolated from cells after 48 h of treatment with 200 µM omeprazole using

RNeasy Mini Kit (Qiagen) according to the manufacturer’s recommendations. RNA

integrity was confirmed using Screen Tape Kit (Agilent) and Screen Tape Station (Agilent).

3’UTR mRNA-Seq library preparation and analysis on an Illumina HiSeq2500 was

performed by the working group of Prof. Dr. Michael Hölzel as described previously (Layer

et al. 2017).

Transcript-level quantification was performed using salmon version 0.11 with the Ensembl

GRCh38 assembly as reference genome. Resulting count estimates were then merged

above all samples and transformed to gene-level using tximport version 0.16. Differential

expression analysis was performed on the resulting gene-counts table using Deseq2

version 1.18. Data processing from quantification to differential expression analysis was

kindly conducted by Jan Forster.

Expression changes were considered significant with Padj < 0.05 and log2-fold change

(log2FC) <-1 or <1. Principal component analysis and heat map clustering was performed

using Perseus software (Max Planck Institute for Biochemistry, Martinsried, Ver-

sion 1.5.5.3). Among all groups, Euclidean clustering was carried out for differential ex-

pression data for genes being significantly altered between experimental groups A and B.

4.12 Gene set enrichment analysis (GSEA)

Gene count matrix file from RNA-Seq was used for gene set enrichment analysis (GSEA)

using java-based GSEA software v3.0 and the curated hallmark gene set collection

(Mootha et al. 2003 , Subramanian et al. 2005). Parameters were set to 1,000

permutations and gene-set permutation mode.

4.13 In vivo experiments

4.13.1 Orthotopic lung xenografts

Orthotopic transplantation as well as subsequent bioluminescence imaging (BLI) was con-

ducted at the University of California, San Francisco (UCSF) by Dr. Ross A. Okimoto or

Dr. Frank Breitenbücher. Human adenocarcinoma cell lines were orthotopically implanted

into immunocompromised mice as described previously (Okimoto et al. 2017). Briefly, cell

suspensions were prepared with Matrigel at a final concentration of 105 cells/µl. Six- to

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Methods

eight-week-old female SCID CB.17 mice (purchased form Taconic, Germantown, NY)

were anesthetized with 2.5 % inhaled isoflurane and the left thorax was surgically opened

to access the lateral ribs. 10 µl of cell suspension (106 cells) were injected into lung

parenchyma of the left lung lobe through the intercostal space using a 30-gauge hypo-

dermic needle. Mice were observed for pneumothorax before primary wound closure and

allowed to recover for one week prior to imaging.

4.13.2 In vivo and ex vivo bioluminescence imaging

Transgenic cell lines used for the orthotopic mouse model were further engineered by

lentiviral transduction to express GFP and Luciferase (Luc) from an EGFP-ffluc epHIV7

vector (kindly provided by Dr. Michael Jensen, Seattle). Isolation of GFP+ cells was con-

ducted by Klaus Lennartz using a BD FACSVantage SE with BD FACSDiVA Option (BD

Biosciences) modified by addition of a S2 bench (Lennartz et al. 2005).

Mice were imaged at the UCSF Preclinical Therapeutics Core with Xenogen IVIS 100

bioluminescence imaging as described previously (Okimoto et al. 2017). For in vivo imag-

ing, mice were anesthetized and injected IP with 200 µl (150 mg/kg) D-Luciferin and bio-

luminescence intensity of tumors was monitored once weekly until week five. After five

weeks, D-Luciferin was injected and mice euthanized to resect organs for ex vivo imaging.

4.13.3 In vivo shRNA screen using orthotopic lung cancer model

The shRNA library screen was performed by Dr. Frank Breitenbücher and Dr. Ross

A. Okimoto prior to this thesis. To this end, a lentiviral pooled barcoded shRNA library was

generated using DECIPHER shRNA Library Human Module 1 (Cellecta Inc.) following the

manufacturer’s protocol. Briefly, HEK293FT cells were transfected with shRNA library

DNA using FuGENE (Promega) and viral supernatants were collected 72 h post trans-

fection. GFP and Luciferase expressing H1975 and A549 cells were transduced with the

shRNA library-containing supernatant. Transduction efficacy was set to 25 % to ensure

that total cell number would exceed the library’s complexity by 1,000-fold. After puromycin

selection, cell populations were orthotopically implanted in the left lungs of CB-17 SCID

mice. Tumor growth was monitored using bioluminescent in vivo imaging until metastases

were detectable. To identify representation of the library’s shRNAs in metastases and

primary tumors, harvested tissues were subjected to parallel sequencing of barcoded

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Methods

regions as previously described (Okimoto et al. 2017). Statistical analyses were

performed by Dr. Saurabh Asthana.

4.13.4 In vivo stress assay

C57BL/6 mice were kindly provided by the working group of Prof. Dr. Jens Siveke and

were 12 months old on average. Prior to tail vein injection, transgenic H1975 cells

expressing AHR-specific or control shRNAs were treated in vitro with omeprazole or

DMSO as control for 48 h. Subsequently, cell suspensions at 106 cells/100 µl PBS were

prepared for all treatment groups and kept on ice until injection. Per mouse, 100 µl of cell

suspension were transplanted intravenously. After 5 min, mice were sacrificed to collect

0.5-1 ml of cardiac blood as well as lung and spleen.

Blood was collected in tubes with 3 µl of 0.5 M EDTA and directly subjected to red blood

cell lysis. To this end, 4 ml of ACK buffer was added and samples were incubated for

10 min at RT. After centrifugation, incubation in ACK buffer was repeated. Finally, cells

were pelleted, resuspended in FACS buffer and stored on ice until flow cytometry analysis.

Lung lobes (n = 3 per mouse) were subjected to tissue digestion as described in

Grüner et al. (Grüner et al. 2016). Briefly, lung tissues were minced with scissors and

incubated in digestion medium for 1 h at 37 °C. Digest was stopped with quenching solu-

tion and cell suspension was filtered through 40 µm mesh, centrifuged and subjected to

red blood cell lysis as described above.

Spleens were filtered through 40 µm mesh and subjected to red blood cell lysis as

described above.

For all samples, cells were pelleted by centrifugation and resuspended in FACS buffer

supplemented with 5 µg/ml DAPI to detect living and GFP+ cells using flow cytometry.

4.14 Statistics

Significance was assessed for all experiments with three biological replicates by statistical

analysis using GraphPad Prism 6. As applicable, either student’s t-test or one-way

analysis of variance (ANOVA) was used.

In graphs, P-values are indicated as following:

ns (not significant), P > 0.05, * P ≤ 0.05, ** P ≤ 0.01, *** P ≤ 0.001,**** P ≤ 0.0001

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Results

5 RESULTS

Due to the complexity of the metastatic process comprising sequential adaptation of

cancer cells during its different steps, the implementation of legit in vivo models for the

preclinical investigation of the underlying molecular mechanisms is of utmost importance.

While several modulators of metastatic processes have been identified, unbiased in vivo

screens reflecting the entire metastatic cascade have the potential to uncover important

genes in this complex biological phenomenon. For this purpose, shRNA libraries targeting

multiple genes have already proven their value for revealing factors involved in

tumorigenesis (Berns et al. 2004 , Gargiulo et al. 2014 , Sims et al. 2011).

5.1 Unbiased shRNA screen in an orthotopic mouse model of lung cancer reveals

potential metastasis genes

In order to identify novel modulators of metastasis in NSCLC, Dr. Frank Breitenbücher

and Dr. Ross A. Okimoto performed an unbiased in vivo shRNA library screen using an

orthotopic mouse model of lung cancer prior to this work. Importantly, this approach

incorporates all sequential steps of the metastatic process thereby constituting a legit

model for factors crucial in lung cancer metastasis. The screen was based on two NSCLC

cell lines, NCI-H1975 (subsequently referred to as H1975), which have low endogenous

metastatic potential, and A549 endogenously capable to form metastases in this ortho-

topic model. A barcoded shRNA library was lentivirally introduced under single hit condi-

tions into A549 and H1975, which were engineered to express Luciferase (Luc) and green

fluorescent protein (GFP) reporters (Figure 3A). Library-expressing A549 and H1975 cell

populations were orthotopically transplanted into immunocompromised mice as described

previously (Okimoto et al., 2017). Bioluminescent imaging (BLI) revealed mainly local

tumor growth of parental H1975, whereas metastatic spread was induced in shRNA-

library transduced H1975 (Figure 3B). Deep sequencing of metastases, primary tumors

and a reference sample from the initial cell population allowed evaluation of barcode

representation of the shRNAs by bioinformatic analyses which were conducted by

Dr. Saurabh Asthana from the UCSF (Figure 3C). A list of 69 putative metastasis-

modulating target genes was identified including aryl hydrocarbon receptor (AHR,

Figure 3C) that has been subjected to profound characterization and validation

experiments during this thesis.

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Results

Figure 3: Unbiased in vivo shRNA screen using an orthotopic mouse model of lung cancer. A) Schematic over-view of experimental layout. B) Bioluminescence images of SCID CB.17 mice transplanted with GFP-Luc+ H1975 expressing shRNA library or parental GFP-Luc+ H1975. C) Statistic analysis for one mouse (m3) displaying shRNA

representation in primary tumor and metastases normalized to shRNA representation in the initial cell population. Aryl hydrocarbon receptor (AHR, red circle) was selected for further characterization as a potential metastasis modulator. These experiments were performed by Dr. Breitenbücher and Dr. Okimoto. Statistical analyses were conducted by Dr. Asthana.

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Results

AHR is a ligand-activated transcription factor, which is involved in many cellular processes

including responses to xenobiotic stimuli, autoimmunity, metabolic imbalance and inflam-

matory diseases (reviewed in Esser et al. 2018, Larigot et al. 2018). Further, a role of AHR

has been controversially discussed with regard to cancer initiation and progression

(D'Amato et al. 2015 , Jin et al. 2014 , Murray et al. 2014 , Opitz et al. 2011).

5.2 Suppression of endogenous AHR increases metastatic potential of H1975

cells in vitro

In order to investigate the role of AHR in the metastatic process of NSCLC, we established

stable cell models by introduction of a shRNA targeting AHR (shAHR) into H1975 using

lentiviral transduction. H1975 stably expressing a non-mammalian target control

shRNA (shScr) were generated as control. As target gene suppression was not detectable

in the bulk population of H1975 shAHR cells (Figure 4A), clonal cell lines (K1, K2 and K3)

were established using limiting dilution to exclude the impact of heterogeneity in the

studied cell population. Expression of AHR was significantly reduced on protein and

mRNA level in H1975 shAHR-K1 and -K2 compared to shScr control cells analyzed by

immunoblotting (Figure 4A) and qRT-PCR (Figure 4B). Suppression of AHR did not affect

proliferation of H1975 in a short term MTT assay (Figure 4C).

Figure 4: Suppression of endogenous AHR by stable integration of shAHR into H1975 cells. AHR protein and mRNA levels in shScr control and shAHR cell clones were assessed by immunoblotting (A) and qRT-PCR (B). A) Actin was used as control. B) Expression was normalized to ACTB and GAPDH relative to the shScr control. Mean ± SD of the two house keeping genes (HKG) is displayed. C) Proliferation was analyzed after 72 h using MTT assay. Data are

shown as mean ± SD relative to the shScr control. n = 3 for all experiments. Significance was assessed using one-way ANOVA.

42

Results

In order to functionally characterize AHR as a modulator of lung cancer metastasis, we

used established in vitro platforms to assess the migratory and invasive capacity of H1975

with regard to AHR expression. In concordance with the results from the in vivo screen,

suppression of AHR significantly increased the invasion of H1975 cells in a transwell

migration invasion assay (Figure 5A-C) though migration was reduced (Figure 5A+C)

compared to controls.

Figure 5: shRNA-mediated suppression of AHR increases metastatic potential of H1975 cells in vitro. A) Number

of migrating and invading H1975 cells expressing shAHR or shScr were assessd using a transwell migration invasion assay. B) Relative invasion was calculated by dividing the mean number of invading by the mean number of migrating cells. C) Representative pictures from transwell inserts. Scale bar 200 µm. D)+E) MMP2 and MMP9 activity were

assessed using gelatine zymography. Relative intensities of gelatinolytic bands from MMP9 were quantified using ImageJ. For A, B and D, data are shown as mean ± SD. n = 3 for all experiments. Significance was assessed using one-way ANOVA (A+D) or student’s t-test (B).

As knockdown of AHR increased the invasion through the matrigel-covered inserts, we

hypothesized that AHR may regulate the activity of matrix-metalloproteases (MMPs)

which are known to be involved in matrix remodeling and metastatic progression (Conlon,

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Results

Murray 2019). Gelatine zymography was applied to assess the activity of the gelatinases

MMP2 and MMP9 using conditioned medium of H1975 shScr cells or H1975 cell clones

expressing shAHR. H1975 shAHR-K2 cells with the most efficient suppression of AHR

expression displayed high MMP9 activity, while MMP2 activity was unaltered irrespective

of AHR expression levels (Figure 5D+E). However, MMP9 activity was not increased in

the other two clonal cell lines expressing shAHR.

Figure 6: Intercellular adhesion is altered upon suppression of AHR in H1975 cells. A) Representative pictures of spheroids formed by GFP-Luc+ H1975 shAHR-K2 and shScr control cells. Scale bar 200 µm. B) CDH1 (E-cadherin) and CDH2 (N-cadherin) mRNA levels in H1975 shScr control and shAHR cell clone K2 were assessed by qRT-PCR. Expression was normalized to ACTB and GAPDH relative to the shScr control. Mean ± SD of the two house keeping genes (HKG) is displayed. Significance was assessed using student’s t-test. n = 3 for all experiments.

To assess the impact of AHR expression on cell growth in three dimensions, which is

important to assess the metastatic and invasive capabilities, cells were plated on repellent

culture surfaces provoking formation of tumor cell spheroids. Increased cell scattering was

observed in GFP-Luc-expressing H1975 shAHR-K2 cells compared to AHR-proficient

cells (Figure 6A), which is described to be associated with increased migratory and inva-

sive capacity (Stadler et al. 2018). Upon metastatic progression of epithelial tumors a

switch from epithelial adhesion molecules, most prominently E-cadherin, to mesenchymal

markers such as N-cadherin is commonly observed in epithelial-mesenchymal transition

(EMT) (Nieto et al. 2016). Interestingly, CDH1 (E-cadherin) expression was sustained

upon shRNA-mediated suppression of AHR while expression of CDH2 (N-cadherin) was

increased (Figure 6B).

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Results

Overall, suppression of AHR in H1975 cells was sufficient to enhance their invasive

capacity in our experimental conditions in vitro.

5.3 Reconstitution of AHR expression by introduction of shAHR-resistant AHR in

H1975 AHR-knockdown cells partially reverses the pro-metastatic phenotype

In order to exclude cell clone specific effects and to confirm the impact of AHR on the

metastatic ability of H1975 cells, we re-expressed AHR in our knockdown cell models by

introduction of shRNA-resistant AHR cDNA. To this end, mutant AHR cDNA harboring

five silent point mutations that abolish shRNA binding efficacy was stably introduced into

the three clonal H1975 shAHR cell lines as well as the shScr control by retroviral trans-

duction. The empty MSCV vector (EV) was transduced to generate the appropriate con-

trols (Figure 7A). By this, AHR mRNA levels were partially increased in H1975 cell clones

expressing shAHR as analyzed by qRT-PCR (Figure 7B), whereas protein levels were not

detectably changed (Figure 7C).

To demonstrate functionality of exogenous AHR in the generated rescue cell models, we

used the AHR agonist omeprazole to examine the induction of the AHR target gene

Cytochrome P450 Family 1 Subfamily A Member 1 (CYP1A1) (Figure 7D). Indeed, acti-

vation of AHR by omeprazole led to a significant increase (200-fold) of CYP1A1 expres-

sion in AHR-proficient H1975 shScr cells, which was significantly dampened in H1975

expressing shAHR (Figure 7E). Partial reconstitution of AHR by stable introduction of

shRNA-resistant AHR cDNA in part restored omeprazole-mediated induction of CYP1A1

expression (Figure 7E). Hence, the rescue cell models were subjected to characterization

of altered metastatic capacity.

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Results

Figure 7: AHR cDNA resistant to shAHR was successfully introduced into H1975 cell models expressing shAHR or shScr. A) Schematic overview of generation of rescue cell models. B) Expression of AHR was assessed using qRT-PCR. GAPDH was used as reference gene. C) AHR protein levels were analyzed using immunoblotting. Actin was used as control (n = 1). D+E) Expression of the AHR target CYP1A1 in the absence and presence of the AHR agonist

omeprazole (omep, 200 µM, 72 h) was analyzed using qRT-PCR. Expression was normalized to GAPDH. n = 3 for all experiments if not indicated otherwise. For B and E, data are shown as mean ± SD normalized to control. Significance

was assessed using one-way ANOVA.

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Results

Here, H1975 cells with suppressed AHR expression (H1975 shAHR-K2 EV) consistently

showed increased invasive abilities in both the transwell migration invasion assay

(Figure 8A+B) and gelatine zymography (Figure 8C+D). Further, reintroduction of AHR in

H1975 shAHR-K2 cells moderately dampened this increase in relative invasion as well as

MMP9 activity suggesting the observed effects to be AHR specific. In conclusion, restoring

of endogenous AHR expression in H1975 shAHR-K2 cells by introducing a shRNA-

resistant AHR partially reversed the metastatic phenotype in vitro.

Figure 8: Reconstitution of AHR expression in H1975 with shRNA-mediated AHR suppression partially rescued metastatic phenotype observed in vitro. A) Evaluation of invasive capability of cells with partially reconstituted AHR

expression using transwell migration invasion assay. Relative invasion was calculated by dividing the mean number of invading by the mean number of migrating cells. Data are shown as mean ± SD. B) Representantive pictures from transwell inserts. Scale bar 200 µm. C)+D): Gelatine zymography was used to determine MMP2 and MMP9 activity of

rescue cell models. Relative intensities of gelatinolytic bands from MMP9 were quantified using ImageJ. Data are shown as mean ± SD normalized to control. n = 3 for all experiments. Significance was assessed using one-way ANOVA.

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Results

5.4 Depletion of AHR favors metastatic spread in vivo

As the metastatic cascade involves multiple steps which cannot completely be recapitu-

lated in vitro, we performed an in vivo validation experiment. Here, metastatic spread of

H1975 expressing shAHR and shScr control was investigated using the orthotopic mouse

model of lung cancer (Figure 9A), which was already applied in the initial shRNA screen.

Figure 9: Targeted suppression of AHR increases metastatic spread of H1975 in an orthotopic lung cancer mouse model. A) Schematic overview of in vivo validation experiment. B) AHR expression was assessed by immuno-blotting. Actin was used as control. C) BLI images of SCID CB.17 mice transplanted with either GFP-Luc+ H1975 shScr or GFP-Luc+ H1975 shAHR-K2. D) Ex vivo bioluminescent imaging of explanted lung lobes. E) Metastasis-free survival of SCID CB.17 mice bearing GFP-Luc+ H1975 expressing shAHR (K2) or shScr. P-value, log-rank. In vivo experiments were conducted by Dr. Okimoto at the UCSF.

In order to enable in vivo bioluminescent imaging (BLI), the clonal H1975 cell line with the

most effective AHR knockdown (shAHR-K2) and shScr control cells were engineered to

stably express GFP and Luc. Persistence of AHR knockdown was confirmed using

immunoblotting (Figure 9B). These GFP-Luc+ H1975 shAHR-K2 cells as well as control

cells were orthotopically implanted into the left lung of immunocompromised mice. Tumor

growth and metastasis formation were monitored for four weeks. Luciferase-based imag-

ing revealed metastatic spread of shAHR-K2 cells compared to mainly localized tumor

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Results

growth of the control cell lines (Figure 7C). Importantly, shRNA-mediated suppression of

AHR significantly increased the metastatic ability of H1975 cells in vivo as displayed by

decreased metastasis-free survival of mice implanted with shAHR-K2 compared to the

control tumors (Figure 9C-E).

Figure 10: Impact of endogenous AHR expression in lung adenocarcinoma on patient outcomes following resection. Kaplan-Meier plots displaying overall survival (OS) and time to first progression (FP) for patients with stage I lung adenocarcinomas with high or low AHR expression (20820_at) (Győrffy et al. 2013). Cutoff median.

To further corroborate the role of AHR as a suppressor of lung cancer metastasis we

analyzed publicly available RNA expression data from patient cohorts with early stage and

locally advanced lung adenocarcinoma (Győrffy et al. 2013). Interestingly, overall survival

(Figure 10A) and time to first progression (Figure 10B) were significantly reduced in

patients with tumors exhibiting low AHR expression.

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Results

Figure 11: Impact of endogenous AHR expression in lung adenocarcinoma on patient outcomes among all disease stages. Kaplan-Meier plots showing overall survival (OS) and time to first progression (FP) for patients with lung adenocarcinomas among all stages with high or low AHR expression (20820_at) (Győrffy et al. 2013). Cutoff median.

Analyzing cohorts of patients with adenocarcinoma among all disease stages, this corre-

lation was less profound for overall survival (Figure 11A) and non-significant regarding

time to first progression (Figure 11B).

5.5 RNA sequencing experiment identifies candidate targets of AHR involved in

stress responses and metastasis

A variety of endogenous and exogenous ligands of AHR have been described (Larigot

et al. 2018, Murray et al. 2014). Although our previous results suggested that suppression

of endogenous AHR was sufficient to impact the metastatic potential of H1975 cells, we

also wanted to consider the impact of AHR activation on the transcriptional response of

target cells. Thus, we included an experimental group in which the AHR-activating ligand

omeprazole was added to the cells prior to RNA sequencing as omeprazole had pre-

viously been linked to reduced metastasis in breast cancer models (Jin et al. 2014).

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Results

Figure 12: Omeprazole inhibits growth of H1975 cells in an AHR-dependent manner. Proliferation and metabolic viability of H1975 shScr and shAHR-K2 upon omeprazole (omep) treatment was studied after 48 h (A) and 72 h (B)

using MTT assay. Data are shown as mean ± SD normalized to respective DMSO control. Significance was assessed using one-way ANOVA.

First, we analyzed the impact of omeprazole on H1975 with regard to AHR expression in

an MTT assay. Proliferation and metabolic activity of AHR-proficient H1975 cells was sig-

nificantly inhibited by treatment with omeprazole in a dose-dependent manner, which was

significantly attenuated in H1975 expressing shAHR (K2) (Figure 12).

In addition to the functional assays performed earlier, we aimed to identify those AHR

effectors involved in regulating lung cancer metastasis. To this end we subjected H1975

with and without shRNA-mediated suppression of endogenous AHR to mRNA

sequencing. Further, we included treatment with omeprazole to discriminate between con-

stitutive and induced expression profiles (Figure 13A). To confirm validity of our experi-

mental settings, expression of the AHR target CYP1A1 was analyzed for all samples prior

to RNA sequencing using reverse transcription to cDNA and qRT-PCR. Indeed, CYP1A1

expression was strongly elevated by the activation of AHR upon omeprazole treatment

(Figure 13B). Moreover, CYP1A1 induction was significantly blunted in H1975 with

shRNA-mediated suppression of AHR. RNA sequencing and initial data preparation were

performed by the group of our collaborator, Prof. Dr. Michael Hölzel, University of Bonn,

and by Jan Forster, M.Sc., Institute of Genetics, respectively. Principal component analy-

sis confirmed reproducibility of gene expression across biological replicates (Figure 13C).

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Results

Figure 13: Constitutive and induced expression signatures of H1975 shAHR cell models were identified using mRNA sequencing. A) Schematic overview of experimental settings for RNA sequencing experiment. B) CYP1A1

expression was analyzed for all RNA sequencing samples after generation of cDNA using qRT-PCR. Omeprazole (omep) was used at 200 µM for 48 h. Expression was normalized to GAPDH. Data are shown as mean ± SD normalized to control. n = 3. C) Principal component analysis recovered clustering of experimental groups. D) Venn diagram of differential gene expression analysis. E) Euclidean clustering was used to generate a heat map displaying gene patterns

for genes that were differentially expressed upon omeprazole treatment. Changes with p < 0.05 were considered significant.

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Results

Differential gene expression analysis was performed among all treatment groups to

determine AHR-dependent expression profiles. Comparing the effect of omeprazole in

AHR-proficient and AHR-suppressed H1975 cells revealed an overlap of 281 regulated

genes (Figure 13D). Moreover, we identified genes being differentially expressed upon

omeprazole treatment in H1975 shScr cells. Clustering of RNA data according to the

Euclidean distance revealed that AHR-proficient cells and shAHR-K2 cells showed com-

parable gene expression patterns upon omeprazole treatment while the amplitude of

target gene regulation was dampened in shAHR-K2 cells (Figure 13E).

To identify transcriptomic programs that are particularly altered upon activation of AHR by

omeprazole or shRNA-mediated suppression of AHR, gene set enrichment analysis

(GSEA) was performed using the ‘Hallmarks of Cancer’ gene set collection (Mootha

et al. 2003, Subramanian et al. 2005).

Here, AHR activation by omeprazole was positively correlated with the unfolded protein

response (UPR) and xenobiotic metabolism (Figure 14A+C). Interestingly, knockdown of

AHR was significantly correlated with increased expression of EMT genes

(Figure 14B+D). Additionally, this gene set was found to be significantly less represented

upon activation of AHR by omeprazole in both H1975 cells with and without suppression

of AHR (Figure 14A, Supplementary Figure 1).

Moreover, inspection of these gene sets associated with AHR expression and activity

revealed several target genes implicated in cancer progression, including several mem-

bers of the matrix metalloprotease family (MMPs, most prominently MMP24), asparagine

synthetase (ASNS) and activating transcription factor 4 (ATF4). Those have been

subjected to further investigation.

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Figure 14: Gene set enrichment analysis links AHR expression and activation to several cancer hallmarks. A) Gene sets differentially represented in H1975 shScr omep (group B) compared to H1975 shScr DMSO (group A). B) Gene sets differentially represented in H1975 shAHR-K2 DMSO (group C) compared to H1975 shScr DMSO (group A). C) Enrichment plot for the gene set ‘Unfolded Protein Response’ enriched in omeprazole treated H1975 shScr (shScr +) compared to the DMSO treated control (shScr -). D) Enrichment plot for gene set ‘Epithelial-Mesenchymal-Transition’ enriched in H1975 shAHR-K2 (shAHR -) compared to the shScr control (shScr -). For A and B, treshhold for significant gene set enrichment was set to FDR < 0.1. Biological replicates are indicated with I, II

and III.

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5.5.1 AHR activation and expression negatively correlates with genes associated

with matrix remodeling and EMT

Matrix-metalloproteases (MMPs) are known to contribute to matrix degradation during

invasion of tumor cells and are associated with enhanced invasiveness of tumor cells and

inferior survival prognosis (El-Badrawy et al. 2014 , Wang et al. 2019). In order to confirm

findings from the mRNA sequencing approach, expression levels of several MMPs were

analyzed for three independent H1975 cell clones expressing shAHR (K1, K2 and K3)

with and without treatment with omeprazole compared to the H1975 shScr control.

Figure 15: AHR regulates expression of matrix-metalloproteases (MMPs) in H1975. Expression of MMPs in H1975

cell clones expressing shAHR (K1-K3) and shScr control was analyzed after treatment with omeprazole (omep, 200 µM, 48 h) or DMSO (-). MMP24 expression was assessed by qRT-PCR (A) and immunoblotting (B). C)+D) qRT-PCR analysis of MMP19 and MMP9 mRNA levels is shown. For A, target gene expression was normalized to ACTB, GAPDH and HPRT1 relative to the shScr control. Mean ± SD of the three house keeping genes (HKG) is displayed. For C and D, target gene expression was normalized to ACTB and GAPDH relative to the shScr control. Data are shown as mean ± SD of the two house keeping genes (HKG). n = 3 for all experiments, excluding D for which n = 2.

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Expression of MMP24 mRNA was highly increased in all three H1975 cell clones express-

ing shAHR, which was significantly attenuated upon omeprazole treatment (Figure 15A).

These findings were confirmed by immunoblotting (Figure 15B). Furthermore, MMP19

expression was elevated in H1975 cell clones shAHR-K2 and shAHR-K3 (Figure 15C).

As we already demonstrated increased MMP9 activity in H1975 shAHR-K2 cells using

gelatine zymography (Figure 5D+E), we also investigated MMP9 expression using

qRT-PCR. MMP9 expression was moderately increased in H1975 shAHR-K2 compared

to shScr cells (Figure 15D). Importantly, in AHR-proficient cells (shScr) MMP9 expression

was repressed upon activation of AHR by omeprazole. This suggests an AHR-dependent

regulation despite the fact that MMP9 expression was not regulated in the two other cell

clones expressing shAHR.

Figure 16: RNA sequencing results suggest a role of AHR in the regulation of collagen expression. Normalized

counts from RNA sequencing for several collagens found to be differentially expressed with regard to AHR expression and activation. Data are shown as mean ± SD.

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Moreover, inspection of the list of EMT genes upregulated in AHR-deficient H1975 cells

in the GSEA (Figure 14D) revealed overexpression of several members of the collagen

family. Collagen is the major structural protein of the extracellular matrix and has been

linked to cancer progression and metastasis (Lee et al. 2019 , Liu et al. 2018 , Nerenberg

et al. 2007). H1975 cell clone K2 expressing shAHR showed high expression of COL12A1,

COL1A1, COL1A2, COL5A1, COL6A2 and COL7A1 as compared to the shScr control

(Figure 16). Additionally, expression of collagens was decreased by omeprazole treat-

ment in H1975 shAHR-K2 cells. Interestingly, collagen-crosslinking genes of the lysyl

oxidase family (LOX, LOXL1 and LOXL2) were positively correlated with AHR suppres-

sion (Figure 14D). These findings are to be validated using qRT-PCR and immunoblotting

as well as functional assays.

5.5.2 AHR activation regulates cellular stress responses in H1975

In contrast to the examined EMT markers being negatively regulated by AHR, results from

the GSEA suggested induction of cellular stress responses such as UPR upon activation

of AHR. In concordance with these results, expression of ASNS was strongly induced by

treatment with omeprazole as validated using qRT-PCR and immunoblotting. Here, treat-

ment with omeprazole elevated both mRNA and protein levels of ASNS, which was sig-

nificantly attenuated in all three H1975 shAHR cell clones (Figure 17A+B). Further,

activation of AHR by omeprazole induced expression of ATF4 and DNA damage inducible

transcript 3 (DDIT3 also known as CHOP), which are part of the UPR signaling cascade

(Figure 17C-E). Comparable to regulation patterns observed for ASNS, omeprazole-

mediated induction of ATF4 expression was dampened in shAHR-expressing H1975 cell

clones K1 and K2 (Figure 17C).

As ASNS has been suggested as direct target of ATF4 under nutritional stress conditions

(Ameri et al. 2010, Chen et al. 2004), we hypothesized that AHR-dependent regulation of

ASNS was mediated by ATF4 in our H1975 cell models. First, we demonstrated that acti-

vation of AHR by omeprazole not only induced expression of ASNS and ATF4 in H1975

but also in two other lung adenocarcinoma cell lines, H1299 and A549 (Figure 18A+B). In

addition, siRNA-mediated suppression of ATF4 completely blocked omeprazole-mediated

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induction of ASNS confirming the suggested regulatory axis (Figure 18A+B). The induc-

tion of ASNS and ATF4 was less profound in A549 compared to H1975 and H1299

cells (Figure 18B).

Figure 17: Suppression of AHR attenuates omeprazole-mediated induction of UPR signaling genes ASNS, ATF4 and CHOP. Expression of potential AHR targets in H1975 cell clones expressing shAHR (K1-K3) and shShr control was analyzed after treatment with omeprazole (omep, 200 µM, 48 h) or DMSO (-). A) ASNS expression assessed by qRT-pCR. Significance was evaluated by one-way ANOVA. B) ASNS protein levels assessed by immunoblotting. C) ATF4 protein levels assessed by immunoblotting. D)+E) ATF4 and CHOP expression was analyzed using qRT-PCR. For A, target gene expression was normalized to ACTB, GAPDH and HPRT1 relative to the shScr control. Mean ± SD of the three house keeping genes (HKG) is displayed. For D and E, target gene expression was normalized to ACTB and GAPDH relative to the shScr control. Mean ± SD of the two house keeping genes (HKG) is displayed. A-C n = 3, D und E n = 1 (indicated by #) or n = 2.

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Figure 18: AHR regulates ASNS expression in an ATF4-dependent manner. Prior to treatment with omeprazole (omep, 200 µM, 48 h), H1975, A549 and H1299 were transfected with siRNAs targeting ATF4 or a non-targeting control (siCtrl). A) Expression of ASNS and ATF4 was assessed using immunoblotting. Actin was used as control. B) qRT-PCR analysis of ASNS and ATF4 mRNA levels normalized to ACTB and GAPDH relative to the respective,

untreated siCtrl control. Mean ± SD of the two house keeping genes (HKG) is displayed. Significance was assessed using one-way ANOVA.

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Taken together, the findings from the GSEA (Figure 14) and the identification of an

AHR-ATF4-ASNS axis in lung adenocarcinoma (Figure 18) suggest that AHR interferes

with mediators of cellular stress responses as well as classical metastasis genes such

as MMPs.

5.5.3 ASNS and ATF4 are confirmed AHR targets in colorectal cancer cells

Regarding tumor initiation and progression, AHR has been controversially discussed

among different entities (D'Amato et al. 2015 , Jin et al. 2014 , Murray et al. 2014) raising

the question whether the regulatory axis of AHR with its targets ATF4 and ASNS could

also be validated in other entities.

To this end, we used two established colorectal cancer (CRC) cell lines that have been

derived from the primary tumor (SW480) and a metastatic lesion at a lymph node (SW620)

of the same patient (Leibovitz et al. 1976). Interestingly, AHR mRNA and protein expres-

sion was significantly reduced in SW620 compared to SW480 cells supporting our

hypothesis of AHR as a metastasis suppressor (Figure 19A+B). Further, ATF4 and ASNS

expression were induced upon omeprazole treatment in both CRC cell lines as demon-

strated by immunoblotting (Figure 19A) and qRT-PCR (Figure 19C+D). Omeprazole-

mediated induction of ASNS expression was attenuated in the metastatic cell line SW620

comparable to our findings in H1975 expressing shAHR (Figure 17A+B). In contrast to the

lung adenocarcinoma cell line, ATF4 expression was not decreased but increased in the

metastatic CRC cell line (Figure 19A+D).

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Figure 19: AHR and its targets ASNS and ATF4 are differentially regulated in a metastatic colorectal cell line compared to the corresponding primary, non-metastatic cells. A) Expression of AHR, ASNS and ATF4 was

detected in SW480 and SW620 cells with or without treatment with omeprazole (omep; 200 µM, 48 h) by immuno-blotting. Actin was used as a control. B-D) AHR, ASNS and ATF4 mRNA expression was assessed by qRT-PCR. Expression was normalized to the two house keeping genes (HKG) ACTB and GAPDH. Mean ± SD of the two HKG is

displayed relative to untreated SW480 cells. n = 3 for all experiments. Significance was assessed using one-way ANOVA.

5.6 AHR is involved in metabolic reprogramming

For metastasizing cancer cells, adaptation to metabolic stresses is of particular

importance during extravasation and metastatic seeding to survive and regain a prolif-

erative state in limiting nutrient conditions at a secondary site (Lambert et al. 2017 , Senft,

Ronai 2016). To investigate the impact of AHR on metabolic stress resistance, we mim-

icked these metabolic challenges by limiting cell culture conditions. Here, FBS and/or

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L-glutamine (L-Gln) was omitted from the culture medium or supplied at limiting concen-

trations. In an MTT assay, the proliferation of three independent H1975 cell clones ex-

pressing shAHR cells was significantly increased under L-Gln starvation and serum star-

vation as compared to H1975 shScr control (Figure 20A). To further confirm this response,

we performed a cell competition experiment in which either fluorescently labelled cell

clone H1975 shAHR-K2 or shScr control cells were mixed with their unlabeled counter-

parts (Mix A and Mix B, respectively, Figure 20B) and co-cultured for two weeks in the

absence or presence of L-Gln. Under normal cell culture conditions, H1975 shAHR-K2

cells were outcompeted by AHR-proficient cells (Figure 20C). However, depletion of L-Gln

resulted in significant enrichment of H1975 shAHR-K2 cells in the mixed cell population

(Figure 20C). These findings indicate that suppression of AHR enhances adaptation to

metabolic stress of lung adenocarcinoma cells.

Figure 20: Depletion of AHR increases resistance to L-glutamine withdrawal. A) Proliferation and metabolic via-

bility of H1975 expressing shAHR (K1-K3) or shScr depending on FBS and L-glutamine (L-Gln) levels was studied using MTT assay. Data are shown as mean ± SD normalized to respective control. Significance was assessed using one-way ANOVA. B) Schematic view of the mixing experiment. C) Relative amount of H1975 shScr and shAHR-K2 was

re-assessed after two weeks of co-cultivation in glutamine-deprived or normal culture settings during the mixing experiment using flow cytometry. n = 3 for all experiments.

Furthermore, we tested the effect of treatment with the glutaminase (GLS) inhibitor

CB-839 thereby limiting the supply of L-glutamate as an intermediate of the tricarboxylic

acid cycle (TCA) cycle. GLS inhibition significantly reduced proliferation of both

H1975 shAHR-K2 and shScr cells at a concentration of 10 µM, however, there was no

difference in sensitivity to CB-839 attributable to AHR expression levels (Figure 21).

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Figure 21: Suppression of AHR does not influence sensitivity to CB-839. MTT assay was used to assess prolif-

eration and metabolic activity of H1975 shScr and H1975 shAHR-K2 upon CB-839 treatment (72 ؘ h). Data are shown as mean ± SD normalized to respective control. Significance compared to respective control was assessed using one-way ANOVA.

Interestingly, parental H1975 cells were less sensitive to CB-839 treatment and L-Gln

withdrawal compared to A549 and H1299 cells as assessed by MTT assay

(Figure 22A+B). However, H1975 also showed decreased proliferation upon serum

reduction.

Figure 22: H1975 are less sensitive to CB-839 treatment and L-glutamine withdrawal compared to A549 and H1299. A) Effects of CB-839 on parental NSCLC cells was assessed after 72 h using MTT assay. B) Proliferation and

metabolic viability of parental NSCLC cells depending on FBS and L-glutamine (L-Gln) levels was studied using MTT assay. n = 3 for all experiments. Significance was assessed using one-way ANOVA. * display significance compared to respective control. # show significance between samples as indicated.

Nutrient supply is well known to limit tumor growth and in particular asparagine availability

mediated by ASNS was previously linked to metastasis (Knott et al. 2018). As we linked

suppression of AHR to both increased resistance to metabolic stress and dampened

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Results

induction of ASNS upon AHR activation, we investigated whether the metabolic pheno-

type of AHR knockdown could be recapitulated by suppression of endogenous ASNS. To

this end, we generated H1975 cell clones with stable shRNA-mediated suppression of

ASNS expression. Knockdown of ASNS was confirmed by western blot analysis

(Figure 23A) and qRT-PCR (Figure 23B) for three cell clones (H1975 shASNS-K1, -K2

and -K3) expressing two distinct shRNAs (shASNS-A for K1 + K2, shASNS-B for K3,

Table 1 in 4.2.3).

Figure 23: Suppression of endogenous ASNS by stable integration of shASNS into H1975. ASNS protein and mRNA levels in H1975 shScr control and shASNS cell clones (K1-K3) were assessed by immunoblotting (A) and qRT-PCR (B). n = 3 for all experiments. For B, data are shown as mean ± SD. Significance was assessed using one-way

ANOVA.

As with the shAHR models, in vitro assays were used to assess the invasive capacity and

metabolic stress resistance of H1975 expressing shASNS or shScr. In contrast to AHR

knockdown, suppression of ASNS expression did not increase relative invasion in a

transwell migration invasion assay (Figure 24A+B), though migration of

H1975 shASNS-K2 was increased compared to shScr control (Figure 24A). MMP9 activity

was not elevated but even reduced in two cell clones expressing shASNS (Figure 24C+D).

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Figure 24: Suppression of ASNS does not result in increased invasiveness of H1975 cells in vitro. A) Number of

migrating and invading H1975 cells expressing shASNS or shScr were assessd using a transwell migration invasion assay. B) Relative invasion was calculated by dividing the mean number of invading by the mean number of migrating cells. C) MMP2 and MMP9 activity were assessed using gelatine zymography. D) Relative intensities of gelatinolytic

bands from MMP9 were quantified using ImageJ. n = 3 for all experiments. Data are shown as mean ± SD. Significance was assessed using one-way ANOVA.

ASNS is a metabolic enzyme converting aspartate and glutamine to asparagine and

glutamate (Andrulis et al. 1987 , Krall et al. 2016). Thus, we hypothesized that attenuation

of omeprazole-mediated induction of ASNS in AHR-deficient H1975 might rather affect

the metabolic reprogramming than alter the invasive capacity of cells. Indeed, two H1975

clones expressing shASNS showed moderately increased proliferation upon L-Gln

withdrawal in an MTT assay when compared to shScr control, though changes did not

reach significance (Figure 25). Taken together, ASNS knockdown was not sufficient to

fully phenocopy the effects of AHR knockdown.

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Figure 25: Suppression of ASNS does not significantly alter L-glutamine dependency. Proliferation and metabolic

viability of H1975 expressing shASNS (K1-K3) or shScr with regard to FBS and L-glutamine (L-Gln) levels was studied using MTT assay. Data are shown as mean ± SD normalized to respective control. Significance was assessed using one-way ANOVA.

Still, patient outcomes in cohorts with stage I adenocarcinomas showed correlation of high

ASNS expression with superior overall survival (Figure 26A) and lower likelihood of

progression (Figure 26B), suggesting a role of ASNS in the progression of early stage

NSCLC.

Figure 26: Impact of endogenous ASNS expression in lung adenocarcinoma on patient outcomes following resection. Overall survival (OS) and time to first progression (FP) of patients with stage I lung adenocarcinomas was

analyzed with regard to ASNS expression (205047_at) using the publicly available KM plotter tool (Győrffy et al. 2013). Cutoff lower tertile.

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5.7 In vivo stress assay

During metastatic progression, tumor cells accomplishing invasion of the microenviron-

ment surrounding the primary tumor and intravasation into the blood stream face unfavor-

able conditions during the transit in the circulation. Further, circulating tumor cells (CTCs)

need to extravasate to access secondary sites while being exposed to immune cells as

well as oxidative, nutritional and mechanical stress (Lambert et al. 2017).

Figure 27: Schematic overview of in vivo stress assay. Briefly, GFP-Luc+ H1975 shAHR-K2 and GFP-Luc+

H1975 shScr were pretreated with omeprazole (omep, 200 µM) or DMSO for 48 h and injected intravenously into C57BL/6 mice. Lungs, spleens and blood samples were collected from sacrificed mice after 5 min of incubation and subjected to analysis for GFP+ cells using flow cytometry.

In order to mimic mechanical and environmental stress during dissemination of tumor

cells, we performed an in vivo stress assay in which GFP-Luc+ AHR knockdown and

control cells were pretreated with omeprazole or DMSO and injected intravenously into

C57BL/6 mice. After 5 min, mice were sacrificed and blood, lung and spleen subjected to

further analysis for GFP+ cells (Figure 27).

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Figure 28: Effect of AHR expression and activation on environmental stress resistance and adhesion to the lung in vivo. GFP-Luc+ H1975 cells expressing shAHR (K2) or shScr were pretreated with omeprazole (omep, 200 µM,

48 h) or DMSO and then subjected to an in vivo stress assay. GFP+ cells in the blood and lung tissue were analyzed using flow cytometry. Absolute (A) and relative (B) number of GFP+ cells detected in blood samples is shown. C) Viability of GFP+ cells collected from blood samples was determined by DAPI exclusion. D) Relative amount of GFP+

cells deteced in lung samples after digestion. Data are shown as mean ± SD.

Interestingly, total numbers of detected GFP+ cells in the blood samples were rather low

among all treatment groups despite the short period of incubation (Figure 28A+B). Thus,

interpretation of the following survival analysis is limited due to low cell numbers. Never-

theless, neither suppression of AHR expression nor omeprazole treatment seemed to

confer a benefit for the survival of H1975 cells in the blood stream under these short-term

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stress conditions in vivo (Figure 28C). However, this finding has to be additionally vali-

dated. In order to investigate adhesion of H1975 shAHR-K2 and shScr cells to secondary

tissues, three lung lobes as well as the spleen from each mouse were processed for

detection of GFP+ cells by flow cytometry. In cell populations isolated from the spleens,

no GFP+ cells were detectable. Regarding tumor cell adhesion to the lung, no significant

difference could be concluded regarding AHR expression or activation due to high vari-

ance within the treatment groups (Figure 28D).

Figure 29: Effect of AHR expression and activation on adhesion to T-HUVEC cells in vitro. GFP-Luc+ H1975

shScr and GFP-Luc+ H1975 shAHR-K2 pretreated with omeprazole (omep, 48 h, 200 µM) or DMSO were added to a confluent monolayer of T-HUVEC and adhesion was analyzed after 20 min of incubation. Relative number of GFP+ cells was determined using flow cytometry. Data are shown as mean ± SD relative to untreated H1975 shScr control. n = 2.

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During metastatic dissemination, tumor cells face the challenge of extravasation initially

requiring adhesion to the endothelial cells of lymph or blood vessels. In order to further

investigate the impact of AHR on the adhesion of H1975 cells, we performed an in vitro

adhesion assay using immortalized human umbilical vein endothelial cells (T-HUVECs).

GFP-Luc+ H1975 cells expressing shAHR (K2) or shScr were pretreated with omeprazole

or DMSO and seeded on confluent monolayers of T-HUVECs. GFP+ cells adherent after

20 min were quantified by flow cytometry. Here, we did not detect any significant differ-

ence in the adhesion capacity of H1975 with regard to AHR expression or activation

(Figure 29), suggesting that AHR is not crucially involved in facilitating homing to second-

ary sites during metastasis of H1975 cells.

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Discussion

6 DISCUSSION

Curative treatment with long-term eradication of the tumor is the ultimate goal of cancer

therapy. However, despite major improvements in treatment and detection modalities,

curing cancer remains an unmet goal for the majority of patients with the exception of few

entities (Robert Koch-Institut 2016). Still, lung cancer shows one of the poorest clinical

outcomes not exceeding 20 % overall survival at five years which is mainly due to late

detection of disease, acquisition of therapy resistance and metastatic relapse (Herbst

et al. 2018, Robert Koch-Institut 2016). Although detection of lung cancer at early stage

was improved using low-dose CT scans, highly effective risk reduction therapies that

enhance curative potential of surgery are missing for patients with local or locally

advanced disease (Aberle et al. 2011 , Anderson et al. 2019 , Zhong et al. 2018). The

development of cancer therapies specifically targeting and preventing metastatic

progression would potentially increase curative capacity of treatment modalities.

6.1 AHR as a suppressor of lung cancer metastasis

Though several potential targets for anti-metastatic treatment approaches have been sug-

gested including but not limited to transforming growth factor-β (TGF-β) signaling, matrix-

metalloproteases (MMPs) and angiogenesis (Anderson et al. 2019 , Padua,

Massagué 2009), there is still no clinically approved treatment specifically targeting

cancer metastasis. This might be due to the fact that many of the preclinical models that

have been used to identify those targets do not reflect the complexity of the metastatic

disease. We hypothesized that identification and mechanistic evaluation of surrogates of

the metastatic process in lung cancer would be fundamental for the development of novel

anti-metastatic interventions.

Against this background, our group in collaboration with scientists from the UCSF Cancer

Center has performed an unbiased shRNA screen using an orthotopic mouse model of

lung cancer in order to identify putative modulators of non-small-cell lung cancer (NSCLC)

metastasis. Notably, this in vivo model comprises all stages of cancer metastasis including

dissemination, intra- and extravasation as well as metastatic colonization. Previously, we

have demonstrated that this model is qualified for the investigation of crucial factors in the

metastatic process (Okimoto et al. 2017). For the in vivo screen, the two NSCLC cell lines

H1975 and A549 were used that display low and high metastatic potential, respectively.

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Discussion

Further, H1975 cells exhibit constitutively activated epidermal growth factor receptor

(EGFR) signaling due to two mutations L858R and T790M, and are thus commonly used

as a model for EGFR-mutant lung cancer (Sordella et al. 2004). Implementation of non-

metastatic H1975 allowed for the identification of metastatic modulators initiating lung

cancer metastasis when suppressed by specific shRNAs from a barcoded shRNA library.

Among others, we here identified aryl hydrocarbon receptor (AHR) as a significantly

overrepresented shRNA target in metastases compared to primary tumors suggesting

metastasis-suppressing functions for AHR (5.1).

AHR is a ligand-regulated transcription factor involved in numerous signaling pathways

mediated by both endogenous and xenobiotic ligands (Esser et al. 2018 , Murray

et al. 2014). Due to the direct exposure of the lung to cigarette smoke and environmental

pollutants, initially, AHR and its activation by xenobiotics has been mainly considered to

promote tumorigenesis in lung cancer (Guerrina et al. 2018 , Tsay et al. 2013). Further,

immunohistochemistry demonstrated elevated expression of AHR in lung carcinomas

compared to healthy tissue supporting the impact of AHR in tumorigenesis (Lin

et al. 2003). Although being previously described as pro-tumorigenic factor (D'Amato

et al. 2015, Murray et al. 2014, Opitz et al. 2011 , Shimizu et al. 2000), emerging evidence

suggests a more complex role for AHR in carcinogenesis and tumor progression in which

AHR functions are regulated in an entity-, stage- and ligand-dependent manner (Murray

et al. 2014). Analyses of the impact of AHR on triple-negative breast cancer (TNBC)

showed conflicting results regarding the formation of metastases. While AHR activation

by omeprazole reduced metastatic spread in a mouse model of breast cancer, tryptophan

2,3-dioxygenase (TDO2)-mediated production of kynurenine was shown to activate AHR

which in turn enhanced invasive and metastatic capacity of TNBC cells (D'Amato et al.

2015, Jin et al. 2014). Moreover, kynurenine-mediated activation of AHR suppressed

tumor immunity and increased cancer cell motility in malignant brain tumors (Opitz et al.

2011). Most recently, treatment with kynurenine has also been demonstrated to impair

metastatic spread of subcutaneously transplanted neuroblastoma cells in an in vivo

mouse model (Wu et al. 2019a). However, the role of AHR in lung cancer metastasis has

not yet been functionally and mechanistically confirmed in an orthotopic model of lung

cancer.

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Discussion

To the best of our knowledge, we here validated AHR for the first time as a suppressor of

metastasis in a legit in vivo model of metastasis in EGFR-mutant lung cancer (5.4). By

allowing for orthotopic tumor growth and spontaneous formation of metastases from the

primary tumor site, the sequential cascade of metastasis is fully recapitulated. Here,

targeted suppression of AHR enabled metastatic spread of non-metastatic H1975 cells.

Importantly, low intratumoral AHR expression was associated with inferior clinical out-

comes of patients harboring early stage adenocarcinomas supporting our findings (5.4).

6.2 Mechanistic insights to AHR-regulated metastatic pathways

Despite intensive research in the field of cancer metastasis, the picture of its molecular

mechanisms is not yet completely understood and further exhibits stage- and entity-

dependent differences.

Within this thesis, we uncovered AHR-mediated regulation of metastatic programs in

ligand-induced and constitutive expression patterns using functional and mechanistic

studies (5.5, 5.6). Acquisition of mesenchymal features by tumor cells via epithelial-

mesenchymal transition (EMT)-like processes increases tumor cell invasiveness facili-

tating evasion from the primary tumor site (Chaffer, Weinberg 2011 , Lambert et al. 2017).

Using RNA sequencing technology, we demonstrated that higher AHR expression as well

as omeprazole-mediated activation of AHR decreased EMT signatures in H1975 shScr

cells compared to AHR-deficient cells, thus suggesting a negative correlation between

AHR and EMT (5.5.1). Hence, silencing of AHR expression during cancer progression

might endow tumor cells with increased invasive capacity allowing for local invasion of the

surrounding tumor microenvironment.

The loss of epithelial adhesion molecules such as E-cadherin has been demonstrated to

occur in cells undergoing EMT and was suggested to be advantageous for the process of

metastatic progression (Polyak, Weinberg 2009 , Wirtz et al. 2011). In this work, suppres-

sion of AHR expression in H1975 cells increased cell scattering in tumor cell spheroids

indicating alteration in intercellular adhesion (5.2). Further, colorectal cancer cells

excluded form tumor spheroids showed increased invasiveness (Stadler et al. 2018) and

the loss of E-cadherin was associated with decreased density of spheroids (Ivascu,

Kubbies 2007 , Stadler et al. 2018). As E-cadherin expression was sustained in our H1975

AHR knockdown model, altered spheroid formation ability was not caused by loss of

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Discussion

E-cadherin. However, targeted suppression of AHR increased N-cadherin expression

suggesting a potential role for AHR in the regulation of adhesion molecules (5.2).

Recently, Beerling at al. demonstrated epithelial-mesenchymal plasticity in metastasizing

cells of mammary tumors without exogenous EMT inducers in a mouse model using intra

vital microscopy (Beerling et al. 2016). Additionally, sustained E-cadherin expression dur-

ing metastatic progression has been suggested to be crucial for tumor growth upon

hypoxia (Chu et al. 2013). Interestingly, suppression of E-cadherin was observed during

collective invasion of breast cancer cells allowing for partial perpetuation of intercellular

cohesion whereas its complete loss blocked cell tether formation and ultimately sup-

pressed metastasis formation in vivo (Elisha et al. 2018). In our RNA sequencing analysis,

not only AHR expression but also its ligand-mediated activation affected expression of

EMT gene sets (5.5, 8.1, Supplementary Figure 1). Thus, AHR could potentially mediate

temporary transition between epithelial and mesenchymal cell states depending on the

presence or absence of endogenous ligands. The interplay between EMT-activating

endogenous factors such as TGF-β or hypoxia and AHR expression and activation seems

a promising field to investigate. Interestingly, AHR expression was described to attenuate

basal and TGF-β-induced EMT in murine keratinocytes and epithelial NMuMG cells (Rico-

Leo et al. 2013).

In order to enter the circulation, disseminating tumor cells have to overcome and degrade

the extracellular matrix (ECM) as well as the basement membrane (BM) surrounding the

primary tumor. Degradation of ECM molecules facilitates tumor cell invasion and migration

(Conlon, Murray 2019). In H1975, targeted suppression of AHR was associated with ele-

vated expression of several MMPs including MMP9, MMP19 and MMP24 stressing a role

of AHR in acquisition of invasive phenotypes in EGFR-mutant adenocarcinomas (5.5.1).

In concordance with our results from the AHR knockdown model, Okimoto et al. demon-

strated MMP24-dependent gain of metastatic competence in H1975 cells after genomic

loss of Capicua (CIC) (Okimoto et al. 2017). Importantly, CIC knockout was excluded to

be present in our AHR-deficient cells suggesting an alternative mechanism for MMP

induction (8.1, Supplementary Figure 2). However, the possibility of a post-transcriptional

suppression of CIC mediated by MAPK-ERK signaling as proposed by Okimoto et al. has

not yet been investigated in our AHR knockdown cells. As MMPs are usually secreted as

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Discussion

inactive precursors, we analyzed MMP9 and MMP2 activity using gelatine zymography

(Kleiner, Stetler-Stevenson 1994). Indeed, MMP9 activity was increased in H1975 with

pronounced AHR suppression (5.2). Interestingly, El-Badrawy et al. demonstrated

increased MMP9 expression and activity in NSCLC over healthy tissue which was further

associated with late stage disease (El-Badrawy et al. 2014). Additionally, VEGFR1-

dependent induction of MMP9 in lung endothelial cells has been shown to form pre-

metastatic niches for lung-specific metastasis (Hiratsuka et al. 2002). Hence, AHR-

dependent regulation of MMPs might be a promising target to reduce local invasion as

well as formation of pre-metastatic niches induced by secretion of MMPs.

A reciprocal modulation of EMT and ECM has been demonstrated in several studies.

Collagen, as one of the major components of the ECM, has been implicated in tumor

progression and metastatic homing to the lung (Lee et al. 2019, Liu et al. 2018, Nerenberg

et al. 2007). Our RNA sequencing results indicate an upregulation of several types of

collagens and collagen-crosslinking enzymes of the lysyl oxidase family upon suppression

of AHR expression (5.5.1). Interestingly, Peng et al. demonstrated increased collagen

deposition and ZEB1-mediated crosslinking of planar collagen fibers in metastatic tumors

compared to non-metastatic tumors in a mouse model of lung cancer using subcutaneous

transplantation (Peng et al. 2017). Furthermore, signaling via collagen binding receptors

such as discoidin domain-containing receptor 1 (DDR1) was demonstrated to increase

invasiveness and metastatic homing to the lung in bladder cancer models (Lee

et al. 2019). Synthesis of collagen was inhibited upon activation of AHR in a study using

intestinal fibroblasts (Monteleone et al. 2016) further supporting an AHR-mediated

regulation of collagen formation, stabilization and signaling. Collectively, our findings

strongly support an impact of AHR on EMT-mediated matrix remodeling and on the tumor

microenvironment.

During metastatic progression, disseminating tumor cells are exposed to numerous stress

stimuli including oxidative pressure as well as nutrient and oxygen limiting conditions

(Lambert et al. 2017). Interestingly, activation of AHR by omeprazole was associated with

increased unfolded protein response (UPR) signaling as demonstrated in the gene set

enrichment analysis (5.5, 5.5.2). In contrast to exhibiting increased EMT and MMP activity,

AHR-deficient cells appeared to attenuate omeprazole-induced stress response genes

75

Discussion

including activating transcription factor 4 (ATF4), DNA damage inducible transcript 3

(DDIT3 also known as CHOP) and asparagine synthetase (ASNS). Previously, ATF4 has

been demonstrated to induce ASNS in oncogenic KRAS models (Gwinn et al. 2018).

Figure 30: Proposed regulatory AHR-ATF4-ASNS axis. AHR-dependent induction of ASNS expression is ATF4-

dependent and attenuated in H1975 expressing shAHR which exhibit increased metastatic potential.

Using RNAi, we here could demonstrate for the first time that induction of ASNS

expression by activation of AHR via omeprazole is requiring ATF4 in oncogenic EGFR-

and Ras-driven adenocarcinomas (5.5.2). This strongly supports our hypothesis of a

regulatory AHR-ATF4-ASNS axis in lung cancer (Figure 30). Further, omeprazole-

mediated induction of CHOP expression, a key mediator in ER stress-induced apoptosis

that is transcriptionally regulated by ATF4, was attenuated upon AHR knockdown (5.5.2).

The UPR signaling is induced by ER-stress, hypoxia, oxidative stress and nutritional

limitations leading to intrinsic activation of apoptotic pathways in the absence of adaptation

processes (Vandewynckel et al. 2013). Our results demonstrate suppressed induction of

UPR signaling in AHR-deficient H1975 cells which might confer survival advantages upon

exogenous stress stimuli experienced during metastatic dissemination. The impact of

AHR on expression and activation of UPR mediators after exogenous stress remains to

be experimentally determined. Additionally, AHR activation mediated the induction of

ASNS and ATF4 in colorectal cancer (CRC) cells suggesting a potential general validity

also in other entities (5.5.3). Additionally, SW620 cells derived from the metastatic lesion

76

Discussion

of a CRC patient displayed lower AHR expression as well as attenuated ASNS induction

compared to the non-metastatic SW480 cells derived from the primary tumor from the

same patient. Hence, AHR apparently was downregulated before or upon metastatic pro-

gression in this patient-derived CRC model complementing our concept of AHR as

metastatic suppressor.

Once that a growing tumor exceeds two millimeter in diameter, cancer cells start to get

deprived of nutrients and oxygen (Weber 2016). In order to evade apoptosis induced by

persistent nutrient lack or hypoxia, cancer cells exhibit major remodeling of metabolic

dependencies and pathways (Elia et al. 2018 , Vandewynckel et al. 2013). Tumor cells

show increased glucose uptake and catabolism via oxidative glycolysis, also known as

Warburg effect. However, this phenomenon is frequently replaced by alternative routes of

energy supply during metastasis as the lack of cellular adhesion impairs the glucose

metabolism (Celià-Terrassa, Kang 2016 , Elia et al. 2018 , Weber 2016). Thus, the

important role of supply with other metabolites such as amino acids has been discussed

more recently with regard to tumor progression.

Emerging evidence suggests a rate-limiting role for cytosolic aspartate in terms of tumor

growth under glutamine deprived conditions (Alkan et al. 2018). Further, aspartate was

limiting for tumor growth under hypoxic conditions as mimicked by electron transport chain

(ETC) inhibition (Garcia-Bermudez et al. 2018 , Sullivan et al. 2018). Garcia-

Bermudez et al. showed that expression of SLC1A3, an aspartate-glutamate transporter,

can rescue sensitivity to ETC inhibition by enabling the import of aspartate from the extra-

cellular space (Garcia-Bermudez et al. 2018). However, no evidence for SLC1A3 expres-

sion was found in our cell model. In contrast, exogenous supply with asparagine could

rescue growth arrest of cancer cells under glutamine deprivation (Pavlova et al. 2018). In

our AHR knockdown models, ATF4-mediated induction of ASNS was repressed and fur-

ther a decreased sensitivity to glutamine withdrawal was found (5.5.2, 5.6). ASNS is a

metabolic enzyme converting asparagine form aspartate in a glutamine- and ATP-

dependent manner (Andrulis et al. 1987, Krall et al. 2016). Thus, we hypothesize that

blockade of ASNS induction in AHR-deficient cancer cells shifts the equilibrium to

increased cytosolic aspartate levels which in turn might facilitate cancer cell growth under

limiting nutrient and oxygen conditions. Although targeted suppression of ASNS partially

77

Discussion

mimicked the phenotype of AHR-deficient H1975 with regard to glutamine dependency, it

was not sufficient to phenocopy the alterations in the metastatic capacity in terms of

invasion and MMP activity (5.6). Hence, AHR modulates additional, ASNS-independent

programs to suppress lung cancer metastasis.

Taken together, downregulation of endogenous AHR increased metabolic stress

resistance of lung cancer cells suggesting a dynamic role of AHR in metabolic reprogram-

ming potentially regulated by varying exogenous stimuli such as endogenous indole

derivatives including kynurenine. Due to the highly artificial nutrient conditions applied

during in vitro settings, the impact of AHR on metabolic programs in EGFR-mutant lung

cancer needs to be validated using in vivo models.

Upon dissemination, epithelial cancer cells require alteration of their intercellular adhe-

sions in order to overcome their immobility and enable translocation from the primary

tumor. Here, the concept of phenotypic plasticity has been introduced by Nieto et al. sug-

gesting EMT-related phenotypic changes including the regulation of epithelial and

mesenchymal adhesion molecules (Nieto et al. 2016).

Albeit we did see AHR-mediated alterations in spheroid formation capacity and expression

of adhesion molecules, the adhesion of H1975 to endothelial cells was not affected by

AHR expression or activation neither in vitro nor in vivo (5.3, 5.7). However, as tumor cell

transplantation was achieved by intravenous injection in the absence of a primary tumor,

there are some limitations to conclusions drawn from this experiment as this model fails

to recapitulate the complexity of the metastatic cascade. On the other hand, these results

might also imply that the suppression of AHR is more relevant for invasion and/or

metastatic seeding, which are mostly neglected in this experimental setting. As emerging

evidence suggest a crucial role for colonization during the metastatic process, the impact

of AHR expression and activation on metastatic seeding and outgrowth of metastases

should be analyzed in more detail. Further, AHR has been implicated in the regulation of

immune effector cells and suppression of tumor immunity (Gutiérrez-Vázquez,

Quintana 2018, Rothhammer, Quintana 2019). As we here evaluated the impact of

endogenous AHR in human adenocarcinoma models H1975 and A549, our in vivo

experiments were limited to immunocompromised mouse strains. Although the role of

AHR on immune system functions are certainly important, results obtained from

78

Discussion

immunocompetent mouse models will be of limited value due to only 80 % sequence

homology of murine and human AHR. Therefore, humanized mouse model or

retrospective analysis of patient samples should be considered.

6.3 AHR-regulated pathways as a target in anti-metastatic therapy of lung cancer

Current therapies to prevent or target metastases are basically the same as applied for

eradication of the primary tumor disregarding their biological differences. Development of

effective anti-metastatic therapies therefore requires dissection of molecular mechanisms

underlying metastatic progression to identify specific targets that are crucial for the

formation of metastases (Anderson et al. 2019 , Lambert et al. 2017).

Our findings are complemented by clinical data from publicly available databases (5.4,

(Győrffy et al. 2013)), which indicate that evaluation of AHR expression in primary adeno-

carcinomas after resection is promising to identify a subgroup of patients facing a higher

risk to suffer from metastatic relapse. However, the validity of AHR as a clinical biomarker

remains to be determined by additional clinical trials. Further, it is tempting to speculate

that hyperactivation of suppressed AHR and AHR-regulated anti-metastatic programs in

a neoadjuvant or adjuvant setting might prevent metastatic progression in early stage lung

cancer. A variety of xenobiotic as well as some endogenous AHR agonist have been iden-

tified that exhibit different binding affinities and induce tissue- and ligand-specific regula-

tion patterns (Denison, Faber 2017 , Murray et al. 2014). Thus, the complexity of regulatory

networks induced upon AHR activation as well as the evidence for pro-tumorigenic func-

tions of AHR have to be carefully considered in terms of therapeutic interventions targeting

AHR and its downstream effectors. Activation of AHR by its ligand omeprazole has been

suggested to inhibit cancer cell metastasis in preclinical models of breast cancer (Jin

et al. 2014). Interestingly, omeprazole is a proton pump inhibitor (PPI), which is commonly

utilized in the treatment of co-morbidities during the therapy of cancer patients

(Tvingsholm et al. 2018). However, the administration of omeprazole could not yet been

linked to clinical outcomes of cancer patients (An et al. 2018). Further, an accurate evalu-

ation whether PPIs impact clinical outcomes with special regard to metastatic progression

might be challenging due to its frequent application among cancer patients and therefore

lack of control groups. The role of other AHR ligands in the therapy of lung cancer remains

to be investigated.

79

Discussion

With regard to matrix remodeling and invasion, MMP inhibitors were considered as

potential anti-metastatic therapeutics. However, broad spectrum MMP inhibitors such as

marimastat and prinomastat failed to show robust clinical activity until now while showing

serious adverse effects. This might be due to the fact that clinical trials were conducted in

late stage disease in contrast to the preclinical models starting treatment before or soon

after tumor implantation (Anderson et al. 2019 , Overall, Kleifeld 2006 , Zucker et al. 2000).

However, the development of more specific MMP inhibitors might improve safety profiles

and enable their application in adjuvant treatment settings in order to prevent metastasis

in high-risk populations. Further, small molecule inhibitors targeting lysyl oxidases have

demonstrated anti-metastatic effects in preclinical models (Anderson et al. 2019 , Tang

et al. 2017).

In our studies, UPR signaling was significantly attenuated in AHR-deficient H1975 cells

exhibiting gain of metastatic capacity (5.5, 5.5.2). Therefore, reactivation of these path-

ways might be capable to induce UPR-mediated apoptosis in disseminated cancer cells.

However, therapeutic targeting of the UPR remains challenging due to the complexity of

the UPR signaling network including alternative routes of activation that could cause

severe adverse effects (Vandewynckel et al. 2013). Administration of global UPR activa-

tors such as thapsigargin have been demonstrated to provoke acute toxicity, so that tar-

geted strategies are more promising and currently under investigation (Axten et al. 2012).

As we demonstrated suppression of ASNS inducibiltiy in both metastatic H1975 shAHR

and SW620 cells as compared to their non-metastatic controls (5.5.2, 5.5.3), reactivation

of this pathway might present a promising strategy to prevent metastatic seeding.

However, ASNS knockdown was not sufficient to recapitulate the gain in metastatic

capacity as observed in H1975 upon AHR loss. Hence, other AHR-mediated pathways

should be prioritized for therapeutic interventions. Still, a better mechanistic understanding

of metabolic dependencies is of great interest for the diagnosis and therapy of metastases.

In order to investigate the clinical correlation of AHR and its targets identified in this study

including ASNS, ATF4 and MMP24, we are currently establishing protocols for the retro-

spective analysis of tissue from resected lung cancer patients using RNA scope in collab-

oration with the pathology of the University Hospital Essen.

80

Discussion

Stratification of patients by AHR expression and activation signatures should be further

validated. If these findings substantiate, they could complement established treatment

modalities such as adjuvant chemo-, radio- or targeted therapy potentially and ultimately

improve OS and progression free survival (PFS) in patients with lung adenocarcinomas.

6.4 Conclusion and outlook

In summary, our findings strongly support a role for AHR as suppressor of lung cancer

metastasis. Downregulation of endogenous AHR conferred a metastatic phenotype in a

legit in vivo model. AHR is a sensor and regulator of the endogenous defense system

against xenobiotic chemicals being responsible for their decomposition and elimination.

AHR suppression in lung cancer cells correlated with increased metabolic stress

resistance and invasiveness. Intriguingly, we here show that AHR orchestrates anti-

metastatic programs which require suppression in order to enable metastatic progression.

The clinical relevance of our findings is supported by the inferior outcomes of patients with

early stage or advanced lung adenocarcinomas exhibiting low endogenous AHR expres-

sion. Thus, AHR regulated pathways display promising therapeutic targets in the preven-

tion of metastasis in lung cancer. However, the complexity of AHR signaling networks and

pleiotropic effects requires careful study design to achieve the intended clinical outcomes.

Further, AHR has been demonstrated to regulate tumor immunity suggesting a potential

role of AHR for the immune evasion during metastatic progression.

Altogether, our findings validate AHR as suppressor of metastasis of EGFR-mutant lung

cancer and suggest AHR-regulated anti-metastatic programs as potential targets for the

development of novel and specific pharmacologic strategies to prevent metastasis in early

stage lung cancer.

81

References

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101

Appendix

8 APPENDIX

8.1 Supplementary figures

Supplementary Figure 1: Gene set enrichment analysis links AHR activation to the EMT cancer hallmark. A) Enrichment plot for gene set ‘Epithelial-Mesenchymal-Transition’ (EMT) enriched in H1975 shScr control (shScr -) compared to the shScr omeprazole (shScr +). B) Enrichment plot for gene set ‘Epithelial-Mesenchymal-Transition’

(EMT) enriched in H1975 shAHR-K2 control (shAHR -) compared to the shAHR-K2 omeprazole (shAHR +). Biological replicates are indicated with I, II and III.

Supplementary Figure 2: No genetic loss of Capicua (CIC) was detected in H1975 expressing shAHR. CIC expression in H1975 shScr and H1975 shAHR-K2 (A) and GFP+Luc+ H1975 shScr and H1975 shAHR-K2 cells (B) was assessd by qRT-PCR analysis. mRNA levels were normalized to ACTB and GAPDH relative to the respective control. Mean ± SD of the two house keeping genes (HKG) is displayed. Significance was assessed using student’s t-test.

102

Appendix

8.2 Materials and reagents

8.2.1 Eukaryotic cell lines

Table 7: Cell lines used and established in this project.

cell line tissue properties source

A549 human lung

adenocarcinoma

KRAS Codon 12

mutation (G12S),

EGFR

overexpression

Molecular

Oncology group,

purchased from

ATCC

NCI-H1299 (referred to

as H1299)

human lung

adenocarcinoma

p53 deletion, NRAS

mutation (Q61K)

Molecular

Oncology group,

purchased from

ATCC

NCI-H1975 (referred to

as H1975)

human lung

adenocarcinoma

EGFR double

mutation (L858R,

T790M)

Molecular

Oncology group,

purchased from

ATCC

H1975 shRNA AHR K1 human lung

adenocarcinoma

cell clone K1 stably

transduced with

pLKO.1-shRNA

AHR vector

present work

H1975 shRNA AHR K2 human lung

adenocarcinoma

cell clone K2 stably

transduced with

pLKO.1-shRNA

AHR vector

present work

H1975 shRNA AHR K3 human lung

adenocarcinoma

cell clone K3 stably

transduced with

pLKO.1-shRNA

AHR vector

present work

H1975 shRNA ASNS K1 human lung

adenocarcinoma

cell clone K1 stably

transduced with

pGFP-V-RS -shRNA

ASNS-A vector

present work

H1975 shRNA ASNS K2 human lung

adenocarcinoma

cell clone K2 stably

transduced with

pGFP-V-RS -shRNA

ASNS-A vector

present work

103

Appendix

H1975 shRNA ASNS K3 human lung

adenocarcinoma

cell clone K3 stably

transduced with

pGFP-V-RS -shRNA

ASNS-B vector

present work

H1975 shScr (lenti) human lung

adenocarcinoma

stably transduced

with pLKO.1-non

targeting shRNA

present work

H1975 shScr (retro) human lung

adenocarcinoma

stably transduced

with pGFP-V-RS-

non targeting

shRNA

present work

HEK283FT human embryonic

kidney

viral packaging cells Scholl/Fröhling

group

hTERT-HUVEC

(T-HUVEC)

human umbilical

vein endothelial

cells

immortalized with

expression of

hTERT

Grüner group

Phoenix (FNX) human embryonic

kidney

viral packaging cells Nolan lab,

Stanford

University, USA

SW480 human colorectal

carcinoma

established from

primary tumor

Molecular

Oncology group,

purchased from

ATCC

SW620 human colorectal

carcinoma

established from

metastatic

recurrence in lymph

node from the same

patient as SW480

Molecular

Oncology group,

purchased from

ATCC

104

Appendix

8.2.2 Plasmids and primers

Table 8: Plasmids used and generated in this project.

name properties manufacturer

EGFP-ffluc epHIV7 lentiviral vector encoding

EGFP and Luciferase

Dr. Michael Jensen,

Seattle

Hit60 (MLV gag-pol) retroviral packaging vector

(gag-pol expression)

C. Benedict

MSCV-tdTomato-PGK-

Neo

retroviral vector, neomycin

resistance

Dr. Barbara M.

Grüner

MSCV-PGK-Neo

(referred to as MSCV

vector or empty vector)

MSCV-tdTomato-PGK-Neo

truncated for tdTomato

Dr. Sophie Kalmbach

MSCV-CDS-AHR (AHR

rescue vector)

CDS of AHR with 5 silent

point mutations cloned into

MSCV-PGK-Neo

present work

pCMV.VSV-G retroviral packaging vector

(envelope protein

expression)

W. Nishioka

pGFP-V-RS shRNA scr

retroviral vector with non-

targeting shRNA, puromycin

resistance

OriGene

pGFP-V-RS

shRNA ASNS-A

retroviral vector with shRNA-

A targeting ASNS,

puromycin resistance

OriGene

pGFP-V-RS

shRNA ASNS-B

retroviral vector with shRNA-

B targeting ASNS,

puromycin resistance

OriGene

pLKO.1-shRNA AHR lentiviral vector with shRNA

targeting AHR gene,

puromycin resistance

Sigma-Aldrich

pLKO.1-shRNA scr lentiviral vector with non-

mammilian target shRNA,

puromycin resistance

Sigma-Aldrich

pMD2.VSV-G lentiviral packaging vector

(envelope protein

expression)

Scholl/Fröhling group

pSPAX lentiviral packaging vector

(gag-pol expression)

Scholl/Fröhling group

105

Appendix

Table 9: Oligonucleotide primers used for qRT-PCR. All primers are targeting human genes.

gene sequence (5’ - 3’) comment

ACTB For - GGATTCCTATGTGGGCG

Rev - GGCGTACAGGGATAGC

AHR For - TACCGAAGACCGAGCTGAAT

Rev - GGAGACCAGTGGCTTCTTCA

ATF4 For - n/a Qiagen QuantiTect®

Primer Assay Rev - n/a

ASNS For - TCACTTCCAATATGATCTGCCA IDT RTU mix

Rev - AGTACAGTATCCTCTCCAGACA

CDH1 For - TGCCCAGAAAATGAAAAAGG

Rev - GTGTATGTGGCAATGCGTTC

CDH2 For - ACAGTGGCCACCTACAAAGG

Rev - CCGAGATGGGGTTGATAATG

CHOP For - AGAACCAGGAAACGGAAACAGA

Rev - TCTCCTTCATGCGCTGCTTT

CIC For - TGGAGGGAAAGATGTCTGCA

Rev - ATGACAAGGTGCCATACTCC

CYP1A1 For - CCCAGCTCAGCTCAGTACCT

Rev - AGGCCCTGATTACCCAGAAT

GAPDH For - ATTGCCCTCAACGACCACT

Rev - TCTTCCTCTTGTGCTCTTGCT

HPRT1 For - GCGATGTCAATAGGACTCCAG IDT RTU mix

Rev - TTGTTGTAGGATATGCCCTTGA

MMP9 For - GCACGACGTCTTCCAGTACC (Safranek et al.

2009) Rev - CAGGATGTCATAGGTCACGTAGC

MMP19 For - TTCCGAGTGTCTGCCCTTTG

Rev - ATCCATTGTGTTCGAGGCGA

MMP24 For - GGGGCGAGATGTTTGTCTTT

Rev - TCCCATCGGCCCTTTCATAG

106

Appendix

8.2.3 Antibodies

Table 10: Antibodies used in this project.

antibody source manufacturer

primary antibodies

anti-Actin mouse MP Biomedicals

anti-AHR rabbit Cell Signaling

anti-ASNS rabbit Thermo Fisher Scientific

anti-ATF4 rabbit Cell Signaling

anti-MMP24 rabbit GeneTex

secondary antibodies

anti-mouse (HRP-

conjugated)

goat Pierce Antibodies

anti-rabbit (HRP-

conjugated)

goat Pierce Antibodies

8.2.4 Commercial kits

Table 11: Commercial kits used in this project.

kit manufacturer

GeneArtTM Site-Directed Mutagenesis System

Kit

Thermo Fisher Scientific

LightCycler 480 SYBR Green I Master Roche Molecular Systems, Inc.

PCR Purification Kit Qiagen

High Pure RNA Isolation Kit Roche Molecular Systems, Inc

One ShotTM Stbl3TM E. coli invitrogen

QIAGEN Plasmid Plus Maxi Kit Qiagen

QIAprep Spin Miniprep Kit Qiagen

QIAquick Gel Extraction Kit Qiagen

RNeasy Mini Kit Qiagen

Screen Tape Kit Agilent

Trans-Blot® Turbo™ RTA Mini Nitrocellulose

Transfer Kit

BioRad

Transcriptor High Fidelity cDNA Synthesis Kit Roche Molecular Systems, Inc

107

Appendix

8.2.5 Chemicals

Table 12: Chemicals and reagents used in this project.

chemical/reagent manufacturer

3-(4,5-Dimethylthiazole-2-yl)-2,5-diphenyl-2H-

tetrazolium bromide (MTT)

Carl Roth

acetic acid Carl Roth

acrylamide solution (Rothiphorese Gel 30) Carl Roth

agarose Thermo Fisher Scientific

ammonium persulfate (APS) Merck

ampicillin Sigma-Aldrich

aqua (A. dest) Braun

bromphenol blue Sigma-Aldrich

Circlegrow® (Capsules) MP Biomedicals

collagenase PAN BioTech

comassie Blue Roth

cOmplete protease inhibitor cocktail 25X Roche

4′,6-diamidino-2-phenylindole (DAPI) Carl Roth

dimethylsulfoxid (DMSO) Sigma-Aldrich

DNaseI Sigma-Aldrich

entellan Merck

ethanol absolute Sigma-Aldrich

ethidium bromide solution (0.025%) Carl Roth

ethylenediaminetetraacetic acid (EDTA) Carl Roth

fetal bovine serum (FBS) PAN Biotech

HEPES Carl Roth

gelatine (porcine) Sigma-Aldrich

glyerol Carl Roth

glycine Carl Roth

isopropanol Merck

kanamycin Carl Roth

methanol Fluka

β-mercaptoethanol Carl Roth

Nonidet® P 40 Substitute

[Nonylphenylployethylene glycol] (NP40)

Fluka

O’GeneRulerTM DNA Ladder Mix Fermentas

omeprazole Sigma-Aldrich

Page Ruler Pre-Stained Protein Ladder Fermentas

PBS powder 9.55 g/l, w/o Ca2+, w/o Mg2+ Biochrom

108

Appendix

phosphatase Inhibitor Cocktail 2 Sigma-Aldrich

phosphatase Inhibitor Cocktail 3 Sigma-Aldrich

polybrene Sigma-Aldrich

ponceau S Carl Roth

puromycin, dihydratechloride Calbiochem

sodium chloride Carl Roth

sodium deoxycholate Fluka

sodium dodecyl sulfate (SDS) pellets Carl Roth

T4 DNA ligase New England Biolabs

tetramethylethylenediamine (TEMED) Sigma-Aldrich

TRIS Carl Roth

triton X-100 Carl Roth

tween-20 Carl Roth

8.2.6 Media, reagents and commercial buffers

Table 13: Media, reagents and commercial buffers used in this project.

media/reagent/buffer manufacturer

6X Orange DNA Loading Dye Fermentas

AccuPrime Polymerase invitrogen

bradford reagent BioRad

collagenase IV PAN Biotech

crystal violet solution, 1%, aqueous Sigma-Aldrich

dispase Corning

DMEM gibco

D-PBS, w/o Ca2+, w/o Mg2+ gibco

FuGene HD Transfection Reagent Promega

fibronectin Merck

Leibovitz’s L-15 medium Thermo Fisher Scientific

L-glutamine 200 mM (L-Glu) gibco

Lipofectamine® RNAiMAX Reagent invitrogen

MISSION® esiRNA targeting human ATF4 Sigma-Aldrich

MISSION® siRNA Universal Negative Control Sigma-Aldrich

neomycin (G418) Carl Roth

opti-MEM I Reduced Serum Medium gibco

Penicillin-Streptomycin (Pen/Strep) gibco

Restore™ Western Blot Stripping Buffer Thermo Fisher Scientific

RPMI Medium 1640 gibco

109

Appendix

SuperSignalTM West Pico Chemiluminescence

Substrate

Thermo Fisher Scientific

SuperSignalTM West Femto

Chemiluminescence Substrate

Thermo Fisher Scientific

T4 DNA Ligase Buffer (10X) New England Biolabs

0.05% trypsin-EDTA (1X) gibco

trypan Blue stain 0.4% invitrogen

8.2.7 Buffers and solutions

Table 14: Buffers and solutions used in this project. If not indicated otherwise A. dest was used to prepare buffers.

buffer/solution components

10X NET-G 1.5 M NaCl

50 mM EDTA

500 mM Tris-HCl, pH 7.5

0.5 % Tween-20

0.4 % gelatine (porcine)

5X non-reducing zymography

sample buffer

400 mM Tris, pH 6.8,

5 % SDS

20 % gycerol

0.03 % bromphenol blue

5X SDS-PAGE running buffer 125 mM Tris

960 mM glycine

175 mM SDS

5X SDS-PAGE sample buffer 250 mM Tris-HCl (pH 6.8)

8 % SDS

40 % glycerol

200 mM β-Mercaptoethanol

0.2 % bromphenol blue

50X TAE 2 M Tris

250 mM acetic acid

50 mM EDTA

10X ACK buffer 1.5 M NH4Cl

100 mM KHCO3

10 mM EDTA

blocking solution (1X NET-G) 10X NET-G diluted 1:10

digestion medium 1 mg/ml collagenase IV

10 % dispase

10 % trypsin-EDTA (0.05%)

110

Appendix

in HBSS-free (w/o Ca2+ and Mg2+)

FACS buffer 2 % FBS

in D-PBS

FACS buffer (for in vivo stress

assay)

2 % FBS

2 mM EDTA

in D-PBS

MTT solution 5 mg/ml MTT

in D-PBS

MTT solubilization buffer 10% SDS

0.01 M HCl

NP40 lysis buffer 50 mM HEPES

250 mM NaCl

5 mM EDTA

0.1 % NP40

before use complemented with

1:25 cOmplete 25X stock solution,

1:100 Phosphatase Inhibitor Cocktail 2 & 3

ponceau S solution 0.2 % ponceau S

5 % acetic acid

RIPA lysis buffer

150 mM NaCl

50 mM Tris-HCl (pH 8)

1 % triton X-100

0.5 % sodium deoxycholate

0.1 % SDS

before use complemented with

1:25 cOmplete 25X stock solution,

1:100 Phosphatase Inhibitor Cocktail 2 & 3

quench solution 10 % FBS

18.75 mg/ml DNaseI

in L15 medium

SDS-PAGE stacking gel solution 5 % acrylamide

126 mM Tris-HCl, pH 6.8

0.1 % SDS

0.1 % APS

0.1% TEMED

SDS-PAGE resolving gel solution 8-12 % acrylamide

380 mM Tris-HCl, pH 8.8

0.1 % SDS

0.1 % APS

0.04% TEMED

111

Appendix

zymography enzyme buffer 50 mM Tris-HCl, pH 7.5

200 mM NaCl

5 mM CaCl2

1 % Triton X-100

8.2.8 Restriction enzymes and buffers

Table 15: Restriction enzymes and buffers used in this project.

name concentration manufacturer

FspAI 5 U/µl Thermo Fisher Scientific

BglII 10 U/µl Thermo Fisher Scientific

buffer O 10X Thermo Fisher Scientific

8.2.9 Consumables

Table 16: Consumables used in this project.

item manufacturer

0.2 µm filter Sartorius

0.45 µm filter Sartorius

10 cm dishes BD Falcon

6 well plate BD Falcon

12 well plate BD Falcon

15 ml Falcon tubes Greiner bio-one

24 well plate BD Falcon

40 µm cell mesh BD Falcon

50 ml Falcon tubes Greiner bio-one

96 well plate Corning

96 well plate with cell repellent surface Greiner bio-one

BioCoatTM GFR Matrigel Invasion

Chambers (8.0 µm)

Corning

BioCoatTM control inserts (8.0 µm) Corning

CountessTM cell counting chamber slides invitrogen

cuvettes, semi-micro, PS LLG Labware

eppendorf tubes Eppendorf

FACS tubes Greiner bio-one

microscope slides VWR

cover slips VWR

pasteur pipettes Brand

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Appendix

pipette tips Greiner bio-one

serological pipettes Greiner bio-one

8.2.10 Technical equipment

Table 17: Technical equipment used in this project.

device manufacturer

AxioObserver.Z1 Zeiss

BD FACSVantage SE BD Biosciences

BIOREVO BZ-9000 Keyence

centrifuges

SORVALL® RC 6 PLUS

Rotor: SLA-1500

Heraeus MultiFuge 3RS+

Rotor: Swing-out rotor, 4-place

Mikro 200R

Rotor: Angle rotor, 24-place

Thermo Scientific

Thermo Scientific

Thermo Scientific

DJB Labcare

Hettich

Hettich

Chemiluminescence-imager

Chemi Smart 5000

Vilber Lourmat

Countess automated cell counter Invitrogen

FACSCelestaTM BD

Heraeus Function Line Thermo Scientific

Incubator HeraCell 1500 CO2 Thermo Fisher Scientific

LightCycler®480 System Roche

Mini-PROTEAN electrophoresis system Bio-Rad

Orbital shaker Sigma-Aldrich

pH electrode InoLab pH720 WWTW

Photometer Gene Quant pro Amersham

NanoDrop lite spectrophotometer Thermo Fisher Scientific

Power Pac 300 BioRad

Primovert microscope Zeiss

Protein electrophoresis system BioRad

Roller mixer SRT6D stuart

Screen Tape Station Agilent

Thermomixer 5436 Eppendorf

Trans-Blot® Turbo™ Transfer System BioRad

Vortexer Bio Vortex V1 Biosan

Water bath 1013 GFL

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Appendix

8.2.11 Software

BD FACSDiva (BD Biosciences)

FlowJo Software (BD Biosciences)

GraphPad Prism (GraphPad Software, version 6)

GSEA software (Broad Institute, Inc., Massachusetts Institute of Technology, version 3.0)

Perseus software (Max Planck Institute for Biochemistry, Martinsried, version 1.5.5.3)

Primer3 (www.primer3plus.com)

Adobe Illustrator CS3 (Adobe Systems)

Adobe Photoshop CS3 (Adobe Systems)

Affinity Designer (Serif, version 1.7.1.404)

ImageJ (Wayne Rasband, NIH, US)

8.3 List of figures

Figure 1: Overview of the metastatic cascade. .............................................................. 17

Figure 2: Model of cellular plasticity through transitional EMT/MET states. ................... 21

Figure 3: Unbiased in vivo shRNA screen using an orthotopic mouse model of lung

cancer. ........................................................................................................................... 40

Figure 4: Suppression of endogenous AHR by stable integration of shAHR into H1975

cells. .............................................................................................................................. 41

Figure 5: shRNA-mediated suppression of AHR increases metastatic potential of H1975

cells in vitro. ................................................................................................................... 42

Figure 6: Intercellular adhesion is altered upon suppression of AHR in H1975 cells. .... 43

Figure 7: AHR cDNA resistant to shAHR was successfully introduced into H1975 cell

models expressing shAHR or shScr. ............................................................................. 45

Figure 8: Reconstitution of AHR expression in H1975 with shRNA-mediated AHR

suppression partially rescued metastatic phenotype observed in vitro. ......................... 46

Figure 9: Targeted suppression of AHR increases metastatic spread of H1975 in an

orthotopic lung cancer mouse model. ............................................................................ 47

114

Appendix

Figure 10: Impact of endogenous AHR expression in lung adenocarcinoma on patient

outcomes following resection. ........................................................................................ 48

Figure 11: Impact of endogenous AHR expression in lung adenocarcinoma on patient

outcomes among all disease stages. ............................................................................. 49

Figure 12: Omeprazole inhibits growth of H1975 cells in an AHR-dependent manner. . 50

Figure 13: Constitutive and induced expression signatures of H1975 shAHR cell models

were identified using mRNA sequencing. ...................................................................... 51

Figure 14: Gene set enrichment analysis links AHR expression and activation to several

cancer hallmarks. .......................................................................................................... 53

Figure 15: AHR regulates expression of matrix-metalloproteases (MMPs) in H1975. ... 54

Figure 16: RNA sequencing results suggest a role of AHR in the regulation of collagen

expression. .................................................................................................................... 55

Figure 17: Suppression of AHR attenuates omeprazole-mediated induction of UPR

signaling genes ASNS, ATF4 and CHOP. ..................................................................... 57

Figure 18: AHR regulates ASNS expression in an ATF4-dependent manner................ 58

Figure 19: AHR and its targets ASNS and ATF4 are differentially regulated in a metastatic

colorectal cell line compared to the corresponding primary, non-metastatic cells. ........ 60

Figure 20: Depletion of AHR increases resistance to L-glutamine withdrawal. .............. 61

Figure 21: Suppression of AHR does not influence sensitivity to CB-839. .................... 62

Figure 22: H1975 are less sensitive to CB-839 treatment and L-glutamine withdrawal

compared to A549 and H1299. ...................................................................................... 62

Figure 23: Suppression of endogenous ASNS by stable integration of shASNS into

H1975. ........................................................................................................................... 63

Figure 24: Suppression of ASNS does not result in increased invasiveness of H1975 cells

in vitro. ........................................................................................................................... 64

Figure 25: Suppression of ASNS does not significantly alter L-glutamine dependency. 65

Figure 26: Impact of endogenous ASNS expression in lung adenocarcinoma on patient

outcomes following resection. ........................................................................................ 65

Figure 27: Schematic overview of in vivo stress assay. ................................................. 66

Figure 28: Effect of AHR expression and activation on environmental stress resistance

and adhesion to the lung in vivo. ................................................................................... 67

115

Appendix

Figure 29: Effect of AHR expression and activation on adhesion to T-HUVEC cells in vitro.

...................................................................................................................................... 68

Figure 30: Proposed regulatory AHR-ATF4-ASNS axis. ............................................... 75

Supplementary Figure 1: Gene set enrichment analysis links AHR activation to the EMT

cancer hallmark. .......................................................................................................... 101

Supplementary Figure 2: No genetic loss of Capicua (CIC) was detected in H1975

expressing shAHR. ...................................................................................................... 101

8.4 List of tables

Table 1: Sequences for shRNAs targeting AHR or ASNS. ............................................ 27

Table 2: PCR program for generation of full-length CDS of AHR. ................................. 28

Table 3: Primer sequences for cloning of rescue vector. ............................................... 29

Table 4: Reaction mixes for restriction digest of MSCV backbone and AHR PCR product.

...................................................................................................................................... 29

Table 5: Primer sequences for AHR mutagenesis. ........................................................ 34

Table 6: Standard protocol for qRT-PCR at LightCycler®480. ...................................... 35

Table 7: Cell lines used and established in this project. .............................................. 102

Table 8: Plasmids used and generated in this project. ................................................ 104

Table 9: Oligonucleotide primers used for qRT-PCR. .................................................. 105

Table 10: Antibodies used in this project. .................................................................... 106

Table 11: Commercial kits used in this project. ........................................................... 106

Table 12: Chemicals and reagents used in this project. .............................................. 107

Table 13: Media, reagents and commercial buffers used in this project. ..................... 108

Table 14: Buffers and solutions used in this project. ................................................... 109

Table 15: Restriction enzymes and buffers used in this project. .................................. 111

Table 16: Consumables used in this project. ............................................................... 111

Table 17: Technical equipment used in this project. .................................................... 112

116

Appendix

8.5 List of abbreviations

ACTB actin beta

AHR aryl hydrocarbon receptor

AJ adherens junction

ANOVA analysis of variance

ALK anaplastic lymphoma kinase

ARNT aryl hydrocarbon receptor nuclear translocator

ASNS asparagine synthetase

ATF4 activating transcription factor 4

ATP adenosine triphosphate

BaP benzo[a]pyrene

BLI bioluminescent imaging

BM basement membrane

BRAF serine/threonine-protein kinase B-raf

BSL-2 biosafety level 2

CBCT cone-beam computed tomography

CDS coding sequence

CFRT conventionally fractionated radiation therapy

CHOP aliase for DDIT3

CM conditioned medium

CNS central nervous system

COL12A1 collagen type XII alpha 1 chain

COL1A1 collagen type I alpha 1 chain

COL1A2 collagen type I alpha 2 chain

COL5A1 collagen type V alpha 1 chain

COL6A2 collagen type VI alpha 2 chain

COL7A1 collagen type VII alpha 1 chain

CRC colorectal cancer

CSC cancer stem cell

CT computed tomography

117

Appendix

CTC circulating tumor cell

CTLA4 cytotoxic T-lymphocyte antigen-4

CYP cytochrome P450

CYP1A1 cytochrome P450 family 1 subfamily A member 1

DDIT3 DNA damage inducible transcript 3

DDR1 discoidin domain-containing receptor 1

DTC disseminated tumor cell

DNA deoxyribonucleic acid

DS desmosome

ECM extracellular matrix

EGFP enhanced green fluorescent protein

EGFR epidermal growth factor receptor

EMT epithelial-mesenchymal transition

EMT-TF epithelial-mesenchymal transition transcription factors

ETC electron transport chain

EV empty vector

FADH2 flavin adenine dinucleotide dihydrogen

FBS fetal bovine serum

FGF fibroblast growth factor

FNX phoenix cells

FP time to first progression

GAPDH glyceraldehyde-3-phosphate dehydrogenase

GFP green fluorescent protein

GFP+ GFP-positive

GLS glutaminase

GLUT1 glucose transporter 1

GSEA gene set enrichment analysis

HER2 human epidermal growth factor 2

HER4 human epidermal growth factor 4

HGF hepatocyte growth factor

118

Appendix

HKG house keeping gene

HPRT1 hypoxanthine phosphoribosyltransferase 1

HRP horseradish peroxidase

HUVEC human umbilicial vein endothelial cells

IL-2 interleukin-2

IMRT intensity modulated radiation therapy

IFN interferon

L-Gln L-glutamine

log2FC log2-fold change

LOX Llysyl oxidase

LOXL1 lysyl oxidase like 1

LOXL2 lysyl oxidase like 2

Luc Luciferase

MET mesenchymal-epithelial transition

miR microRNA

MMP matrix-metalloprotease

mRNA messenger ribonucleic acid

MTT 3-(4,5-Dimethylthiazole-2-yl)-2,5-diphenyl-2H-tetrazolium bromide

NADH nicotinamide adenine dinucleotide hydrogen

ns not significant

NSCLC non-small-cell lung cancer

NTRK neurothrophic tropomyosin receptor kinases

omep omeprazole

OS overall survival

Padj adjusted P-value

PCR polymerase chain reaction

PD-1 programmed cell death-1

PD-L1 programmed cell death ligand-1

PFS progression free survival

PPI proton pump inhibitor

119

Appendix

qRT-PCR quantitative real-time PCR

RET proto-oncogene tyrosine-protein kinase receptor Ret

RNA ribonucleic acid

ROS reactive oxygen species

ROS1 proto-oncogene tyrosine-protein kinase ROS

RT room temperature

SBRT stereotactic body radiation therapy

SCLC small-cell lung cancer

shAHR shRNA targeting AHR

shASNS shRNA targeting ASNS

shRNA small hairpin ribonucleic acid

shScr non-mammalian target shRNA control

STR short tandem repeat

TAA tumor-associated antigens

TCA tricarboxylic acid cycle

TCDD 2,3,7,8-tetrachlorodibenzo-p-dioxin

TEM trans-endothelial migration

TGF-β transforming growth factor-β

T-HUVECs hTERT human umbilicial vein endothelial cells

TJ tight junction

TKI tyrosine kinase inhibitor

TME tumor microenvironment

TNBC triple-negative breast cancer

UCSF University of California, San Francisco

UPR unfolded protein response

VEGF vascular endothelial growth factor

VEGFR2 vascular endothelial growth factor receptor 2

XRE xenobiotic responsive elements

120

Acknowledgements

9 ACKNOWLEDGEMENTS

The work presented in this thesis was supported by funding from the ‘Förderverein Innere

Klinik - Tumorforschung - Essen e.V’ of the University Hospital Essen.

First of all, I would like to thank my supervisor, Prof. Dr. Martin Schuler, for the great

opportunity to perform my PhD project in the Laboratory of Molecular Oncology at the

Department of Medical Oncology of the University Hospital Essen. Further, I would like to

express my deep gratitude for his continuous support, invaluable counsel and guidance.

Special thanks also to Dr. Frank Breitenbücher for the opportunity to be involved in this

interesting and fruitful project as well as for his supervision and all the helpful advice.

Further, I would like to thank him and Dr. Ross A. Okimoto for all their work on the shRNA

screen and the orthotopic mouse model conducted in the group of Dr. Trever G. Bivona

at the UCSF. Additional thanks to Dr. Saurabh Asthana for performing the statistical

analyses of the sequencing data of the shRNA screen.

Many thanks also to Prof. Dr. Alexander Schramm for the supervision and counsel in the

last two years helping to forward the project and prepare the manuscript. Also, I highly

appreciate his rapid proofreading of this thesis.

In addition, I would like to acknowledge the support and advice of Dr. Barbara M. Grüner,

in particular invaluable during the period of lab transitions.

A huge ‘thank you’ to Dr. Sophie Kalmbach for all her support and strength especially

during the times of our ‘two-women lab’. Without you I would not have made it. Further,

I want to thank Jeannette Phasue, Dr. Sarah Wieczorek and Stephanie Meyer for all their

encouragement and the great atmosphere in the ‘AG Schuler lab’. Special thanks also to

Madeleine Dorsch for her scientific input, methodological advice and mental support as

well as to Dr. Marc Schulte for all the productive discussions particularly appreciating his

innovative ideas. Further, I would like to deeply thank Clotilde Thumser-Henner,

Cassandra Ho and Christina Hassiepen not only for their help in the lab but also for their

continuous support and so many fabulous lunch times – of course including Madeleine.

Thank you also to Alicia Tüns, Sabine Dreesmann and Anja Lingott-Frieg for their support

with my experiments and to Sebastian Vogt for solving all sorts of problems occurring in

the lab.

121

Acknowledgements

Moreover, I would like to acknowledge the contribution of the group of Prof. Dr. Michael

Hölzel at the University of Bonn performing the mRNA sequencing and Jan Forster from

the DKTK who conducted the RNA sequencing data preparation. Additional thanks to all

other co-authors that have contributed to this project and provided input for the

manuscript. Further, I would like to thank Prof. Dr. Jens Siveke for providing access to his

laboratory devices as well as Dr. Marija Trajkovic-Arsic, Dr. Sven-Thorsten Liffers and

Konstantinos Savvatakis for their helpful advice. Many thanks also to Prof. Dr. Karl S.

Lang for giving me access to his Keyence microscope. I would like to give credit to the

group of Dr. Alexander Carpinteiro, especially Gabriele Hessler and Melanie Kramer, as

well as to the group of PD Dr. Iris Helfrich, particularly Dr. Stefanie Löffek, for sharing their

methodological and scientific knowledge. Further, I am grateful for the possibility to be

part of the BIOME graduate school and want to thank Delia Cosgrove for the coordination.

Last but not least, I am especially indebted to my family and friends for their unfailing

support and continuous encouragement. Ladies, I am exceptionally grateful for our deep

friendship and want to thank you for all your enduring support and the sorely needed

distractions. Especially, I wish to give thanks to my partner for lovingly bearing with me

also in heavily stressful phases and continuously fostering my confidence. Thank you to

my sister and my brother for providing help and shelter whenever needed. Additional

thanks to my sister and mother for proofreading this thesis. Finally, I am inexpressively

grateful to my parents providing unconditional support, invaluable advice and always

believing in me.

122

Curriculum Vitae

10 CURRICULUM VITAE

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123

Curriculum Vitae

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124

Curriculum Vitae

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125

Declarations

11 DECLARATIONS

Erklärung:

Hiermit erkläre ich, gem. § 6 Abs. (2) g) der Promotionsordnung der Fakultät für Biologie

zur Erlangung der Dr. rer. nat., dass ich das Arbeitsgebiet, dem das Thema „Identification

and characterization of aryl hydrocarbon receptor (AHR) as a suppressor of non-small-

cell lung cancer metastasis“ zuzuordnen ist, in Forschung und Lehre vertrete und den

Antrag von Silke Nothdurft befürworte und die Betreuung auch im Falle eines Weggangs,

wenn nicht wichtige Gründe dem entgegenstehen, weiterführen werde.

________________________________________

Name des Mitglieds der Universität Duisburg-Essen in Druckbuchstaben

Essen, den _________________ ________________________________________

Unterschrift eines Mitglieds der Universität Duisburg-Essen

Erklärung:

Hiermit erkläre ich, gem. § 7 Abs. (2) d) + f) der Promotionsordnung der Fakultät für

Biologie zur Erlangung des Dr. rer. nat., dass ich die vorliegende Dissertation selbständig

verfasst und mich keiner anderen als der angegebenen Hilfsmittel bedient, bei der

Abfassung der Dissertation nur die angegeben Hilfsmittel benutzt und alle wörtlich oder

inhaltlich übernommenen Stellen als solche gekennzeichnet habe.

Essen, den _________________ _______________________________________

Unterschrift des/r Doktoranden/in

Erklärung:

Hiermit erkläre ich, gem. § 7 Abs. (2) e) + g) der Promotionsordnung der Fakultät für

Biologie zur Erlangung des Dr. rer. nat., dass ich keine anderen Promotionen bzw.

Promotionsversuche in der Vergangenheit durchgeführt habe und dass diese Arbeit von

keiner anderen Fakultät/Fachbereich abgelehnt worden ist.

Essen, den _________________ _______________________________________

Unterschrift des/r Doktoranden/in