The Role of Fibulin-2 in ECM-Driven Resistance to Targeted Therapy of Head and Neck Squamous Cell Carcinoma

The Role of Fibulin-2 in ECM-driven Resistance to Targeted Therapy of Head and Neck Squamous Cell Carcinoma

Zanna Decapmaker Student number: 01307098

Promoter Ghent University: Prof Geert van Loo

Erasmus Promoter: Prof Cedric Gaggioli Scientific supervisor: Sanya Kuzet

Master’s dissertation submitted to Ghent University to obtain the degree of Master of Science in Biochemistry and Biotechnology. Major Biomedical Biotechnology

Academic year: 2017- 2018

Department: VIB-Ugent center for inflammation research (IRC), ghent

Department: Institute for Research on Cancer

and Ageing (IRCAN), Nice

Acknowledgements

Firstly, I would like to thank my promotor Dr. Cedric Gaggioli, who welcomed me in his lab at the IRCAN. Thank you for giving me the opportunity to perform my thesis abroad and to live in the beautiful city Nice. I really enjoyed working on this subject and I learned many valuable things. I could always come to you for discussing results and for scientific advice. I am especially grateful to my scientific supervisor, Sanya Kuzet for the guidance, the support and all the life lessons. Next, I would like to thank the other members of the research team for their scientific advice during the period I was working in the lab. Professor Geert van Loo, thank you so much for making time form me when I needed help and for answering all my questions. Thank you to my friends who kept me motivated during the writing process. Laure, thank you for making your home a writing space where we had a lot of writing sessions and Simon for giving me advice on the statistical analysis. Thank you Céline, Vera, Justine and Anais for the support. Finally, I want to express my gratitude to my family and in particular my parents for supporting me all these years, for listening to all my stories about the things I have learned and especially for being there when I needed it.

Table of contents Acknowledgements ...... i Table of contents ...... ii List of abbreviations ...... iv Abstract ...... vi PART 1 : introduction ...... 1 1.1 Cancer is a heterogeneous disease ...... 1 1.2 The tumor-microenvironment plays an import role in cancer development and progression ...... 1 1.2.1 The different players in the tumor-microenvironment ...... 1 1.2.2 Cancer-associated fibroblasts are the most abundant non-malignant cells in the tumor micro-environment ...... 3 1.2.3 Cancer-associated fibroblasts produce and modify the extracellular matrix ...... 4 1.2.4 The role of cancer-associated fibroblasts and the ECM in cancer progression ...... 5 1.3 Head and neck squamous cell carcinoma (HNSCC) ...... 8 1.3.1 Environmental risk factors contribute to the development of HNSCC ...... 8 1.3.2 Molecular parameters involved in HNSCC ...... 10 1.3.3 HNSCC therapy: targeting the epidermal growth factor receptor ...... 11 1.4 Resistance to targeted therapy in head and neck squamous cell carcinoma ...... 13 1.4.1 Multiple mechanisms can lead to resistance to therapy ...... 13 1.4.2 The role of cancer associated fibroblasts and the extracellular matrix in resistance towards targeted therapy ...... 13 1.5 The extracellular matrix protein fibulin-2 and its role in cancer ...... 14 1.5.1 Fibulin-2 is a glycoprotein with repeated domain structure ...... 14 1.5.2 Fibulin-2 engages interactions with many ECM-proteins ...... 14 1.5.3 The function of fibulin-2 in normal development and disease ...... 15 PART 2: AIM ...... 17 PART 3: RESULTS ...... 19 3.1 Preliminary results obtained in the lab ...... 19 3.2 Confirming the efficiency of the siRNA sequences targeting FBLN2 ...... 22 3.3 Confirming the role of fibulin-2 in ECM-derived protection of head and neck squamous cell carcinoma ...... 23 3.3.1 Cell survival of SCC12 cells cultured on CAF(FBLN2 KD)-derived matrix ...... 23 3.3.2 Cell survival of SCC12 cells cultured on cell-derived matrix produced by normal human fibroblasts that were stimulated with human recombinant fibulin-2 ...... 25 3.3.3 Cell survival of CAL27 cultured on CAF(FBLN2 KD)-derived matrix ...... 27

3.4 Studying the matrix properties of NHF- and CAF-derived matrices ...... 29 3.4.1. Matrix properties of CAF (FBLN2 KD)-derived matrices ...... 29 3.5 Unraveling the molecular mechanism involved in FBLN2-driven resistance to targeted therapy in HNSCC ...... 34 3.5.1. Hypothesis ...... 34

3.5.2. A20 expression and EGFR activation in SCC12 cells cultured of CAF(FBLN2 KD)-derived matrix ...... 35 3.5.3. The role of fibulin-2 in actomyosin contractility of fibroblasts ...... 36 PART 5 : DISCUSSION ...... 39 5.1. Preliminary remarks ...... 39 5.2. Confirmation of the role of fibulin-2 in ECM-driven resistance to targeted therapy in head and neck squamous cell carcinoma ...... 40 5.3. Fibilin-2 is important for the structural integrity of cell-derived matrices ...... 41 5.4. Unraveling the molecular mechanism involved in FBLN2-driven resistance to targeted therapy . 43 5.5. Concluding remarks and perspectives ...... 44 5.6. Possible application or implications ...... 45 PART 5: MATERIAL AND METHODS ...... 46 Part 6: References ...... 50 PART 7: ADDENDUM ...... 59 7.1. Experimental procedures ...... 59 7.2. Output generated by SPSS after statistical analysis ...... 65 7.2.1. cell survival of SCC12 cultured on matrix produced by CAFs in which FBLN2 is knocked down by siRNA ...... 65 7.2.2. Cell survival of SCC12 cultured on matrix produced by NHFs that were stimulated with hrFBLN2 ...... 66 7.2.3. Cell survival of CAL27 cultured on CAF (FBLN2 KD)-derived matrix ...... 66 7.2.4. The role of fibulin-2 in contraction of CAF and NHF ...... 67 7.3. Additional data ...... 68 7.3.1. Picrosirius red staining of cell-derived matrix ...... 68

iii

List of abbreviations

4-NQU 4-Nitroquinoline 1-oxide ADH Alcohol dehydrogenase AFM Atomic force microscopy ALDH2 Aldehyde dehydrogenase 2 ATM ataxia telangiectasia mutated Breg cells Regulatory B cells CAF Cancer associated fibroblast CTLA4 cytotoxic T-lymphocyte antigen 4 DC Dendritic cells CYP2E1 cytochrome P450 2E1 DUBs Deubiquitinating enzymes EBV Epstein Barr virus ECM Extracellular matrix EGF Epidermal growth factor EGFR Epidermal growth factor receptor FAP Fibroblast activating protein FBLN2 Fibulin-2 FGF Fibroblast growth factor FN Fibronectin FSP-1 Fibroblast specific protein-1 HNSCC Head and neck squamous cell carcinoma HPV Human papilloma virus hrFBLN2 Human recombinant fibulin-2 IFN-γ Interferon- γ IL-1 Interleukin-1 IRF-1 Interferon regulator factor 1 JAK Janus-activated kinase KD Knock down LOX Lysyl oxidase MMP Matrix metalloproteinase NK cells Natural killer cells NKK 4-(methyl-nitrosamino)-1-(3-pyridyl)-1-1-butanone NSCLC non-small cell lung cancer PD-1high Programmed cell death-1 high Rb Retinoblastoma protein RNAi RNA interference

ROCK Rho-Rho-kinase ROS Reactive oxygen species SCC Squamous cell carcinoma SDS Sodium dodecyl sulfate SLRPs small leucine-rich proteoglycans Α-SMA α-smooth muscle actin STAT3 signal transducer and activator of transcription 3 Th1 cells T helper 1 cells TGF-β Transforming growth factor-β TKI Tyrosine kinase inhibitor TNF-α tumor necrosis factor-α Treg cells Regulatory T cells VEGFR vascular endothelial growth factor receptor

Abstract The project focused on studying and confirming the role of fibulin-2 (FBLN2) in extracellular matrix-driven protection of head and neck squamous cell carcinoma (HNSCC) cells against the tyrosine kinase inhibitor gefitinib. Nowadays it is a well-known fact that tumor initiation and progression not solely depends on cancerous cells, but that the tumor stroma is also involved. Cancer cells and the surrounding stroma altogether are called the tumor microenvironment (TME) which includes immune cells, endothelial cells, cancer associated fibroblasts (CAF), extracellular matrix (ECM) and adipocytes. Head and neck squamous cell carcinoma (HNSCC) is a commonly used model to study the TME in cancer initiation progression since CAF and other TME components are abundantly present in the tumor stroma. Every year, HNSCC affects approximately 500 000 people worldwide and is associated with a highly malignant phenotype. The epidermal growth factor receptor (EGFR) is a rational target for HNSCC treatment as it is expressed or upregulated in 90% of the tumors. Nevertheless, HNSCCs are refractory to EGFR tyrosine kinase inhibitors including gefitinib and the molecular mechanisms of resistance towards TKI therapy are unknown. In order to unravel the role of CAF and ECM in resistance to gefitinib, researchers in the lab of Dr. Cedric Gaggioli identified 52 differentially regulated proteins in CAF- and fibroblast-derived matrix through a proteomic based approach. An RNAi-based screen of the 52 identified proteins revealed FBLN2 as an interesting target to study. FBLN2 is an ECM-protein that belongs to the FBLN-family of glycoproteins and engages strong interactions with other ECM-proteins including fibronectin and nidogen-1. FBLN2 is involved in elastic fiber formation and is abundantly expressed in the aorta and in developing and adult heart valves. Its role in cancer initiation and progression is dual as it has been described both as a tumor suppressor and as an oncogene. In this project we examine its role in the tumor microenvironment and more specifically in the role of ECM-driven resistance to targeted therapy. First, we confirmed that FBLN2 increases cell survival of the squamous cell carcinoma cell lines SCC12 (skin) and CAL27 (tongue) cultured on CAF-derived matrix upon gefitinib treatment. FBLN2 is also essential to maintain the structural integrity of CAF-derived ECM as FBLN2 knockdown in CAF decreases the density and alignment of CAF-derived matrices, while stimulation of quiescent fibroblasts with human recombinant FBLN2 increases the density of fibrils in NHF-derived matrix. In addition, the project provides clues concerning the molecular mechanisms involved. FBLN2 increases A20 and pEGFR expression in SCC12 cells upon EGF stimulation and could potentially be a regulator of actomyosin contractility of CAF.

PART 1 : introduction 1.1 Cancer is a heterogeneous disease Cancer is a multifactorial disease that affects approximately 14 million people every year. Cancer incidence is still rising due to ageing of the population and environmental risk factors such as smoking and obesity (Torre et al, 2015; Parsa, 2012). It is an umbrella term that describes a group of diseases that are characterized by uncontrolled growth and proliferation of cells which have the capacity to invade surrounding tissue. Tumors arise in different cell types including epithelial cells, hematopoietic cells, nerve cells and epithelial cells (Frank, 2007). Mutations that cause cancer occur in 3 broad classes of genes: proto-oncogenes, tumor-suppressor genes and caretaker genes. Proto-oncogenes promote cell growth but activating mutations change them into oncogenes that contribute to the formation of malignant tumors. The opposite applies to tumor- suppressor genes that normally restrain cell growth, however uncontrolled cell division is observed when inactivating mutations arise (Fearon & Vogelstein, 1990; Kinzler & Vogelstein, 1997). The third class of genes which are called caretaker genes are a more specialized group of tumor-suppressor genes that are not directly involved in cell proliferation, but play a role in processes such as cell death and DNA repair (Kinzler & Vogelstein, 1997). Previously, scientists considered tumors as simple tissues and research focused mainly on the genetic alterations in cancer cells. However, it turned out that tumors are complex tissues which resemble ‘organs’ that are made up out of multiple cell types such as immune cells, endothelial cells, adipocytes and fibroblasts. The dynamic environment in which cancer develops is termed the stroma or tumor microenvironment (TME). The TME plays a critical role in tumor initiation, progression and resistance to therapy. Moreover, the TME could be an important factor for finding targets for developing new therapeutic approaches (Bloch & Harel, 2016).

1.2 The tumor-microenvironment plays an import role in cancer development and progression 1.2.1 The different players in the tumor-microenvironment To get a better understanding of the tumor-stroma interactions that take place and how they aid in cancer initiation and progression, it is important to get to know the different players in the TME (Fig. 1). The composition of immune cells in the TME depends on the tumor type and deviates from individual to individual. The subset of immune cells that is present in the tumor is related with the patient’s clinical prognosis. Different T cell populations are observed in tumors, especially at the invasive tumor margin and in draining lymphoid organs. The presence of CD8+ memory T cells, which are supported by CD4+ T helper 1 (Th1) cells, is associated with a good prognosis (Fridman et al, 2012). They suppress tumor growth mainly by producing interferon- γ (IFN-γ) (Hui & Chen, 2015). The role of other T cell populations, such as CD4+ Th2 cells, is more doubtful as they have been associated with both poor and

1 good prognosis (Fridman et al, 2012). In many types of cancer, the presence of CD4+ T regulatory (Treg) cells is related with very poor clinical outcome. Treg cells are characterized by the expression of FOXP3 and CD25 and are the T cell subpopulation that generally suppress the immune system by downregulating the induction and proliferation of T cells in an antigen-dependent manner (Corthay, 2009). They exert their tumor promoting function through the production of interleukin-1 (IL-1), transforming growth factor- β (TGF-β) and cell-mediated contact through cytotoxic T-lymphocyte antigen 4 (CTLA4) (Balkwill et al, 2012; Campbell & Koch, 2011). B-lymphocytes are most commonly observed in draining lymph nodes, but are also present at the invasive margins of tumors. The role of B cells in the TME is dual (Balkwill et al, 2012). B cells are associated with a favorable clinical outcome in some breast cancers, however the mechanism that is involved is largely unknown. These infiltrating B cells are clonally expanded populations that are able to recognize target antigens (e.g. ganglioside D3). They exert their tumor suppressing properties probably by secreting antibodies and by presenting antigens to CD4+ and CD8+ T cells (Balkwill et al, 2012; Milne et al, 2009). Another population of B- cells, called regulatory B cells (Bregs), are recognized to be key immune suppressors that are able to promote tumor growth in some type of cancers. In hepatocellular carcinoma, a programmed cell death-1high (PD-1high) subset of B cells produces IL-10 after triggering of PD-1 by PD-L1. IL-10 is an immuno-suppressive cytokine that after prolonged expression causes T cell dysfunction (Ren et al, 2006; Sarvaria et al, 2017). Another type of immune cells that is abundantly present in the TME are the tumor associated macrophages (TAM). They are associated with poor clinical outcome as they are involved in malignant cell migration, invasion and metastasis (Balkwill et al, 2012). Besides the abovementioned immune cells, dendritic cells (DC) and natural killer (NK) cells are also observed in the TME but will not be discussed in further detail. Angiogenesis is the process that is responsible for the development of the tumor vasculature, which is characterized by chaotic branching of vessels, uneven vessel volume and vessel leakiness. Soluble factors provided by tumor cells and inflammatory cells in the TME stimulate endothelial cells and pericytes which in their turn stimulate angiogenesis and tumor growth. One of the most important angiogenic factors in the TME is VEGF. It is produced by both tumor cells and inflammatory cells and stimulates growth and proliferation of endothelial cells (Carmeliet & Jain, 2011; Balkwill et al, 2012). Tumors can invade existing lymphatic vessels or they can drive lymphangiogenesis by the production of VEGFC or VEGFD (Balkwill et al, 2012). Lymphatics play an important role in the dissemination of cancer cells, however they can also mechanically modulate the TME and therefore affect the progression of cancer. An increased interstitial flow is detected at the tumor margin when there is an increased fluid drainage from the tumor together with a heightened pressure gradient. An increased interstitial flow induces mechanical stress on the ECM and stromal cells. The results is increased TGF-β and stromal stiffening. (Swartz & Lund, 2012; Balkwill et al, 2012) A cell-type that is less frequently observed and studied in the TME are adipose cells. It is known that obesity increases the risk to develop certain types of cancer including prostate and endometrial cancer. Adipocytes in white adipose tissue could potentially act as a potent endocrine organ by secreting growth factors and inflammatory cytokines. The pro- tumorigenic environment created by the adipose tissue could contribute to tumor cell

2 motility, invasion and metastasis, but it is certainly not the only factor that is involved (Gilbert & Slingerland, 2013; Vona-Davis & Gibson, 2013). In addition, adipose stem cells are recruited to the TME by cancer cells, where they can stimulate cancer progression (Zhang et al, 2012).

1.2.2 Cancer-associated fibroblasts are the most abundant non-malignant cells in the tumor micro-environment Fibroblasts are elongated cells from mesenchymal origin which are the principal source of ECM constituents, regulate epithelial differentiation and are involved in wound healing (Tomasek et al, 2002; Kalluri & Zeisberg, 2006). In connective tissue, they are present in a quiescent state but they can become activated through multiple mechanism. Myofibroblasts proliferate increasingly and produce higher amounts of ECM constituents during wound healing. However, they revert to a resting phenotype once the wound is repaired. Activated fibroblasts which are present in the TME are called cancer associated fibroblasts (CAFs) and are constitutively activated, in contrast to activated fibroblasts in wound healing. Activation of CAFs can be mediated through cytokines including TGF-β1, IL-1β, PDGFα, FGF2, IL-6 and LIF (Kalluri & Zeisberg, 2006; Albrengues et al, 2014; Kuzet & Gaggioli, 2016). Other mechanisms that induce activation of CAFs include environmental stimuli such as hypoxia and matrix stiffness (Albrengues et al, 2015). CAFs can be isolated from different types of cancer e.g. breast cancer, lung cancer and HNSCC but are less frequently observed in brain, renal and ovarian cancers (Shiga et al, 2015). There is still no consensus among scientists concerning the origin of CAFs and multiple theories are supported. Possible predecessors include resident tissue fibroblasts, epithelial cells, bone marrow derived mesenchymal stem cells and adipocytes. It is a possibility that CAF are derived from different cell types, which would partly explain their heterogeneity (Shiga et al, 2015). CAFs can be distinguished from normal fibroblasts based on several markers (Fig.2). The most commonly used markers to differentiate CAFs are α-smooth muscle actin (α-SMA) and fibroblast activation protein (FAP), while resting fibroblast only express fibroblast- specific protein-1 (FSP-1). α-SMA is an intermediate-filament-associated protein which increases the contractility of fibroblasts and is a specific marker for myofibroblast. Fibroblast activation protein (FAP), a type II integral membrane protein, is another myofibroblast-specific marker which role is to help degrading ECM proteins. Several other markers such as tenascin-C and vimentin are also reported to be CAF markers. However, it is important to keep in mind that CAFs are a heterogeneous group of cells and that none of the markers is specific for CAF or resting fibroblasts exclusively. Several studies have shown that there can be multiple subpopulations of CAFs in a tumor. Costa and colleagues demonstrated that there are 4 subsets of CAF in breast cancer and that the CAF composition varies in different subtypes of breast cancer (Costa et al, 2018). Also on the cellular level there is a difference between quiescent fibroblasts and CAFs. CAFs have a large euchromatic nucleus with one or two nucleoli as they produce large amounts of ECM constituents. They contain rough endoplasmic reticulum and a prominent Golgi apparatus. In contrast, resting fibroblasts can be recognized by a smaller endoplasmic reticulum and a flattened, heterochromatic nucleus (Tarin & Croft, 1970; Kalluri & Zeisberg, 2006).

Activation of fibroblasts in cancer is primarily mediated by tumor cells through paracrine signaling molecules such as TGF-β and IL-1β. This induces the expression of FAP and the functional marker α-SMA in the activated fibroblasts. TGF-β is known to be one of the dominant factors in the induction of FAPα expression, which can increase the proliferation and migration of fibroblasts (Chen et al, 2009). A study performed by Henrikkson and colleagues confirmed this as their data indicate that colorectal cancer cells are able to transform fibroblasts in activated fibroblasts by inducing FAP-expression. These FAP- positive fibroblasts increase the migratory capacity of the colorectal cancer cells by fibroblasts growth factor 1 (FGF1) expression (Henriksson et al, 2011). The transition of quiescent fibroblast to activated CAF is also mediated by immune cells in the tumor stroma (LeBleu & Kalluri, 2018).

1.2.3 Cancer-associated fibroblasts produce and modify the extracellular matrix The extracellular matrix (ECM) is a dynamic structure that offers structural support to surrounding cells, but also controls fundamental behaviors of cells such as proliferation, migration and apoptosis (Yue, 2014). The ECM is mainly composed out of collagen fibers, elastic fiber, proteoglycans and multi-adhesive matrix proteins such as laminin and fibronectin. These components make up basement membrane, which is a sheet-like network of matrix proteins that outlines epithelia, blood vessels and muscle fibers, and interstitial matrix, which is present in between different cells (Halfter et al, 2015). CAFs are responsible for ECM remodeling in cancer which is mediated by producing, secreting and assembling high amounts of matrix proteins. Deregulated ECM is a cancer hallmark as ECM remodeling in cancer leads to increased matrix stiffening which results in tumor progression, metastasis and chemoresistance. A brief overview of the most important ECM components and their role in cancer follows. Collagen fibers provide mechanic strength and structural integrity to the ECM and approximately 28 different collagen types are identified in vertebrates. The different collagen types are subdivided into fibril-forming collagens (type I, II, III), network-forming collagens (type IV), fibril-associated collagens with interruption in their triple helices (FACITS) and others. Interstitial matrix is mainly composed of type I and type III collagen which are structurally characterized by a triple helical structure (Gelse et al, 2003). Type IV collagen is the most important structural component of basement membranes (Hudson et al, 1993). Fang and colleagues described collagens as a double-edged sword in cancer. Collagen increase and decrease are both involved in tumor progression and collagens are regulators of immune cell infiltration which can promote and inhibit tumor progression (Fang et al, 2014). Fibrous components of the ECM include besides collagens also elastic fibers. They are bundles of proteins made up of elastin and elastic microfibrils which are essential for elastogenesis. Tropoelastin is the 60 kDa, monomeric precursor of elastin and is characterized by its alternating hydrophobic and hydrophilic domain structure (Rodrıguez- Cabello & Alonso, 1999). Microfibrils consist of fibrillins and microfibril-associated proteins including fibulins (Liu et al, 2004). During elastogenesis, tropoelastin is deposed on microfibrils through interaction of its C-terminal domain with the N-terminal domain of the microfibrillar-associated glycoproteins. Cross-linking of tropoelastin leads to the

4 formation of an insoluble elastin-network (Debelle & Tamburro, 1999). Elastin can interact with cancer cells through the two elastin-binding proteins s-gal/EBP and galectin-3. This binding is associated with the metastatic potential of various cancer types including breast cancer (Lapis & Timar, 2002). Fibronectin (FN) is a large, fibrous protein that is directly involved in the organization of both interstitial ECM and basement membrane. FN plays an important role in cell adhesion, migration, growth and differentiation and engages multiple interactions with proteins that are present in the ECM. In addition, FN is a ligand for several proteins of the integrin family whereby it mediates in the binding of the ECM with the intracellular cytoskeleton (Pankov, 2002). It is a dimeric glycoprotein composed out of two 250 kDa subunits, which are connected by a pair of disulfide bonds at their C-termini. (Frantz et al, 2010; Zollinger & Smith, 2017). Basement membranes also contain laminins, which are high-molecular weight proteins characterized by their heterotrimeric structure and their role in tissue morphogenesis and homeostasis (Beck et al, 1993; Hamill et al, 2009). Akhavan and colleagues reported that laminin anchoring at the cell surface is essential for assembly and signaling of the ECM. Moreover, defective laminin anchoring is noticed regularly in aggressive cancer subtypes e.g. aggressive breast cancer, and is associated with poor clinical outcomes (Akhavan et al, 2012). Finally, another essential component of the ECM are proteoglycans which offer structural support in different tissues e.g. aggrecan generates elasticity in cartilage, and are implicated in cell signaling and biological processes such as angiogenesis. All proteoglycans are made up of a core protein to which glycosaminoglycan (GAG) side chains are attached. They are subdivided into three main families: small leucine-rich proteoglycans (SLRPs) (e.g. lumican), modular proteoglycans and cell-surface proteoglycans. (Yue, 2014; Frantz et al, 2010)

1.2.4 The role of cancer-associated fibroblasts and the ECM in cancer progression Scientists believed for a long time that tumor proliferation, invasion and metastasis was mediated by cancer cells themselves, but nowadays it is proven that also CAFs contribute to cancer progression by secreting oncogenic factors, metabolites and modifying the ECM. Firstly, CAFs promote angiogenesis by expressing VEGF and other angiogenic factors such as FGF (Shiga et al, 2015). In addition, they act as a source of energy for cancer cells. Otto H. Warburg postulated that cancer cells rely on glycolysis for the production of ATP, even in the presence of oxygen and called this principle the ‘warburg effect’. The end-products of aerobic glycolysis are pyruvate and lactate which can be secreted by the cancer cells to feed other cancer cells (Pavlides et al, 2009). A decade ago, Vincent and colleagues showed that the Warburg effect is not only confined to cancer cells, but that CAFs display similar bioenergetics (Vincent et al, 2008). A model proposed by Pavlides and colleagues hypothesizes that epithelial cancer cells induce ‘aerobic glycolysis’ in stromal fibroblasts, after which they undergo myofibroblastic differentiation. These CAFs then secrete lactate and pyruvate, what can be used as an energy source for epithelial cancer cells (Pavlides et al, 2009; Shiga et al, 2015). Thirdly, different constituents of the TME, including CAF and the ECM, also contribute to resistance in cancer cells (Shiga et al, 2015). Finally, CAF also

play a role in tumor progression and resistance by modifying the ECM. Fibroblasts acquire an contractile phenotype upon activation, characterized by α-SMA expression and the formation of microfilament bundles (Eddy et al, 1988). Actomyosin contractility allows CAF to remodel the ECM and permits cell migration. Cytokine signaling through GP130- IL6ST/JAK1 regulates Rho-Rho-kinase (ROCK)-dependent actomyosin contractility, which is required for force-mediated matrix remodeling. MYPT1, the targeting subunit of myosin phosphatase, is phosphorylated by ROCK which subsequently results in decreased myosin phosphatase activity and increased phosphorylation of myosin light-chain 2 (MLC2) (Ito et al, 2004; Gaggioli et al, 2007; Sanz-Moreno et al, 2011). ECM remodeling also requires the secretion of ECM degrading matrix metalloproteinases (MMPs) and lysyl oxidases (LOX), which directly affects the invasiveness of cancer cells. MMPs are critical for cancer cell migration and invasion since they modulate cell-cell and cell-ECM interactions by degrading various cell adhesion molecules (Gialeli et al, 2011). LOX initiate the crosslinking of collagens and elastin in the ECM what contributes to tissue strength and would have a dual role in cancer progression (Wang et al, 2016).

Figure 1. Illustration of the major components of the tumor microenvironment. Malignant cells in a tumor are surrounded by a complex microenvironment. The cellular constituents of the tumor microenvironment include immune cells such as T cells, B cells and macrophages, cancer associated fibroblasts and adipocytes. Besides that, the TME has its own vascular network consisting of blood vessels surrounded by endothelial cells and pericytes and own lymphatic network (Figure based on Cui & Guo, 2016).

Figure 2. Activation of fibroblasts to cancer-associated fibroblasts. Fibroblasts are embedded in the extracellular matrix which (ECM) constitutes mainly out of collagen type I and type III, fibrillary glycoproteins and fibronectin. On the cellular level they can be distinguished from CAF based on their fusiform cell with prominent actin skeleton and flattened, heterochromatic nucleus. Fibroblasts can be activated by growth factors, e.g. TGF-β and chemokines which are mainly produced by cancer cells. Cancer associated fibroblasts (CAF) remodel and secrete ECM proteins including type I collagen. The ECM produced by CAF is denser and more rigid compared to fibroblast-derived matrix. α-smooth muscle actin expression is characteristic for the CAF phenotype. Quiescent fibroblasts are distinguished in normal tissues based on the expression of fibroblasts-specific protein 1 (FSP-1) (Figure based on Kalluri & Zeisberg (2006) and Kuzet & Gaggioli (2016)).

1.3 Head and neck squamous cell carcinoma (HNSCC) A model that is commonly used to study the TME and where the tumor stroma plays a substantial role in cancer initiation and progression is HNSCC. HNSCC stroma is rich in CAF, moreover CAF are observed both in primary and metastatic HNSCC. Overall survival of HNSCC patients and tumor recurrence are negatively correlated with the abundance of stromal myofibroblasts (Koontongkaew, 2013; Vered et al, 2010). Head and neck cancer comprises a group of tumors that affect the lip, oral cavity, nasal cavity, pharynx, larynx and paranasal sinuses. More than 90% of head and neck tumors arise in squamous cells and are commonly referred to as head and neck squamous cell carcinomas (HNSCC) (Safdari et al, 2014; Bhave et al, 2010). Squamous cells are a type of epithelial cells and can make up simple or stratified epithelium which lines the outer surface of organs and blood vessels. Other common types of squamous cell carcinoma (SCC) include SCC of the skin, lung and vagina. Every year, approximately 500 000 new patients suffer from HNSCC by which it is one of the ten most occurring cancers worldwide (Safdari et al, 2014). The five-year survival rate of these patients depends on the region that is involved and on the presence of metastasis. Patients suffering from laryngeal cancer, oropharyngeal cancer, salivary glands cancer and tongue cancer have a 5-year survival rate of approximately 60%, while this is reduced to 50% and 27% for cancer of the oral cavity and hypopharyngeal cancer respectively (Pulte & Brenner, 2010). Even at early disease stages, patients show invasion of the tumor into surrounding tissues and metastasis to distant organs (Safdari et al, 2014). The presence of distant metastasis decreases the median overall survival rate approximately 9 months (Bhave et al, 2010).

1.3.1 Environmental risk factors contribute to the development of HNSCC Different risk factors such as oral hygiene, diet and exposure to carcinogens can contribute to the development of HNSCC. Two of the most established risk factors are exposure to tobacco smoke and alcohol abuse (Pai & Westra, 2009). Tobacco smoke is composed of approximately 4800 compounds of which 69 are thought to be carcinogenic. The most relevant carcinogens are N-nitrosamines, carbon monoxide, hydrogen cyanide and alkenes (Hoffmann et al, 2001). The mechanism by which tobacco smoke induces HNSCC is not completely unraveled yet, however several mechanisms are proposed. For example, p53 mutations are frequently observed in tobacco-related cancers (Pfeifer et al, 2002). In addition, Weber and colleagues showed that the major tobacco carcinogen 4-(methylnitrosamino)-1-(3-pyridyl)-1-1-butanone (NNK) activates AKT in head and neck cancer. NKK is a nitrosamine that is produced during curing and processing of tobacco alkaloids. NKK activates AKT by phosphorylation which leads to activation of downstream signaling mediators and increased cell proliferation and survival (Weber et al, 2011). The risk that is associated with tobacco smoke increases with duration and intensity of smoking and the consumption of more than 20 cigarettes a day is a major risk factor to acquire pharyngeal, laryngeal or oral cancer. Strikingly, also passive smoking is associated with an elevated risk for HNSCC, especially when the exposure lasts more than 15 years (Pai & Westra, 2009; Curado & Hashibe, 2009). Alcohol consumption is associated to a lesser extent with HNSCC, however it also entails a major risk to developing head and neck cancer (Zhang et al, 2015). Alcohol metabolism

8 results in the production of several carcinogenic compounds such as acetaldehyde, reactive oxygen species (ROS) and adducts of acetaldehyde or ROS with DNA. It is known that acetaldehyde can induce alcohol-associated carcinogenesis and it is recognized as a carcinogen in experimental animals. Acetaldehyde is produced after oxidation of ethanol by alcohol dehydrogenase (ADH), through the action of cytochrome P450 2E1 (CYP2E1) or by microbes living in the gastrointestinal tract. acetaldehyde is subsequently oxidized to acetate by aldehyde dehydrogenase 2 (ALDH2) (Fig. 3). At least 7 different genes code for human ADH (ADH1-ADH7) and different alleles are described (Seitz & Becker, 2007). For example, ADH1B and ADH1C are polymorphic and the different alleles are known to oxidize ethanol at a different rate which results in the accumulation of different amounts of acetaldehyde. A study performed by Peters and colleagues showed that heavy drinkers (> 29 consumptions/week) carrying the ADH1C2 (homozygous) allele have an increased risk to develop HNSCC compared to people carrying ADH1C1 allele, which is the more rapidly metabolizing allele. In addition, they suggest that high alcohol consumption is not only carcinogenic because of the production of toxic intermediates but also directly through the interaction of alcohol with e.g. tobacco smoke (Peters et al, 2005). Alcohol abuse is also a prognostic factor for HNSCC as the survival rate is lower for patients who consume a lot of alcohol (Sawabe et al, 2017; Leoncini et al, 2015). Several infectious agents such as Epstein Barr virus (EBV) and human papillomavirus (HPV) are associated with an increased risk for HNSCC. High risk HPV is a well-established risk factor besides alcohol abuse and tobacco smoke, however the type of cancer seems to be different concerning several aspects such as the anatomical sites that are affected and molecular mechanisms involved. HPV-positive HNSCC are most often observed in the oropharynx, however other sites can also be affected. Interestingly, the incidence of oropharyngeal cancers increases while the incidence of laryngeal, hypopharyngeal and oral cavity cancers is decreasing. This can be explained by the fact that there is a decrease in the use of tobacco and alcohol, but an increase in infections with HPV (Dok & Nuyts, 2016). High risk strains that are linked with HNSCC are HPV-16, -18, -31, -33 and -35. HPV is a dsDNA virus that belongs to the family of papillomaviridae. The genome of HPV consist of 3 main regions: a long control region, early genes (E1-8) and the late genes (L1-L2). The viral oncoproteins E6 and E7 are known to be able to transform oral epithelial cells. E6 binds to E6-AP, which is an ubiquitin/protein ligase, and to p53. The result is proteolytic degradation of p53 through ubiquitination. The E7 viral oncoprotein is able to bind and destabilize the retinoblastoma protein (pRb), whereby pRb cannot bind E2F anymore which leads to cell cycle progression (Lajer & Buchwald, 2010). The prognosis for patients with HPV-positive HNSCC is remarkably better compared to patients with HPV-negative cancer (Husain & Neyaz, 2017). After adjustment for age, stage, treatment, smoking, alcohol, education and comorbid disease, Schwartz et al. found that patients with HPV-16 positive tumors have reduced overall and disease-specific mortality rates (Schwartz et al, 2001).

Figure 3. alcohol metabolism. Ethanol can be oxidized to acetaldehyde through several mechanisms: alcohol dehydrogenase, the action of microbes in the gut or cytochrome P450 2E1. Acetaldehyde is then oxidized by aldehyde dehydrogenase 2 to acetate. ADH: alcohol dehydrogenase, ALDH2: aldehyde dehydrogenase 2.

1.3.2 Molecular parameters involved in HNSCC HNSCC describes a broad group of cancers that were previously seen as a uniform group of tumors that differed only by anatomical site. Molecular genetic and epigenetic analysis revealed that these tumors are characterized by distinct molecular (epi)genetic profiles (Pai & Westra, 2009), what can be partly explained by the different risk factors that are involved. Pathways that are regularly altered include p53, epidermal growth factor receptor (EGFR), signal transducer and activator of transcription 3 (STAT3) and vascular endothelial growth factor receptor (VEGFR) (Bhave et al, 2010). Mutation of the p53 gene are observed in more than 50% of tumors, which makes it one of the most commonly occurring mutations in HNSCC (Graves et al, 1992). Due to the inactivation of p53, the cell is not able to control its own growth and it cannot respond to stress or DNA damage (Vogelstein et al, 2000). However, dysregulation of the p53- pathway can also be caused by mutations that occur in other genes in the pathway. Double-stranded DNA breaks activate ataxia telangiectasia mutated (ATM), which is an damage-activated protein kinase. On its turn, ATM activates transcriptional activation of p53 by its phosphorylation. Silencing of ATM leads to loss-of-function of p53 (Bolt et al, 2005). Alterations in growth factor signaling pathways are also commonly observed in HNSCC. EGFR is a receptor tyrosine kinase (RTK) that belongs to the ErbB/Her family of receptors, which also includes Her2-4. EGFR is activated upon binding of one of its ligands which include epidermal growth factor (EGF) and tumor necrosis factor-α (TNF-α). Activation leads to a conformational change in the receptor whereby it homodimerizes or heterodimerizes with other member of the ErbB/Her family leading to autophosphorylation and activation of downstream signaling pathways (Herbst, 2004;

Klein & Grandis, 2010). All ligands can induce activation of the RAS/RAF/MEK/ERK which needs the presence of the adaptor proteins Grb2 and Shc. Signaling through the RAS/ERK pathway stimulates gene expression and cell cycle progression (Sasaoka et al, 1994; Lowenstein et al, 1992; Jorissen et al, 2003). Also c-Src, a non-receptor tyrosine kinase, has been implicated in signal transduction from the EGFR and is involved in oncogenic processes such as cell survival and proliferation (Thomas & Brugge, 1997). Other signaling pathways include Janus activated kinase (JAK) /STAT and phospholipid metabolism (e.g. PI3-K) (Jorissen et al, 2003) (Fig. 4). Expression of EGFR in normal epithelial cells ranges from 40 000 to 100 000 receptors, however the receptor is overexpressed in the majority of solid tumors such as breast cancer, non-small cell lung cancer (NSCLC) and head and neck cancer (Herbst, 2004). Overexpression is not the only mechanism by which EGFR is constitutively activated. A deletion in exons 2-7 leads to a mutant form of EGFR, called EGFRvIII, which is characterized by a truncated ligand binding domain (Klein & Grandis, 2010). STAT3 is a transcription factor that is involved in cellular responses towards cytokines and growth factors and belongs to the STAT family. Signals that activate the pro-transcription effects of STAT3 include members of the IL-6 cytokine receptor family, RTKs and non- receptor tyrosine kinases such as JAKs and Src family kinases. In HNSCC, no oncogenic mutations that activate STAT3 are discovered yet. Nevertheless, deviant STAT3 expression is mediated by upstream growth factor receptors including JAK and EGFR (Geiger et al, 2017; Klein & Grandis, 2010). Another molecular parameter that is critically altered in HNSCC is VEGFR. It is activated by its ligand VEGF which is abundantly expressed by both tumor cells and stromal cells and its main function is to initiate angiogenesis. In addition, there is elevated expression of VEGFR-2 in tumor-derived vascular endothelial cells (Yigitbasi et al, 2004). VEGF expression is also a prognostic factor for disease-free survival rate in HNSCC. Patients that present with high VEGF expression are more likely to develop metastasis through lymph node spread, what is correlated with a poor survival rate (Mineta et al, 2000).

1.3.3 HNSCC therapy: targeting the epidermal growth factor receptor In the 20th century, treatment of HNSCC consisted mainly out of surgery, radiotherapy, chemotherapy or a combination of the previous (Cognetti, 2008). All of the previous mentioned treatment methods are associated with an increased risk for speech and swallowing difficulties (Rinkel et al, 2016). In addition, the clinical benefit of chemotherapy is often counterbalanced by the increased toxicity that the treatment entails. Nowadays, chemotherapy is combined with targeted therapy to increase the survival rate of HNSCC patients. However, the only molecular target that has been shown clinical benefit for patients is the EGFR. The mechanisms that are used to target EGFR with targeted therapy include monoclonal antibodies such as cetuximab and small molecule inhibitors that target the intracellular domains of EGFR such as gefitinib and erlotinib (Echarri et al, 2016). Gefitinib is an oral quinazoline that inhibits EGFR by binding reversibly to the ATP binding domain of the receptor. It is an FDA-approved drug for locally advanced or metastatic NSCLC. However, a phase III randomized, placebo-controlled trial in patients with recurrent or metastatic

head and neck cancer with gefitinib in combination with docetaxel did not show any clinical benefit for the patients (Argiris et al, 2013). In addition, another phase III clinical trial in which treatment with 250 or 500 mg/day gefitinib was compared to standard methotrexate did also not reveal any clinical benefit (Stewart et al, 2009). Erlotinib is a small molecule inhibitor that works through the same mechanism as gefitinib. There are currently no phase III clinical trials ongoing as the overall response rate in phase II clinicial trials was low. Nevertheless, a phase II study showed an response rate of 62% after addition of erlotinib to first-line cisplatin and doxetaxel, which represents an improvement of historical records (William et al, 2018). At the moment, cetuximab is the only FDA- approved targeted therapy that is used to treat HNSCC. It is an IgG1 monoclonal antibody that inhibits EGFR by blocking its ligand-binding domain (Bonner et al, 2006). Monoclonal antibodies have a greater specificity compared to small molecule inhibitors and they can be used at lower concentrations (Herbst, 2004).

Figure 4. Epidermal growth factor receptor signaling in cancer. The EGFR is expressed and upregulated in multiple types of cancer including HNSCC. Its activation leads to signaling through multiple signaling pathways under which the RAS/RAF/MEK/ERK, JAK1/STAT3, C-SRC and PI3K/AKT/mTOR pathway which induces cell proliferation, migration and survival. The EGFR is often targeted in cancer treatment. Cetuximab is a monoclonal antibody that inhibits EGFR signaling through competing with the binding of ligands on the receptor. Small- molecule inhibitors including gefitinib and erlotinib (Figure based on Vallath et al, 2014)

1.4 Resistance to targeted therapy in head and neck squamous cell carcinoma 1.4.1 Multiple mechanisms can lead to resistance to therapy Inhibition of the EGFR is a rational method to treat HNSCC because of its critical role in cell survival and proliferation. However, the efficiency of EGFR inhibitors is often undermined due to the development of resistance. Cancer therapy resistance is a major problem that is observed in cancer patients who are treated with chemotherapy or targeted therapy. In general, multiple mechanisms can contribute to the development of resistance against drugs. One of the main causes of drug resistance is tumor heterogeneity. Different tumor phenotypes due to another combination of genetic and epigenetic alterations lead to a different response towards a certain drug. It is also possible that cancer cells acquire resistance over time causing a decrease in the efficacy of the treatment. Acquired resistance refers to the accumulation of mutations in tumor cells which lead to a different response while de novo drug resistance can be soluble- factor mediated drug resistance or cell-adhesion mediated drug resistance. The first is induced by chemokines, growth factors and cytokines while the latter is caused the interaction of cancer cells with components of the TME via surface receptors (Senthebane et al, 2017). 1.4.2 The role of cancer associated fibroblasts and the extracellular matrix in resistance towards targeted therapy Due to the contribution of CAFs and the ECM in tumor initiation progression of HNSCC, it is interesting to study their role in the development of resistance to targeted therapy. CAFs can contribute to cancer drug resistance by producing growth factors, via interaction with cancers cells and by modulating the ECM (Senthebane et al, 2017). Wang and colleagues showed that lung cancer cells can attract fibroblast upon gefitinib treatment. CAFs produce HGF, which activates the MET/PI3K/AKT pathway in cancer cells and contributes to resistance towards TKI (Wang et al, 2009). Persistent AKT activation was also shown to be partly responsible for cetuximab resistance in HNSCC (Rebucci et al, 2011) (Fig. 4). As already mentioned, the ECM that is produced by CAF is stiffer compared to the matrix in normal tissues due to ECM remodeling and increased deposition of ECM components. Increased matrix stiffness is associated with processes such as migration, differentiation, proliferation and cancer drug resistance. A study performed by Zhang and colleagues revealed that stiff micro-environmental condition in breast cancer mitigates resistance to cancer therapy (Zhang et al, 2017). Nevertheless, the role of CAF and increased ECM stiffness in resistance to targeted therapy in HNSCC was not examined yet.

1.5 The extracellular matrix protein fibulin-2 and its role in cancer In order to unravel the role of CAF and ECM in resistance to targeted therapy in squamous cell carcinoma of the head and neck, researchers in the lab of Dr. Cedric Gaggioli searched for proteins in the ECM that could protect cancer cells against TKI such as gefitinib. Through a proteomic approach, the lab identified fibulin-2 as a potential mediator of ECM- driven resistance to targeted therapy. 1.5.1 Fibulin-2 is a glycoprotein with repeated domain structure FBLN2 is a member of the fibulin family of genes which is a family of extracellular matrix proteins. FBLNs are glycoproteins that are structurally characterized by a series of EGF- like motifs and a carboxy-terminal fibulin-type module (FC domain) (Fig. 5). FBLN2 contains 10 EGF-like domains which are known to possess a conserved sequence for calcium- binding. Calcium-binding seems essential, since depletion of calcium disrupts the structure of elastic microfibrils (Sasaki et al, 1996a). FBLN2 differs from the other members of the family as it contains both a unique N-terminal domain of 400 amino acids and three anaphylatoxin-like motifs. These anaphylatoxin-like motifs are also observed in fibulin-1 and are homologous to the complement proteins C3a, C4a and C5a which are pro- inflammatory peptides. The function of these domains in FBLN1 and FBLN2 is not described yet (Argraves et al, 1990; Olijnyk et al, 2014; Klos et al, 2009). Two different variants of FBLN2 occur due to alternative splicing. FBLN2 variant 1 (V1) consists of 18 exons, while FBLN2 variant 2 (V2) consists of 17 exons and lacks EGF-like motif 3 (Olijnyk et al, 2014). 1.5.2 Fibulin-2 engages interactions with many ECM-proteins FBLN2 stabilizes supramolecular ECM structures such as basement membranes, elastic fibers and fibronectin matrix and interacts with multiple ECM-components (Olijnyk et al, 2014) (Fig. 5). FBLN2 has the highest binding affinity with fibronectin and nidogen-1 (Sasaki et al, 1995). The binding of FBLN2 with FN is calcium-dependent and both proteins are expressed at equal levels. By immunofluorescence, it was shown that FBLN2 and FN colocalize in ECM fibrils (Sasaki et al, 1996b). Nidogen-1 is a member of the nidogen-family of sulfated glycoproteins. They are considered as adaptor proteins in interstitial matrix and basement membrane. Nidogen-1 binds with FBLN2 through its G3 domain in a calcium- independent manner, whereby tertiary complexes can be formed with other ECM-proteins such as fibulin-1, collagen IV and perlecan. Besides FN and nidogen-1, FBLN2 also has a range of other interaction partners with which it engages weaker interactions including proteoglycans, laminins and elastin. Aggrecan is expressed by chondrocytes in cartilage while versican is expressed in various tissues such as blood vessels and dermis (Olin et al, 2001). Both proteins interact with FBLN2 through their C-type lectin domain. In addition, FBLN2 interacts with perlecan through its proteoglycan core protein (Sasaki et al, 1995). Perlecan is widely distributed in the basement membrane of skin, lung and heart and is associated with tumor progression and angiogenesis (Murdoch et al, 1994; Jiang & Couchman, 2003). Sasaki and colleagues also showed that FBLN2 is a strong ligand for tropoelastin, the precursor of elastin and that FBLN2 possibly mediates the attachment of microfibrils to elastin structures(Sasaki et al,

1999; Pan et al, 1993). Finally, FBLN2 also interacts with laminin-1 and laminin-5 through conserved amino acid sequences. FBLN2 forms a bridge between both laminins and other matrix proteins and provides in this way a linkage between the cell surface and the basement membrane (Utani et al, 1997). 1.5.3 The function of fibulin-2 in normal development and disease FBLNs are highly conserved between different species and have a large range of ligands with which they interact to stabilize the organization of supramolecular ECM structures. FBLN2 but also other member of the FBLN family are involved in elastic matrix fiber assembly and function (Sasaki et al, 1999; Argraves et al, 2003). However, FBLN2 is dispensable for elastic fiber formation in mice due to functional redundancy with FBLN1. On the other hand, FBLN2 is not able to functionally compensate for loss of FBLN1 since it has a more restricted expression pattern compared to FBLN1 (Sicot et al, 2008). FBLN1 and FBLN2 are both highly expressed during cardiac valvuloseptal formation and in developing and adults heart valves (Bouchey et al, 1996; Tsuda et al, 2001; Zhang et al, 1995). Furthermore, FBLN2 is prominently expressed in aorta and vessels and is associated with several heritable and inheritable aortic disorders including abdominal and thoracic aortic aneurysm. (Chu & Tsuda, 2004; Hasham et al, 2003). FBLN2 has a dual role in tumorigenesis as it can act both as a tumor-suppressor and as a oncogene. Li et al. suggest that FBLN2 is involved in breast cancer progression and invasion. They found that the protein is downregulated in several breast cancer cell lines and primary tumors and re-expressing FBLN2 in certain clones of the MDA-MB-231 and BT-20 breast cancer cell lines revealed a reduced cellular invasion by 50% (Yi et al, 2007). Alcendor et al. found a similar role for FBLN2 in Kaposi sarcoma, an angioproliferative tumor caused by Kaposi’s sarcoma-associated herpesvirus infection of vascular endothelial cells (Alcendor et al, 2011). Nevertheless, other studies show an oncogenic role of FBLN2 in cancer progression. FBLN2 is abundantly expressed in metastatic lung cancer cells and is a driver of malignant progression in lung adenocarcinoma by stabilizing the tumor ECM (Baird et al, 2013).

Figure 5. schematic structure and interaction network of fibulin-2. (A) Schematic representation of the structure of FBLN2. Members of the FBLN family all have a series of EGF-like domains and a C-terminal fibulin-type module (Fc domain) in common. In addition, FBLN2 is characterized by three anaphylatoxin domains and a large N- terminal domain. This domain contains a cysteine rich and cysteine free region. (figure based on Argraves et al, 2003) (B) Interaction network of FBLN2 showing some of the most important interaction partners of FBLN2 that are located in the extracellular matrix. ACAN: Aggregan, BCAN: Brevican, ELN: Elastin, FBLN2: Fibulin-2, FN1: fibronectin-1, LAMA1: laminin-1, LAMA5: laminin-5, NID1: Nidogen-1 VCAN: Versican (based on the interaction network that is available on www.esyn.org) ((Sasaki et al, 1995; Olin et al, 2001; Fontanil et al, 2014).

PART 2: AIM

Head and neck cancer describe a group of cancers of which 90% are squamous cell carcinomas. The global incidence amounts between 400 000 and 600 000 new cases per year and the mortality rate around 300 000 deaths per year. The five year survival rate is 40% to 60% depending on the affected site, however the incidence of tumor recurrence is high and the prognosis for patients with advanced tumor is bad, due to metastasis and drug resistance (World Health Organisation, 2014; Hui et al, 2017; Howell & Grandis, 2005). Lately, the role of the TME and more specifically CAF and ECM has gained increased attention in research on the development of resistance in cancer patients. However, the molecular and cellular mechanisms of EGFR-TKIs resistance in HNSCC are unknown. One of the main research projects in the lab of Dr. Cedric Gaggioli is to decipher the molecular mechanisms that are involved in TME-driven resistance towards TKI in HNSCC. Using mass spectrometry, they found that 52 proteins are differentially expressed in matrix produced by normal human fibroblasts (NHF) and CAF on the one hand and CAF compared to CAF treated with ruxolitinib (10 µM) on the other hand. Ruxolitinib is a small molecule inhibitor that blocks JAK1 and JAK2 kinase by competing with ATP for its binding site (Ostojic et al, 2011). Next, they performed an RNA interference (RNAi)-based screen to examine the effect of downregulating the 52 identified proteins within CAF on the produced matrix. SCC12 cells were cultured on the cell-derived matrix and treated with gefitinib (5 µM), after which the cell survival of the cancer cells was determined. The screen revealed that FBLN2 knockdown within CAF-derived matrix with small interfering RNA (siRNA) was able to restore the sensitivity of SCC12 cells (skin squamous cell carcinoma) towards gefitinib-induced cell death. FBLN2 is a glycoprotein belonging to the FBLN family of ECM proteins which plays a role in elastic fiber formation and the development of heart valves. In addition, FBLN2 is known to play a dual role in different types of cancer as it acts both as a tumor-suppressor and oncogene. However, the role of FBLN2 in ECM-driven resistance to targeted therapy in HNSCC has not been studied yet. The overall aim of the thesis project was to confirm and to investigate the specific role of FBLN2 in resistance towards EGFR-targeted therapy in HNSCC in vitro (Fig. 6). First, we focused on confirming the results obtained from the RNAi-based screen. To do so, FBLN2 was knocked down in CAF and subjected to cell-derived matrix production. After the removal of the CAF, SCC12 were grown on the matrix and treated with gefitinib (5 µM). Cell survival of the cancer cells was quantified and compared between the different conditions. In addition, the experimental procedure was repeated with CAL27 cells (tongue squamous cell carcinoma) and a gain-of-function (GOF) experiment was performed to study if stimulation of NHF with human recombinant FBLN2 (hrFBLN2) increases cell survival of SCC12 grown on the cell- derived matrix. Once the role of FBLN2 in ECM-driven protection of cancer cells was confirmed, the properties of cell-derived matrix were studied. The composition of the matrix produced by NHF, CAF and CAF (FBLN2 KD) was analyzed by making use of immunofluorescent staining of the ECM proteins FBLN2 and fibronectin. In addition, the cross-linking between collagen type I and type III was visualized with picrosirius red staining. The third part of the project consisted of providing clues to unravel the molecular mechanisms involved in matrix- derived protection by FBLN2. The protection provided by FBLN2 could be mediated by a direct

17 interaction between CAF and SCC cells or the effect could be indirect by modulating the contractility of CAF and subsequently matrix remodeling. The first hypothesis was studied by assessing protein expression of A20 and pEGFR in SCC12 cultured on CAF(FBLN2)-derived matrix. The cancer cells were stimulated with EGF to induce EGFR signaling or left untreated. To study the effect of FBLN2 KD on the contractility of CAF, a contraction assay was performed. In addition, the contractility of NHF and CAF was respectively compared to the contractility of NHF and CAF that were stimulated with hrFBLN2.

Figure 6. Schematic overview of the different experimental steps in the thesis project. The project focuses on confirming and analyzing the role of FBLN2 in ECM-driven therapeutic resistance of HNSCC. (1) The first goal was to confirm the preliminary results obtained in the lab of Dr. Cedric Gaggioli which suggest a role for FBLN2 in matrix-derived protection of SCC cells. Cell survival of SCC12/CAL27 cells was quantified after they were grown on cell-derived matrix produced by either CAF (FBLN2 KD) or NHF that were stimulated with hrFBLN2. (2) The second part of the project consisted of analyzing the matrix properties of cell-derived matrix produced by CAF (FBLN2 KD) or NHF that were stimulated with hrFBLN2. (3) Thirdly, the molecular mechanisms involved were examined.

PART 3: RESULTS 3.1 Preliminary results obtained in the lab Approximately 500 000 people develop squamous cell carcinoma in the head and neck region every year and there are currently no treatments which improve the survival rate of patients with locally advanced or metastatic HNSCC. Discovering new targetable genes is crucial for developing new therapies to prolong the life of these patients. Nowadays, the role of the TME is inevitable in tumor progression and resistance to cancer therapy, so studying the interaction between the different players in the TME is one way to identify new drug targets. Research in the lab of Dr. Cedric Gaggioli focuses on two major axes: on the one hand researchers study the signaling pathways in SCC cells that convert resident fibroblasts into CAF and lead to cancer progression. On the other hand, they try to identify the molecular pathways in CAF that contribute to SCC cell invasion and resistance to targeted therapy. To study the interaction between these players of the TME, the lab uses among other things cell-derived matrices which form a physiological relevant method to study in vitro the in vivo-like behavior of cells. Fibroblasts are plated on gelatin-coated cell culture dishes and stimulated with ascorbic acid for 7 days to produce cell-derived matrix, thereafter they are depleted from the cell-derived matrices. Ascorbic acid is essential for the expression of stable collagen proteins (Kaukonen et al, 2017). It is well-known that CAF-derived matrix is more rigid than cell-derived matrix produced by quiescent fibroblasts. This was also shown in the lab by measuring the rigidity of cell- derived matrices with atomic force microscopy (AFM) (Fig. 7.A). These results confirmed that CAF-derived matrices are significantly stiffer than NHF-derived matrices. Treatment of CAFs with the JAK1/2-inhibitor ruxolitinib during cell-derived matrix production reduces the stiffness of the matrix significantly. Inhibition of JAK1 activity blocks fibroblast contractility and ECM remodeling which leads to inhibition of cancer cell invasion in vitro and in vivo (Albrengues et al, 2014). Furthermore, the lab showed that SCC12 cells cultured on CAF-derived matrix show an increased survival rate upon gefitinib treatment compared to SCC12 cells cultured on NHF-derived matrix (Fig. 7.B). To do so, SCC12 cells were cultured on NHF or CAF-derived matrix and treated with 5 µM gefitinib. altogether, increased stiffness of the ECM seems to protect SCC12 cells against cell death mediated by the TKI gefitinib. To identify ECM-proteins that play a role in resistance to targeted therapy, cell-derived matrices produced by either NHFs, CAFs or CAFs treated with ruxolitinib were compared with mass spectrometry. 52 differentially expressed proteins were revealed and a Venn diagram illustrating the number of proteins that NHF, CAF and CAF(+ ruxolitinib) share was made (Fig 7.C). 115 proteins are common to all three types of matrices, while NHF- and CAF-derived matrix share 2 additional proteins, CAF- and CAF (+ ruxolitinib)-derived matrix share 136 proteins and NHF- and CAF (+ruxolitinib)-derived matrix shares 4 proteins. Although the rigidity of ECM produced by CAF is significantly stiffer than ECM produced by CAF (+ ruxolitinib), both types of matrices still share a lot of proteins that are not expressed in NHF-derived matrix.

Then, an RNAi-based screen was performed to evaluate which of the 52 identified proteins could abolish the ECM-driven protection of SCC cells upon gefitinib treatment. The proteins were knocked down with siRNA in CAFs, which were subjected to cell-derived matrix production and denuded from the matrix after 7 days. The results of the screen are partly shown in figure 7.D. FBLN2 seemed to be the most interesting target to study as the percentage of survival of untreated SCC12 cultured on CAF (FBLN2 KD)-derived matrix is similar to the survival rate of SCC12 cells grown on CAF- derived matrix. In addition, the survival rate of gefitinib-treated SCC12 cells decreases to approximately 55% when they are cultured on CAF (FBLN2 KD)-derived matrix, while the survival rate remains around 80% when cultured on CAF-derived matrix. Cell survival of untreated SCC12 cells is lower after knockdown of HTRA3, NID1 and JAK1 in CAF compared to SCC12 cells cultured on CAF-derived matrix, whereby they are less suitable targets to study. The opposite applies to ADAMTSL4, as cell survival of untreated SCC12 cells is increased when cultured on cell- derived matrix in which ADAMTSL4 is knocked down.

Figure 7. Fibulin-2 is a valid target to study in ECM-driven resistance to targeted therapy in head and neck squamous cell carcinoma. (A) Stiffness of ECM produced by NHF (FHN), CAF and CAF treated with ruxolitinib (CAF RX). The stiffness is measured by making use of atomic force microscopy in Pascal (Pa). (***p< 0,001) (B) Ratio of surviving SCC12 cells cultured on NHF- and NHF (+ TGF-β)- derived matrix. Cells were treated with 5 µM gefitinib or left untreated. (C) The results obtained after comparing cell-derived matrices of both NHF/CAF and CAF/CAF(+ruxolitinib) with mass spectrometry to identify differentially expressed proteins. 52 different proteins were discovered. A Venn-diagram displays the number of proteins NHF-, CAF- and CAF (+ ruxolitinib)- derived matrices share. (D) Percentage of cell survival of SCC12 cultured on CAF-derived matrix in which the indicated proteins were knocked down with siRNA. siLUC was used as a control for transfection. SCC12 cells were treated with 5 µM gefitinib or left untreated.

3.2 Confirming the efficiency of the siRNA sequences targeting FBLN2 Prior to studying and confirming the role of FBLN2 in matrix-derived protection of HNSCC cells, the efficiency of four distinct siRNA sequences was tested in both CAF (Fig. 8.A) and cell-derived matrix (Fig. 8.B). To verify whether the different sequences knockdown FBLN2 to the same extent, CAF were transfected with siFBLN2(#1-4) and cell lysates were prepared after 48 hours. Western blot analysis of cell lysates of CAF showed that the four different siRNA sequences downregulate FBLN2 to the same extent, while FBLN2 is still expressed in the control condition. Additionally, FBLN2 knockdown in cell-derived matrices was validated. Since FBLN2 is differentially expressed between CAF- and CAF (+ruxolitinib)-derived matrices, we also examined FBLN2 expression in CAF-derived matrices after JAK1 knockdown. CAF were transfected with siJAK1 or siFBLN2(#1-2) and subjected to cell-derived matrix production for 7 days. Subsequently, the CAF were depleted from the cell-derived matrix. Knockdown of FBLN2 was also observed in the cell- derived matrix after transfection of CAF with siFBLN2#1-2, while FBLN2 is still abundantly expressed in the control condition. JAK1 knockdown in CAF reduces FBLN2 expression in the ECM, what confirms that FBLN2 is differentially expressed in CAF- and CAF (+ ruxolitinib)-derived matrices. As there are no household genes present in the ECM, equal loading across the different conditions was ascertained by ponceau S staining (not shown).

Figure 8. knockdown of fibulin-2 in cancer associated fibroblasts and cell-derived matrix with different siRNA sequences. (A) Immunoblot showing FBLN2 expression in CAF after knockdown with 4 different siRNA sequences (siF2#1-4). siLUC serves as a control for transfection. (B) Immunoblot showing the expression of FBLN2 in CAF- derived matrix after downregulation of JAK1 and FBLN2 (#1-2) with siRNA. CAF were transfected with the respective siRNA sequences and subjected to cell-derived matrix production. After 7 days, CAF were denuded from the cell-derived matrix. siLUC served as a control for transfection.

3.3 Confirming the role of fibulin-2 in ECM-derived protection of head and neck squamous cell carcinoma 3.3.1 Cell survival of SCC12 cells cultured on CAF(FBLN2 KD)-derived matrix First, we focused on verifying the results that were obtained from the RNAi-based screen which showed that cell survival of SCC12 cells cultured on CAF-derived matrix in which FBLN2 was knocked down by siRNA was reduced compared to SCC12 cells that were cultured on CAF-derived matrix after gefitinib treatment. Besides that, cell survival of SCC12 cells cultured on CAF (JAK1 KD)-derived matrix was also assessed. For this purpose, CAFs were transfected with siJAK1, siFBLN2(#1-2) and subjected to cell-derived matrix production. After denudation of the CAFs, SCC12 cells were plated on the cell-derived matrix and after two days treated with 5 µM gefitinib or left untreated. After 48 hours, the cancer cells were stained with DAPI staining and the cell number was quantified by making use of ImageJ (Fig. 8.A/C). Next, the percentage of surviving cells was calculated by normalizing the cell number in the gefitinib-treated condition to their own control, as the goal is to determine the effect of the cancer treatment (Fig. 8.B). Cell number is similar across all conditions for non-treated SCC12 cells except for the SCC12 cells cultured on CAF (FBLN2#2 KD)-derived matrix, as a slight increase in cell number is observed. Treatment with gefitinib reduces cell number to the greatest extent for SCC12 cultured on CAF(FBLN2#1-2 KD). 74,7% of SCC12 that are cultured on CAF- derived matrix survive after treatment with gefitinib compared to non-treated SCC12. Depletion of JAK1 in CAF reduces cell survival of SCC12 with 11,2% compared to SCC12 cell cultured on CAF-derived matrix while knockdown of FBLN2 in CAF further decreases cell survival of SCC12 to 51,4% and 50,1%, for siRNA sequence #1 and #2 respectively. A statistical analysis was performed to analyze whether the reduction in cell survival between the different conditions was significant. The experiment was repeated three times indepentently whereby it is not possible to assess whether the assumption of a ‘normal distribution’ is fulfilled so a non-parametric Mann-Whitney U test was used. This test is equivalent to the Willcoxon Rank Sum test and is often used when the sample size of an experiment is small (Vermeulen et al, 2015). The p-values were not corrected for multiple comparison since the experiment comprised only 4 conditions. Depletion of JAK1 in CAF does not signficantly alter cell survival of SCC12 cells compared to control (Mann- Whitney U = 2,000, n1 = n2 = 3, p = 0,275). FBLN2 knockdown did not significantely increase the percentage of SCC12 cells who die upon gefitnib treatment (Mann-Whitney U = 0,00, n1 = n2 = 3, p = 0,05). However, this does not neceserally means that there is no biological signficiant effect. Due to the small sample size, the non-parametric Mann- whitney U test lacks power to reject the null hypothesis i.e. cell survival of SCC12 cells cultured on CAF-derived matrix does not significantly alter upon FBLN2 knockdown in CAF. Although there was no statistically significant effect, the data confirm the results previously obtained in the lab and support the hypothesis that FBLN2 is involved in ECM- derived protection of SCC cells.

Figure 9. Fibulin-2 protects SCC12 cells against cell death upon gefitinib treatment. CAFs were transfected with siRNA targeting JAK1, FBLN2(#1-2) or LUC (transfection control) and subjected to cell-derived matrix production by changing the media supplemented with ascorbic acid every other day. After 7 days, the CAFs were removed and SCC12 cells were plated on the cell-derived matrix. After 48 hours, the SCC12 cells were treated with 5 µM gefitinib. DMSO was used as a control. (A) Absolute cell count of SCC12 cells, 48 hours after gefitinib treatment. Data are represented as the mean of three independent experiments. (B) The percentage of cell survival of SCC12 cells was obtained by normalizing the absolute cell count of gefitinib-treated SCC12 cells over the different condition to their respective control. Data are represented as the mean ± SD of three independent experiments ( *p < 0,5). (C) Representative images of DAPI staining of SCC12 cells after they were treated with 5 µM gefitinib or left untreated.

3.3.2 Cell survival of SCC12 cells cultured on cell-derived matrix produced by normal human fibroblasts that were stimulated with human recombinant fibulin-2

Preliminary data showed that SCC12 cells that are cultured on NHF-derived matrix survive less upon gefitinib compared to their survival on CAF-derived matrix (Fig. 7.B). Since FBLN2 knockdown in cell-derived matrix increased cell death of SCC12 cells upon gefitinib treatment, the goal was to study during the following experiment if stimulating NHF with hrFBLN2 could increase the matrix-derived protection of SCC12 cells as it is provided by CAF. NHF were subjected to cell-derived matrix production and stimulated with 5 ng/ml hrFBLN2 every other day. After one week, the fibroblasts were denuded and SCC12 cells were plated on the cell-derived matrix and treated with 5 µM gefitinib. Then, cell survival was quantified after DAPI staining by normalizing the cell number of gefitinib-treated SCC12 cells to non-treated SCC12 cells. Representative pictures of DAPI-stained SCC12 cells are shown for all conditions (Fig. 10.C). The cell number of SCC12 cells was approximately the same across all three conditions. This indicates that increased matrix stiffness does not alter cell survival of untreated SCC12 cells, as ECM produced by CAF is known to be stiffer than ECM produced by NHF (Fig. 10.A). Gefitinib treatment reduced cell number the most for SCC12 cells cultured on NHF-derived matrix while there was only a slight decrease noticed when SCC12 cells were cultured on NHF (hrFBLN2)- and CAF-derived matrix. After normalization to non-treated cells, cell survival amounts 70,0% for SCC12 cells cultured on NHF-derived ECM what is not significantly lower than cell survival of SCC12 on CAF-derived ECM (Mann-Whitney U = 0,00, n1 = n2 = 3, p = 0,05). Stimulation of NHF with hrFBLN2 during cell-derived matrix production does not significantly alter cell survival compared to control (Mann-whitney U = 0,00, n1 = n2 = 3, p = 0,275). We can conclude that stimulating NHF with 5 ng/ml hrFBLN2 does not significantly alters the percentage of cell survival of SCC12, however there seems to be a slight increase increase in cell survival compared to cancer cells cultured on NHF- derived matrix.

Figure 10. Cell survival of SCC12 cells cultured on cell-derived matrix produced by normal fibroblasts that were stimulated with hrFBLN1. NHFs were subjected to cell-derived matrix productions and stimulated with 5 ng/ml hrFBLN2. NHF- and NHF(TGF-β)-derived matrix was used as a control. After denudation of the fibroblasts, SCC12 cells were plated on the cell-derived matrix and after two days treated with 5 µM gefitinib for 48 hours. DMSO was used as a control. (A) Absolute cell count of gefitinib-treated or untreated SCC12 cells. Data are represented as the mean of three independent experiments. (B) the percentage of cell survival of SCC12 was obtained by normalizing the absolute cell count of gefitinib-treated SCC12 cells over the different condition to their respective control. Data are represented as the mean ± SD of three independent experiments ( *p < 0,5) (C) Representative images of DAPI staining of SCC12 cells after 2-day treatment with 5 µM gefitinib.

3.3.3 Cell survival of CAL27 cultured on CAF(FBLN2 KD)-derived matrix To confirm the results of the RNAi-based screen, cell survival of SCC12 cells upon gefitinib treatment was assessed after knockdown of FBLN2 in CAF-derived matrix. However, the principal objective of the project is to study ECM-driven therapeutic resistance in squamous cell carcinoma of the head and neck. To validate the role of FBLN2 in ECM- derived protection of HNSCC cells, the experiments were repeated with CAL27 cells, a tongue squamous cell carcinoma cell line. The experimental procedure was identical as described in 3.2.1. Representative pictures of DAPI-stained CAL27 are shown for all conditions (Fig. 11.C). Due to a lack of time, we could not study cell survival of CAL27 on NHF (hrFBLN2)-derived matrices. Cell number for untreated CAL27 cells was remarkably lower for cells cultured on CAF (FBLN2#2 KD)-derived matrices compared to CAF (FBLN2#1)-derived matrices and this tendency was noticed over all three, independent experiments (Fig. 11.A). An off-target effect of one of the siRNA-sequences could explain the differences in cell number. 89,1% of CAL27 cells survive upon gefitinib treatment compared to untreated cells cultured on CAF-derived matrices. Knockdown of FBLN2 in cell-derived matrices reduces the percentage of survival of CAL27 to respectively 36,9% and 57,8% for siFBLN2#1 and siFBLN2#2 (Fig. 11.B). The large discrepancy between the effect mediated by the two different siRNA sequences can be partly explained by the difference in cell number in untreated condition. Nevertheless, cell number of CAL27 cells cultured on CAF (FBLN2#1)- derived matrix decreases to a greater extent than cancer cells cultured on CAF (FBLN2#2)- derived matrix. There was also no significant difference between cell survival of CAL27 cultured on CAF-derived matrices and CAF(FBLN2#1-2)-derived matrices (Mann-Whitney U = 0,00, n1 = n2 = 3, p = 0,05). As mentioned above, this is probably due to a lack of power of the statistical test.

Figure 11. FBLN2 protects CAL27 against cell death after treatment with gefitinib. CAFs were transfected with siRNA targeting JAK1, FBLN2(#1-2) or LUC (transfection control) and subjected to cell-derived matrix production. After 7 days, the CAFs were removed and CAL27 cells were plated on the cell-derived matrix. CAL27 cells were treated with 5 µM gefitinib for 48 hours. DMSO was used as a control. (A) Absolute cell count of SCC12 cells, 48 hours after gefitinib treatment. Data are represented as the mean of three independent experiments. (B) The percentage of cell survival of CAL27 cells was obtained by normalizing the absolute cell count of gefitnib-treated SCC12 cells over the different condition to their control. Data are represented as the mean ± SD of three independent experiments ( *p < 0,5) (C) Representative images of DAPI staining of CAL27 cells after treatment with 5 µM gefitinib.

3.4 Studying the matrix properties of NHF- and CAF-derived matrices Quiescent fibroblasts are embedded in the ECM while activated fibroblasts are known to actively produce and remodel the ECM. The ECM produced by NHFs can be described as not dense and non-aligned, while the ECM produced by CAF is dense, aligned and rigid. Moreover, it provides an environment that stimulates cancer progression, metastasis and resistance towards cancer treatment. After confirming the role of FBLN2 in ECM-driven resistance to targeted therapy of HNSCC, the next phase involved studying how FBLN2 downregulation in CAFs or upregulation in NHF alters the structure and composition of cell-derived matrix since FBLN2 interacts with multiple proteins of the ECM. Especially the interaction with FN and NID1 is known to be strong. However, FBLN2 also engages less strong interactions with several proteoglycans and laminins an and forms tertiary complexes with fibulin-1 and type IV collagen through binding with NID1.

3.4.1 Matrix properties of CAF (FBLN2 KD)-derived matrices Cell-derived matrix was produced by CAF (FBLN2 KD) and after 7 days, the cells were denuded from the matrix. CAF-derived matrix was then used to stain with fibronectin and FBLN2 by making use of immunofluorescence and to visualize the structure of the fibers. The cell-derived matrix was compared to matrix produced by CAF, while siLUC was used as a control for transfection. CAFs cultured in medium supplemented with 0,5% or 10% FCS were stimulated to produce cell-derived matrices since it is known that FCS contains additional growth factors and cytokines that can activate fibroblasts. Mentlein and colleagues showed that FAP-α, a protein that is almost exclusively reported on activated fibroblasts, was upregulated in glioblastoma tissues after stimulation with 10% FCS (Mentlein et al, 2011). We were aiming to see if a different percentage of FSC in the medium activates fibroblasts to a greater extent and if this changes the structure and density of the produced cell-derived matrix. CAF(10% FCS)-derived matrix (Fig. 12.A) is denser compared to the matrix produced by CAF (0,5% FCS) (Fig. 12.B). In addition, the ECM is also more aligned. FBLN2 knockdown in CAFs reduced the density of the ECM to the same extent in CAF cultured in 0,5% or 10% FCS. To decide in which conditions the cell-derived matrix was aligned or not, the fibrils were analyzed with the ‘FibrilTool’ extension in ImageJ. Cell-derived matrices are considered as aligned when more than 30% of fibers are orientated towards the same angle. The matrix produced by CAF (10% FCS) is aligned since more than 30% of the fibers are orientated in -80° and 80°, while the angles of the matrix produced by CAF (FBLN2 KD) are spread over the range of 10° to 80° (Fig. 12.C). Fibril alignment quantification showed also that CAF (0,5%)-derived matrix is aligned, however there are regions of the matrix that are not aligned (not shown). For this reason, other experiments were performed with fibroblasts that were cultured in DMEM supplemented with 10% FCS and TGF-β unless otherwise indicated.

FN expression is similar in CAF- and CAF (FBLN2 KD)-derived matrices (Fig. 12.A). However, the intensity of immunofluorescence was not quantified since pictures were not made with a confocal microscope. In addition, western blot analysis of CAF- and CAF (FBLN2 KD)- derived matrices also showed that FBLN2 knockdown does not alter FN expression (Fig. 14). Immunofluorescent FBLN2 staining of cell-derived matrix shows that FBLN2 is downregulated in CAF (FBLN2 KD)-derived matrix compared to CAF-derived matrix (Fig. 13). Summarizing, CAF-derived matrices are dense and aligned, however CAFs that are cultured in medium supplemented with 10% FCS are more activated. The ECM produced by this CAF shows increased stiffness and density compared to ECM produced by CAFs cultured in 0,5% FCS. Although CAF (siFBLN2 KD)-derived matrices are less dense and fibers are not aligned, the intensity of the FN-staining is approximately the same in the fibers over the different conditions. Western blot analysis of cell-derived matrices did also not reveal a difference in FN expression in both conditions.

Figure 12.Fibronectin staining and fiber alignment of CAF-derived matrix. CAFs were transfected with siRNA that targeted FBLN2(#2) and subjected to cell-derived matrix production. After 7 days, CAFs were denuded from the matrix. (A/B) Representative pictures of FN staining in cell-derived matrix produced by CAFs that were maintained in DMEM supplemented with 10% or 0,5% FCS respectively. (C/D) Quantification of fiber alignment in cell-derived matrix produced by CAFs that were maintained in 10% FCS and 0,5% FCS medium respectively by making use of the ‘FibrilTool’ in ImageJ. Graphs are based on the orientation of 50 fibrils per condition.

Figure 13. Immunofluorescent staining of Fibulin-2 in CAF-derived matrices. CAFs were transfected with siRNA targeting FBLN2(#2) and subjected to cell-derived matrix production. After 7 days, CAFs were denuded from the matrix. CAFs were transfected with siLUC as a control for transfection. Representative pictures of immunofluorescent staining of fibulin-2 are displayed.

Figure 14. Fibulin-2 knockdown in cell-derived matrices does not alter fibronectin expression. Immunoblot showing fibronectin and fibulin-2 expression in CAF- and CAF (FBLN2#2-3 KD)- derived matrices. siLUC was used as a control for transfection.

3.4.2 Studying the matrix properties of cell-derived matrix produced by NHF that were stimulated with hrFBLN2 FBLN2 knockdown in CAF changes the composition and structure of cell-derived matrix, so we assessed whether stimulating NHF with hrFBLN2 increased the density and alignment of cell- derived matrix. NHF were subjected to cell-derived matrix production while stimulated with 5 ng/ ml hrFBLN2 and subsequently compared to NHF- and CAF-derived matrices. NHF-derived matrix is not structured and non-aligned while the CAF-derived matrix is extremely dense and aligned, as fiber alignment quantification showed that over 60% of the fibrils is oriented in an angle of 50° and 60° (Fig. 15). Stimulation of NHF with hrFBLN2 alters the cell-derived matrix structurally, as it seems more dense and structured compared to NHF- derived matrix. However, quantification of fibril alignment showed that the matrix was not aligned. The fluorescent intensity of fibronectin-staining is similar between NHF- and NHF (hrFBLN2)-derived matrices, however it is difficult to make a comparison with CAF-derived matrix as the staining was impeded by the density of the matrix. In addition, NHF- and CAF- derived matrices were immunofluorescently stained for FBLN2 to evaluate whether stimulation of NHF with hrFBLN2 indeed leads to an increased incorporation of FBLN2 into the ECM (Fig. 16). FBLN2 expression is clearly enhanced in matrix produced by hrFBLN2-stimulated NHF and seems to be even higher than the expression in CAF-derived matrix.

Figure 15. Fibronectin staining and fiber alignment of NHF (hrFBLN2)-derived matrix. Cell-derived matrix was produced by NHF stimulated with 5 ng/ml hrFBLN2. Cells were denuded from the cell-derived matrix after 7 days. Cell-derived matrices produced by NHF and CAF served as a control. CAF were cultured in DMEM supplemented with 10% FCS and TGF-β. (A) Representative pictures of FN staining of cell derived matrix for each condition. (B) Quantification of fiber alignment of cell-derived matrix produced by NHF, NHF stimulated with hrFBLN2 and CAF by making use of a ‘FibrilTool’ in ImageJ. Graphs are based on the orientation of 50 fibrils per condition.

Figure 16. immunofluorescent staining of fibulin-2 in NHF- and CAF-derived matrices. Cell-derived matrix was produced by NHF that were stimulated with 5 ng/ml hrFBLN2. fibroblasts were denuded from the cell-derived matrix after 7 days. NHF- and CAF-derived matrix served as a control and CAF were cultured in DMEM supplemented with 0,5% FCS and TGF-β. Representative pictures of immunofluorescent FBLN2 staining of cell- derived matrix are displayed for each condition.

3.5 Unraveling the molecular mechanism involved in FBLN2-driven resistance to targeted therapy in HNSCC 3.5.1. Hypothesis As previous experiments showed that FBLN2 indeed protects SCC cells against the tyrosine kinase inhibitors gefinitib, the next step was to unravel the molecular mechanisms that are involved. FBLN2 could increase resistance towards tyrosine kinase inhibitors through a variety of mechanisms such as direct interaction with and altering the signaling pathways in SCC cells or by changing the contractile force of CAF. When CAF lose their contractile force they are not able to remodel the ECM which is one of the factors that contributes to cell migration and metastasis of cancer cells (Sanz-Moreno et al, 2011). Based on previous hypotheses, different possible theories were studied to discover the molecular pathways involved. FBLN2 consist structurally out of a large N-terminal domain, 3 anaphylatoxin-like domains, EGF-like domains and a C-terminal fibulin-type module (Fig. 5.A). EGF-like domains are known to be calcium-binding and are also observed in other proteins which are present in the ECM such as laminin and tenascin. Engel suggested that EGF-like domains in ECM- proteins and in the extracellular portion of membrane proteins could serve as signals for cellular growth and differentiation. However, it is important to mention that the mitogenic function that is attributed to laminin is not only confided to the EGF-like domains but to a region that also consists of other structural domains (Engel, 1989). Later, Swindle and colleagues showed that EGF-like domains in tenascin-C could elicit mitogenesis and EGFR autophosphorylation in an EGFR-dependent manner (Swindle et al, 2001). Since EGFR is expressed and upregulated in nearly all head and neck tumors, EGF-like domains in ECM- proteins could potentially activate EGFR and FBLN2 contains EGF-like domains, it was interesting to explore whether FBLN2 knockdown in cell-derived matrix could alter EGFR activation in SCC cells. Another research project in the lab headed by Dr. Cedric Gaggioli deals with molecular signaling pathways that are differentially regulated in SCC cells that are cultured on soft and stiff cell culture conditions. A gel composed of collagen type I and 4 mg/ml matrigel is used to mimic soft cell culture conditions while cell culture dishes are coated with 40 µg/ml collagen type I to resemble stiff cell culture conditions. However, these cell culture conditions do not correspond to physiological conditions so to mimic physiological relevant conditions, researchers in the lab also make use of Petrisoft hydrogels which range from 1 to 50 kPa. Healthy tissue in the head and neck region has a stiffness of 1 to 10 kPa, however increased stiffness in the range of > 12 kPa can lead to abnormal cell cycle progression and tumor initiation. (Herman et al, 2017; Janmey & Miller, 2011). Several experiments performed in the lab showed that SCC cells cultured on soft conditions are more sensible to treatment with EGFR inhibitors than SCC cells cultured on stiff cell culture conditions. RNA-sequencing was used to analyze which genes are upregulated between soft and stiff culture conditions. SCC12 were plated on 1 kPa and 50 kPa hydrogels and the analysis revealed that A20 was upregulated in SCC12 cultured on stiff cell culture conditions. A20 is a protein that is known to have anti-inflammatory effects by modulating the NF-κB and interferon regulatory factor (IRF) pathways (Catrysse et al, 2014). One of the mechanisms by which it downregulates NF-κB signaling is by its ubiquitin-editing domains. The amino-terminal domain of A20 is a deubiquitinating enzyme (DUBs) while

34 its C-terminus functions as an ubiquitin ligase with which it catalyzes the formation of K48- linked polyubiquitin chains that are targets for proteosomal degradation (Wartz et al, 2004). Independent of its role as a modulator of NF-κB signaling, it has also an anti- apoptotic function in different cell types (Catrysse et al, 2014). A20 is reported previously multiple times as a tumor-suppressor or oncogene in cancer. In hepatocytes, A20 acts as a protective factor preventing chronic liver inflammation and hepatocellular carcinoma (Catrysse et al, 2016). However, the protein has an opposite role in aggressive basal-like breast cancers since it promotes metastasis by mono-ubiquitinylating SNAIL1 at 3 lysine residues (Lee et al, 2017). The first experiments performed in the project, which deals with the role of A20-driven therapeutic resistance in cancer cells, seem to confirm the hypothesis that A20 provides protection against EGFR-inhibitors in HNSCC. It seemed interesting to study if there is a connection between the molecular mechanisms that are involved in ECM-driven and tumor cell-driven chemoresistance in HNSCC towards EGFR inhibitors. Another possibility is that FBLN2 affects the contractile force of cancer associated fibroblasts. Actomyosin contractility plays a role in migration of tumor cells and in ECM remodeling by tumor fibroblasts (Sanz-Moreno et al, 2011). Rho-Rho-kinase (ROCK) signaling regulates force-mediated matrix remodeling through phosphorylation of MYPT1. The result is a decrease in myosin phosphatase and consequently increased phosphorylation of MLC2 and activity of myosin II (Gaggioli et al, 2007; Sanz-Moreno et al, 2011). One of the pathways that activates ROCK-dependent actomyosin contractility is the GP130-IL6ST/JAK1 axis (Sanz-Moreno et al, 2011). Since FBLN2 is differentially regulated between CAF and CAF treated with ruxolitinib, a JAK1 inhibitor, the protein could potentially play a role in regulating actomyosin contractility. To check this hypothesis, a contraction assay was performed with CAF in which FBLN2 was downregulated with siRNA and NHF and CAF that were stimulated with hrFBLN2. In addition, the expression of α-SMA and MLC2/pMLC2 was analyzed in NHFs upon TGF-β stimulation.

3.5.2. A20 expression and EGFR activation in SCC12 cells cultured of CAF(FBLN2 KD)- derived matrix CAFs were transfected with siRNA targeting siJAK1, siFBLN2(#1-2) and siLUC (transfection control) and subjected to cell-derived matrix production. CAFs were denuded and SCC12 were plated on the cell derived matrix. After 2 days, SCC12 were stimulated with 5 ng/ml EGF for 10 minutes, since EGF is one of the ligands that activates the EGFR signaling pathway. Then, expression of A20 and pEGFR was studied by making use of western blot (Fig. 17.A). pEGFR expression is very low when SCC12 are not stimulated with EGF. Depletion of JAK1 or FBLN2 in CAF does not seem to alter the expression of pEGFR in SCC12. However when the cancer cells are stimulated with EGF, pEGFR is upregulated in the SCC12 that were cultured on the matrix produced by CAF and CAF (JAK1 KD). Knockdown of FBLN2 slightly decreases phosphorylation of EGFR, what could indicate that FBLN2 in the cell-derived matrix is able to stimulate phosphorylation of EGFR. Depletion of JAK1 and FBLN2 in CAF does not alter A20 expression in unstimulated SCC12 while A20 expression slightly decreases in both conditions when the cancer cells are stimulated with EGF (Fig. 17.B).

These results could indicate that the ECM-protein FBLN2 is involved in regulating EGFR signaling and A20 expression in EGF-stimulated SCC12 cells since depletion of FBLN2 in the cell-derived matrix leads to a moderate decrease of both proteins.

Figure 17. Expression of A20 and tubulin in SCC12 after stimulation with EGF. (A) Cell-derived matrices were produced by CAFs in which JAK1 or FBLN2(#1-2) was knocked down with siRNA. siLUC was used as a control of transfection. CAFs were subjected to cell-derived matrix production for 7 days after which the cells were denuded. SCC12 were plated on the cell-derived matrices and after 2 days stimulated with 10 nM EGF or left untreated for 10 minutes. (B) Immunoblot showing pEGFR and A20 expression in SCC12 upon EGF-stimulation. Tubulin is used as a loading control.

3.5.3. The role of fibulin-2 in actomyosin contractility of fibroblasts Increased contractility is one of the characteristics of activated fibroblasts that is involved in tumor progression and resistance towards cancer therapy. One of the main pathways regulating the contractile force of CAF is the GP130/JAK1 axis and blocking JAK1 decreases the capacity of CAF to contract collagen gels (Sanz-Moreno et al, 2011). Since depletion of JAK1 in CAFs alters the expression of FBLN2, it is very interesting to explore the role of FBLN2 in actomyosin contractility. Contractility of cells is evaluated with collagen gel contraction assays in which the cells are embedded in a gel consisting out of collagen type I and Matrigel. The percentage of contraction is determined by measuring the circumference of the gel. First, a contraction assay was performed to measure the actomyosin contractility of CAFs in which FBLN2 was knocked-down with siRNA (Fig. 19). CAFs were transfected and the day after, a gel contraction assay was performed and after 7 days the gel size was measured. CAFs are known the have an increase actomyosin force compared to NHF and are used as a positive

36 and negative control respectively. CAFs were transfected with siLUC as a control for transfection. Y27 inhibits ROCK-signaling and subsequently actomyosin contractility and is used as a negative control. NHFs contract the collagen gel 31,8%, while after activation of fibroblasts the percentage of contraction is 57,7% and 50,6% respectively for CAF and CAF (siLUC). The ROCK-inhibitor Y27 completely blocks actomyosin signaling. Depletion of FBLN2 reduces the percentage of contraction to 45% in CAF (siFBLN2#1) and to 22% in CAF(siFBLN2#2). A Kruskall-wallis test and the Dunn post hoc test was performed to test if this reduction was significant. The Kruskall-Wallis test is a non-parametric test that is used for comparing two or more independent groups. To correct for multiple comparison the Dunn post hoc test was performed. There was no significant reduction in contractility between both CAF (siLUC) and CAF (siFBLN2#1) (N1 = N2 = 4, p = 1,00) or CAF (siLUC) and CAF(siFBLN2#2) (N1 = N2 = 4, p = 0,957) . The same experiment was performed with two other sequences (#3- 4) targeting FBLN2, since there was a big difference (21%) in collagen gel contraction between CAF transfected with siFBLN2#1 and siFBLN2#2. No statistical analysis was performed because the experiment was only executed twice. The percentage of contraction of collagen by NHFs amounts 41,0% while this increases to 60,1% and 55,5% for CAF and CAF (siLUC) respectively. Depletion of FBLN2 with siRNA sequences #3-4 reduces the ability to contract collagen gels to 28,1% and 14,4%. The actomyosin contractility of CAF (FBLN2 KD) is reduced compared to CAF and CAF(siLUC), however it is difficult to conclude to which extent FBLN2 plays a role in the contractile force of CAF as the reduction in contractility differs depending to the siRNA sequence used. Next, a collagen contraction assay was performed to determine if stimulating NHFs and CAFs with hrFBLN2 could alter their contractile force. During the contraction assay, NHFs and CAFs were stimulated with 5 ng/ml hrFBLN2 every other day. Stimulation with hrFBLN2 increased the ability to contract collagen gel of NHFs with 1,3% while this decreased with 5,1% in CAFs. Stimulation of fibroblasts with hrFBLN2 does not alter their ability to contract collagen gels. The experiment was performed twice, so no statistical analysis was performed. Then, the expression of contractility-associated proteins α-SMA and MLC2 was assessed in NHFs to examine whether FBLN2 is involved in their regulation (Fig. 20). α-SMA is a myofibroblast-specific marker and MLC2 activation is an essential component of the ROCK- signaling pathway which becomes phosphorylated when it is activated. NHFs were transfected with siRNA targeting FBLN2#1-2 and treated with TGF-β for 24 hours. Western blot analysis shows that FBLN2 knockdown is not complete, however there is a decrease in expression compared to TGF-β stimulated and non-stimulated NHF. There is no difference in α-SMA expression across the different conditions. TGF-β stimulation increases total MLC2 expression and MLC2 phosphorylation in NHF compared to unstimulated NHF. FBLN2 knockdown in NHF reduced total MLC2 expression, but surprisingly not MLC2 phosphorylation.

Figure 18. The role of FBLN2 in actomyosin contractility of cancer associated fibroblasts. (A) The percentage of matrix contraction of CAFs in which FBLN2 was downregulated with different siRNA sequences targeting FBLN2(#1-2). Y27 is a ROCK-signaling inhibitor. SiLUC is a control for transfection (n=4, ± SD, *p < 0,5)) (B) The percentage of matrix contraction of CAFs in which FBLN2 was downregulated with different siRNA sequences targeting FBLN2(#3-4). Y27 is a ROCK-signaling inhibitor. siLUC is a control for transfection (n=2) (C) The percentage of matrix contraction of NHFs and CAFs that were stimulated with 5 ng/ml rhFBLN2 every other day. (n = 2).

Figure 19. Expression of markers of actomyosin contractility in fibroblasts after fibulin-2 knockdown. NHFs were transfected with different siRNA sequences targeting FBLN2(#1-2). After two days, they were stimulated with TGF-β for 24 hours. siLUC was used as a control for transfection. (A) Immunoblot showing the expression of FBLN2 and α-SMA in TGF-β-stimulated or unstimulated fibroblasts. Tubulin was used as a loading control. (B) i- Immunoblot showing the expression of MLC2 and pMLC2 in TGF-β-stimulated or unstimulated fibroblasts. Tubulin was used as a loading control.

PART 5 : DISCUSSION

Squamous cell carcinoma of the head and neck is one of the ten most occurring cancers worldwide and is characterized by a highly malignant phenotype. The survival rate of patients depends mainly on the site that is affected and on the presence of local and systematic metastasis. At presentation, approximately 10% of patients shows distant metastasis which decreases the survival rate dramatically with more than 50%. A major effort was made to develop new treatments, but the survival rate for patients with advanced disease did not improve for the last 20 years (Sanderson & Ironside, 2002). Treatment consist primarily of chemotherapy combined with EGFR targeting therapy. At the moment, cetuximab is the only FDA-approved EGFR inhibitor that is used in the clinic to treat HNSCC. Small-molecule inhibitors such as gefitinib and erlotinib failed to improve the disease-free survival rate of head and neck cancer patients in clinical trials and resistance towards targeted therapy is a phenomenon that is observed a lot in head and neck cancer patients (Echarri et al, 2016). As the contribution of the tumor microenvironment is inevitable in HNSCC, it is interesting to study its potential role in resistance to EGFR-inhibitors. Preliminary research in the lab of Dr. Cedric Gaggioli showed that increased stiffness of the ECM protects SCC12 cells against cell death induced by the TKI gefitinib. siRNA screening of 52 proteins that were differentially expressed between NHF-, CAF-, and CAF (+ ruxolitinib)-derived matrices revealed that fibulin-2 could be involved in ECM-driven protection of SCC cells to TKI. Cell survival of SCC12 cells cultured on CAF (FBLN2 KD)-derived matrix was similar to survival on CAF-derived matrix in untreated condition while treatment with gefitinib reduced cell survival considerably. Knockdown of the other potential targets in CAF led either to a reduction in cell survival of non-treated SCC12 cells compared to cell survival of SCC12 cultured on CAF-derived matrix or treatment with gefitinib did not alter cell survival of SCC12 cells substantially. In view of the foregoing, FBLN2 seemed to be the best target to study. The goal of the project was to examine if the ECM-protein FBLN2 is one of the key players in resistance to targeted therapy in HNSCC by increasing matrix stiffness, influencing actomyosin contractility in CAF or through interaction with SCC cells. 5.1. Preliminary remarks The different experimental procedures were mainly based on the production of cell- derived matrix and contractility of NHF and CAF. Since the HNSCC-derived CAF available in the lab lost partly their CAF-properties, they were replaced by NHF obtained from foreskin of a child and treated with TGF-β, since this is one of the dominant factors in stimulating the conversion of fibroblasts to their activated form. TGF-β induces the expression of FAP and the functional marker α-SMA (Chen et al, 2009). NHF treated with TGF-β were referred to as CAF for simplicity. The first goal of the project was to confirm the results obtained from the RNAi-based screen which showed that FBLN2 knockdown in the ECM decreased cancer cell survival upon gefitinib treatment. The results of the screen were obtained by assessing cell survival of SCC12 which are skin squamous cell carcinoma cells. The same cell line was used to validate these results after which cell survival of CAL27 cells (tongue squamous cell carcinoma cells) upon gefitinib treatment was analyzed. During subsequent experiments, SCC12 were used due to problems with several HNSCC cell lines. However, it is important

to keep in mind that there are also a lot of differences between these two types of cancer. For example, the major risk factors for HNSCC are tobacco smoke and alcohol consumption while this is UV light for cutaneous squamous cell carcinoma. Although the risk factors between these two types of cancer differ, EGFR is a molecular marker that is common for both HNSCC and cutaneous SCC. Since the main research subject HNSCC is, it is essential to confirm the obtained results in a HNSCC cell line.

5.2. Confirmation of the role of fibulin-2 in ECM-driven resistance to targeted therapy in head and neck squamous cell carcinoma The first step in the project comprised validating the role of FBLN2 in ECM-derived protection of SCC cells. To prove this, SCC12 cells were cultured on cell-derived matrix in which FBLN2 was knocked down by making use of siRNA. Cell-derived matrices form a 3D- scaffold that mimics the in vivo situation in a better way than 2D surfaces or other 3D cell culture methods including Matrigel which lack complexity since they are composed of hundreds of different proteins and proteoglycans. However, this entails that the composition of the matrix is not known which could result in variability among experimental data. FBLN2 depletion from the cell-derived matrix led to a substantial decrease in cell survival of SCC12 compared to control. The difference in cell survival amounted 23% for both siRNA sequences siFBLN2#1 and siFBLN2#2. This was not the case for SCC12 cultured on cell- derived matrix produced by CAF(JAK1 KD). This is surprising since JAK1 inhibition with ruxolitinib in CAF reduces matrix stiffness and SCC cells cultured on cell-derived matrix with reduced stiffness are more prone to cell death upon gefitinib treatment. Furthermore, inhibition of the IL-6R/JAK1/STAT3 signaling pathway in NSCLC cells reduced resistance to the TKI afatinib (Kim et al, 2012). A difference in the extent to which JAK1 is inhibited or knocked down by ruxolitinib or siRNA sequences could explain these results. It is also possible that JAK1 knockdown solely is not sufficient to abrogate the ECM-derived protection of SCC cells. Nevertheless, these data confirm the role of FBLN2 in ECM-driven resistance to targeted therapy. It could be informing to repeat the experiment with the two other siRNA sequences (FBLN2#3-4) since the results obtained in other experiments show that there could be some off-targets effects. Next, we tested if stimulation of NHF with hrFBLN2 could increase cell survival of gefitinib- treated SCC12 cultured on cell-derived matrix compared to NHF-derived matrix. Cell survival of cancer cells was then compared to cell survival of SCC12 cells on NHF- and CAF- derived matrices. Absolute cell counts revealed that the cell number was the same across all conditions for non-treated SCC12 cells which indicates that differences in stiffness of the ECM does not affect cell survival of SCC cells. No significant increase in cancer cell survival was measured after stimulation of NHF with hrFBLN2 compared to SCC12 cultured on NHF-derived matrix. This results should be confirmed by repeating the experimental procedure with increasing concentration of hrFBLN2. Since the projects main subject is squamous cell carcinoma of the head and neck region, the results validating the role of FBLN2 in ECM-derived protection of SCC cells needed to be confirmed in HNSCC cells. The experiments were repeated with the CAL27 cell line, which are tongue squamous cell carcinoma cells. FBLN2 depletion in CAF-derived matrix

led to an increase in cell death of 52,2% and 31,4%, for respectively CAL27 cells cultured on CAF(siFBLN2#1)- and CAF(siFBLN2#2)-derived matrix, compared to survival of CAL27 on CAF-derived matrix. Strikingly, there was a large difference between the percentage of cell survival of CAL27 cells when FBLN2 was knocked down with siFBLN2#1 and siFBLN2#2. This could indicate an off-target effect of one of the siRNA sequences since western blotting showed that all 4 sequences knock FBLN2 down to the same extant in CAF. The idea that siRNA sequences can have off-target effects due to certain properties of the siRNA themselves or by the technologies used to deliver them, is nowadays supported widely. Off-target effects associated with siRNA are mediated through multiple mechanisms including microRNA-like off-target effects, inflammatory response through activation of Toll-like receptors and influencing microRNA processing and function through saturation of the endogenous RNAi machinery (Jackson & Linsley, 2010). There exist multiple algorithms to detect off-target effects associated with siRNA e.g. Sylamer is a tool that can be used to analyze siRNA off-target effects from expression data (Dongen et al, 2008). One of the methods to mitigate these off-target effects is by reducing the siRNA concentration to 1 nm (Caffrey et al, 2011). The cell survival experiment could be repeated with reduced siRNA concentration to analyze whether the effect mediated by the different siFBLN2 sequences would be more alike. However, it is important to verify that FBLN2 is still sufficiently downregulated when using low siRNA concentrations. Previous experiments were repeated three times independently. Due to the small sample size, the assumption of normal distributed data was not fulfilled and data were analyzed with the non-parametric Mann-Whitney U test. This showed that there is no statistically significant decrease in cell survival of CAL27 cultured on CAF- or CAF(FBLN2 KD)-derived matrix. Either this means that FBLN2 knockdown does not significantly decreases cells survival of CAL27 or that there is indeed a biologically relevant effect which could not be proven with statistics due to lack of power to reject the null hypothesis. This could be avoided by increasing the sample size. Altogether, previous experiments confirm that FBLN2 in involved in ECM-driven therapeutic resistance of both SCC12 and CAL27 cells.

5.3. Fibilin-2 is important for the structural integrity of cell-derived matrices We then focused on studying the effect of FBLN2 knockdown in CAFs on the structure and composition of cell-derived matrix. ECM was produced by CAFs or CAFs (FBLN2 KD) during 7 days and thereafter CAF were depleted from the cell-derived matrix and subsequently stained for FN and FBLN2. The experiment was repeated with fibroblasts that were cultured in DMEM supplemented with 0,5% or 10% FCS and TGF-β to see to which extent FCS further activates fibroblasts. The CAF (10% FCS)-derived matrix is more dense and the ECM fibers are more aligned than CAF (0,5% FCS)-derived matrix, which is aligned but also contains non-aligned regions. FBLN2 knockdown in both types of CAF alters the structure of the cell-derived matrix to the same extent as the matrix is less dense and as fibers lose their alignment. Fibronectin expression does not alter upon FBLN2 knockdown, which was shown with both immunofluorescent staining and western blot. In addition, FBLN2 was visualized in CAF-derived matrices by immunofluorescent staining which showed that FBLN2 expression decreases in cell-derived matrix upon knockdown in CAF. Still, it is

41 essential to visualize the cell-derived matrix with confocal microscopy and to quantify the intensity of the FN and FBLN2 signal to verify the results. As the ECM produced by NHF is non-aligned and less dense compared to CAF-derived matrix, we examined the effect of FBLN2-stimulation of NHF during the production of ECM. The density of the ECM was increased compared to NHF-derived matrix and seems to be more structured, however fiber alignment quantification showed that the matrix was not aligned. FBLN2-staining of the cell-derived matrices proved that stimulating NHF with hrFBLN2 increases FBLN2 expression in the ECM. Moreover, FBLN2 expression seems to be higher than in CAF-derived matrices. As mentioned above, the intensity of the immunofluorescent signal should be quantified both for FN and FBLN2 staining after imaging the ECM with confocal microscopy. Evaluating other properties of the cell-derived matrix should be the next step in the project. Another characteristic of stiffened extracellular matrix is increased cross-linking of type I and type III collagen which is studied by picrosirius red staining. The experiments were performed, however the necessary filters were not available to visualize the crosslinking as this requires polarized light (Fig.20/21). Then, the rigidity of CAF (FBLN2 KD)- derived matrix should be assessed with atomic force microscopy AFM. It is plausible to suggest that FBLN2 knockdown could reduce the rigidity of ECM since its knockdown in CAF results in less structured and non-aligned ECM. If FBLN2 would indeed decrease the rigidity of ECM, then we also expect a decrease in collagen crosslinking. These finding would allow to conclude that FBLN2 is involved in ECM-derived protection of SCC cells through increasing the rigidity of the matrix. Finally, it could also be informing to analyze the ECM composition upon FBLN2 knockdown and compare it to the composition of CAF- and ECM derived matrix to examine whether other matrix proteins are differentially expressed. Quantification of ECM proteins is mostly performed with MS analysis using soft ionization methods such as ESI and MALDI-TOF. Altogether, FBLN2 is important in maintaining the structural integrity of the ECM as its downregulation in CAF-derived matrix abolishes alignment of the ECM while stimulation of NHF results in an increase in density and structure of cell-derived matrix. FBLN2 knockdown in CAF decreases FBLN2 in the ECM while stimulating NHF with hrFBLN2 increases FBLN2 expression. Fibronectin expression does not seem to alter upon FBLN2 knockdown, however further experiments have to confirm this. To get to know its specific role in the structural integrity of the ECM, the rigidity and composition of the ECM should also be studied.

5.4. Unraveling the molecular mechanism involved in FBLN2-driven resistance to targeted therapy Next, we tried to unravel the mechanisms that are involved in matrix-derived protection of HNSCC cells mediated by FBLN2. FBLN2 contains multiple EGF-like domains, which are also observed in other ECM proteins and can activate EGFR signaling. Absence of FBLN2 in cell-derived matrix does not alter pEGFR expression in SCC12 cells. However, there is a decrease in EGFR activation when EGF-stimulated SCC12 cells are cultured on CAF-derived matrix compared to CAF (FBLN2)- derived matrix. If EGF-like domains in FBLN2 are capable of acting as a ligand of the EGFR than there would also be a decrease in pEGFR expression in non-stimulated SCC12 cells. Therefore, FBLN2 probably activates EGFR signaling through another mechanism. JAK1 knockdown in CAF did not lead to a difference in pEGFR expression. The biacore system could be used to study if there is a direct interaction between FBLN2 and the EGFR. The system consists of a CHIP to which one protein is attached while the potential interaction partner is injected across the surface. An advantage is that the proteins do not have to be labeled as with e.g. FRET. Biacore relies on the principle of surface plasmon resonance and can be used to study the affinity and kinetics of protein-protein interactions. However, this probably lies outside the scope of the project (Lakey & Raggett, 1998). Another hypothesis was that FBLN2 induced activation of certain signaling pathways that would lead to increased A20 expression. Preliminary data in the lab showed that A20 is upregulated in SCC12 cells cultured on stiff conditions and provides protection to SCC12 cells upon treatment with EGFR inhibitors. Identical to what was observed for pEGFR expression, A20 expression does not change in SCC12 cultured on CAF-derived matrices compared to CAF (FBLN2 KD)-derived matrices while there is a small decrease when the SCC12 are stimulated with EGF. These results were also surprising, if FBLN2 increases the stiffness of cell-derived matrix than we would also expect that A20 is upregulated in SCC cells cultured CAF-derived matrix. Another experiment that could be performed to verify this involves culturing SCC cells in which A20 is knocked down on CAF (FBLN2 KD)-derived matrix. When both proteins provide protection to SCC cells via the same molecular mechanism, than we expect no or only a slight decrease in cell survival of SCC12. On the other hand, when they are not part of the same molecular mechanism than a large increase in cell death is expected. Fibroblast actomyosin contractility is essential for matrix remodeling and subsequently cancer progression and resistance to cancer therapy. FBLN2 knockdown decreased actomyosin contractility of CAFs compared to the contractility of CAFs. However, knockdown of FBLN2 with different siRNA sequences also led to a different percentage of reduction in actomyosin contractility, indicating again that there could be an off-target effect of some of the sequences. Contractility of hrFBLN2 stimulated CAFs and NHFs did not differ from contractility of non-stimulated cells.

Western blot analysis of NHFs showed that α-SMA is not differentially expressed upon TGF-β activation and FBLN2 knockdown. This is surprising as TGF-β is one of the cytokines that activates fibroblasts and induces α-SMA expression, a myofibroblast-specific marker. FBLN2 knockdown in NHFs led to a decrease of total MLC2 but not of pMLC2. This is remarkable and could be explained by technical issues. At the moment, we cannot conclude if FBLN2 alters the actomyosin contractility of fibroblasts. First, it should be verified if there is an off-target effect of the siRNA sequences. In addition, previous experiments show that although the fibroblasts were starved in medium supplemented with 0,5% FCS for 5 days, they are still activated to a certain extent. Under normal circumstances, α-SMA should not be expressed in quiescent fibroblasts and they should not be able to contract the collagen gel. Probably the NHF were in culture too long.

5.5. Concluding remarks and perspectives The project provides evidence concerning the role of fibulin-2 in ECM-driven therapeutic resistance in head and neck squamous cell carcinoma. We showed that FBLN2 provides protection against cell death induced by the tyrosine kinase inhibitor gefitinib and that fibulin-2 is essential for the structural integrity of CAF-produced ECM. Furthermore, fibulin-2 is potentially one of the regulators of EGFR activation and A20 expession in EGF- stimulated SCC12 cells and could reduce actomyosin contractility in CAF. In addition to its role in ECM-driven resistance to targeted therapy, it could be interesting to study if fibulin-2 is also involved in other cancer-related processes including cancer cell invasion and metastasis since it is well-known that increased stiffness of the ECM and actomyosin contractility are not only mediators of cancer drug resistance. Organotypic invasion assays are in vitro models to study SCC cell invasion which recapitulate the morphology of SCC cells in vivo. To do so, CAF in which FBLN2 is knocked down are embedded in a gel composed of type I collagen and Matrigel while CAL27 cells are plated on top. The cultures are fixed after 7 days and processed to perform haematoxilyn and eosin (H&E) staining. Then, the invasion of CAL27 cells can be assessed (Nyström et al, 2005; Albrengues et al, 2014). Subsequently, the results obtained with in vitro experiments should be confirmed by examining the effects of FBLN2 knockdown in vivo. However, it is essential to mention that FBLN2 knockout (KO) mice develop phenotypically normal and are indistinguishable from wild-type mice. Sicot and colleages reported that FBLN2 is dispensable for elastic fiber formation in mice, probably due to functional redundancy with fibulin-1. FBLN1 KO mice display a perinatally lethal phenotype what indicates that FBLN2 cannot compensate for FBLN1 loss (Sicot et al, 2008). Nevertheless, FBLN2 KO mice develop a phenotype of reduced cardiac tissue remodeling after myocardial infarction indicating the requirement of FBLN2 for tissue repair after hypoxic stress which is one of the drivers of malignant progression (Baird et al, 2013). With regard to the in vitro experiments, it is necessary to explore whether there is also an compensatory effect mediated by FBLN1 in HNSCC, since this was not described before in any type of cancer. First, it should be examined if there is

an increase in FBLN1 in cell-derived matrix that is depleted in FBLN2 compared to CAF- derived matrices. If this is the case, cell survival experiments should be reperformed to examine if double knockdown of FBLN1 and FBLN2 could further abolish the resistance upon gefitinib treatment of HNSCC cells. Also the conclusions drawn from other experiments should be re-evaluated. Then, the role of FBLN2 in ECM-driven resistance to targeted therapy should be studied in a mouse model. FBLN2 KO mice are viable and are commercially available in e.g. the 129/SvEv-C57BL/6 background. Oral squamous cell carcinoma can then be induced through administrating 4-Nitroquinoline 1-oxide (4-NQO) in the drinking water of the miceFBLN2-/- (Tang et al, 2004). Another possibility is to co-inject HNSCC cells and CAFs in which FBLN2 is knocked down in immunodeficient mice e.g. BALB/c mice. Tumors should be treated with gefitinib and tumor progression should be followed by measuring the tumor size. Immunohistological staining of FBLN2, FN and collagen should be performed after the mice are sacrificed.

5.6. Possible application or implications Cancer treatment strategies focus mainly on targeting the cancer cells themselves. However, resistance to classical chemotherapy and targeted therapy is observed often in patients after a certain treatment period. As the role of the tumor microenvironment is inevitable in cancer initiation, progression and resistance to therapy nowadays, new treatment methods should combine targeting the cancerous cells and the tumor stroma. The project confirms the role of fibulin-2 in ECM-driven resistance to targeted therapy in HNSCC, so further research should verify if fibulin-2 could be a direct target or if molecules involved in the molecular mechanism could be targeted with reduced resistance.

PART 5: MATERIAL AND METHODS Cell culture Primary normal human fibroblasts (NHF) were isolated from foreskin of a child (2006) and were cultured in DMEM (Gibco, Thermo Fisher Scientific) supplemented with 10% Fetal Calf Serum (FCS) and 2 mM glutamine. SCC12 were a gift from E. Sahai (The Francis Crick institute, UK) and were maintained in DMEM supplemented with 10% FCS, 2mM glutamine, insulin- transferrin-selenium ((41400-045), Gibco) and 0,5 µg/ml hydrocortisone (H-1305, Sigma- Aldrich). CAL27 were and cultured in DMEM supplemented with 10% FCS and 2 mM glutamine. All cell lines were incubated at 37 °C in humidified 5% CO2 atmosphere and experiments were performed at passages 5-10. Fibroblast depletion and the generation of activated fibroblasts All the experiments were performed with activated normal fibroblasts, since CAF were not available. NHF were cultured in 0,5% or 10% FCS medium supplemented with 2 ng/ml TGF-β for 5 to 7 days to develop constitutively activated fibroblasts and are referred to as CAF. NHF were depleted in DMEM supplemented with 0,5% FCS for 5 days prior to experiments. Antibodies Antibodies against JAK1 (#3332; 1/500), MLC2 (#3672; 1/500), pThr18/19-MLC2 (#3674; 1/500) were purchased for Cell Signaling (Cell Signaling Technology). Anti-FN (#F3648; 1/200) and FBLN2 (#SAB2702003; 1/200) was purchased from Sigma-Aldrich (Merck). Anti-Tubulin (SC-8035; 1/10000) was purchased from Santa Cruz. Secondary HRP-coupled anti-mouse and anti-rabbit antibodies were purchased from DAKO (respectively #P0447 and #P0448; 1/5000). Secondary antibodies AF488-coupled antibodies anti-mouse and anti-rabbit were purchased from Invitrogen (Thermo Fisher Scientific) (respectively #28175 and #27034; 1/400). Transfection of fibroblasts with siRNA siFBLN2#1 GCGCAUAUCUUCCGCAUUG siFBLN2#2 GGGCAAGGCCUGAAGAGAA siFBLN2#3 GUGGAGAGCUCAUCUGCUA siFBLN2#4 CCCAAUACCUGCAAAGACA CAF were plated the afternoon before transfection at 60-80% confluence in DMEM supplemented with 10% FCS. 30 minutes prior the transfection, the medium was changed to Opti-MEM medium (serum-free medium) (Gibco, Thermo Fisher Scientific). Cells were transfected with Dharmafect 3 transfection reagent (#T-2002-02, Dharmacon) and 20 nM final concentration of siRNA. Both the transfection reagent and siRNA were diluted in opti-MEM medium and mixed in a 1:1 ratio. After 15 minutes, the formed siRNA-lipid complexed were gently added to the cells. After 6-8 hours the cells were plated on the gelatin-coated cell culture dishes (if applicable).

Cell-derived matrix production Tissue culture dishes were coated with 1% gelatin and gelatin was cross-linked with 1% glutaraldehyde. CAF were transfected with siRNA one day before plating them on gelatin- coated culture dishes. The next day, 2 . 105 cells were seeded per well (6-well plate) in DMEM medium supplemented with 10% FCS and 2 mM glutamine. After overnight incubation, the medium was changed and supplemented with 50 µg/ml ascorbic acid (A4403, Sigma-Aldrich) every other day for a period of 7 days. Then, the CAF were removed from the cell-derived matrix by making use of cell extraction buffer (PBS, 0,5% Triton-X-100, 20 mM NH4OH) and the cell-derived matrix was available for use in subsequent experiment. The cell-derived matrix was stored maximally one month. Cell survival assay Cells (SCC12/CAL27) were plated at a density of 5.104 per well (6-well plate) on the cell-derived matrix. After two days, the cancer cells were treated with 5 µM gefitinib or 5 µM DMSO (control) diluted in DMEM supplemented with 0,5% FCS and 2 mM glutamine and incubated for 2 days. Cells were fixed in 3,7% Paraformaldehyde (diluted in PBS) for 30 minutes and washed 2 times in PBS. Afterwards, the cells were stained with DAPI staining (1/2000) for 5 minutes and washed one time in PBS. To quantify the cell number, six pictures were acquired per condition with the ‘Evos FL’ fluorescent microscope (Thermo Fisher Scientific) and analyzed with the ‘Analyze Particles’ function of ImageJ. Cell numbers obtained in the gefitinib-treated condition were normalized to the control of each condition respectively. Western blot Depending on the type of sample, cells were lysed in lysis buffer (25 mM Tris (pH 6.8), 2% Sodium Dodecyl Sulfate (SDS), 5% Glycerol, 1% β-mercaptoethanol 0,01% Bromophenol Blue) or RIPA buffer(10 mM Tris-Cl (pH = 8.0), 1 mM EDTA, 0,5 mM EGTA, 1% Triton X-100, 0,1% sodium doxycholate, 0,1% SDS, 140 mM NaCl, 50 mM NaF). Samples containing cell-derived matrix were lysed in lysis buffer on ice and the volume of lysis buffer that was used depended on the cell number. Cell lysates were sonicated for 15 sec, centrifuged for 15 sec, cooked for 5 minutes and finally, centrifuged for 15 sec. Other samples were lysed on ice in RIPA buffer during 20 minutes and centrifuged for 20 minutes at 12 000 rpm to remove debris. The supernatant was transferred to a new Eppendorf and protein concentration was measured by making use of the Pierce BCA Protein Assay kit (Thermo Fisher Scientific). Equal amounts of protein were loaded and separated by SDS-PAGE and transferred onto immobilon-P PVDV transfer membranes (Merck). The immunoblots were blocked in 5% Bovine Serum Albumine (BSA) in PBS/T (10 mM Tris-HCl (pH 7,5), 500 mM NaCl, 0,1% Tween-20) for 1 hour at room temperature. After blocking, the immunoblots were incubated overnight in primary antibodies at 4 °C. The next morning, the membranes were washed three times in TBS/T for 10 minutes and probed for 1 hour in HRP-tagged secondary antibodies at room temperature. Finally, the immunoblots were washed three times 5 minutes in TBS/T and proteins were detected by chemilluminescence using the Immobilon Western Chemiluminescent HRP

Substrate (WBKLS0500, Merck). Immunofluorescent bands were visualized with the Pierce ECL Western Blotting substrate (Thermo Fisher Scientific).

Contraction assays Fibroblasts were transfected one day before the start of the contraction assay with the indicated siRNA sequences. The next day, fibroblasts were trypsinized and 25 . 103 cells were embedded in 100 µl of matrix gel (5x media, DMEM containing 0,5% FCS, HEPES (15630056, Gibco), matrigel (354234, Corning), 4 mg/ml Collagen type I (354249, Corning)) and seeded in triplicate into a 96 well plate. After 30 minutes incubation at 37 °C, the matrix gel was overlaid with 100 µL of DMEM supplemented with 0,5% FCS and 2 mM glutamine and the indicated inhibitors. The medium was changed every other day. A scan was taken every day of the 96- well plate from the moment contraction started until day 7 to measure the relative diameter of the well and each matrix gel. The diameter of the well and the gel was calculated using the ‘Polygon Selection’ and ‘Measure’ tool in ImageJ. The percentage of gel contraction was determined using the following formula: 100 x ( well diameter – gel diameter) / well diameter (Hooper et al, 2010; Bonan et al, 2016).

Immunofluorescent staining of cell-derived matrices and cells Gelatin-coated cover slips were prepared in a 24-well plate. CAF were transfected one day before the start of cell-derived matrix production (if applicable). After 7 days, fibroblasts were denuded from the cell-derived matrix which was fixed in 3,7% PFA for 30 minutes and subsequently washed 2 times in PBS. The cell-derived matrices were then blocked in 3% BSA/PBS for 30 minutes at room temperature after which they were incubated overnight in primary antibody against FN, FBLN2 or collagen type I at 4°C. The next morning, the cell- derived matrices were washed 3 times in PBS/T, incubated in secondary antibody for 1 hour at room temperature and washed 3 times in PBS/T again. Then, the cover slips were mounted and visualized with the Evos FL fluorescence microscope. Picrosirius red staining of cell-derived matrices Cell-derived matrices were prepared as described above. After denudation of the fibroblasts with cell lysis buffer, the cell-derived matrices were fixed in 3,7% PFA at room temperature for half an hour and subsequently washed with PBS. Then, the matrices were stained in picrosirius red solution (0,5 g Sirius red in 1,3% aqueous solution of picric acid) at room temperature for 1,5 hour. The slides were rinsed in acidificated H2O (250 µl acetic acid, 50 µl H2O) for 10 seconds. The slides were dehydrated by two changes in absolute alcohol followed by two changes in xylene and mounting. Quantification of fiber alignment Fibers in the cell-derived matrix were quantified by making use of the ‘FibrilTool’ developed by Boudaoud et al. to measure the direction and anisotropy of fibrillary structures in cell biology. 50 fibers were analyzed per condition by making use of the ‘Polygon tool’ and the ‘FibrilTool’ in ImageJ. Data was exported to excel, the calculated angels were ordered from - 90° to 90 and subsequently the number of fibers per category (-90°- 90°) were calculated. The

48 number of fibers/category was then normalized to the number of measured fibers. If more than 30% of the fibers belong to the same category, then the cell-derived matrix was regarded as aligned. In case the fibers belonged to multiple categories and none of them contained more than 30% of the fibers, the cell-derived matrix was considered not to be aligned.

Statistical analysis Cell culture experiments were performed three times independently unless otherwise indicated. No statistical analysis was performed when experiments were repeated less than three times. Results for the cell culture experiments and contraction assays are displayed as mean ± standard deviation. Samples from cell survival experiments were compared with the non-parametric Mann-Whitney U test. There was no correction for multiple comparison as the experiment did not contain more than 4 conditions. Contraction assays were analyzed with the non-parametric Kruskall-Wallis test followed by the post-hoc Dunn test to correct for multiple comparison. A P-value of ≥ 0,5 was considered significant. All statistical analysis have been performed in SPSS software.

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PART 7: ADDENDUM 7.1. Experimental procedures Generation of cell-derived matrix Preparation of cover slips and tissue culture dishes (6-well plate)

1. Prepare 1% gelatin in H2O and dissolve at 37°C during 30 minutes 2. Add 1,5 ml of 1% gelatin in each well and incubate for 1h at 37°C 3. Remove the gelatin and wash 2x with PBS 4. Add 1,5 ml of 1% glutaraldehyde for 20 minutes at room temperature 5. Remove the 1% glutaraldehyde and wash abundantly with PBS 6. (The plates can be stored at 4°C) 7. Wash 1x with DMEM 8. Plate 200 000 cells/well 9. After overnight incubation at 37°C change the medium to DMEM supplemented with 50 µg/ml ascorbic acid (Sigma A4403) 10. Change the medium every 2 days for a period of 6-8 days Denudation of CAF ! be careful not to dry the matrix ! be careful when the medium is removed not to detach the matrix 1. Wash 2x with PBS 2. Add very gently (with P1000 pipet) 1 ml of extraction buffer that is preheated at 37°C

(extraction buffer: 50 ml PBS + 125 µl 0.5% Triton-X-100 + 69 µl 20 mM NH4OH 3. Check under the microscope if there are no cells remaining and remove very carefully the extraction buffer 4. Add carefully 2 ml of PBS 5. Wash several times with PBS before the matrix can be used for following experiments 6. (The matrix can be stored at 4°C for 1 month)

Immunofluorescent staining of cell-derived matrix 1. Prepare matrix as described in: 1. Generation of cell-derived matrix 2. Wash the CDM 2x with PBS 3. Fix with 3.7% PFA/PBS for 30 minutes at room temperature 4. Remove the 3.7% PFA/PBS and wash 2x with PBS 5. Block with 3% BSA/PBS for 30 minutes at room temperature 6. Incubate the cover slips with CDM overnight at 4°C in 50 µl of primary antibody (3% BSA/PBS)

Table 1. Antibodies used for immunofluorescent staining of cell-derived matrix. Antibody Dilution Fibronectin (mouse) 1/400 Fibulin-2 (rabbit) 1/200

7. Wash 3x with PBS/Tween 8. Incubate the coverslips in 50 µl of secondary antibody for 1h (donkey antimouse or donkey antirabbit according to the primary antibody) 9. Wash 3x with PBS/Tween

10. Wash 1x with H2O 11. Mount the cover slips and visualize

DAPI staining 1. Wash the plates with the cells 2x with PBS 2. Fix with 3.7% PFA/PBS for 30 minutes at room temperature 3. Remove the 3.7% PFA/PBS and wash 2x with PBS 4. Incubate the cells for 5 minutes in 1/2000 DAPI in PBS 5. Wash the plates once with PBS 6. Visualize Contraction assay Preliminary work 1. Plate 100 000 cells/condition (every condition is performed in triplicates)

Preparation of the gel 2. Prepare the proper amount of gel according to the amount of conditions

Table 2. Composition of the gel used for contraction assays. 1 ml 5 ml 5x medium 80 400 0.5% medium (without 200 1000 antibody) HEPES 20 100 Matrigel 200 1000 collagen 400 2000 Cells 100 500

Contraction assay 3. Lyse the cells and resuspend in 30 µl 0.5% medium 4. Mix the cells with 270 µl of the gel 5. Put 90 µl of gel in each well (96-well plate)(triplicates) 6. Incubate for 30 minutes at 37°C 7. Add 100 µl of 0.5% medium (supplemented with the required inhibitors or stimulations) 8. Change the media every 2 days 9. Scan the plate every day when contraction begins Picrosirius red staining 1. Prepare matrix as described in: 1. Generation of cell-derived matrix 2. Fix the matrix in 3.7% PFA/PBS for 30 minutes at room temperature 3. Incubate the cover slips for 2h in picrosirius red solution (1.3% picrius acid + 0.5g Sirius red) at room temperature

4. Wash the cover slips for 10s in acidificated H2O (250 µl acetic acid + 50 µl H2O) 5. Wash : i. 2x 2 minutes in 70% ethanol ii. 2x 2 minutes in 96% ethanol iii. 2x 2 minutes in 100% ethanol iv. 2x 2 minutes in xylene (do not use plastic!) 6. Mount and visualize

Transfection of CAF

preliminary work 1. Plate the right amount of cells the day before the transfection according to the type of cell culture dish (60-80% confluence) Transfection 2. Wash the plates 2x with PBS 3. Add the proper amount of OptiMEM (reduced serum medium) 4. Dilute the DharmaFect transfection reagent in optiMEM medium 5. Dilute the siRNA in OptiMEM medium 6. Add the transfection reagent to the siRNA in a 1:1 ratio 7. Incubate 5-20 minutes 8. Add the siRNA complexes to the cells Table 3. siRNA sequences of FBLN2, JAK1 and LUC siRNA Sequence sequence FBLN2#1 GCGCAUAUCUUCCGCAUUG FBLN2#2 GGGCAAGGCCUGAAGAGAA FBLN2#3 GUGGAGAGCUCAUCUGCUA FBLN2#4 CCCAAUACCUGCAAAGACA

Transfection of SCC12 cells

preliminary work 1. Plate the right amount of cells the day before the transfection according to the type of cell culture dish Transfection 2. Wash the plates 2x with PBS 3. Add the proper amount of OptiMEM (reduced serum medium) 4. Dilute the Lipofectamine RNAiMAX transfection reagent in optiMEM medium 5. Dilute the siRNA in OptiMEM medium 6. Add the siRNA to the lipofectamine RNAiMAX Reagent in a 1:1 ratio 7. Incubate 5-20 minutes 8. Add the siRNA complexes to the cells

Western blot

Sample preparation Cell lysis in laemmli buffer 1. Prepare 1x laemmli buffer (+ β-mercaptoethanol) 2. Lyse the cells in 1x laemmli buffer on ice and scrape the cells from the cell culture dishes with a cell scraper, then transfer the cell suspension to a tube 3. Sonicate the samples for 15s while moving the sample up and down to break the cell wall 4. Spin the samples (short spin) 5. Cook the samples for 5 minutes 6. Spin the samples (short spin) 7. Samples can be stored at -4°C

Cell lysis in RIPA buffer 1. Prepare the prepare the proper amount of RIPA buffer or defrost RIPA buffer on ice 2. Wash the cells with ice-cold PBS 3. Add the ice-cold RIPA buffer, scrape the cells from the cell culture dishes with a cell scraper and transfer the cell suspension to a pre-cooled tube 4. Incubate the cell suspension for 30 minutes on ice 5. Centrifuge the cell suspension for 20 minutes at 12 000 rpm at 4°C 6. Place the tubes back on ice and remove the supernatant from the pellet and transfer to a new tube 7. Measure protein concentration with the BCA Protein Assay kit (Thermo Fisher Scientific):

Add 3 µl of sample to 47 µl of H2O Add 200 µl of reagent A/reagent B (1:1) to the sample Incubate for 20 minutes at 37 °C and measure protein concentration 8. Prepare the samples for western blot according to the protein concentration that was measured Preparation of the polyacrylamide gel Running gel Table 4. Composition of the running gel for western blot Gel percentage Volume (1 gel) 7%

H2O 4.3 ml Acrylamide 1.8 ml 10% H2O 3.6 ml Acrylamide 2.5 ml 12% H2O 3.1 ml Acrylamide 3 ml

SDS 10% 100 µl Tris 1M pH 8.8 3.75 ml APS 50 µl TEMED 10 µl

Stacking gel Table 5. composition of stacking gel for western blot. Volume (1 gel) H20 3.675 ml Acrylamide 0.625 ml SDS 10% 50 µl Tris 1M pH 8.8 0.625 ml APS 25 µl TEMED 5 µl

Running

1. Prepare 2 liter of running buffer (1.8 L H2O, 0.2 L TG-SDS 10x) 2. Load equal amounts of proteins into the wells of the gel 3. Run the gel (20-40 mA/gel)

Blotting : protein transfer 4. Prepare transfer buffer (1,4 L H2O, 20% ethanol, 200 ml TGF 10x) 5. Activate the PVDV membrane with ethanol 6. Prepare the transfer cassette and place it in the holder in such a way that the gel is facing the cathode (-). 7. Blot during 1-1.30h at 100V 8. When blotting is finished, the proteins can be visualized with ponceau S staining

Blocking 9. Prepare blocking solution (5%BSA/TBST) 10. Incubate the membranes for 1h in the blocking solution

Incubation with primary and secondary antibody 11. Incubate the membrane in the primary antibody solution overnight at 4°C 12. Wash 3x for 10 minutes with TBS/Tween 13. Incubate the membranes in the secondary antibody solution for 1h at room temperature 14. Wash 3x for 5 minutes with TBS/Tween

Developing 15. Mix Detection Reagent 1 and 2 in a 1:1 ratio (ECL western blotting reagent 16. Incubate the membrane in the ECL western blotting substrate solution and visualize

Buffers

Tris 1M (1L) 121,2g Tris Fill until 1L with distilled H2O TBS 10x (pH=7,4)(2L) 200 ml Tris 1M (pH=7,4) 176g NaCl Fill until 2L with distilled H2O Laemmli buffer (2x) 5 ml Tris 1M (pH=6,8) 10 ml SDS 10% 5 ml glycerol 30 ml distilled H2O Bromophenol blue For lysis : Add 14 µl β-mercaptoethanol to 1 ml of laemmli buffer (1x) RIPA buffer 10 mM Tris-Cl (pH = 8.0) 1 mM EDTA 0,5 mM EGTA 1% Triton-X-100 0,1% sodium doxycholate 0,1% SDS 140 mM NaCL Add before use : 50 mM NaF TBS Tween 0,1% (2L) 200 ml TBS 10x 2 ml Tween 20 Fill until 2L with distilled H2O PBS Tween 0,1% (2L) 200 ml PBS 10x 2 ml Tween 20 Fill until 2L with distilled H2O

7.2. Output generated by SPSS after statistical analysis 7.2.1. cell survival of SCC12 cultured on matrix produced by CAFs in which FBLN2 is knocked down by siRNA

7.2.2. Cell survival of SCC12 cultured on matrix produced by NHFs that were stimulated with hrFBLN2

7.2.3. Cell survival of CAL27 cultured on CAF (FBLN2 KD)-derived matrix

7.2.4. The role of fibulin-2 in contraction of CAF and NHF

7.3. Additional data 7.3.1. Picrosirius red staining of cell-derived matrix

Figure 20. Visualizing type I and type III collagen in NHF-derived matrix. NHF- and CAF- derived-matrices were prepared as described above and stained with picrosirius red staining to visualize type I and type III collagen.

Figure 21. Visualizing type I and type III collagen in CAF-derived matrix. FBLN2 was knocked down in CAFs and CAF-derived matrices were prepared as described above and stained with picrosirius red staining to visualize type I and type III collagen.