Monoclonal Antibody Targeting of ABCB5 in Human Malignant Melanoma

From the Department of Dermatology, Venereology and Allergology at St. Josef-Hospital Bochum -University-Hospital- of Ruhr-University Bochum Director: Prof. Dr. med. E. Stockfleth

Inaugural-Dissertation for the Attainment of a Doctor’s Degree in Medicine at the high Medical Faculty of the Ruhr-University Bochum

Submitted by Ani K. Stoyanova from Sliven 2018

Dean: Prof. Dr. med. Ralf Gold

Referent: Prof. Dr. med. Eggert Stockfleth

Co-Referent: Professeur honoraire PD Dr. med. A. K. Stephan El Gammal

Date of oral exam: 04.04.2019

Abstract Stoyanova Ani Monoclonal Antibody Targeting of ABCB5 in Human Malignant Melanoma

Background: A BCB5 (ATP-binding cassette transporter, sub-family B (MDR/TAP), member 5) is a cell-surface marker for a small population of cancer stem cells in diverse human malignancies, including melanoma. ABCB5-expressing cells possess a pronounced tumorigenicity, self-renewal capacity and play a major role in the tumor-maintenance, chemoresistance and metastasizing. Therefore, in agreement with the stem cell concept in cancer, ABCB5 presents as an important target for melanoma treatment.

Methods: The ABCB5-expressing human melanoma cell lines SK-MEL-28 and A375 were treated with the anti-ABCB5 monoclonal antibodies 3C2-1D12 and 3B9 to estimate binding afﬁnity and dissociation constants, using ﬂow cytometry. Functional effects of the ABCB5-blocking, such as IL8-inhibition, were examined with qPCR and ELISA. Finally, LDH apoptosis assay was used for evaluation of direct apoptotic effects of targeting ABCB5.

Results: The flow cytometric binding affinity evaluation with the melanoma cell lines showed a preferential and stronger binding of the examined anti-ABCB5 antibodies to ABCB5 compared to isotype control. Blocking ABCB5 with the anti-ABCB5 antibodies for 48h significantly inhibited IL8 secretion. Furthermore, direct apoptotic effects of blocking ABCB5 could be observed after treatment with anti-ABCB5 antibodies in a concentration gradient.

Conclusion: The results of this study provide a basis for in vivo validation studies with the purpose of developing therapeutic monoclonal antibodies, which target ABCB5 and melanoma stem cells in combined therapies, potentially resulting in eliminating the disease.

1. Introduction………………………………………………………………………….... 7

1.1. Malignant melanoma………………………………………………………..7

1.1.1. E pidemiology……………………………………………………... 7

1.1.2. Cau ses and risk factors…………………………………………... 7

1.1.3. Molecular pathology…………………………………………….... 8

1.1.4. Diagnosis………………………………………………………….. 9

1.1.5. Subtypes………………………………………………………….. 11

1.1.6. Melanoma treatment……………………………………………. 11

1.2. Therapeutic Monoclonal Antibodies…………………………………….. 13

1.3. Melanoma stem cells…………………………………………………….... 15

1.4. ABCB5 – melanoma stem cell marker…………………………………... 17

2. Materials and methods…………………………………………………………….... 23

2.1. Materials………………………………………………………………….... 23

2.1.1. Melanoma cell lines……………………………………………... 23

2.1.2. Antibodies………………………………………………………... 23

2.1.3. Secondary antibodies………………………………………….... 23

2.1.4. Chemicals and compounds…………………………………….. 24

2.1.5. Kits………………………………………………………………... 24

2.1.6. Equipment……………………………………………………….. 25

2.1.7. Buffers and solutions………………………………………….... 27

2.1.8. Incubation of cell cultures…………………………………….... 27

2.2. Methods……………………………………………………………………. 28

2.2.1. Binding afﬁnity assay………………………………………….... 28

2.2.2. Synchronized cold-shock turbo apoptosis……………………. 28

2.2.3. Extraction and puriﬁcation of RNA and cDNA……………….. 28

1 2.2.4. RT-PCR………………………………………………………….... 30

2.2.5. Flow cytometry ………………………………………………….. 31

2.2.6. ELISA…………………………………………………………….. 31

2.2.7. LDH Cytoxicity Assay…………………………………………... 32

2.2.8. ATP-Luminescent Cell Viability Assay……………………….... 33

2.3. Statistical analyses………………………………………………………... 34

3. Results………………………………………………………………………………... 34

3.1. Characterization of the ABCB5 cell surface expression (SK-MEL-28) and binding afﬁnity of 3C2-1D12 and the human mAb 3B9……………….... 35 3.3. ABCB5 peptide competition of mAbs on SK-MEL-28 cells……………. 40

3.4. Inhibition of IL8 secretion through ABCB5 targeting………………….. 43

3.5. Induction of ABCB5 through ABCB5 blockade……………………….... 46

3.6. Monoclonal Antibody-mediated cell death (LDH release assay, ATP-cell viability assay) through reversal of ABCB5 anti-apoptotic function…….... 48

3.6.1. LDH release assay……………………………………………………….. 48

3.6.2. Luminescence cell viability assay……………………………………....54

4. Discussion………………………………………………………………………….... 57

Literature………………………………………………………………………………..65

Appendix………………………………………………………………………………...84

2 ABBREVIATIONS

ADCC Antibody-dependent cell cytotoxicity AJCC American Joint Committee of Cancer ALM Acral lentiginous melanoma ATCC American Type Culture Collection ATP Adenosine triphosphate cDNA Complementary deoxyribonucleic acid CSC Cancer stem cell DMSO Dimethyl sulfoxide DNA Deoxyribonucleic acid E. coli Escherichia coli EDTA Ethylenediaminetetraacetic acid EIA Enzyme immunoassay ELISA Enzyme-linked immunosorbent assay FACS Fluorescent-activated cell sorting FBS Fetal bovine serum FDA Food and drug administration gDNA Genomic deoxyribonucleic acid HCC Hepatocellular cancer HEPES 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid IL Interleukin LDH Lactate dehydrogenase LMM Lentigo maligna melanoma mAb Monoclonal antibody MDR Multidrug resistance ml Milliliter mM Millimol MMIC Malignant-melanoma-initiating cells NK-cells Natural killer cells nm Nanometer

3 NMM Nodular malignant melanoma PBS Phosphate buffered saline PCR Polymerase chain reaction qPCR Quantitative polymerase chain reaction RNA Ribonucleic acid RT-PCR Reverse-transcriptase polymerase chain reaction SEM Standard error of the mean SSM Superﬁcial spreading melanoma U Unit UV Ultraviolet UVA Ultraviolet A UVB Ultraviolet B UVR Ultraviolet radiation μg Microgram μl Microliter WHO World Health Organization

O2 Oxygen 5-FU 5-Fluorouracil

4 List of ﬁgures

Figure 1. Structure of a monoclonal antibody (mAb)...... 14 Figure 2. The cancer stem cell concept……………………………………………....17 Figure 3. Cell surface binding on ABCB5-positive SK-MEL-28 cells by 3C2-1D12…………………………………………………………………………….36 Figure 4. Concentration-dependent binding afﬁnity of 3C2-1D12 mAb…………....37 Figure 5. Cell surface binding on ABCB5-positive SK-MEL-28 cells by 3B9……....38 Figure 6. Concentration-dependent binding afﬁnity of 3B9 mAb…………………..39 Figure 7. Peptide competition of anti-ABCB5 mAbs………………………………...42 Figure 8. Dose-dependent inhibition of IL8 secretion through ABCB5 targeting with 3C2-1D12………………………………………………………………..44 Figure 9. Inhibition of IL8 secretion through ABCB5 targeting with 3B9 mAb…...45 Figure 10. Dose-dependent induction of ABCB5 mRNA expression through ABCB5 targeting in SK-MEL-28 melanoma cells…………………………………….46 Figure 11. Dose-dependent induction of ABCB5 mRNA expression through ABCB5 targeting in A375 melanoma cells……………………………………………47 Figure 12. Concentration-dependent direct cellular toxicity of 3C2-1D12………...50 Figure 13. Concentration-dependent direct cellular toxicity of 3B9……………….53 Figure 14. SK-MEL-28 cell viability after treatment with the anti-ABCB5 mAb 3B9………………………………………………………………………………....56

5 List of tables

Table 1: Melanoma staging and 10-year survival rate according to AJCC…………10 Table 2: List of FDA-approved drugs for melanoma treatment…………………….12 Table 3: Selected side effects of FDA-approved mAbs……………………………...63 Table A1: Concentration-dependent binding afﬁnity of 3C2-1D12 mAb raw data...84 Table A2: Concentration-dependent binding afﬁnity of 3B9 mAb raw data……….84 Table A3: Dose-dependent induction of ABCB5 mRNA expression through ABCB5 targeting in SK-MEL-28 melanoma cells raw data………………………....85 Table A4: Dose-dependent induction of ABCB5 mRNA expression through

ABCB5 targeting in A375 melanoma cells raw data………………………...... 85 Table A5: Inhibition of IL8 secretion through ABCB5 targeting with 3B9 mAb raw data………………………...... 85 Table A6: Dose-dependent inhibition of IL8 secretion through ABCB5 targeting with 3C2-1D12 raw data (qPCR)………………………...... 86 Table A7: Concentration-dependent direct cellular toxicity of 3C2-1D12 raw data (LDH assay)………………………...... 86 Table A8: Concentration-dependent direct cellular toxicity of 3B9 raw data (LDH assay) ………………………...... 87 Table A9: Luminescence cell viability assay: concentration dependent SK-MEL-28 cell viability after treatment with the anti-ABCB5 mAb 3B9 raw data………………………...... 87 Table A10. Luminescence cell viability assay: concentration dependent SK-MEL-28 cell viability after treatment with the anti-ABCB5 mAb 3B9 versus blocked 3B9 mAb raw data.………………………...... 88

6 1. Introduction

1.1. Malignant Melanoma

1.1.1. Epidemiology

Human malignant melanoma is a type of cancer originating from the melanocytes in the skin epidermis. It is one of the most aggressive human cancers with increasing incidence worldwide and highest rates in Australia and New Zealand (Jemal et al., 2004; Boniol et al., 2002). Every year more than 230,000 people are diagnosed with malignant melanoma resulting in 55,000 deaths (World Cancer Report 2014. WHO). Melanoma makes up a very small fraction of all cutaneous cancers (less than 5%), yet still accounts for 75% of the deaths related to those (American Cancer Society. Cancer Facts & Figures 2015. Atlanta: American Cancer Society 2015). Although the risk of developing melanoma increases as people age, occurrence in young patients is not uncommon. In fact, among young populations under the age of 39, melanoma is the third most common invasive malignancy (Weir et al., 2011).

1.1.2. Causes and risk factors

At an increased risk for developing melanoma are individuals with multiple naevi, history of malignant diseases in the past, cases of melanoma in the family or immunosuppression. However, melanoma is mainly caused by intermittent and excessive exposure to solar UV-radiation, especially at an early age (Green et al., 2011; Jemal et al., 2001; Whiteman et al., 2001). Particularly affected are individuals with fair skin and hair complexion (Evans et al., 1988).

7 1.1.3. Molecular pathology

Malignant melanoma is a disease with a very complex pathogenesis underlined by environmental as well as genetic factors. The human skin serves as a natural barrier against a number of external destructive agents including UV (ultraviolet) - radiation. Nevertheless, absorption of the sunlight spectrum components UVB and UVA by the pigmented melanocytes can induce DNA damage (Nishisgori, 2015). A well-studied trigger of DNA lesions is UVB that generates 6-4 photoproducts and pyrimidine dimers resulting in C-to-T transitions: a signature melanoma mutation (Pleasance et al., 2010; Jhappan et al., 2003). The deeper inﬁltrating sunlight component, UVA, can also cause DNA-damage. Oxidative stress-induction through UVA leads to G-to-T mutation and ROS-ampliﬁcation resulting in melanoma development (Kvam and Tyrell, 1999).

Although the majority of mutations causing melanoma occur sporadically, about 10% of the cases have a hereditary background (Goldstein and Tucker, 2001, Platz et al., 2000). Carriers of CDKN2A mutations have for example a 28% risk of melanoma by the age of 80 (Begg et al., 2005). CDKN2A encodes the inhibitor of two tumor supressors: the cyclin-dependent kinase 4 (INK4A) and the GTP-binding protein ARF. As a result, a mutation of CDKN2A can induce unconstrained cell cycle progression (Monzon et al., 1998; Sharpless et al., 2003). A more common mutation affects the melanocortin 1 receptor (MC1R). MC1R is a regulator of skin and hair color, and it is expressed on the melanocytes surface. Binding of the α -melanocyte stimulating hormone (α -MSH) to the MC1R induces the conversion of phaeomelanin to eumelanin. Eumelanin possesses a photoprotective effect against the UV-radiation. Thereby, genetic variations of MC1R can potentially interfere with this process, causing accumulation of phaeomelanin and deﬁciency of eumelanin, and increasing the risk of melanoma development (Palmer et al., 2000; Sturm, 2002; Rouzaud et al., 2005).

8 The most common non-hereditary alterations in melanoma occur in the RAS–RAF–MEK–ERK–MAPK signal transduction pathway whereby the oncogenes NRAS and BRAF are affected in more than 80% of all melanomas resulting in hyperactivation of the MAPK (mitogen-activated protein kinase) pathway (Davies et al., 2002).

Two mutations of BRAF are signiﬁcant for melanoma development: 1) V600E – a missense substitution of valine to glutamic acid, and 2) V600K – a missense substitution of valine to lysine (Rubinstein et al., 2010; Davies et al., 2002). Interestingly, the V600E mutation of the BRAF gene is found in more than 80% of the benign naevi, whereby additional circumstances such as UV-radiation are required for initiating tumorigenesis (Deluca et al., 2008). The second most common melanoma-linked mutation can be found in the NRAS gene. Approximately 20% of the melanoma patients carry an NRAS mutation, which leads to a hyperactivation of the NRAS gene (Milagre at al., 2010).

1.1.4. Diagnosis

Although melanoma is among the few types of cancer, for which diagnosis is possible based on their clinical and dermoscopic appearance, established set of criteria, abbreviated as “ABCDE”, can be utilized to distinguish between a benign mole and a malignant melanoma candidate (Kaufmann et al., 1995a; 1995b). The “ABCDE” set of criteria for identifying melanoma comprises the following: A=asymmetry, B=border (irregular or scalloped edges), C=color (different shades of brown or a variety of colors), D=diameter (greater than 6mm), E=elevation (enlarging or evolving over time in terms of size, color, shape, elevation). However, the pathological diagnosis of malignant melanoma is vastly complicated by its heterogeneity. In this respect, the American Joint Committee of Cancer (AJCC) provides a Melanoma Staging Database, which offers further criteria and predictions regarding diagnosis, disease progression and survival rate (Table 1).

9 The criteria consider Breslow lesion thickness, Clark level of invasion, mitotic rate, ulceration, regional lymph node micro- and macrometastasis, distant metastasis and LDH level. Further important features include cell type, growth pattern, invasion of blood vessels or nerves and inﬂammatory response (Balch et al., 2009).

Table 1. Melanoma staging and 10-year survival rate according to AJCC (*approximate percentage of 10-year survival rate).

10-year Distant Stage Thickness Regional metastasis survival metastasis rate*

In 0 NA (Lesion is limited to the epidermis) NA NA 100% situ

I IA <1,00mm, without ulceration NA NA 88%

<1,00mm with ulceration; or IB NA NA 81% 1,01-2,00mm without ulceration

1,01-2,00mm with ulceration; or II IIA NA NA 64% 2,01-4,00mm without ulceration

2,01-4,00mm with ulceration; or IIB NA NA 53% >4,00mm without ulceration

IIC >4mm with ulceration NA NA 32%

Any thickness without Micrometastasis III IIIA NA 60% ulceration 1-3 positive nodes

Any thickness without Macrometastasis IIIB NA 40% ulceration 1-3 positive nodes

Macrometastasis IIIC Any thickness with ulceration NA 20% 1-3 positive nodes

Any thickness with or without Distant IV Any nodes <15% ulceration metastasis

10 1.1.5. Subtypes

Four principal subsets of melanocytic neoplasia can be distinguished based on histologic and clinical patterns: superﬁcial spreading, nodular, lentigo maligna and acral lentiginous malignant melanoma.

The superficial spreading melanoma (SSM), which constitutes the majority of all melanomas (65%), presents as a slow-growing lesion that remains in a radial growth phase for a prolonged period of time. The second most common type, but also the most aggressive and prognostically infaust one is the nodular malignant melanoma (NMM). Due to the invasive vertical growth of the tumor and also the occurrence of amelanotic lesions, the NMM cannot be diagnosed utilizing the “ABCDE”-rule. Diagnostically beneficial in the case of NMM is the “EFG”-mnemonic: E=elevated, F=firm to touch and G=growing progressively ever more than a month. Lentigo maligna melanoma (LMM) is an atypical melanocytic hyperplasia and is considered to be a form of melanoma in situ that arises from Lentigo maligna and mostly affects chronically sun-damaged and atrophic skin. The acral lentiginous melanoma (ALM) develops on palmar, plantar and subungual regions. ALM tends to a superficial horizontal growth, however patients with this type of melanoma have a poorer prognosis, as they are often diagnosed at advanced stages (Duncan, 2009).

1.1.6. Melanoma treatment

Early-stage melanoma can be treated effectively with standard complete surgical excision. In this instance, adequate, wide surgical margins depending on the tumor thickness and follow-up patient examinations are often sufﬁcient requirements for a promising long-term prognosis. However, once the tumor has inﬁltrated the dermis and reached the blood vessels, the therapeutic conditions dramatically change and a surgical excision is no longer an ultimate solution. In

11 this regard, the course of melanoma treatment is determined by tumor thickness and ulceration, mitosis rate, lymph node inﬁltration and absence or presence of metastasis. Depending on the tumor stage, there are several different key therapy options beside surgical excision: chemo- and radiotherapy, targeting agents and immunotherapeutics (Garbe et al., 2011; Coit et al., 2016). Table 2 provides a list of the currently approved drugs for melanoma treatment by the FDA an d their basic mechanism of action.

Table 2. List of FDA-approved drugs for melanoma treatment (FDA: Hematology/Oncology (Cancer) Approvals & Safety Notiﬁcations, December 24 th 2017)

Dacarbazine An alkylating agent; adds an alkyl group to the cancer cell DNA Talimogene Oncolytic herpes virus laherparepvec High-dose Immunomodulation, antiangiogenesis interferon alfa-2b Pembrolizumab Humanized mAb, PD-1 blocker Nivolumab Humanized mAb, PD-1 blocker; also in combination with ipilimumab Trametinib Inhibitor of V600E or V600K mutated BRAF; also in combination with dabrafenib Dabrafenib MEK-pathway inhibitor; also in combination with trametinib Interleukin 2 Immunomodulation, activates T- and NK-cells Peginterferon Immunomodulation, antiangiogenesis alfa-2b

12 Ipilimumab Anti-CTLA-4 antibody, T-cell-activation and –proliferation; also in combination with nivolumab Vemurafenib Inhibitor of V600E mutated BRAF; also in combination with cobimetinib Cobimetinib MEK-inhibitor; only in combination with vemurafenib

1.2. Therapeutic Monoclonal Antibodies

Monoclonal antibodies (mAb) are large Immunoglobulin G proteins that have the ability to bind specific molecules. With the development of the hybridoma technology in 1975 a new era in tumor immunology and immunotherapy was set (Koehler and Milstein, 1975). Hybridoma allows the synthesis of mAbs by a single B-lymphocytes clone through fusion of drug-selected myeloma cells with murine spleen cells immunized with a specific antigen. As a result, the myeloma cells lose the ability to produce nucleic acids and their own immunoglobulines. However, within the hybridoma the B-lymphocytes are immortalized and the hybridomas can be cloned indefinitely, producing theoretically unlimited quantities of homogenous mAb populations (Levy et al., 1979; Milstein, 1980).

Each mAb consist of two light and two heavy chains, connected by disulﬁde bonds and building together an Y-shaped structure with two identical sites called antigen-binding fragments (Fab) (Fig. 1). The other end of the Y-molecule is called Fc-fragment (fragment crystallizable or constant region) and performs as a mediator of most biological functions of the antibody such as cell lysis, degranulation or opsonization (Davies and Metzger, 1983; Forthal, 2014).

Figure 1. Structure of a monoclonal antibody.

MAbs can achieve their efﬁcacy through several different mechanisms. These include immune-mediated tumor cell killing for example through effector cell induction or T-lymphocytes modulation such as phagocytosis, antibody-dependent cell mediated cytotoxicity (ADCC) or complement-dependent cellular cytotoxicity (CDC) (Campoli et al., 2010; Tai and Anderson, 2011; Chavez-Galan et al., 2009). MAbs can also exercise direct effects through antigen crosslinking on tumor cell surfaces leading to apoptosis, antagonist receptor binding, mediating kinase activation and downstream signaling, or through transducing pro-apoptotic signaling in the tumor cells (Chiu et al., 2007). Another form of direct apoptotic signaling is represented by immunoconjugates where mAbs deliver active toxic compounds such as radionuclides, bacterial toxins, enzymes, pro-drugs, toxic

14 chemicals or cytokines in order to induce a localized tumor cell cytotoxic effect. MAb-conjugates can also induce vascular and stromal cell damage through receptor antagonism or ligand trapping (Campoli et al., 2010; Scott et al., 2012).

MAbs have become the focal point of cancer research because of their exquisite monovalent binding afﬁnity and basically unrestrained cloning potential. Currently, mAbs are the fastest growing class of therapeutic molecules. Roughly 50 different mAbs have already been approved for patient treatment and diagnosis of a variety of diseases (Kelley, 2009; Ecker et al., 2015). The diverse therapeutic effects of mAbs are above all used for the treatment of malignancies, chronically inﬂammatory, infectious and autoimmune diseases (Weiner et. al., 2012; reviewed in Nelson, 2010). Of a special interest is the targeting of cancer stem cells with mAbs, for example as a combined therapy, with the purpose of overcoming tumor intrinsic mechanisms, leading to drug resistance and tumor reoccurrence (Naujokat, 2014).

1.3. Melanoma stem cells

Somatic stem cells give rise to every organ in the human body during development. Each stem cell is deﬁned by a self-renewal potential through asymmetric division (Yamashita et al., 2010). The yet unclear mechanism of the asymmetric division enables the capacity of giving rise to differentiated cells and further generations of stem cells at the same time (Morrison and Kimble, 2006). Based on the stem cell concept, there is increasing evidence that cancer stem cells regulate tumor formation, maintenance and therapeutic resistance (Clark et al., 2006; Clevers, 2011). The cancer stem cell does not necessarily need to originate from the somatic stem cell, just shares its property (Visvader, 2011). On the other hand, cancer stem cells have a tumorigenic potential, i.e., the potential to generate cancer cells. There is also evidence that fully differentiated somatic stem cell can give rise to a cancer stem cell (Martínez-Climent et al., 2006).

The therapeutic promise of the cancer stem cell concept is a consideration, that conventional therapies may kill most of the bulk cells within the tumor but that cancer stem cells are less susceptible to apoptosis, immune rejection, hypoxia, chemotherapy and radiation (Fig. 2) (Frank et al., 2010; Dick, 2008; Reya et al., 2001, Clarke et al., 2006). Subsequently, this small population of cancer stem cells often remains unharmed and the tumor may relapse (Scatena et al., 2012; Khan et al., 2014). According to a major theory in current cancer research, stem cell targeted therapies would speciﬁcally address the subpopulation of cells within the malignancy, thereby depriving the cancer by its driving force leaving more differentiated progenitor cells behind with a more limited life span. Mounting evidence suggests that combined therapies that target the bulk cells within the tumor as well as cancer stem cells facilitate potential tumor eradication.

Figure 2. The cancer stem cell concept. According to the cancer stem cell concept, each tumor contains tumor bulk cells and a small population of cancer stem cells that possess tumorigenic abilities.

These considerations highlight the need for identifying speciﬁc molecular markers that hallmark cancer stem cells and establishing molecules that target precisely these markers, ultimately resolving in elimination of the tumor.

1.4. ABCB5 – melanoma stem cell marker

Members of the ATP-binding cassette (ABC) transporter superfamily are of great interest in cancer stem cell research due to their potential as cancer stem cell markers. The ABC transporters are the largest family of transmembrane protein

17 and comprise 49 members in humans (Vasiliou et al., 2009). They are responsible for ATP-dependent movement of a wide variety of xenobiotics including drugs, lipids and metabolic products across the plasma and intracellular membrane. Therefore, elevated expression of ABC transporters, especially members of the subfamily B, has been linked to increased occurrence of multidrug resistance (MDR) due to an increased efﬂux of chemotherapeutics and reduction of their intracellular levels (Dean and Allikments, 2001; Haimeur et al., 2004; Chen et al., 2005; Lee et al., 2012).

Dr. Frank’s laboratory has identified a novel member of the ATP-binding-cassette transporter family. ABCB5 [subfamily B (MDR/TAP), member 5] is a multiple plasma membrane-spanning transport P-glycoprotein and a drug-efflux transporter, consisting of five transmembrane helices and three extracellular loops. ABCB5 was at first found in the physiological human skin and reported to mediate the fusion of progenitor cells in the epidermis (Frank et al., 2003; 2005). Overexpression of ABCB5 can be found in stem cell niches such as the human placenta and the limbal stem cells of the cornea (Volpicelli et al., 2014; Ksander et al., 2014). Tissue microarray assays also show that ABCB5 is expressed up to a substantially higher level in various human malignancies. In colorectal cancer, ABCB5-expressing tumor cells have been reported to induce 5-FU-chemoresistance, which can be partially reversed through shRNA-knockdown of ABCB5 (Wilson et al., 2011). Another example is the hepatocellular cancer (HCC), where ABCB5 can also induce chemoresistance, and targeting ABCB5 could sensitize the tumor cells for the treatment with doxorubicin. Furthermore, ABCB5 plays a major role in the recurrence of HCC after liver resection in liver cancer patients (Cheung et al., 2011a; Cheung et al., 2011b; Wong et al., 2014).

In the past few years, ABCB5 has been established as a functional cell-surface marker also for melanoma stem cells. Based on preclinical therapeutic targeting

18 studies, elevated expression of ABCB5 associates with tumorigenicity capabilities, rapid disease progression, tumor recurrence, and multidrug resistance (Wilson et al., 2011).

Studies show that treatment with reference chemotherapeutics participates to the chemoresistant phenotype of melanoma and tumor recurrence by selecting tumor cell populations such as ABCB5-expressing cells. As a member of the ABC transporter family, ABCB5 is thought to play a major role in drug efﬂux. This was supported by experiments measuring the intracellular accumulation of Rhodamine 123 or doxorubicin in melanoma (Frank et al., 2005). Furthermore, certain melanoma chemotherapeutics can potentially enhance the ABCB5 expression. Treatment with dacarbazine and doxorubicin for example can lead to an enhancement of the expression of ABCB5 at the cell surface (Chartrain et al., 2012).

Based on their stem-cell-like features, ABCB5-positive melanoma cells are also known as malignant-melanoma-initiating cells (MMIC). MMIC possess higher tumorigenic capacity and display survival advantage over ABCB5-negative bulk tumor cells. Additionally, ABCB5-positive can give rise to ABCB5-positive and –negative cells, as opposed to ABCB5-negative cells, which are only able to generate the better differentiated ABCB5-negative cells (Schatton et al., 2008). Investigating the functional role of ABCB5 in maintaining the MMIC, Wilson et al. showed, that ABCB5 can control the IL-1β secretion and thereby regulate IL8/CXCR1 signaling in MMIC (Wilson et al., 2014). IL8/CXCR1 is known to associate with cancer progression and cancer-stem-cell properties in diverse human malignancies (Singh et al., 2013; Chen et al., 2014).

Gene expression analysis show that ABCB5 is found to be co-expressed with the vascular growth factor receptor VEGFR-1 on melanoma initiating tumor cells and contributes to vascular mimicry in melanoma, a phenomenon, characteristic for

19 particularly aggressive melanoma tumor cells with embryonic-like features (Frank et al. 2011; Larson et al., 2014). Moreover, shRNA knockdown of VEGFR-1 in xenograft models inhibited the tumor growth and production of laminin, which is a driver of angiogenesis and tumor growth in melanoma (Akalu et al., 2007).

Further evidence, which supports the notion of ABCB5 as a stem cell marker in melanoma, is the co-expression of ABCB5 with the nerve growth factor receptor CD271 (Murphy et al., 2014). The cell surface marker CD271 identifies a subpopulation of melanoma-initiating cells and has been linked to an increased tumorigenicity and stem-cell-like properties in melanoma (Boiko et al., 2010; Redmer et al., 2014). ABCB5 is also shown to be co-expressed with the receptor activator of NF-κB RANK. RANK-expressing cells are reported to be more common in lymph node metastasis compared to the primary tumors and also increased levels of RANK were found in the peripheral blood from patients with metastatic melanoma (Kupas et al., 2011). A recent study showed, that the combined administration of cyclophosphamide and the genetically modified stable Salmonella strain VNP20009, carrying an ABCB5 silencing element, resulted in suppressed melanoma tumor growth in mice (Zhang et al., 2016; Low et al., 2007). This finding further supports the concept, that targeting ABCB5 could sensitize tumor cells towards reference chemotherapeutics. Furthermore, it was shown that ABCB5 could modulate melanoma tumor growth due to its close co-regulation with the melanoma tumor antigen p97 (melanotransferrin) (Suryo Rahmanto et al., 2007). An important interplay has been observed between ABCB5 and the transcription factor Oct4 in melanoma. Oct4 is found in undifferentiated embryonic stem cells and plays a crucial role during the embryo development by maintaining the self-renewal capacity and pluripotency of the inner cell mass (Nichols et al., 1998). Changes in the expression of Oct4 can easily lead to a differentiation of those cells (Niwa et al., 2000). In this regard, induction of Oct4 results in melanoma cell dedifferentiation and causes enhancement of ABCB5 expression in melanoma cell lines and xenografts, creating more aggressive

20 tumors with increased metastatic potential (Kumar et al., 2012). Another recent study shows that ABCB5 is also strongly expressed in advanced melanoma and metastatic lesions compared to melanocytic naevi (Gamblicher et al., 2016).

A translational function of ABCB5 has recently been identified in the corneal tissue, where ABCB5 is responsible for the maintenance and regeneration of limbal stem cells, protecting them from apoptosis. In this study, ABCB5-positive cells, expressed on the surface of limbal stem cells, showed the ability to regrow human corneas on mice with limbal stem cell deficiency. These findings provide the basis of selecting cells for corneal regeneration und more successful corneal transplants (Ksander et al., 2014).

All of the above-mentioned considerations underline the importance of ABCB5 as a stem-cell marker and the urge to study the possibilities of targeting ABCB5 in human malignant melanoma, in order to conquer the currently invincible cell subset that maintains one of the most aggressive and deadliest types of cancer nowadays.

21 Aims and organization of the thesis

The goal of this study was to evaluate the potency of anti-ABCB5 IgG1 mAbs to target melanoma cancer stem cells.

1. First, mAbs speciﬁcities and dissociation constants for binding to the native human ABCB5 protein were estimated using ﬂow cytometric evaluation of ABCB5 expressing human melanoma cell lines.

2. The functional effects of ABCB5-targeting with mAbs, such as changes in IL8- and ABCB5-production were studied using qPCR and ELISA.

3. Finally, direct apoptotic effects through ABCB5-blockade were examined, using the LDH apoptosis assay and the luminescent cell viability assay.

22 2. Materials and methods

2.1. Materials

2.1.1. Melanoma cell lines

SK-MEL-28 ATCC, Catalog Nr. HTB-72, Manassas, VA, USA A375 ATCC, Catalog Nr. CRL-1619, Manassas, VA, USA

2.1.2. Antibodies

3C2-1D12 IgG1κ anti-ABCB5 monoclonal antibody, Maine Biotechnology Services, Inc., Portland, ME, USA MOPC 31C Monoclonal MOPC31C, IgG1, Kappa murine myeloma, Sigma, St. Louis, MO, USA 3B9 Human anti-ABCB5 extracellular loop-associated peptide mAb, Pﬁzer Centers for Therapeutic Innovation and Boston Children’s Hospital human IgG1 Recombinant human IgG1 Kappa antibody, Clone: AbD18705_hIgG1, AbD Serotec, Bio-Rad, Hercules, CA, USA mouse Isotype mouse IgG1, kappa monoclonal [MG1-45], Abcam, Cambridge, MA, USA

2.1.3. Secondary antibodies

PE Goat Anti-Mouse Ig (Multiple Adsorption), Cat. Nr. 550589, BD Pharmingen, San Jose, CA, USA Gt F(ab’)2 Anti-Human IgG (Υ) R-PE Conjugate Cat. Nr. H10104, Invitrogen, Carlsbad, CA, USA

23 2.1.4. Chemicals and compounds

Ethanol Sigma, St. Louis, MO, USA FBS Gibco, Life Technologies, Carlsbad, CA, USA HEPES HyClone, South Logan, UT, USA Interleukin-2 Gibco, Life Technologies, Carlsbad, CA, USA L-Glutamin Lonza, Walkersville, MD, USA MycoZap Plus-CL Lonza , Hopkinton, MA, USA PBS HyClone, South Logan, UT, USA Penicillin/Streptomycin Gibco, Life Technologies, Carlsbad, CA, USA Peptide, blocking New England Peptide Inc., Gardner, MA, USA Propidium Iodide (PI) BD Pharmingen, San Jose, CA, USA RNase-free water Sigma, St. Louis, MO, USA RPMI 1640 HyClone, South Logan, UT, USA Triton X-100 Sigma, St. Louis, MO, USA Versene (EDTA-4Na) Gibco Life technologies, Carlsbad, CA, USA

2.1.5. Kits

Advantage RT-for-PCR Kit Clontech Laboratories, Inc., Mountain View, CA, USA LDH Cytotoxicity Detection Kit Clontech Laboratories, Inc., Mountain View, CA, USA RNeasy Plus Mini Kit Qiagen, Valencia, CA, USA

24 Human CXCL8/IL-8 ELISA Kit Quantikine ELISA Kit, R&D Systems, Minneapolis, MN, USA Cell Viability Assay CellTiter-Glo Luminiscent Cell Viability Assay, Promega, Madison, WI, USA

2.1.6. Equipment

Cell culture plates, Flat Bottom Corning Costar, Corning, NY, USA (6, 12, 24, 96 wells) Cell culture plates, V Bottom Corning Costar, Corning, NY, USA (96 wells) Cell culture flasks (75 cm2 ) Corning, Sigma-Aldrich, St. Louis, MO, USA Cell scrapers Corning Costar, Cambridge, MA, USA Centrifuges Eppendorf Centrifuge 5415 R Centrifuge tubes (15 ml, 50 ml) Corning CentriStar, Corning, NY, USA Filter pipet tips (200 μl) VWR, Radnor, PA, USA Flow cytometer FACSCalibur, Becton Dickinson, San Jose, CA, USA Freezers Thermo Scientific Revco UxF - 86°C, Waltham, MA, USA Hemocytometer Fisher Scientific, Pittsburgh, PA, USA Incubator HERAcell 150, Heraeus Laminar flow cabinet SterilGARD Hood Class II Type A/B3, The Baker Company, Inc. Sanford, ME, USA Luminometer GloMax, Madison, WI, USA Microfuge tubes (1,5 ml) Ambion, Invitrogen, Carlsbad, CA, USA Microscope Nikon Eklipse TS100, Hanson, MA, USA Multichannel pipettor Denville Scientific, Holliston, MA, USA

25 Pipet filler Thermo Scientific, Waltham, MA, USA Pipettors Denville Scientific, Holliston, MA, USA Pipet tips (10 μl) Denville Scientific, Holliston, MA, USA Pipet tips (200 μl) Denville Scientific, Holliston, MA, USA Pipet tips (1250 μl) MedSupply Partners, Atlanta, GA, USA Real Time – PCR Machine Applied Biosystems, Step One Plus, Foster City, CA, USA Round-Bottom Polystyrene Tubes BD Falcon, Bedford, MA, USA Falcon Corning, Corning, NY, USA Serological pipettes Corning Costar Stripette, Sigma-Aldrich, Corning, NY, USA Spectrophotometer NanoVue Plus, GE Healthcare Life Sciences, Pittsburgh, PA, USA Sterile Hood SterilGARD® Hood Class II Type A/B3, The Baker Company, Inc., Sanford, ME, USA Thermal cycler Eppendorf Mastercycler Pro vapo.protect, Hauppage, NY, USA Tissue culture dishes (15 cm2 ) Falcon Corning, Corning, NY, USA Vortex Scientific Industries Inc., NY, USA Water bath Precision™Microprocessor Controlled 280 Series Water Bath, Marietta, OH, USA

26 2.1.7. Buffers and solutions

PBS: NaCl 137 mM KCl 27 mM

Na2 H PO4 100 mM

KH2 P O4 18 mM

CaCl2 10 mM

MgCl2 5 mM pH 7,4

Complete RPMI-1640: 10% FBS Glutamine 1 mM HEPES 25mM Penicillin 100 U/ml Streptomycin 100 μg/ml pH 7,5

2.1.8. Incubation of cell cultures

Cell cultures were incubated in a conventional environment at 37 °C, 5% CO2 and 100% humid atmosphere. SK-MEL-28 and A375 melanoma cell lines were obtained from the American Type Culture Collection. All cell lines were grown in culture flasks (75 cm2 ) in RPMI 1640 media, supplemented with 10% fetal bovine serum (FBS), 1% Penicillin/Streptomycin and MycoZap in 75 cm2 plastic cell culture flasks. The cells were subcultured every two or three days using phosphate buffered saline (PBS) and incubated with 0,2 g/l EDTA-4Na (Versene 1:5000) for 5 min before splitting into new flasks.

27 2.2. Methods

2.2.1. Binding afﬁnity assay

For the flow cytometry analysis, SK-MEL-28 cell populations were suspended at a concentration of 1 x 10 7/ ml in a 10% RPMI-1640 medium and seeded in a 96-well V-bottom plate. Each well contained 200 μl of the cell suspension (resp. 200 000 cells per sample). Human and mouse monoclonal antibodies were titrated to different concentrations using PBS and added to the corresponding wells of the 96-well plate and the samples were incubated for 30 min on ice. After that, the samples were washed three times by spinning the plate for 5 min at 2000 rpm and resuspending the cell palettes with 2% FACS buffer. For the final staining, a secondary PE/FL2 antibody was added to each sample followed by a light-protected incubation on ice for 30 min. The washing procedure was repeated two times and the samples were resuspended in 400 μl FACS buffer in round-bottom tubes for the flow cytometry analysis.

2.2.2. Synchronized cold-shock turbo apoptosis

The cold-shock turbo apoptosis is a method for inducing synchronized cell killing without using toxic compounds or antibodies. The cell lines were cultured in RPMI-1640 with 10% FBS (fetal calf serum) and 1% penicillin/streptomycin. The suspended cell lines were diluted with media to a concentration of 1 x 10 6 cells/ml and placed in FACS tubes. For the cold-shock the tubes were stored on ice for 2 h and subsequently rewarmed at 37o C in the incubator for 24 h.

2.2.3. Extraction and puriﬁcation of RNA and cDNA

Total RNA was extracted and puriﬁed from cell lines using the RNeasy Plus Mini Kit from Qiagen. The cell suspensions, homogenized with 350 μl of RLT Plus

28 Buffer, were placed in QIAshredder tubes and spun for 2 min at maximum speed. The supernatants were transferred to gDNA Eliminator columns and centrifuged for 30 s at 10 000 rpm to avoid genomic DNA contamination. 350 μl of 70% Ethanol were added to the ﬂow-through and a total volume of 700 μl of the mixture was placed in a RNeasy Mini spin column, which was then spun for 17 s at 10 000 rpm. The ﬂow-through was discarded and 700 μl RW1 Buffer were added to the RNeasy Mini spin column. Two washing procedures were performed, using RPE buffer. Afterwards, the columns were placed in new collection tubes and 50 μl of RNase free water was added to the membrane of the columns to elute the RNA.

CDNA was collected using Advantage® RT-for-PCR Kit from Clontech and Eppendorf Mastercycler Pro vapo.protect™. The appropriate amount of RNA (0,5-1,0 μl) of each sample was placed in a 0,5 ml microcentrifuge tube and diluted in DEPC-treated H2 0 up to a total volume of 12,5 μl. After 1,0 μl of a random hexamer primer was added to the samples, the mixture was heated at 72°C for 2 min for denaturation of the RNA secondary structure and then rapidly cooled on ice, in order that the primer anneals to the RNA. A master reagent mix was prepared using the following components:

5x reaction buffer: 4 μl 250 mM Tris-HCl, pH 8.3 375 mM KCl 15 mM MgCl2 dNTP primer mix (10mM) 1,0 μl (10 mM) Recombinant RNase inhibitor 0,5 μl (40 units/μl) MMLV reverse transcriptase _ 1,0 μl (200 units/μl) Total volume per sample 6,5 μl

29 A total volume 6,5 μl from the Reaction mixture was added to the PCR strip tubes and the samples were incubated in the thermal cycler at 42°C for 60 min and then heated for 5 min at 94°C to stop the cDNA synthesis. After diluting each sample up to a total volume 100 μl with DEPC-treated H2 O , the cDNA product was used directly or stored at -20°C.

2.2.4. RT-PCR

The real-time quantitative polymerase chain reaction is an established quantiﬁcation technique, which allows the simultaneous ampliﬁcation and detection of nucleic acids. QPCR (SYBR Green I dye) used 18s as a normalizing control. IL8 primers were from Origene. The primers for ABCB5 (Homo sapiens ATP-binding cassette, sub-family B (MDR/TAP), member 5 (ABCB5), transcript variant 2, mRNA NCBI Reference Sequence: N M_178559.5) detection were: 1) 5’-CACAAAAGGCCATTCAGGCT-3’ (forward) and 2) 5’-GCTGAGGAATCCACCCAATCT-3’ (reverse).

PCR reaction mixture: SYBR Master Mix 6,25 μl Primer 1,0 μl

RNase-free H2 O 3,25 μl cDNA 2,0 μl Total volume 12,5 μl

Reaction conditions: Step 1 50°C 2 min 1 cycle Step 2 95°C 10 min 1 cycle Step 3 95 °C 15 sec 40 cycles Step 4 60 °C 1 min 40 cycles

30 2.2.5. Flow cytometry

Flow cytometry is a quantitative and qualitative technique for cell counting, cell sorting and analyzing physical characteristics of individual particles, e.g. internal complexity, granularity, or cell number. For the binding affinity analysis, SK-MEL-28 cell populations were suspended at a concentration of 1 x 10 7/ ml in a 10% RPMI-1640 medium and seeded in a 96-well V-bottom plate. Each well contained 200 μl of the cell suspension (resp. 200 000 cells per sample). Human and mouse monoclonal antibodies were titrated to different concentrations using PBS and added to the corresponding wells of the 96-well plate and the samples were incubated for 30 min on ice. After that, the samples were washed three times by spinning the plate for 5 min at 2000 rpm and resuspending the cell palettes with 2% FACS blocking buffer. For the final staining, a secondary PE/FL2 antibody was added to each sample followed by a light-protected incubation on ice for 30 min. The washing procedure was repeated two times and the samples were resuspended in 400 μl FACS buffer in round-bottom tubes for the flow cytometry analysis.

2.2.6. ELISA

The enzyme-linked immunosorbent assay (ELISA), also known as an enzyme immunoassay (EIA), is a quantitative laboratory method, used to determine the concentration of a particular protein in solutions such as cell culture supernatants or blood products (serum, plasma). The analyte in the sample is immobilized on the bottom of a polystyrene 96-well plate, which was previously coated with the capture antibody against the target antigen. After washing the microplate to remove any unbound agents, an enzyme-linked secondary antibody that conjugates speciﬁcally to the antibody’s Fc-region is applied to the surface of the wells. A color developing substrate is now added and the quantiﬁed signal produced through the color change is proportional to the concentration of the

31 target antigen in the sample. The cell lines were pre-treated with anti-ABCB5 monoclonal antibodies for the ELISA-analysis for 48 h. These experiments were performed using Human CXCL8/IL-8 Quantikine ELISA Kits from R&D Systems (Minneapolis, USA). 100 μl of the Assay Diluent RD1-85 were added to each of the 96 wells, followed by 50 μl of IL-8 Standard and samples to the corresponding wells. The plate was then sealed and incubated at room temperature for 2 h. Subsequently the wells were washed four times, using 400 μl of diluted Wash Buffer (20 ml Wash buffer in 480 ml distilled water) and ﬁlled with 100 μl of the IL-8 Conjugate prior a 1-hour-incubation at room temperature. The washing procedure was repeated one more time and 200 μl of the Substrate Solution were added to each well. Afterwards the plate was incubated for 30 min at room temperature, protected from light and then loaded with 50 μl of a Stop solution for discontinuing the reaction process. The optical density of the samples was immediately measured at 450 nm in a microplate reader.

2.2.7. LDH Cytoxicity Assay

Lactate Acid Dehydrogenase (LDH) is an enzyme, which catalyzes the conversion of lactate to pyruvate. Testing LDH levels is an established non-speciﬁc clinical method for detecting tissue-damaging processes in the human body. The LDH Cytotoxicity assay is a colorimetric assay for quantifying cellular cytotoxicity, based on the increased release of LDH after rupturing or damaging plasma membranes. The LDH cytoxicity assay was performed using LDH Cytotoxicity Detection Kit (Clontech Laboratories, Inc., A Takara Bio Company).

Reaction Mixture: 250 µl C atalyst (diluted in 1 ml distilled water) 11,25 ml Dye Solution

32 SK-MEL-28 cells were suspended to a cell concentration of 100 000 cells per ml and incubated in a 96-well plate over 48 h (100 µl cell suspension per well). Human monoclonal antibodies were titrated to different concentrations using PBS and added to the cell suspensions immediately after seeding the cells and a second time after 24 h. Supernatants were harvested twice every 24 h. The samples were centrifuged at 2000 rpm for 10 min and 50 µl of the supernatants were transferred to a homologous 96-well plate, followed by equal volume of the assay reaction mixture, prepared immediately before use. After a light-protected incubation for 30 min at room temperature, the absorbance of the samples was measured at 490 nm using a multiwell plate reader.

2.2.8. ATP-Luminescent Cell Viability Assay

In order to determine the effect of ABCB5-monoclonal antibodies on target cell death, we used an ATP-Luminescent Cell Viability Assay (CellTiter-Glo, Promega) - a method based on quantiﬁcation of ATP-levels. Intracellular ATP is an universal energy source for the cellular metabolism. In this assay a stable form of luciferase puriﬁed from Photuris pennsylvanica (LucPpe2) catalyzes the mono-oxygenation of luciferin in the presence of ATP while emitting a bioluminescent signal. This signal correlates directly with the number of viable cells in the culture.

2+ Luciferin + ATP + O2 + Mg Oxyluciferin + AMP + PPi + CO2 + hv

This assay was performed according to the manufacturer’s instructions. In order to avoid any temperature gradients affecting the enzyme reaction, all of the participating components including plates and cell suspensions were equilibrated to room temperature for at least 30 min. 100 000 cells per ml (10 000 cells per well) were seeded into 96-well plates and treated with anti-ABCB5 antibodies as described above. 50 μl of CellTiter-Glo Reagent were added to 100 μl of medium containing cells in each well. Cell lysis was induced by shaking on an orbital

33 shaker for 2 min, after which the plate was incubated at room temperature for 10 min. 100 μl from each well were transferred to an opaque-walled plate and the luminescence was measured using a GloMax Microplate Luminometer with an integration time of 0,5 second per well. All treatments were performed in triplicates or quadriplicates in several independent experiments. The background control was represented by RPMI 1640 Media and it was subtracted from the luminescence of the antibody treated samples.

2.3. Statistical analyses

Data reported are expressed as means ± SEM of at least three replicates. Statistical significance was determined using the one-way analysis of variance and the Dunnett post-test or two-way analysis of variance and Bonferroni correction with significance level Alpha 0,05 (95% confidence intervals) from Prism 5 software, where p<0,05 was considered to be statistically significant (marked with *) and p<0,01 and p<0,001 were considered highly statistically significant (marked respectively with ** and ***).

34 3. Results

3.1. Characterization of the ABCB5 cell surface expression (SK-MEL-28) and binding afﬁnity of 3C2-1D12 and the human mAb 3B9

The binding of mAbs to their native target antigen is an absolute requirement for their therapeutic efficacy. In order to examine the ABCB5 cell surface expression and determine the mAbs specifities and estimate dissociation constants for binding to the native ABCB5 protein, the well-studied SK-MEL-28 cell line (also expressing the mutant B-Raf (V600E) and wild type N-Ras) was immunostained with the commercially available extracellular loop-specific antibody clone 3C2-1D12 and the human mAb 3B9. Using flow cytometric evaluation, we showed that the mAbs recognized and bound to a substantially higher number of ABCB5-positive cells compared to Isotype control.

The following figures display a multicolor flow cytometry analysis of human SK-MEL-28 cells incubated with the mouse (Fig. 3) or human (Fig. 5) isotype control (first column) and the mAbs 3C2-1D12 (Fig. 3) and 3B9 (Fig. 5) (second column). For the secondary staining all samples have been incubated with the FL-2-positive PE Goat anti-mouse antibody for 3C2-1D12 and anti-human IgG (Υ) R-PE conjugate for 3B9. The analysis show a concentration-dependent binding of the mouse antibody 3C2-1D12 and the human mAb 3B9 to the cell-surface of the ABCB5-positive SK-MEL-28 cells. Figures 4 and 6 show the equilibrium one-site specific binding of the 3C2-1D12 and 3B9 mAbs as a nonlinear regression curve fit with a logarithmic X-axis. Results are expressed as the mean of FL-2 fluorescence determined by flow cytometry and corrected for background, non-specific fluorescent intensity by subtraction of sample values corresponding to isotype matched controls.

36 Figure 3. Cell surface binding on ABCB5-positive SK-MEL-28 cells by 3C2-1D12. Mouse isotype control (ﬁrst column); mAb 3C2-1D12 (second column). Third column: Grey contour = mouse isotype control; red contour=3C2-1D12.

Figure 4. Concentration-dependent binding afﬁnity of 3C2-1D12 mAb. Presented is an estimated value of the equilibrium dissociation constant (Kd ) , determined from the FL-2 mean ﬂuorescence and corrected for background.

38 Figure 5. Cell surface binding on ABCB5-positive SK-MEL-28 cells by 3B9. Human isotype control (ﬁrst column); mAb 3B9 (second column). Third column: Grey contour = human isotype control; red contour=3B9.

Figure 6. Concentration-dependent binding afﬁnity of 3B9. Presented is an estimated value of the equilibrium dissociation constant (Kd ) , determined from the FL-2 mean ﬂuorescence and corrected for background.

39 3.3. ABCB5 peptide competition of mAbs on SK-MEL-28 cells

To determine the speciﬁcity of the anti-ABCB5 antibodies, immunizing peptide-blocking experiments were performed. The antibodies were neutralized through incubation with an excess of peptide that corresponds to the epitope recognized by the antibody. The antibody that was successfully bound to the blocking peptide was no longer available to bind to the epitope present in the protein in the cells. SK-MEL-28 cells were incubated with 0,39 μ g/ml of the MOPC31C mouse isotype (Figure 7, A), 0,39 μ g/ml of 3C2-647 mAb, co-incubated with a control peptide (Fig. 7, B), 0,39 μ g/ml of MOPC31C mouse isotype, co-incubated with an anti-ABCB5 peptide (Fig. 7, C) and 0,39 μ g/ml of 3C2-647 mAb, blocked by an anti-ABCB5 peptide (Fig. 7, D). As shown in Figure 7, the mAb 3C2-647 bound notably high number of ABCB5-positive SK-MEL-28 cells compared to the 3C2-647 mAb, incubated and blocked by the B5-peptide. These experiments represent the basis for the following cytotoxicity assays.

Figure 7. Peptide competition of anti-ABCB5 mAbs. A. MOPC31C mouse isotype control. B. 3C2-647 with control peptide. C. MOPC31C with B5-peptide. D. 3C2-647 with B5-peptide. E. Percentages of bound SK-MEL-28 cells.

42 3.4. Inhibition of IL8 secretion through ABCB5 targeting

To further study the functional effects of ABCB5 blockade in melanoma, SK-MEL-28 cells were treated with different doses of the anti-ABCB5 monoclonal antibody 3C2-1D12.

IL8 protein secretion was measured using ELISA, after treatment of SK-MEL-28 cells with the ABCB5 targeting mAb 3C2-1D12 over 48h (Figure 8). Data were obtained in triplicates, error bars represent SEM. All data were corrected for background. Statistical significance was determined using the one-way analysis of variance and the Dunnett post-test for comparison between to MOPC31C mouse isotype control and the 3C2-1D12-treated samples. The significance level Alpha is 0,05 (95% confidence intervals), where p<0,05 is considered to be statistically significant (marked with *) and p<0,01 and p<0,001 is considered highly statistically significant (marked respectively with ** and ***). A dose-dependent inhibition of IL8 protein levels was observed over the course of a 48-h-treatment with 3C2-1D12 compared to isotype control antibody.

Figure 8. Dose-dependent inhibition of IL8 secretion through ABCB5 targeting with 3C2-1D12. Error bars represent SEM, ns=not signiﬁcant, * p<0,05, ** p<0,01, *** p<0,001.

Using ELISA, the IL8 secretion was also measured for the human mAb 3B9. Accordingly, SK-MEL-28 cells were treated with the ABCB5 targeting mAb 3B9 over 48h. Data were obtained in triplicates, error bars represent SEM. All data were corrected for background. Statistical significance was determined using the one-way analysis of variance and the Dunnett post-test for comparison between to IgG1 human isotype control and the 3B9-treated sample. The significance level Alpha is 0,05 (95% confidence intervals), where p<0,001 is considered highly statistically significant (marked with ***).

Figure 9. Inhibition of IL8 secretion through ABCB5 targeting with 3B9. Error bars represent SEM, ns = not signiﬁcant, *** p < 0,001.

45 3.5. Induction of ABCB5 through ABCB5 blockade.

The ABCB5 mRNA expression was evaluated using qPCR. For this experiment two different melanoma cell lines, SK-MEL-28 (Figure 10) and A375 (Figure 11) were incubated with different doses of the ABCB5-mAb 3C2-1D12 over 48 h. Data were obtained in triplicates and normalized against 18s control. All data were analyzed, using two-way analysis of variance and the Bonferroni correction. Although not statistically signiﬁcant, there was a trend towards elevation of the mRNA level after a 48-h-treatment of SK-MEL-28 cell line with 3C2-1D12 mAb. MRNA expression was signiﬁcantly elevated after a 48-h-treatment of A375 cell line with 50 µg/ml of the 3C2-1D12 mAb.

Figure 10. Dose-dependent induction of ABCB5 mRNA expression through ABCB5 targeting in SK-MEL-28 melanoma cells. Error bars represent SEM, ns = not signiﬁcant.

Figure 11. Dose-dependent induction of ABCB5 mRNA expression through ABCB5 targeting in A375 melanoma cells. Error bars represent SEM, ns = not signiﬁcant, * p < 0,05.

47 3.6. Monoclonal Antibody-mediated cell death (LDH release assay, ATP-cell viability assay) through reversal of ABCB5 anti-apoptotic function

3.6.1. LDH release assay

In order to demonstrate a regulating role of ABCB5 in anti-apoptotic signaling pathways and mAb-mediated melanoma cell death through reversal of that anti-apoptotic function, SK-MEL-28 cells were incubated with different concentrations of ABCB5 mAbs over 48h. Targeting of ABCB5 led to decreased viability of SK-MEL-28 melanoma cells, in contrast to treatment with isotype control. Furthermore, the mAbs were blocked by an ABCB5-blocking peptide to minimize any potential background non-specific cytotoxic effects of the mAbs. The effect of the ABCB5 peptide was initially verified by a flow cytometry evaluation, attesting blockade of the mAbs by the ABCB5 peptide in contrast to the preserved binding affinity of mAbs treated with a control peptide. Treatment with mAbs, pre-incubated with an ABCB5 peptide maintained the viability of SK-MEL-28 cells, in contrast to treatment with mAbs alone or mAbs pre-incubated with a control peptide (Figure 12). Target cell death was measured by LDH release into supernatant media after 48h treatment. Figure 12A represents cytotoxicity comparison between the treatment of SK-MEL-28 cells with 3C2-1D12 mAb alone, 3C2-1D12 and control peptide, and 3C2-1D12 and B5 blocking peptide. The average background control value was subtracted from the average absorbance of each triplicate. The absorbance of each triplicate was then normalized to the average of the negative control (spontaneous LDH release from the untreated cells). For the positive control, maximum LDH activity was achieved through synchronized cold shock apoptosis by measuring the LDH release from 100% dead cells into the supernatant media. Data were obtained in triplicate and analyzed using two-way analysis of variance and the Bonferroni correction. Error bars represent SEM, where * is p < 0,05 and ns (not significant). Significance levels (*, ns) refer to the statistical comparison between the samples

48 treated with 3C2-1D12 + control peptide and 3C2-1D12 + B5 peptide.

49 B.

50 Figure 12. Concentration-dependent direct cellular toxicity of ABCB5 mAb 3C2-1D12. E rror bars represent SEM, ns=not signiﬁcant, * p<0,05.

Target cell death was also measured by LDH release into supernatant media after 48h treatment after treatment of SK-MEL-28 cells with the human mAb 3B9. Figure 13A shows a cytotoxicity comparison between the treatment with 3B9 mAb alone, 3B9 and control peptide, and 3B9 and B5 blocking peptide. The average background control value was subtracted from the average absorbance of each triplicate. The absorbance of each triplicate was then normalized to the average of the negative control (spontaneous LDH release from the untreated cells). As a positive control, maximum LDH activity was achieved through synchronized cold shock apoptosis by measuring the LDH release from 100% dead cells into the supernatant media. Data were analyzed using two-way analysis of variance and the Bonferroni correction. Error bars represent SEM, where * is p < 0,05 and ns - not signiﬁcant. Signiﬁcance levels (***, ns) refer to the statistical comparison between the samples treated with 3B9 + control peptide and 3B9 + B5 peptide.

52 B.

Figure 13. Concentration-dependent direct cellular toxicity of ABCB5 mAb 3B9. Error bars represent SEM, ns=not signiﬁcant, *** p<0,001.

3.6.1. Luminescence cell viability assay

The luminescence cell viability assay was applied to further prove the anti-apoptotic effect of ABCB5 and the reversal of this effect through ABCB5 blockade. In contrary to the LDH release assay, this experiment demonstrates cell viability, based on the measurement of ATP produced by metabolically active cells. Cell cytotoxicity was determined by measuring the number of viable cells, based on the ATP level in the supernatant media after treatment of SK-MEL-28 cells with increasing doses of the 3B9 mAb over 48 h. Figure 14A shows a dose-dependent increase of cytotoxicity after treatment with 3B9. Data were normalized against the non-treatment control. Figure 14B represents a comparison of treatment with 3B9 mAb and treatment with ABCB5 peptide-blocked 3B9 mAb. Results suggest a trend towards reduced viability among the cells, treated with the blocked 3B9 mAb. Data were obtained in triplicates. Statistical analyses were performed using one-way analysis of variance and Dunnett post-test (A.) and two-way analysis of variance and Bonferroni correction (B.). Error bars show SEM, the significance level Alpha is 0,05 (95% confidence intervals), where p<0,05 is considered to be statistically significant (marked with *) and p<0,01 and p<0,001 is considered highly statistically significant (marked respectively with ** and ***), ns (not significant).

Figure 14. SK-MEL-28 cell viability after treatment with the anti-ABCB5 mAb 3B9. A. No treatment versus treatment with 3B9. B. Treatment with 3B9 versus treatment with B5-blocked 3B9.

56 4. Discussion

The main goal of this study was to characterize a panel of novel monoclonal antibodies that target the ABCB5 membrane protein – a hallmark of melanoma stem cells. Furthermore, we evaluated their potential for therapeutic efﬁcacy in vitro, demonstrating direct cytotoxic effects of ABCB5 targeting in melanoma. The ﬁndings of this study provide a basis for planned in vivo validation studies of select mAb candidates in the course of further preclinical development for malignant melanoma therapy.

As detailed below, the results of this study support previous work in Dr. Frank’s laboratory, who ﬁrst identiﬁed and researched ABCB5 as a cell-surface marker of melanoma stem cells (Schatton et al., 2008) and could demonstrate that ABCB5 plays a major role in the maintenance and recurrence of malignant melanoma.

In agreement with previously shown results by Dr. Wilson (Wilson et al., 2014), this study provides evidences that ABCB5 serve as a functional driver of melanoma growth and regulates the secretion of IL8 in human malignant melanoma, whereby the blockade of ABCB5 could consequently suppress tumor aggressiveness features, such as tumor metastasizing potential and chemotherapy resistance through modiﬁcation of the proinﬂammatory cytokine signaling axis (Singh and Varney, 2000).

Furthermore, this study displayed that anti-ABCB5 mAbs have the ability to promote direct melanoma cell cytotoxicity. The results of this study are congruent with the work in Dr. Ksander’s laboratory, who has also identiﬁed direct cell cytotoxicity effects by blockade of ABCB5 with the human mAb 3B9 (Ksander et al., 2014). A dose-dependent cytotoxicity through blocking ABCB5 could be achieved with a human mAb (3B9) after 48 h of treatment. This direct apoptotic effect is consistent with the observations of Ksander et al., who showed that blocking ABCB5 with the mAb 3B9 induces a substantial level of apoptosis among

57 ABCB5-expressing limbals stem cells. Moreover, targeting of ABCB5 induced the pro-apoptotic p53 and suppressed the anti-apoptotic Bcl2 and Bcl-X, which further underlines the ABCB5-dependent regulation of apoptotic signaling pathways (Ksander et al., 2014).

Additionally, recent studies suggest similar functions of ABCB5 and effects of blocking the membrane protein in other malignancies besides melanoma and colorectal cancer, for example Merkel cell carcinoma, where blockade of ABCB5 could reverse the chemoresistance of the tumor toward etoposide and carboplatin (Kleffel et al., 2016). Kleffel et al. demonstrated that the combination treatment with an anti-ABCB5 and the aforementioned chemotherapeutics could signiﬁcantly increase the tumor cell death compared to the isotype control, supporting the role ABCB5 as an efﬂux drug transporter, suggesting that monotherapy with common chemotherapeutics leads to selective survival of ABCB5-positive cells . The study also validates the results of this thesis, showing that blocking ABCB5 leads to a compensatory increase of the ABCB5 mRNA.

Melanoma is the ﬁfth most common type of cancer. Therapeutic approaches vary from a simple surgical excision to comprehensive and often unavailing treatment depending on the stage and molecular aspects of the tumor. Despite major advances in our understanding of the molecular foundations of the disease, current treatment options are of limited efﬁcacy in patients with metastatic melanoma.

Melanoma presents a great challenge for clinicians and researchers, not only because of the rapid tumor progression and high risk of early metastasis, but also because of its ability to escape the approaches of conventional chemotherapy. More than three decades, the alkylating agent dacarbazine (DTIC) was the standard and the only FDA-approved chemotherapeutic drug for treatment of advanced melanoma with response rates of 6 to 20% and no improvement of the overall survival rate (Serrone et al., 2000). Besides targeted therapy, further

58 advances in melanoma treatment are based on the assumption that immunomodulation could prevent cancer occurrence and disease progression. High-dose recombinant Interleukin 2 (IL-2) is the ﬁrst FDA-approved non-chemotherapeutic immunotherapy approach in melanoma treatment that beneﬁts some patients with metastatic melanoma by activating cytotoxic T cells but could potentially cause severe toxicity side effects and even death by sepsis (Atkins et al., 1999).

Biologic therapy or immunotherapy is an approach based on modulation of the patient’s immune system, ultimately resolving in boosting the body’s natural defenses against cancer. Based on these findings, in 1995 interferon-therapy became the first FDA-approved adjuvant regimen for patients with advanced stages of malignant melanoma (Kirkwood et al., 1996; Balch and Buzaid, 1996; Mocellin et al., 2013). However, additionally to its possible grievous side effects such as hepatotoxicity, myelosuppression and severe fatigue (Hausschild et al., 2008), in later studies it was shown that although it does prolong the the recurrence-free survival, the therapy with interferon does not have a significant impact over the overall survival of the melanoma patients (Eggermont et al., 2008).

Currently, two melanoma treatment options are of special interest. An attractive area of melanoma research has become the immune checkpoint inhibition by ipilimumab (humanized anti-CTLA-4 monoclonal antibody) (Sharma and Allison, 2015). Ipilimumab is currently approved for both treatment-naïve and previously treated metastatic melanoma patients. Another candidate just recently started outranking ipilimumab as ﬁrst-line melanoma therapy (Wolchok, 2015). The IgG4-κ-Immunoglobulin nivolumab has anti-tumor and immunostimulating features at the same time (Brahmer et al, 2015). Nivolumab binds the PD-1 receptor (Program death receptor-1) on T-lymphocytes and prevents the interaction between the PD-L1 and PD-L2 ligands, leading to activation and proliferation of T-cells (Topalian et al., 2012; Johnson et al., 2015). The

59 combination of both agents has been recently approved for treatment of patients with unresectable stage III and stage IV melanoma (Wolchok et al., 2013).

Despite major breakthroughs in melanoma research, additional studies are needed to improve our understanding of the molecular mechanisms behind the low response rates to melanoma treatment and tumor recurrence. Combination therapy and the therapeutic promise of targeting melanoma stem cells may be able to overcome therapeutic resistance and improve progression-free survival of patients with advanced melanoma.

Since the development of the hybridoma technique in 1970, the promising potential of mAbs has been explored in many clinical areas. Therapeutic mAbs represent the fastest growing and the most promising branch for cancer treatment. MAbs can facilitate their therapeutic effects through direct (antibody-directed) or indirect (antibody-mediated) elimination of tumor cells (Ludwig et al., 2003). The indirect effects of mAbs are mostly illustrated by ADCC or CDC. However, of a special interest are antibodies, which can activate apoptotic signaling directly, for example through antigen-crosslinking, death receptor activation and modulation of anti-apoptotic pathways.

As one of the most aggressive types of cancer with an extremely poor prognosis, malignant melanoma is of great interest with regard to mAbs development. However, a considerable obstacle to the development of an effective therapy for melanoma is ﬁnding a treatment regimen, which not only eliminates the main tumor bulk population, bus also the signiﬁcant small pool of cancer stem cells that drive tumor recurrence and therapeutic resistance.

Cancer cells are not all the same. According to the cancer stem cell theory, a signiﬁcant small pool of cancer stem cells represents the driving force of the malignancies. Each stem cell is deﬁned by three substantial characteristics: 1) long-term self-renewal capacity, demonstrated by serial xenotransplantation and genetic lineage tracking experiments, 2) ability of differentiation into tumor bulk

60 cells without the stem cell implications, and 3) indeﬁnite proliferation, causing tumor growth.

As the biopharmaceutical industry matures, targeting specific markers on the cancer cells surface has become the focal point of mAbs research over the past decade. Identifying a reliable marker, which defines a cancer stem cell, is the first step towards developing specific targeting agents. Previous studies have detected a small, ABCB5-expressing population of melanoma cells mirroring the behavior of human stem cells. ABCB5 overexpression has been shown to correlate with 1) clinical tumor progression, 2) multidrug-resistance, 3) metastasis and 4) tumor recurrence. Moreover, ABCB5 plays a major role in the maintenance of malignant melanoma initiating cells (MMIC) (Wilson et al., 2014). It has been shown that ABCB5 overexpression leads to IL-2 inhibition, a mechanism through which melanoma stem cells escape host antitumor immunity and immunotherapeutic approaches. Further characteristics of ABCB5-positive cells are the preferential expression of the B7 family member B7-2 and PD-1, and also a B7-2-dependent IL-10 induction (Schatton et al., 2010). B7-2 and PD-1 govern major immunomodulatory functions such as regulation of T-cell activation and have already been used as immune checkpoints in melanoma treatment (Greenwald et al., 2005; Fellner, 2012; Wolchok et al., 2013).

Melanoma formation and growth in xenografts can be inhibited by targeting ABCB5 with mAbs through antibody-dependent cell-mediated cytotoxicity (ADCC) (Schatton et al., 2008). ADCC requires the introduction of antibody-bound tumor cells to the immune system, specifically the peripheral blood mononuclear cells (PBMCs). In the case of ADCC, the effector cells, e.g. NK-cells, macrophages, lymphocytes etc. induce the lysis of the target or cancerous cells, whereby the IgG-antibody serves as a mediator between both types of cells. However, there are several obstacles, which confine the efficacy of ADCC-dependent therapy in patients. ADCC requires high affinity and strong binding between the antibody and the antigen. About 80% of the population presents with an FcγRIIIa

61 polymorphism. This lower afﬁnity receptor variant is associated with an inadequate ADCC response in those patients (Chames et al., 2009).

The mAbs, evaluated in this study, presented with an estimated dissociation constants (Kd ) in the range between 23,38 nM for the human mAb 3B9 and 61,27 nM for 3C2-1D12. For comparison, ipilimumab binds to CTLA-4 with Kd of 18,2 nM (He et al., 2017), and the PD-1 blockers pembrolizumab and nivolumab bind PD-1 with a Kd of 3,06 pM and 29 pM respectively (Fessas et al., 2017). Ideally, high afﬁnity antibodies for the clinical use possess a Kd of less than 1 nM (Rathanaswami et al., 2007; Kennel et al., 1983; Liu et al., 2015), which indicate a need to improve the binding afﬁnity of the human mAbs, that were evaluated in this study.

Another obstacle that could potentially disturb ADCC is that, mAbs interact not only with activating receptors but also with inhibitory receptors, such as the FcγRIIb, which can decrease the efficacy of ADCC. Finally, reaching a sufficient concentration in the patient’s serum is crucial in order that the therapeutic mAbs would be able to compete with the patient’s immunoglobulines for triggering therapeutic ADCC (Chames et al., 2009). In this regard, it might be of advantage to develop antibodies that deploy their efficacy at least partially via other manners beside ADCC. As mentioned above, the results of this study suggest that ABCB5-targeting can also have direct therapeutic anticancer effect, independent of ADCC through the described function of the molecules as confirmed by the results of Ksander et al. (Ksander et al., 2014).

All of these features make ABCB5 an ideal candidate for developing a next generation of melanoma therapeutics based on ABCB5 targeting mAbs. Protein molecules such as mAbs present with a number of significant characteristics: 1) wide spectrum of application fields, 2) homogeneity, 3) high precision and specificity, 4) long half-lives and 4) rapid and robust production. Despite these advantages of mAbs over conventional anti-cancer therapeutics, there are also

62 many challenges associated with these targeted therapeutics such as diverse side effects after administration of the antibodies (Table 3).

Table 3. Selected side effects of FDA-approved mAbs (Hansel et al., 2010).

Immune reactions Serum sickness; acute anaphylactic reactions; tumor lysis syndrome; cytokine release syndrome; systemic inﬂammatory response syndrome

Infections Reactivation of tuberculosis; progressive multifocal leukoencephalopathy

Blood cells disorders Thrombocytopaenia; thrombocythaemia; venous thromboembolisms; neutropaenia; lymphopaenia

Organ toxicities Cardiotoxicity; pulmonary toxicity; vasculitis; hepatitis; renal toxicity

Autoimmune disorders Autoimmune colitis; nephritis; autoimmune hyperthyroidism; Lupus-like syndromes

Skin disorders Dermatitis; urticaria

The application of humanized or fully human mAbs can theoretically reduce some of the above listed undesirable side effects, especially the immune reactions, which can be caused by the nonhuman nature of mAbs. Humanization of mAbs can be achieved through maximum reduction of nonhuman immunoglobulin sequences and replacement with human ones in the constant domain. Moreover, humanization of variable domains induces a further decrease (Hwang and Foote, 2005). As a consequence, this process has the potential to reduce the immunogenicity of the mAbs. The mAb 3B9, evaluated in this study, is a fully human mAb and its administration would potentially carry a lower risk for inducing immune anti-antibody responses in humans than mouse or chimeric antibodies.

63 The ﬁndings of this study provide a rational to examine ABCB5 targeting antibody-dependent reversal of ABCB5 anti-apoptotic function also in further preclinical in vivo experiments in the course of further development of an ABCB5-based melanoma therapy.

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83 Appendix

Table A1. Concentration-dependent binding afﬁnity of 3C2-1D12 mAb raw data.

3C2-1CD12 Normalized by Isotype nM Control 0 0,25 325,520 0,27 5,210,000 0,49 781,250 0,96 10,420,000 1,32 20,830,000 2,66 41,670,000 3,13 83,300,000 6,68

Table A2. Concentration-dependent binding afﬁnity of 3B9 mAb raw data.

Normalized by Isotype 3B9 nM Control 0 0,22 325,520 2,95 5,210,000 2,58 781,250 8,76 10,420,000 20,58 20,830,000 19,84 41,670,000 45,03 83,300,000 37,66

84 Table A3. Dose-dependent induction of ABCB5 mRNA expression through ABCB5 targeting in SK-MEL-28 melanoma cells raw data.

Concen- tration MOPC31C 3C2-1D12 1 μg/ml 9,496,228 9,952,628 1,061,356 6,347,722 8,162,811 9,666,855 5 μg/ml 9,955,295 1,020,761 9,843,994 1,096,867 7,392,737 9,419,816 20 μg/ml 1,054,636 9,977,937 9,527,498 1,812,996 1,176,319 9,789,991 50 μg/ml 9,716,548 1,021,167 1,008,515 1,242,919 1,780,463 1,117,482

Table A4. Dose-dependent induction of ABCB5 mRNA expression through ABCB5 targeting in A375 melanoma cells raw data.

Concen- tration MOPC31C 3C2-1D12 1 μg/ml 9,650,726 1,019,788 1,017,074 1,139,946 8,139,172 528,513 5 μg/ml 9,584,858 1,051,715 9,941,744 734,724 1,258,459 3,127,785 20 μg/ml 9,758,177 1,005,991 1,019,187 1,269,283 8,724,384 1,873,926 50 μg/ml 9,113,889 1,038,528 1,063,974 1,799,269 1,738,304 1,590,120

Table A5. Inhibition of IL8 secretion through ABCB5 targeting with 3B9 mAb raw data.

human IgG1 Isotype 3B9 no treatment 50 μg/ml 50 μg/ml 864,625,000 837,000 465,625,000 761,625,000 880,000 395,625,000 783,625,000 866,000 455,825,000

85 Table A6. Dose-dependent inhibition of IL8 secretion through ABCB5 targeting with 3C2-1D12 raw data (qPCR).

3C2- 3C2- 3C2- MOPC- 3C2- 1D12 1D12 1D12 3C2- 3C2- no treat- 31C 1D12 3,125 6,25 12,5 1D12 1D12 ment 50 μg/ml 1,6 μg/ml μg/ml μg/ml μg/ml 25 μg/ml 50 μg/ml 735,888 641,989 598,398 518,193 535,616 534,583 498,060 454,142 627,266 619,418 535,616 515,148 536,650 469,543 457,012 393,876 681,447 602,789 643,130 550,183 523,288 455,097 479,288 422,168

Table A7. Concentration-dependent direct cellular toxicity of 3C2-1D12 raw data (LDH assay).

no 0,05 3,125 6,25 12,5 treatment μg/ml 0,2 μg/ml 0,8 μg/ml 1,6 μg/ml μg/ml μg/ml μg/ml 1,046,279 976,305 992,966 1,055,165 989,633 1,075,157 1,160,681 1,219,548 964,087 950,759 1,005,183 999,630 939,652 1,100,703 1,139,578 1,178,452 989,633 1,084,043 1,070,715 755,276 990,744 1,447,242 1,465,013 1,401,703 1,043,616 976,305 992,966 1,193,530 1,259,388 1,320,913 1,370,306 1,424,032 1,002,022 950,759 1,005,183 1,267,187 1,297,516 1,376,372 1,407,568 1,481,225 3C2 954,362 1,084,043 1,070,715 1,156,268 1,300,982 1,261,121 1,385,038 1,477,759 1,046,279 1,152,906 1,098,482 1,129,582 1,169,567 1,144,021 1,139,578 1,147,353 964,087 1,115,143 1,171,788 1,230,655 1,031,840 1,115,143 1,231,766 1,297,297 989,633 1,090,707 1,006,294 1,081,822 1,251,759 1,202,888 1,058,497 1,101,814 1,034,341 1,152,906 1,098,482 1,161,139 1,168,183 1,264,162 1,436,748 1,221,016 3C2 + 1,024,655 1,115,143 1,171,788 1,157,617 1,224,538 1,269,445 1,171,705 1,200,763 control peptide 941,004 1,090,707 1,006,294 1,101,262 1,235,104 1,259,759 1,160,258 1,213,091 1,046,279 939,652 1,130,692 1,125,139 1,142,910 1,165,124 1,226,213 1,164,013 964,087 968,530 917,438 981,859 942,984 1,092,929 1,118,475 1,085,154 989,633 1,147,353 987,412 1,050,722 915,217 1,025,176 1,059,608 1,075,157 1,043,616 939,652 1,130,692 1,093,010 1,094,743 1,041,883 1,049,682 1,041,883 3C2 + 1,002,022 968,530 917,438 1,093,010 1,082,611 1,104,275 1,073,946 1,074,812 ABCB5 peptide 954,362 1,147,353 987,412 1,155,401 1,103,408 1,067,880 1,080,878 1,060,947

86 Table A8. Concentration-dependent direct cellular toxicity of 3B9 raw data (LDH assay).

3B9 + ABCB5 peptide 3B9 + control peptide 3B9 no treat- 5,905,3 -2,524, -3,380, 5,905,3 -2,524, -3,380, 5,905,3 -2,524, -3,380, ment 34 418 917 34 418 917 34 418 917 0,05 4,507,8 -2,975, 2,975,2 3,921,8 4,462,8 2,073,6 2,839,9 μg/ml 89 495,868 207 135,237 07 63 10 29 70 0,2 -3,245, -4,643, -3,921, 5,679,9 6,987,2 10,593, 13,343, 7,347,8 8,835,4 μg/ml 680 126 863 40 27 540 350 59 62 0,8 -1,532, -3,155, -1,487, 8,700,2 8,069,1 13,794, 12,802, 9,917,3 11,900, μg/ml 682 522 603 26 21 140 400 56 830 1,6 -2,028, -3,966, -3,380, 12,847, 12,351, 17,986, 3,606,3 16,363, 16,589, μg/ml 550 942 917 480 610 480 11 640 030 3,125 -4,012, -3,290, 14,830, 17,535, 19,924, 15,732, 17,625, 16,949, μg/ml 0 021 759 950 690 870 530 840 660 6,25 -1,577, 12,396, 9,511,6 13,523, 16,228, 15,011, 4,102,1 μg/ml 135,237 -45,079 761 690 45 670 400 270 79 12,5 -1,307, 3,020,2 -1,532, 14,470, 11,990, 14,019, 25,154, 21,232, 16,949, μg/ml 288 86 682 320 980 530 020 160 660

Table A9. Luminescence cell viability assay: concentration dependent SK-MEL-28 cell viability after treatment with the anti-ABCB5 mAb 3B9 raw data. no treat- 0,05 3,125 6,25 12,5 ment μg/ml 0,2 μg/ml 0,8 μg/ml 1,6 μg/ml μg/ml μg/ml μg/ml 1,010 966 911 916 892 944 847 759 991 993 861 968 880 826 893 844 995 1,020 918 1,000 950 854 899 818

87 Table A10. Luminescence cell viability assay: concentration dependent SK-MEL-28 cell viability after treatment with the anti-ABCB5 mAb 3B9 versus blocked 3B9 mAb raw data.

3B9 3B9 + ABCB5 peptide 0,05 μg/ml 966 993 1,020 1,000 994 1,090 0,2 μg/ml 911 861 918 1,000 1,020 1,040 0,8 μg/ml 916 968 1,000 1,010 1,010 1,060 1,6 μg/ml 892 880 950 990 1,030 799 3,125 μg/ml 944 826 854 970 973 1,060 6,25 μg/ml 847 893 899 949 935 979 12,5 μg/ml 759 844 818 903 923 832

88 Acknowledgements

I would like to express my sincere gratitude to Prof. Eggert Stockfleth from the department of dermatology at St. Josef-Hospital in Bochum for the continuous and tremendous support of my study. Prof. Stockfleth is one of those rare leaders who make you feel like you are capable of anything and I am truly thankful for having him as my dissertation chairman.

Profound gratitude goes to my dedicated supervisor Prof. Markus Frank from Boston Children’s Hospital, Harvard Medical School. My stay in Boston has been an amazing experience and I thank Prof. Frank wholeheartedly for his tremendous academic support, for giving me this wonderful opportunity and for sharing his knowledge: from molecular biology and statistics to perfectionism and the value of not giving up.

I would like to thank Brian J. Wilson from the Frank’s laboratory for giving me a crash course in experimental work. I am grateful for his fantastic lab training, for the lessons in work ethics and for his endless patience.

Furthermore, I would like to extend my thanks to Prof. Natasha Frank from the department of genetics at the Brigham and Women’s Hospital and Pallavi, Lynn and Gretchen from the Frank’s laboratory who were always ready to help, supported me during countless presentations and heated lab meetings, and made me feel at home in the lab overseas.

Finally, but by no means least, thanks go to my family: my loving parents, Mariana and Koycho, for the unconditional support in all my pursuits, my caring sister Katrin for believing in me more than I do myself and my brilliant husband Atanas for introducing me to the beauty of science. I am lucky to have you. CURRICULUM VITAE

Angaben zur Person

Name Ani K. Stoyanova Geburtsdatum 13. November, 1990 Geburtsort Sliven, Bulgarien Anschrift Telramundweg 8, 12167 Berlin Handynummer +49 1578 4625187 E-mail [email protected]

Studium und Ausbildung

Seit März ’14 Experimentelle Doktorarbeit an der Ruhr-UniversitätBochum in Kollaboration mit Harvard Medical School, Boston (MA), USA Thema der Dissertation: Monoclonal Antibody Targeting of ABCB5 in Human Malignant Melanoma Betreuung: Prof. Eggert Stockfleth (Ruhr-UniversitätBochum), Prof. Markus Frank, M.D. (Harvard Medical School)

Juni – Okt. ’16 Forschungsaufenthalt Massachusetts General Hospital, Boston (MA), USA Thema: Cancer Mutational Patterns in Protein Structures

August – Okt. ’13 Forschungsaufenthalt Dana-Farber Cancer Instiute, Boston (MA), USA Thema: Protein Interaction Perturbations in Genetic Disorders

Okt. ’09 – Juni ’16 Studium Humanmedizin Charit´eUniversit¨atsmedizin Berlin

Berufserfahrung

Seit Okt ’16 Assistenzärztin Klinik für Allgemein-, Viszeral- und Gefäßchirurgie CharitéUniversitätsmedizin Berlin: Campus Benjamin Franklin

i Praktika und Nebentätigkeiten Seit Mai ’15 Praktisches Jahr CharitéUniversitätsmedizin Berlin Innere Medizin, Chirurgie: Campus Benjamin Franklin Dermatologie: Campus Mitte

Sept. ’13 Famulatur Abteilung f¨ur Onkologie, Dana-Farber Cancer Institute Harvard Medical School, Boston (MA), USA

April – August ’13 Praktikum Bayer Pharma AG, Global Biomarker - Research Biobank, Berlin Thema: Circulating Tumor Cells and W741C Mutant Androgen Receptor in Prostate Cancer

März – April ’13 Famulatur Abteilung für Dermatologie, CharitéUniversitätsmedizin Berlin

Febr. – M¨arz ’13 Famulatur Station f¨ur Gastroenterologie und Kardiologie, St. Marien-Krankenhaus Berlin

Dez. ’12 – März ’13 Studentische Hilfskraft Institut für Geschlechterforschung in der Medizin, CharitéUniversitätsmedizin Berlin Studie: BEFRI: Berliner Frauen Risiko Evaluation

Okt. ’10 – Nov. ’12 Studentische Hilfskraft im Pﬂegedienst Vivantes Krankenh¨auser Berlin

July – Okt. ’12 Famulatur Station für Gynäkologie, Brustzentrum, CharitéUniversitätsmedizin Berlin

Febr. – April ’12 Laborpraktikum Endometriose-Forschungszentrum, Charit´eUniversit¨atsmedizin Berlin Thema: Schmerzpathogenese der peritonealen Endometriose

Publikationen Sahni N, . . . , Ani K. Stoyanova, et al. (2015) Widespread macromolecular interaction perturbations in human genetic disorders. Cell 161:647-660. Sprachen Deutsch (ﬂießend), Englisch (ﬂießend), Bulgarisch (Muttersprache)