University of Groningen Probing the Ligand Receptor Interface of TNF

University of Groningen

Probing the ligand receptor interface of TNF ligand family members RANKL and TRAIL Wang, Yizhou

DOI: 10.33612/diss.127959201

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Probing the ligand-receptor interface of TNF ligand family members RANKL and TRAIL

Yizhou Wang

The research described in this thesis was carried out in the Department of Chemical and Pharmaceutical Biology (Groningen Research Institute of Pharmacy, University of Groningen, The Netherlands) and was financially supported by the China Scholarship Council, the Dutch Top Institute Pharma project TNF-ligands in cancer (project nr. T3-112) and the Dutch Science Foundation (NWO/STW) (grant 11056).

The research work was carried out according to the requirements of the Graduate School of Science, Faculty of Science and Engineering, University of Groningen, The Netherlands.

Printing of this thesis was financially supported by the University Library and the Graduate School of Science, Faculty of Science and Engineering, University of Groningen, The Netherlands.

ISBN: 978-94-034-2667-9 (printed version) ISBN: 978-94-034-2666-2 (electronic version)

Printing: Ridderprint BV, www.ridderprint.nl Cover image: yililiu.com Cover design: Yizhou Wang and Ridderprint

Probing the ligand-receptor interface of TNF ligand family members RANKL and TRAIL

PhD thesis

to obtain the degree of PhD at the University of Groningen on the authority of the Rector Magnificus Prof. C. Wijmenga and in accordance with the decision by the College of Deans.

This thesis will be defended in public on

Tuesday 30 June 2020 at 12.45 hours

Yizhou Wang

born on 22 April 1990 in Hebei, China

Supervisors Prof. W.J. Quax Prof. H.J. Haisma

Assessment Committee Prof. R.A. Bank Prof. B.N. Melgert Prof. V.W. van Beusechem

Table of Contents

Chapter 1 General introduction and scope of the thesis 7

Chapter 2 TNF-family member Receptor Activator of NF-κB 19 (RANK) and RANK-Ligand (RANKL) in bone remodeling

Chapter 3 Novel RANKL DE-loop mutants antagonize RANK- 33 mediated osteoclastogenesis

Chapter 4 Creation of RANKL mutants with low affinity for 59 decoy receptor OPG and their potential anti-fibrosis activity

Chapter 5 Long term secretion of adenovirally-expressed 83 RANKL WT/ Q236D for treatment of fibrosis

Chapter 6 Overcoming senescent cancer cell resistance to 105 extrinsic apoptosis using a death receptor 5 (DR5) selective TNF-related apoptosis inducing ligand (TRAIL) variant

Chapter 7 Novel TRAIL variants with reduced binding to decoy 131 receptor OPG overcome TRAIL resistance in breast cancers

Chapter 8 Summary and future perspectives 151

Samenvatting Nederlandse Samenvatting 159

Appendices Acknowledgements 168 List of publications 173 About the author 175

Chapter 1

General introduction and scope of the thesis

Chapter 1

TNF superfamily

The discovery of tumor necrosis factor (TNF) superfamily dates back to the middle of the nineteenth century when O‘Malley found a tumor-necrotizing factor in the serum that could mediate tumor regression effects [1]. Carswell‘s group renamed this factor as tumor necrosis factor and reported that macrophages were the source of this factor [2]. In 1968, Granger and colleagues described another factor called lymphotoxin (LT) produced by lymphocytes, which could also kill tumor cells [3]. Until 1984, Aggarwal‘s group determined and compared the amino acid sequence of TNF and LT, indicating that the two proteins were homologous [4]. Therefore, they were renamed to TNF-α and TNF-β, respectively. These two factors laid the foundation for the identification of the TNF superfamily.

At present, in total 19 TNF superfamily ligands and 29 receptors have been identified (shown in Table. 1). The TNF superfamily ligands are type II trimeric transmembrane proteins with a C-terminal TNF homology domain (THD). THD is a sequence of around 150 amino acids, which contains a conserved framework of aromatic and hydrophobic residues to fold and form trimeric proteins [5]. The individual monomers are β-sandwich structures containing β strands and loops that form a ―jelly-roll‖ structure: the inner sheets are responsible for trimerization and the outer sheets are for receptor binding [5,6]. The TNF superfamily receptors are type I or type III membrane or soluble proteins containing cysteine-rich domains (CRD) for ligand binding [7].

Among the large family of TNF ligands and receptors, there are 19 ligands and 29 different receptors, indicating the diversity of ligand-receptor interactions. As shown in Table. 1, TNF ligands can bind to one specific or multiple receptors, and different ligands can bind to the same receptor. The TNF receptors can be divided into 3 groups according to their cytoplasmic sequences and their cellular signal pathways [8]. The first group receptors, including Fas, TNFR1, DR3, DR4, DR5, and DR6, contain a death domain (DD) in the cytoplasmic tail. Activation of these DD-containing receptors can lead to the recruitment of adaptor proteins such as TNFR associated death domain (TRADD) or Fas-associated death domain (FADD), which on their turn can activate the caspase cascade and finally induce apoptosis [9]. The second group, including TNFR2, CD40, CD30, CD27, LTβR, OX40, 4-1BB, BAFFR, BCMA, TACI, RANK, NGFR, HVEM, GITR, TROY, EDAR, XEDAR, RELT, and Fn14, contains TNFR associated factor (TRAF)-interacting motifs (TIM). Activation of these TIM- containing receptors can lead to the activation of downstream signaling pathways, including

General introduction and scope of the thesis nuclear factor-κB (NF-κB), mitogen-associated protein kinases (MAPK) such as p38, c-JNK, and the extracellular signal-regulated kinases (ERK) as well as phosphoinositide 3-kinase (PI3K) and Akt [8,10], which finally induce cell survival and inflammation. The third group of TNF receptors includes Decoy receptor 1 (DcR1), DcR2, DcR3, and osteoprotegerin (OPG), which do not contain functional intracellular signaling domains or motifs. They act as decoy receptors to compete and block the binding between the ligand and other functional 1 receptors [8,11,12].

Almost all of the TNF superfamily ligands are expressed by immune cells, while the receptors are expressed by a wide variety of cells [13]. The binding between the TNF superfamily ligands and receptor will cause biological effects such as tumor regression, immune system regulation and hematopoiesis. However, dysregulation of the binding between the ligand and receptor also leads to various diseases [13]. In this thesis, we mainly focus on two TNF superfamily members, RANKL and TRAIL.

Table 1: Ligands and receptors of TNF superfamily [7]

Ligands Receptors

Symbol Common name (alias) Common name TNFSF1 TNF-α TNFR1/TNFR2 TNFSF2 TNF-β (LT-α) TNFR1/TNFR2/HVEM/ LTβR TNFSF3 LT-β LTβR TNFSF4 OX40L (CD252) OX40 TNFSF5 CD40L (CD154) CD40 TNFSF6 FasL (CD95L/Apo1L) Fas/DcR3 TNFSF7 CD27L (CD70) CD27 TNFSF8 CD30L (CD153) CD30 TNFSF9 4-1BBL 4-1BB TNFSF10 TRAIL (Apo2L) DR4/DR5/DcR1/DcR2/OPG TNFSF11 RANKL (OPGL/ODF/TRANCE) RANK/OPG TNFSF12 TWEAK (Apo3L) Fn14 TNFSF13 APRIL (TALL-2/TRDL-1) TACI/BCMA TNFSF13B BAFF (BLYS/THANK) BAFF-R/TACI/BCMA TNFSF14 LIGHT (HVEML/LT-γ) LTβR/DcR3/HVEM TNFSF15 VEGI (TL1A) DcR3/DR3 TNFSF18 GITRL GITR EDA-A1 EDAR EDA-A2 XEDAR N.D. DR6 N.D. RELT N.D. TROY N. D., not determined.

Chapter 1

RANKL/RANK/OPG system

In 1981, Rodan and Martin formulated a detailed hypothesis that osteoblasts influence the formation of osteoclasts [14]. In the late 1990s, OPG was discovered and patented as an important regulator of bone density [15]. Subsequent research was undertaken to identify the ligand of OPG, and contemporaneously an alternative strategy was used to identify TNFR superfamily homologous. As a result, the ligand of receptor activator of nuclear factor κB (RANKL), also known as OPGL, ODF and TRANCE, and its receptor RANK were discovered by different independent groups [16–18].

The RANKL/RANK/OPG system was first found to play an important role in bone remodeling system [19]. In normal conditions, bone homeostasis is maintained by a balance between old bone resorption by osteoclasts and new bone formation by osteoblasts [20]. RANKL is expressed on osteoblasts and RANK is expressed on osteoclast precursor cells [21]. The interaction between RANKL and RANK can induce the differentiation of osteoclasts from osteoclast precursors, and promote osteoclasts activation and survival [20]. The essential signaling pathway after RANKL stimulation includes the adaptor protein TNFR-associated factors (TRAFs) recruitment, NF-κB activation and translocation, and osteoclastogenic genes transcription [22]. OPG, which is also produced by osteoblasts, is a soluble decoy receptor and competes with RANK for RANKL binding [23]. Imbalances in the RANK/RANKL/OPG pathway can dysregulate the bone remodeling to either bone formation or resorption, therefore leading to diseases such as osteoporosis or osteopetrosis.

Apart from the role in bone remodeling, RANKL/RANK signaling also plays important roles in other tissues, since they are produced by a variety of cell types and tissues [22]. Recent studies indicate a number of other physiological and pathophysiological processes involving RANKL/RANK pathways like glandular development and lactation, cancer cell proliferation and metastasis and adaptive immunity [24]. More interestingly, this system may also play a role in fibrosis, which is characterized by excessive accumulation of extracellular matrix (ECM) [25]. In bone tissue, RANKL can bind to RANK on osteoclasts and induce bone ECM degradation. However, whether and how this signaling pathway regulates fibrotic tissue ECM degradation is unclear up to now.

Due to the important roles of the RANK-RANKL pathway in bone and other tissues, targeting RANKL or RANK with either agonistic or antagonistic compounds is a promising strategy for therapeutic intervention. Initially, OPG-Fc/variants or RANKL-targeted peptides were

General introduction and scope of the thesis developed as RANKL scavengers to prevent bone loss and inflammation [21,26,27]. Furthermore, denosumab, an FDA-approved RANKL-specific antibody, was developed and used in the treatment of osteoporosis and bone metastases [28]. However, through titrating away RANKL but not the receptor, they all carry the risk of immune reactions. Therefore, strategies with less immune response are still needed. One other approach was to focus on novel structure-based RANKL variants, which might be of interest to target the receptor 1 directly and trigger the autoimmune system with less impact compared to antibody.

TRAIL and its receptors

TNF-related apoptosis inducing ligand (TRAIL), also known as Apo2 ligand (Apo2L), was discovered in 1995 [29,30]. It is an important ligand protein of TNF superfamily that selectively induces apoptosis in a variety of tumor cells [31]. TRAIL interacts with five cognate receptors, namely death receptor 4 (DR4/TRAIL-R1), death receptor 5 (DR5/TRAIL- R2), decoy receptor 1 (DcR1/TRAIL-R3), decoy receptor 2 (DcR2/TRAIL-R4), and the soluble receptor osteoprotegerin (OPG) [32]. Both DR4 and DR5 contain the death domain (DD) in the intracellular part. Therefore, upon binding to DR4 and DR5, TRAIL can activate the extrinsic pathway through the recruitment of the Fas-associated death domain and the activation of caspase-8 [9,33]. The other receptors act as decoys receptors since DcR1 lacks a cytosolic region and DcR2 only contains a truncated, non-functional death domain [34]. OPG is a soluble protein showing weaker affinity to TRAIL compared to other membrane-bound receptors. However, it can still block the induction of apoptosis through sequestering the available TRAIL [35].

TRAIL can initiate the extrinsic apoptosis pathway through binding to DR4 or DR5, which results in the recruitment of caspase-8 and FADD to form the death-inducing signaling complex (DISC) [9]. This can further activate the downstream effector caspase-3, caspase-6, and caspase-7 and result in apoptosis [36]. In some cases, DISC activation is not sufficient to trigger the caspase cascade and the activation of the intrinsic pathway gets involved. Caspase- 8 activation cleaves Bid to truncated Bid (tBid), which further interacts with Bax and Bak on the mitochondrial membrane to promote the release of apoptotic factors like cytochrome c. These factors will form the apoptosome through binding to apoptotic peptidase activating factor 1 (Apaf-1) and the initiator caspase-9, which in turn activates caspase-3, caspase-6, and caspase-7 to induce apoptosis [37].

Chapter 1

Although TRAIL has been recognized as a representative anti-cancer agent, TRAIL resistance in tumor cells has been considered as a problem for a long time. This resistance may occur at different levels in the signaling pathways, including decoy receptors competition and dysregulation, DISC inhibition, reduced caspase function, imbalance of anti-and pro- proteins expression [35,38]. Therefore, the understanding of the mechanisms of TRAIL resistance and ways to improve TRAIL sensitivity of tumor cells is important for the development of therapeutic approaches with TRAIL.

Recombinant human TRAIL (rhTRAIL, aa 114-281) has been mostly used and developed as a clinical anti-cancer drug [39,40]. Clinical phase I studies showed this rhTRAIL was safe in patients with advanced cancer. However, there was no clinical benefit of rhTRAIL due to its fast kinetics and short half-life. On the other hand, rhTRAIL binds to all five TRAIL receptors, including three decoy receptors, which interfere with TRAIL-induced apoptosis. To overcome TRAIL resistance caused by decoy receptors competition, DR-specific TRAIL variants or antibodies are becoming promising therapeutic approaches in cancer treatment.

Scope of the thesis

The work described in this thesis is aimed to probe the ligand-receptor interface of TNF superfamily members RANKL and TRAIL, and the design and characterization of novel recombinant RANKL and TRAIL variants for their use as potential therapeutics.

Bone, as a dynamic tissue, is maintained by continuous renewal. An imbalance in bone resorption and formation can lead to a range of disorders, such as osteoporosis or osteopetrosis. The RANK/RANKL pathway plays an important role in bone remodeling. In Chapter 2, we review the prospective of interfering with the RANK/RANKL pathway as a therapeutic target for bone diseases and discuss the role of the soluble receptor OPG as a therapeutic in bone diseases. Then we focus on the possibility to develop antagonistic and agonistic variants of RANKL based on computational protein design. Finally, we discuss the development of antagonistic RANKL variants by changing the stoichiometry of the RANKL molecule.

In Chapter 3, we investigate the effect of mutations at position I248 in the DE-loop of RANKL on the interaction of RANKL with RANK and subsequent osteoclastogenesis activation. Two single mutants, RANKL I248Y and I248K, were found to maintain binding

General introduction and scope of the thesis and have the ability to reduce wild type RANKL-induced osteoclastogenesis. The generation of RANK-antagonists based on RANKL structure is a promising strategy for the exploration of new therapeutic approaches against osteoporosis.

RANKL/RANK/OPG signaling system was found to play an important role in the regulation of ECM formation and degradation in bone tissue. However, whether and how this signaling pathway plays a role in fibrotic tissue ECM degradation is unclear up to now. Interestingly, 1 increased decoy receptor OPG levels are found in fibrotic tissues. In Chapter 4, we investigate the role of RANKL/RANK/OPG pathway in fibrosis. We hypothesize that RANKL can stimulate RANK on macrophages and induce the process of ECM degradation. This process may be inhibited by highly expressed OPG in fibrotic conditions. In this case, RANKL mutants that can bind to RANK without binding to OPG might become promising therapeutic candidates. We built a structure-based library containing 44 RANKL mutants and found that RANKL_Q236D can activate RAW cells to initiate the process of ECM degradation and is able to escape from the obstruction by exogenous OPG.

In Chapter 5, to achieve a delivery system for targeting RANKL_Q236D to the fibrotic tissues, without influencing the bone remodeling, we constructed replication-deficient adenoviruses Ad-RANKL WT and Ad-RANKL Q236D. The functionality of virally produced RANKL_WT and RANKL_Q236D was confirmed, and it turned out that virally produced RANKL_Q236D can activate RAW 264.7 cells and make them escape from the inhibition by exogenous OPG. The generation of Ad-RANKL Q236D is a powerful tool that might lead to new therapies against fibrosis.

Since OPG also acts as the decoy receptor of TRAIL, we are also interested in the ligand- receptor interface of TRAIL and its receptors, and TRAIL resistance caused by its decoy receptors. In Chapter 6, we compare the sensitivity of TRAIL in senescent and proliferating cancer cells. We found that therapy-induced senescence resulted in an increased expression of the pro-apoptotic TRAIL receptor death receptor 5 (DR5), as well as an increase in TRAIL decoy receptors DcR1, DcR2, and soluble decoy receptor OPG. A DR5 selective TRAIL variant (DHER), which is unable of binding to OPG, DcR1 or DR4, is more effective in inducing apoptosis of senescent breast cancer cells compared to wild-type TRAIL.

High expression of OPG is also found in breast tumor cells, which inhibits TRAIL-induced apoptosis. Chapter 7 reports on a structure-based design strategy to obtain TRAIL variants with decreased affinity to OPG. We found the double mutant TRAIL_D269H/Y209M and the

Chapter 1 triple mutant TRAIL_D269H/Y209M/K179P showed lowered binding to OPG compared to TRAIL_DHER, and these variants can induce apoptosis in breast cancer cells MDA-MB-231 and MDA-MB-436 in the presence of OPG.

In Chapter 8, we summarize the work presented in this thesis and describe some suggestions for future perspectives.

References:

1 O‘Malley WE, Achinstein B & Shear MJ (1962) Action of bacterial polysaccharide on tumors. ii. damage of sarcoma 37 by serum of mice treated with serratia marcescens polysaccharide, and induced tolerance. J. Natl. Cancer Inst. 29, 1169–1175. 2 Carswell EA, Old LJ, Kassel RL, Green S, Fiore N & Williamson B (1975) An endotoxin induced serum factor that cuases necrosis of tumors. Proc. Natl. Acad. Sci. U. S. A. 72, 3666–3670. 3 Ezperimental T (1968) Lymphocyte in vitro Cytotoxicity : Lymphotoxins of Several Mammalian Species Relationship between Cell Size and Time of Initiation of DNA Replication. 219, 1967–1968. 4 Aggarwal BB, Kohr WJ, Hass PE, Moffat B, Spencer SA, Henzel WJ, Bringman TS, Nedwin GE, Goeddel D V. & Harkins RN (1985) Human tumor necrosis factor: Production, purification, and characterization. J. Biol. Chem. 260, 2345–2354. 5 Bodmer JL, Schneider P & Tschopp J (2002) The molecular architecture of the TNF superfamily. Trends Biochem. Sci. 27, 19–26. 6 Nelson CA, Warren JT, Wang MW-H, Teitelbaum SL & Fremont DH (2012) RANKL employs distinct binding modes to engage RANK and the osteoprotegerin decoy receptor. Structure 20, 1971–1982. 7 Ware CF (2003) Introduction: The TNF superfamily. Cytokine Growth Factor Rev. 14, 181–184. 8 Dempsey PW, Doyle SE, He JQ & Cheng G (2003) The signaling adaptors and pathways activated by TNF superfamily. Cytokine Growth Factor Rev. 14, 193–209. 9 Kischkel FC, Lawrence DA, Chuntharapai A, Schow P, Kim KJ & Ashkenazi A (2000) Apo2L/TRAIL-Dependent Recruitment of Endogenous FADD and Caspase-8 to Death Receptors 4 and 5. Immunity 12, 611–620. 10 Boyle WJ, Simonet WS & Lacey DL (2003) Osteoclast differentiation and activation. Nature 423, 337–342. 11 Nagy V & Penninger JM (2015) The RANKL-RANK Story. Gerontology 61, 534–542.

General introduction and scope of the thesis

12 Marsters SA, Sheridan JP, Pitti RM, Huang A, Skubatch M, Baldwin D, Yuan J, Gurney A, Goddard AD, Godowski P & Ashkenazi A (1997) A novel receptor for Apo2L/TRAIL contains a truncated death domain. Curr. Biol. 7, 1003–1006. 13 Aggarwal BB (2003) Signalling pathways of the TNF superfamily: A double-edged sword. Nat. Rev. Immunol. 3, 745–756. 14 Rodan GA & Martin TJ (1982) Role of osteoblasts in hormonal control of bone resorption - a hypothesis. Calcif. Tissue Int. 34, 311. 1 15 Simonet W., Lacey D., Dunstan C., Kelley M, Chang M-S, Lüthy R, Nguyen H., Wooden S, Bennett L, Boone T, Shimamoto G, DeRose M, Elliott R, Colombero A, Tan H-L, Trail G, Sullivan J, Davy E, Bucay N, Renshaw-Gegg L, Hughes T., Hill D, Pattison W, Campbell P, Sander S, Van G, Tarpley J, Derby P, Lee R & Boyle W. (1997) Osteoprotegerin: A Novel Secreted Protein Involved in the Regulation of Bone Density. Cell 89, 309–319. 16 Yasuda H, Shima N, Nakagawa N, Yamaguchi K, Kinosaki M, Mochizuki SI, Tomoyasu A, Yano K, Goto M, Murakami A, Tsuda E, Morinaga T, Higashio K, Udagawa N, Takahashi N & Suda T (1998) Osteoclast differentiation factor is a ligand for osteoprotegerin/osteoclastogenesis-inhibitory factor and is identical to TRANCE/RANKL. Proc. Natl. Acad. Sci. U. S. A. 95, 3597–3602. 17 Anderson DM, Maraskovsky E, Billingsley WL, Dougall WC, Tometsko ME, Roux ER, Teepe MC, DuBose RF, Cosman D & Galibert L (1997) A homologue of the TNF receptor and its ligand enhance T-cell growth and dendritic-cell function. Nature 390, 175–179. 18 Wong BR, Rho J, Arron J, Robinson E, Orlinick J, Chao M, Kalachikov S, Cayani E, Bartlett FS, Frankel WN, Lee SY & Choi Y (1997) TRANCE is a novel ligand of the tumor necrosis factor receptor family that activates c-Jun N-terminal kinase in T cells. J. Biol. Chem. 272, 25190–25194. 19 Trouvin AP & Goëb V (2010) Receptor activator of nuclear factor-κB ligand and osteoprotegerin: maintaining the balance to prevent bone loss. Clin. Interv. Aging 5, 345–354. 20 Tanaka S, Nakamura K, Takahasi N & Suda T (2005) Role of RANKL in physiological and pathological bone resorption and therapeutics targeting the RANKL-RANK signaling system. Immunol. Rev. 208, 30–49. 21 Naidu VGM, Dinesh Babu KR, Thwin MM, Satish RL, Kumar P V & Gopalakrishnakone P (2013) RANKL targeted peptides inhibit osteoclastogenesis and attenuate adjuvant induced arthritis by inhibiting NF-κB activation and down regulating inflammatory cytokines. Chem. Biol. Interact. 203, 467–479. 22 Boyce BF & Xing L (2007) Biology of RANK, RANKL, and osteoprotegerin. Arthritis Res. Ther. 9. 23 Rachner TD, Khosla S & Hofbauer LC (2011) Osteoporosis: now and the future. Lancet 377, 1276–1287.

Chapter 1

24 Sisay M, Mengistu G & Edessa D (2017) The RANK/RANKL/OPG system in tumorigenesis and metastasis of cancer stem cell: Potential targets for anticancer therapy. Onco. Targets. Ther. 10, 3801–3810. 25 Adhyatmika A, Putri KSS, Beljaars L & Melgert BN (2015) The elusive antifibrotic macrophage. Front. Med. 2, 1–11. 26 Body JJ, Greipp P, Coleman RE, Facon T, Geurs F, Fermand JP, Harousseau JL, Lipton A, Mariette X, Williams CD, Nakanishi A, Holloway D, Martin SW, Dunstan CR & Bekker PJ (2003) A phase I study of AMGN-0007, a recombinant osteoprotegerin construct, in patients with multiple myeloma or breast carcinoma related bone metastases. Cancer 97, 887–92. 27 Higgs JT, Jarboe JS, Lee JH, Chanda D, Lee CM, Deivanayagam C & Ponnazhagan S (2015) Variants of osteoprotegerin lacking TRAIL binding for therapeutic bone remodeling in osteolytic malignancies. Mol. cancer Res. 33, 395–401. 28 Ta HM, Nguyen GTT, Jin HM, Choi J, Park H, Kim N, Hwang H-Y & Kim KK (2010) Structure-based development of a receptor activator of nuclear factor- B ligand (RANKL) inhibitor peptide and molecular basis for osteopetrosis. Proc. Natl. Acad. Sci. 107, 20281–20286. 29 Ashkenazi A, Pitti R, Marsters S, Ruppert S, Donahue C & Moore A (1996) Induction of apoptosis by APO-2 ligand, a new member of the TNF cytokine family. FASEB J. 10. 30 Wiley SR, Schooley K, Smolak PJ, Din WS, Huang CP, Nicholl JK, Sutherland GR, Smith TD, Rauch C, Smith CA & Goodwin RG (1995) Identification and characterization of a new member of the TNF family that induces apoptosis. Immunity 3, 673–682. 31 Van Roosmalen IAM, Quax WJ & Kruyt FAE (2014) Two death-inducing human TRAIL receptors to target in cancer: Similar or distinct regulation and function? Biochem. Pharmacol. 91, 447–456. 32 Van der Sloot AM, Tur V, Szegezdi E, Mullally MM, Cool RH, Samali A, Serrano L & Quax WJ (2006) Designed tumor necrosis factor-related apoptosis-inducing ligand variants initiating apoptosis exclusively via the DR5 receptor. Proc. Natl. Acad. Sci. U. S. A. 103, 8634–8639. 33 Bodmer J-L, Holler N, Reynard S, Vinciguerra P, Schneider P, Juo P, Blenis J & Tschopp J (2000) TRAIL receptor-2 signals apoptosis through FADD and caspase-8. Nat. Cell Biol. 2, 241–243. 34 Reis CR, Van der Sloot AM, Szegezdi E, Natoni A, Tur V, Cool RH, Samali A, Serrano L & Quax WJ (2009) Enhancement of antitumor properties of rhTRAIL by affinity increase toward its death receptors. Biochemistry 48, 2180–2191. 35 Kretz AL, Trauzold A, Hillenbrand A, Knippschild U, Henne-Bruns D, von Karstedt S & Lemke J (2019) Trailblazing strategies for cancer treatment. Cancers (Basel). 11, 1–30. 36 Yuan X, Gajan A, Chu Q, Xiong H, Wu K & Wu GS (2018) Developing TRAIL/TRAIL death receptor-based cancer therapies. Cancer Metastasis Rev. 37, 733–748.

General introduction and scope of the thesis

37 Mahalingam D, N.A.M. Oldenhuis C, Szegezdi E, J. Giles F, G.E. de Vries E, de Jong S & T. Nawrocki S (2011) Targeting Trail Towards the Clinic. Curr. Drug Targets 12, 2079– 2090. 38 Wong SHM, Kong WY, Fang CM, Loh HS, Chuah LH, Abdullah S & Ngai SC (2019) The TRAIL to cancer therapy: Hindrances and potential solutions. Crit. Rev. Oncol. Hematol. 143, 81–94. 39 Yu R, Albarenque SM, Cool RH, Quax WJ, Mohr A & Zwacka RM (2014) DR4 specific TRAIL variants are more efficacious than wild-type TRAIL in pancreatic cancer. Cancer 1 Biol. Ther. 15, 1658–1666. 40 Herbst RS, Eckhardt SG, Kurzrock R, Ebbinghaus S, O‘Dwyer PJ, Gordon MS, Novotny W, Goldwasser MA, Tohnya TM, Lum BL, Ashkenazi A, Jubb AM & Mendelson DS (2010) Phase I dose-escalation study of recombinant human Apo2L/TRAIL, a dual proapoptotic receptor agonist, in patients with advanced cancer. J. Clin. Oncol. 28, 2839–2846.

Chapter 2

TNF-family member Receptor Activator of NF-B (RANK) and RANK-Ligand (RANKL) in bone remodeling

Wim J. Quax, Aart H.G. van Assen and Yizhou Wang

Department of Chemical and Pharmaceutical Biology, Groningen Research Institute of Pharmacy, University of Groningen, A. Deusinglaan 1, 9713 AV Groningen, The Netherlands

Published in IOP Conference Series: Earth and Environmental Science. 2018, 9 p. 012001.

Chapter 2

Abstract

Receptor Activator of NF-κB (RANK) and RANK-Ligand (RANKL) are members of the Tumor Necrosis Factor (TNF)-superfamily involved in bone homeostasis. In a tightly controlled interplay of this receptor and ligand, bone is continuously being remodeled. Several pathological conditions resulting from a misbalance between bone resorption and bone formation have been documented. Most frequently resorption gets the overhand resulting in a lower Bone Mineral Density (BMD), increased fracture risk and reduced mobility of patients. RANKL is expressed on bone producing osteoblasts whereas RANK is expressed on pre-osteoclasts, which can develop in bone resorbing osteoclasts. The binding of RANKL to RANK functions as a trigger for the formation of these bone resorbing osteoclasts. With the development of a monoclonal antibody directed against RANKL a new therapeutic strategy to interfere with bone remodeling has become available some years ago. In this manuscript, we discuss the prospective of interfering with the RANK/RANKL pathway as a therapeutic target for bone diseases. We discuss the role of the soluble receptor osteoprotegerin (OPG) as a therapeutic in bone diseases. Then we focus on the possibility to develop antagonistic and agonistic variants of RANKL based on computational protein design and we discuss the development of antagonistic RANKL variants by changing the stoichiometry of the RANKL molecule.

Keywords: osteoclasts, osteoblasts, TRAIL, OPG, RANKL

RANK and RANKL in bone remodeling

Introduction

The Tumor Necrosis Factor (TNF) - superfamily is a group of cytokines consisting of ligands and receptors whose interactions regulate cell differentiation and controlled cell death (apoptosis) [1]. Thanks to their essential role in cell survival, many TNF-superfamily members are being investigated as potential therapeutic targets for diseases as diverse as cancer [2] and rheumatoid arthritis [3]. TNF-superfamily members Receptor Activator of NF- κB (RANK), RANK Ligand (RANKL) and osteoprotegerin (OPG) have a role in the 2 proliferation of bone cells as they control the balance between bone producing osteoblasts and bone resorbing osteoclasts, thereby forming the human skeleton [4].

From its appearance, the skeleton seems to be a static structure, but bone tissue is continuously being remodeled. The complete human skeleton is renewed in approximately 10 years [5]. Remodeling is necessary to adapt to changes due to mechanical loads [6]. These lead to micro damage, which needs to be repaired to maintain the strength of the skeleton [7]. Differences in inter-individual pressure on the skeleton lead to differences in bone remodeling. Individuals who exercise more and have more physical activity have a lower risk of fractures. Age related thinning of the bone is associated with an increase in fragility of bone, which may result in fractures upon falling. By aging of our population bone diseases become more frequent [8].

Bone diseases can be classified as syndromes with a lowered bone mass, with an increased bone mass and as bone tumors. In osteoporosis, there is an imbalance between osteoblastic and osteoclastic activity in favor of osteoclastic activity, leading to bone fragility and an increased risk of fractures [9]. Paget‘s disease is the most common bone disease in which there is an increased bone mass. It is characterized by the deformation of the bone. Usually, there are one or more focal areas of disorganized bone remodeling. Following osteoporosis, it is the most frequent bone disease [10]. Multiple myeloma is the most common primary malignancy of bone with marrow infiltration of the skeleton, which produces widespread osteolytic bone damage. In multiple myeloma, the balance between osteoblastic and osteoclastic activity is disturbed in favor of osteoclastic activity [11].

Recently, the first biological -denosumab, an antibody directed against RANKL- was introduced and accepted by legal authorities for treating osteoporosis. The monoclonal antibody (mAB) interferes with the RANK/RANKL signaling and thereby inhibits not only osteoclast activity [12] but also bone tumors [13]. Recent discoveries such as the structure of

Chapter 2

RANKL bound to RANK and OPG have given further insight into the molecular mechanisms of RANK/RANKL and OPG in bone remodeling, elucidating key residues interaction of the ligand and the receptors [14–17].

This review will focus on strategies to combat bone diseases making use of the RANK/RANKL pathway. We will discuss the process of RANK/RANKL controlled bone remodeling in the next paragraph and will thereafter discuss mechanisms of action of (new) therapeutic options to treat bone diseases interfering with this pathway.

RANK/RANKL/OPG controlled bone remodeling

Osteoblasts originate from pluripotent mesenchymal cells. Osteoblast cells are responsible for the formation, deposition and mineralization of bone tissue [18]. Bone is an important source for calcium and phosphate and as such important for mineral homeostasis [19]. Parathyroid Hormone (PTH) is a key regulator of calcium metabolism. When blood calcium levels are reduced, PTH is produced and secreted thereby increasing osteoclast mediated bone resorption which increases calcium levels [20].

RANK and its corresponding ligand RANKL play a role in bone homeostasis by tightly controlling the balance between bone resorbing osteoclasts and bone producing osteoblasts. Upon activation by PTH, RANKL is presented on the surface of osteoblasts [5]. RANK is presented on the surface of pre-osteoclasts upon binding of a paracrine factor, Macrophage Colony Stimulating Factor (M-CSF) [21]. Osteoblasts secrete M-CSF, which in turn binds to its corresponding receptor M-CSFR on pre-osteoclasts activating the RANK/RANKL pathway [22].

Interaction between RANKL and RANK leads to the fusion of the osteoclast precursors resulting in multinucleated mature osteoclasts having the capability to resorb bone. Upon RANKL binding to RANK, TNF receptor associated factor-1 (TRAF1), -2, -3, -5, and -6 are recruited to the intracellular domain of RANK [23]. TRAF6 seems to be the most important of these as recruitment leads to the activation of nuclear factor κ (NF-κB) [24]. NF-κB, in turn, regulates the transcriptional activity of osteoclast-specific proteins [25]. OPG acts as a decoy receptor for RANKL thus preventing interaction between RANK and RANKL resulting in less fusion of the OPCs [26]. The RANK-RANKL pathway is important in bone

RANK and RANKL in bone remodeling development in both physiological and pathological situations. Therefore, this signal pathway can be considered as a promising target for bone-related diseases [27].

Interfering with the RANK/RANKL pathway in combatting bone diseases

1. Antagonizing RANKL 2

The natural antagonist for suppressing RANKL titers is OPG. This soluble receptor of the TNF family is present at high concentrations in bone and it plays a natural role in protecting bone mass, hence, its name osteoprotegerin. OPG and RANK bind to slightly different regions of RANKL. RANK distributes its contacts evenly around the DE-loop and A‘A‘‘- loop of RANKL. In contrast, the contacts made by OPG are limited to the E-strand and DE- loop region of RANKL, almost completely avoiding the A‘A‘‘-loop region [14]. OPG exerts its function as a decoy receptor by blocking residues essential for RANKL to bind RANK [28]. Initial trials to use OPG as a therapeutic have failed due to the poor pharmacokinetic and pharmacodynamic properties and due to interference with the heparin binding domain in mice [29]. As a result, numerous fusion proteins containing a variety of residues of human OPG fused to human Fc fragments were tested and some were found to be 200 times more active than full-length OPG in vivo. A recombinant Fc-OPG, AMGN-0007, was in phase I clinical study for osteolytic bone metastasis and was discontinued due to the potential safety risk due to immune response [30]. The human RANKL binding domain of RANK fused Fc fragment (RANK-Fc) was also found to be more effective than native OPG. However, in primates, following repeated dosing of human RANK•Fc, inactivating autoantibody titers against RANK were detected and the development was discontinued. Subsequently, monoclonal antibodies were selected and one monoclonal antibody obtained from immunization of the IgG2 XenoMouse emerged as a potent inhibitor of RANKL induced osteoclast formation. The resulting monoclonal antibody (an IgG2κ antibody) was originally designated AMG 162 and is now known as denosumab. Alternatively, peptide mimics of OPG (OP3-4 peptide) [31], RANK [32] and the tumor necrosis factor (TNF) receptor (WP9QY peptide) [33] were also developed. Although they showed inhibitory activity against the RANKL-induced osteoclastogenesis, further research of them is needed before these can be applied for therapeutic treatment.

Chapter 2

The use of OPG in bone malignancies is limited as OPG also functions as a decoy receptor for Tumor Necrosis Factor Related Apoptosis Inducing Ligand (TRAIL) as well, preventing the apoptosis of tumor cells. Therefore, structure-based OPG mutants have been designed that still do antagonize RANKL inhibiting osteoclastogenesis, but which do not bind TRAIL and therefore do not interfere with tumor apoptosis [34]. TRAIL cancer therapy has been shown to be effective. Recombinant human TRAIL variants with a decreased affinity for OPG have been investigated and this research was done to overcome TRAIL resistance when applied in the bone environment [35].

2. Antagonizing RANK

One other approach to target bone diseases is to target and antagonize RANK directly. The advantage of targeting the receptor over targeting the ligand RANKL can be found in the direct inactivation of the receptor. Although denosumab titrates away RANKL, it does not block the receptor. Furthermore, the administration of antibodies such as denosumab carries the risk of immune reactions [36]. Compared with antibody, the administration of structure- based protein mutants most likely triggers the autoimmune system with less impact, as the mutations in the proteins involve less residues. Therefore, the design of antagonistic proteins based on the RANKL seems to be an attractive approach.

The feasibility to design variants of TNF-ligands with altered binding properties was first shown for TRAIL [37]. In many cancer cells, apoptosis seems to occur primarily via only one of the two TRAIL death receptors and the introduction of receptor selectivity is a way to create more potent TRAIL agonists. With computational protein design, it is possible to predict protein segments and amino acids important for binding, affinity and strength of the ligand-receptor complexes [38]. All residues in the receptor binding interface can be mutated into any possible other amino acids. A set of predicted energetic values for the wild type TRAIL - receptor complex formation was compared with the obtained energetic values after mutagenesis. The change in binding energy at every residue can be used as a prediction for improved or decreased binding. Afterward predicted variants were expressed, purified and screened for receptor selectivity by surface plasmon resonance (SPR). TRAIL variants selective for a specific TRAIL death receptor could be obtained this way [37,39,40].

RANK and RANKL in bone remodeling

Due to the high homology among TNF ligands and their cognate receptors, an alternative strategy to predict variants with agonistic or antagonistic properties is to compare different TNF-superfamily members; interaction domains and interacting residues do show similarity among TNF ligands and receptors. One of these interaction loops is the so-called DE-loop. There is a conserved tyrosine in the DE-loop of all TNF-ligands except CD40L and RANKL. Shibata and others found that mutations in this hydrophobic residue of the DE-loop in TNF-α yielded TNF-receptor 1 selective antagonist [41]. The 3D structure of the complex between RANK and RANKL suggests that hydrophilic interactions are predominant among all the 2 surface interactions between the DE-loop of RANKL and RANK. However, RANKL mutation at the equivalent residue 248 from isoleucine to aspartate resulted in an eightfold lower activity [16]. Then, the effect of further mutations at position I248 in the DE-loop of murine RANKL on the interaction of RANKL with RANK was investigated. Two single mutants, RANKL I248Y and I248K were found to compete with wild-type RANKL binding to RANK while reducing wild-type RANKL-induced osteoclastogenesis [42]. These mutations suggest that the DE-loop of RANKL is important for osteoclastogenesis and two newly formed mutants, RANKL I248Y and I248K, can offer a starting point for novel therapeutic proteins in new osteoporosis treatments (Figure 1).

Figure 1. Structural overview of the area surrounding the DE loop of (A) Refined structure of RANKL (orange) - RANK (green) complex. The DE loop of RANKL is shown in yellow. The figure was derived from the

Chapter 2 published structure of RANK:RANKL complex (PDB ID: 4GIQ). (B) Close-up view of residues near I248 in the DE-loop of RANKL changes in the stoichiometry of the receptor.

3. Changes in the stoichiometry of the receptor

An important characteristic of the TNF superfamily is the multimeric organization of receptors and ligands. For RANK and RANKL a trimeric RANK receptor binds to a trimeric RANKL ligand; this is needed for the biological effect [43]. RANK trimerizes through hydrophobic interactions at the core of the trimer, leading to the assembly of a homotrimer [16]. However, TNF ligands can also bind to their corresponding monomeric and dimeric receptor subunits. It was found that there is a high affinity for the first binding to a monomeric subunit of the receptor. Using Surface Plasmon Resonance a high affinity binding between RANKL and the first monomeric subunit of RANK was demonstrated. A dissociation 5 -1 -1 -4 -1 -1 constant (KD) of 0.67 nM with ka=4.9 × 10 M s and kd=3.3 × 10 M s could be calculated [44].

The development of RANKL variants occupying only one monomer of the RANK receptor obstructing the binding to three monomeric RANK receptors will have an antagonistic effect on osteoclast formation [45]. By creating RANKL variant that only has a single intact receptor binding interface, one RANK receptor might still be bound but additional receptor molecules can no longer be recruited to form the biologically active trimeric receptor complex. This leaves less receptor molecules available to trimerize. Thus, these variants do not only block RANK-RANKL interaction by competition with trimeric RANKL but also leave less RANK receptor molecules available on the cell surface.

Interestingly, monoclonal antibodies, such as denosumab, bind to trimeric TNF family members mostly in a 3:2 complex, meaning 3 denosumab antibody molecules bind two RANKL molecules (trimeric), resulting in complicated kinetics [46]. Compared with the antibodies, structure-based variants binding in a 1:1 complex might exhibit simpler kinetics resulting in a reduction of the risk of side effects.

Conclusion

RANK and RANKL in bone remodeling

The TNF-superfamily members RANKL and RANK are important for bone remodeling. Their roles in osteoclast derived bone resorption have been the subject of study for a long time. With the development of a monoclonal antibody derived against RANKL, a new therapeutic approach to combat bone diseases became available. In the review we presented three ways to develop new possible therapeutics to interfere with RANK/RANKL signaling. First, we focused on the possibility to use OPG, the natural decoy receptor for RANKL. Then we discussed the development of RANKL variants with antagonistic properties, based on computational design using conserved domains in the TNF-superfamily. Finally, we discussed 2 antagonistic molecules interfering with the trimerization of RANK, a conformation essential for signal transduction. Interfering with the RANK/RANKL pathway is a promising strategy to develop therapeutics to combat bone diseases.

References

1 Aggarwal BB (2003) Signalling pathways of the TNF superfamily: A double-edged sword. Nat. Rev. Immunol. 3, 745–756. 2 Azijli K, Weyhenmeyer B, Peters GJ, De Jong S & Kruyt FAE (2013) Non-canonical kinase signaling by the death ligand TRAIL in cancer cells: Discord in the death receptor family. Cell Death Differ. 20, 858–868. 3 Vinay DS & Kwon BS (2012) Targeting TNF superfamily members for therapeutic intervention in rheumatoid arthritis. Cytokine 57, 305–312. 4 Yasuda H (2013) RANKL, a necessary chance for clinical application to osteoporosis and cancer-related bone diseases. World J. Orthop. 4, 207. 5 Manolagas SC (2000) Birth and death of bone cells: basic regulatory mechanisms and implications for the pathogenesis and treatment of osteoporosis. Endocr. Rev. 21, 115–37. 6 Cameron JA, Milner DJ, Lee JS, Cheng J, Fang NX & Jasiuk IM (2013) Employing the biology of successful fracture repair to heal critical size bone defects. Curr. Top. Microbiol. Immunol. 367, 113–132. 7 Eriksen EF (2010) Cellular mechanisms of bone remodeling. Rev. Endocr. Metab. Disord. 11, 219–227. 8 Brent Richards J, Zheng HF & Spector TD (2012) Genetics of osteoporosis from genome- wide association studies: Advances and challenges. Nat. Rev. Genet. 13, 576–588. 9 Davidson MR (2003) Pharmacotherapeutics for osteoporosis prevention and treatment. J. Midwifery Womens. Health 48, 39–52. 10 Ralston SH (2013) Paget‘s Disease of Bone. N. Engl. J. Med. 368, 644–650.

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11 Tosi P, Tsuda E, Goto M, Mochizuki S, Yano K, Kobayashi F, Morinaga T, van Tur V, Szegezdi E, Mullally MM, Cool RH, der Sloot AM, Samali A & Sci USA (2006) Diagnosis and Treatment of Bone Disease in Multiple Myeloma: Spotlight on Spinal Involvement. Scentifica 104546 Epub Isol. a Nov. cytokine from Hum. fibroblasts that specifically Inhib. Osteoclastogenes. Biochem Biophys Res Commun Des. tumor necrosis factorrelated apoptosisinducing ligand Var. Initiat. apoptosi 234, 137– 142. 12 Brown JP, Reid IR, Wagman RB, Kendler D, Miller PD, Jensen JEB, Bolognese MA, Daizadeh N, Valter I, Zerbini CAF & Dempster DW (2014) Effects of Up to 5 years of denosumab treatment on bone histology and histomorphometry: The FREEDOM study extension. J. Bone Miner. Res. 29, 2051–2056. 13 Shapiro CL, Moriarty JP, Dusetzina S, Himelstein AL, Foster JC, Grubbs SS, Novotny PJ & Borah BJ (2018) Cost-effectiveness analysis of monthly zoledronic acid , zoledronic acid every 3 months , and monthly denosumab in women with breast cancer and skeletal metastases : CALGB 70604 ( Alliance ). J. Clin. Oncol. 35, 3949–3956. 14 Nelson CA, Warren JT, Wang MW, Teitelbaum SL, Fremont DH & Engage R (2012) RANKL employs distinct binding modes to enage RANK and the osteoprotegerin decoy receptor. Structure 20, 1971–1982. 15 Liu C, Walter TS, Huang P, Zhang S, Zhu X, Wu Y, Wedderburn LR, Tang P, Owens RJ, Stuart DI, Ren J & Gao B (2010) Structural and Functional Insights of RANKL-RANK Interaction and Signaling. J. Immunol. 184, 6910–6919. 16 Lam J, Nelson CA, Ross FP, Teitelbaum SL & Fremont DH (2001) Crystal structure of the RANCE/RANKL cytokine reveals determinants of receptor ligand specificity. J. Clin. Investig. 108, 971–979. 17 Luan X, Lu Q, Jiang Y, Zhang S, Wang Q, Yuan H, Zhao W, Wang J & Wang X (2016) Crystal structure of human RANKL complexed with its decoy receptor opsteoprotegerin. J. Immunol. 189, 245–252. 18 Phan TC, Xu J & Zheng MH (2004) Interaction between osteoblast and osteoclast: impact in bone disease. Histol Histophathol 19, 1325–1344. 19 Bergwitz C & Jüppner H (2010) Regulation of Phosphate Homeostasis by PTH, Vitamin D, and FGF23. Annu. Rev. Med. 61, 91–104. 20 Gaffney-Stomberg E, Lutz LJ, Rood JC, Cable SJ, Pasiakos SM, Young AJ & McClung JP (2014) Calcium and vitamin D supplementation maintains parathyroid hormone and improves bone density during initial military training: a randomized, double-blind, placebo controlled trial. Bone, 46–56. 21 Lagasse E & Weissman IL (1997) Enforced expression of Bcl-2 in monocytes rescues macrophages and partially reverses osteopetrosis in op/op mice. Cell 89, 1021–1031. 22 Boyce BF, Rosenberg E, de Papp AE & Duong LT (2012) The osteoclast, bone remodelling and treatment of metabolic bone disease. Eur. J. Clin. Invest. 42, 1332–1341. 23 Galibert L, Tometsko ME, Anderson DM, Cosman D & Dougall WC (1998) The involvement of multiple tumor necrosis factor receptor (TNFR)- associated factors in the signaling mechanisms of receptor activator of NF-kappaB, a member of the TNFR

RANK and RANKL in bone remodeling

superfamily. J Biol Chem 273, 34120–34127. 24 Darnay BG, Besse A, Poblenz AT, Lamothe B & Jacoby JJ (2007) TRAFs in RANK signaling. Adv. Exp. Med. Biol. 597, 152–159. 25 Honma M, Ikebuchi Y, Kariya Y & Suzuki H (2014) Regulatory mechanisms of RANKL presentation to osteoclast precursors. Curr. Osteoporos. Rep. 12, 115–120. 26 Simonet WS, Lacay DL, Dunstan CR, Kelley M & Chang MS (1997) Lüthy, R., . Osteoprotegerin: a novel secreted protein involved in the regulation of bone density. Cell 89, 309–319. 27 Tanaka S, Nakamura K, Takahasi N & Suda T (2005) Role of RANKL in physiological 2 and pathological bone resorption and therapeutics targeting the RANKL-RANK signaling system. Immunol. Rev. 208, 30–49. 28 Luan X, Lu Q, Jiang Y, Zhang S, Wang Q, Yuan H, Zhao W, Wang J & Wang X (2012) Crystal Structure of Human RANKL Complexed with Its Decoy Receptor Osteoprotegerin. J. Immunol. 189, 245–252. 29 Bekker PJ, Holloway D, Nakanishi a, Arrighi M, Leese PT & Dunstan CR (2001) The effect of a single dose of osteoprotegerin in postmenopausal women. J. Bone Miner. Res. 16, 348–60. 30 Body JJ, Greipp P, Coleman RE, Facon T, Geurs F, Fermand JP, Harousseau JL, Lipton A, Mariette X, Williams CD, Nakanishi A, Holloway D, Martin SW, Dunstan CR & Bekker PJ (2003) A phase I study of AMGN-0007, a recombinant osteoprotegerin construct, in patients with multiple myeloma or breast carcinoma related bone metastases. Cancer 97, 887–92. 31 Heath DJ, Vanderkerken K, Cheng X, Gallagher O, Prideaux M, Murali R & Croucher PI (2007) An osteoprotegerin-like peptidomimetic inhibits osteoclastic bone resorption and osteolytic bone disease in myeloma. Cancer Res. 67, 202–208. 32 Ta HM, Nguyen GTT, Jin HM, Choi J, Park H, Kim N, Hwang H-Y & Kim KK (2010) Structure-based development of a receptor activator of nuclear factor- B ligand (RANKL) inhibitor peptide and molecular basis for osteopetrosis. Proc. Natl. Acad. Sci. 107, 20281–20286. 33 Aoki K, Saito H, Itzstein C, Ishiguro M, Shibata T, Blanque R, Mian AH, Takahashi M, Suzuki Y, Yoshimatsu M, Yamaguchi A, Deprez P, Mollat P, Murali R, Ohya K, Horne WC & Baron R (2006) A TNF receptor loop peptide mimic blocks RANK ligand- induced signaling, bone resorption, and bone loss. J. Clin. Invest. 116, 1525–1534. 34 Higgs JT, Jarboe JS, Lee JH, Chanda D, Lee CM, Deivanayagam C, Honma M, Ikebuchi Y, Kariya Y & Suzuki H (2014) Variants of Osteoprotegerin Lacking for Therapeutic Bone Remodeling in Osteolytic Malignancies. Mol Cancer Res Jan 30 pii molcanres0492 Epub ahead print Regul. Mech. Rank. Present. to osteclast precursors Curr Osteoporos Rep Mar 12, 115–120. 35 Bosman MCJ, Reis CR, Schuringa JJ, Vellenga E & Quax WJ (2014) Decreased affinity of recombinant human tumor necrosis factor-related apoptosis-inducing ligand (rhTRAIL) D269H/E195R to osteoprotegerin (OPG) overcomes trail resistance mediated by the bone microenvironment. J. Biol. Chem. 289, 1071–1078.

Chapter 2

36 Hansel TT, Kropshofer H, Singer T, Mitchell JA & George AJ (2010) The safety and side effects of monoclonal antibodies. Nat. Rev. Drug Discov., 325-338-NaN-0. 37 Van der Sloot AM, Tur V, Szegezdi E, Mullally MM, Cool RH, Samali A, Serrano L & Quax WJ (2006) Designed tumor necrosis factor-related apoptosis-inducing ligand variants initiating apoptosis exclusively via the DR5 receptor. Proc. Natl. Acad. Sci. U. S. A. 103, 8634–8639. 38 Sloot van der AM & Quax WJ (2011) Computational design of TNF ligand-based protein therapeutics. Adv Exp Med Biol, 521–534. 39 Reis CR, Szegezdi E, Natoni A, Tur V, Cool RH, Samali A, Serrano L & Quax WJ (2009) Enhancement of Antitumor Properties of rhTRAIL by Affinity Increase toward Its Death Receptors. Biochemistry 48, 2180–2191. 40 Reis CR, Natoni A, Szegezdi E, Setroikromo R & Meijer M (2010) Sloot, van der, A. M., . Rapid and efficient cancer cell killing mediated by high-affinity death receptor homotrimerizing TRAIL variants. Cell Death Dis. 101038cddis61 1. 41 Shibata H, Yoshioka Y, Ohkawa A, Minowa K, Mukai Y, Abe Y, Taniai M, Nomura T, Kayamuro H, Nabeshi H, Sugita T, Imai S, Nagano K, Yoshikawa T, Fujita T, Nakagawa S, Yamamoto A, Ohta T, Hayakawa T, Mayumi T, Vandenabeele P, Aggarwal BB, Nakamura T, Yamagata Y, Tsunoda S, Kamada H & Tsutsumi Y (2008) Creation and X-ray structure analysis of the tumor necrosis factor receptor-1-selective mutant of a tumor necrosis factor-alpha antagonist. J. Biol. Chem. 283, 998–1007. 42 Wang Y, van Assen AHG, Reis CR, Setroikromo R, van Merkerk R, Boersma YL, Cool RH & Quax WJ (2017) Novel RANKL DE-loop mutants antagonize RANK-mediated osteoclastogenesis. FEBS J. 284, 2501–2512. 43 Douni E, Rinotas V, Makrinou E, Zwerina J, Penninger JM, Eliopoulos E, Schett G & Kollias G (2012) A RANKL G278R mutation causing osteopetrosis identifies a functional amino acid essential for trimer assembly in RANKL and TNF. Hum. Mol. Genet. 21, 784–798. 44 Reis CR, van Assen AH, Quax WJ & Cool RH (2011) Unraveling the Binding Mechanism of Trivalent Tumor Necrosis Factor Ligands and Their Receptors. Mol. Cell. Prtoeomics, 0–1. 45 Warren JT, Nelson CA, Decker CE, Zou W, Fremont DH & Teitelbaum SL (2004) Manipulation of receptor oligomerization as a strategy to inhibit signaling by TNF superfamily members. Sci Signal 19ra80 doi 101126scisignal948 7. 46 Arthur KK, Gabrielson JP, Hawkins N, Anafi D, Wypych J, Nagi A, Sullivan JK & Bondarenko P V. (2012) In vitro stoichiometry of complexes between the soluble RANK ligand and the monoclonal antibody denosumab. Biochemistry 51, 795–806.

Chapter 3

Novel RANKL DE-loop mutants antagonize RANK- mediated osteoclastogenesis

Yizhou Wang*, Aart H.G. van Assen*, Carlos R. Reis, Rita Setroikromo, Ronald van Merkerk, Ykelien L. Boersma, Robbert H. Cool and Wim J. Quax#

Department of Chemical and Pharmaceutical Biology, Groningen Research Institute of Pharmacy, University of Groningen, A. Deusinglaan 1, 9713 AV Groningen, The Netherlands

*both authors equally contributed to this manuscript

Published in FEBS. J. 2017, 284, 2501-2512.

Chapter 3

Abstract Bone is a dynamic tissue that is maintained by continuous renewal. An imbalance in bone resorption and bone formation can lead to a range of disorders, such as osteoporosis. The Receptor Activator of NF-κB (RANK)-RANK ligand (RANKL) pathway plays a major role in bone remodeling. Here, we investigated the effect of mutations at position I248 in the DE- loop of murine RANKL on the interaction of RANKL with RANK, and subsequent activation of osteoclastogenesis. Two single mutants, RANKL I248Y and I248K, were found to maintain binding and have the ability to reduce wild type RANKL-induced osteoclastogenesis. The generation of RANK-antagonists is a promising strategy for the exploration of new therapeutics against osteoporosis.

Keywords: antagonist, bone homeostasis, osteoporosis, RANK, RANKL

RANKL variants antagonizing osteoclastogenesis

Introduction

Bone is a dynamic tissue that has multiple functions, including support of muscles, protection of vital organs, and fostering hematopoietic marrow [1,2]. Under normal conditions, bone homeostasis is achieved by continuous renewal, mediated by two processes: bone resorption by osteoclasts and bone formation by osteoblasts [3]. An imbalance in bone resorption and formation can cause bone-associated diseases: when the activity of osteoclasts exceeds that of osteoblasts, osteoporosis will be developed. In contrast, osteopetrosis will occur when osteoblastic activity exceeds [4].

Osteoclastogenesis is regulated by a cytokine system, consisting of three major proteins: 3 receptor activator of nuclear factor-κB (RANK), RANK-ligand (RANKL) and osteoprotegerin (OPG) [5]. The binding between RANKL on the surface of osteoblast cells and the RANK on osteoclast precursor cells will trigger activation of several transcription factors and enzymes that induce osteoclast maturation and bone resorption. OPG is a soluble decoy receptor, acting as a natural antagonist of RANKL [6]. The RANK-RANKL pathway plays an important role in both physiological and pathological bone development. Therefore, this signaling pathway is a promising target in bone-related diseases [3].

RANKL is a member of the Tumor Necrosis Factor (TNF) superfamily, a group of cytokines involved in cell proliferation and cell death [7]. The TNF-superfamily consists of 19 multimeric ligands interacting with cognate receptor molecules; most of them require trimerization to initiate their signaling cascade [8]. Ligands belonging to the TNF superfamily are mostly type II transmembrane glycoproteins, containing a C-terminal, receptor-interacting ectodomain, a transmembrane domain, and an N-terminal intracellular tail [4]; the extracellular domain can be either cleaved off by the proteolytic activity of metalloproteases or produced by alternative splicing [9,10].

3D structures of TNF-α, TRAIL and RANKL alone and in complex with their respective receptors have revealed very similar overall structures that comprise unique conserved elements involved in receptor binding [11–18]. One of these elements is the so-called DE- loop. There is a conserved tyrosine in the DE-loop of all TNF ligands, with the exception of an arginine in CD40L and an isoleucine in RANKL. Interestingly, variants of human TNF-α with mutated DE-loop residues including the semi-conserved residue Y87 were shown to be receptor antagonists: some mutants selectively bound to human TNF-receptor 1(TNF-R1) and not TNF-receptor 2 (TNF-R2), while inhibiting wild type TNF-α-mediated effects via TNF-R

Chapter 3

1 [13]. Comparing the 3D structure of the antagonistic TNF-R1-selective mutant with that of wild-type TNFα, it was concluded that the Y87H mutation changed the binding mode of the DE-loop to TNF-R1 from a hydrophobic to an electrostatic interaction [13]. In murine RANKL, mutation of the equivalent residue I248 to aspartate resulted in an eight-fold lower

ED50 [12]. In contrast, another 3D structure has led to the suggestion that the DE loop may not be critical for mRANKL-mRANK binding [11,19].

Here we have investigated the effect of mutations of the I248 residue in the mRANKL DE- loop on the binding to mRANK and on subsequent osteoclastogenesis. Our results show that RANKL mutants I248Y and I248K have the ability to reduce RANKL-induced osteoclastogenesis. Thus, mutagenesis at position I248 of the DE-loop region can form the basis of a general strategy to create RANK-antagonists for the RANKL-RANK pathway, paving the way to novel osteoporosis treatments.

Results

In silico mutagenesis of mRANKL demonstrates importance of position I248

Several 3D structures of mRANKL have been described previously [4,11,12,20,21]. The 3D structure of mRANK in complex with mRANKL (Protein Data Bank accession code 4GIQ) was used for in silico mutagenesis at position I248 in order to estimate differences in ΔΔGi binding to RANK between RANKL mutants and wild type RANKL (WT RANKL) (Fig. 1A, B). A similar strategy has allowed us in the past to successfully generate variants of hTRAIL with desired properties, such as enhancement of affinity and change of receptor selectivity [22–24]. As shown in Fig. 1B, the RANK residues surrounding I248 of RANKL are hydrophilic, including D49, T50, N52, E53 and E54, suggesting that the surface interaction between the DE-loop of RANKL and RANK is predominantly hydrophilic. This is different from the binding between TNF and TNF-R1, where Y87 of TNF is buried in a hydrophobic ―pocket‖ of the TNF-R1. The importance of RANKL residue I248 for the interaction with RANK was investigated by in silico mutagenesis. The effects of variation at position 248 of

RANKL on the calculated ΔΔGi are shown in Fig. 1C. Overall, our data indicate that substitution by other amino acids results in a strong effect on the binding of RANKL to RANK, either positive or negative, suggesting that this residue is indeed important for binding. Given the overall estimated effects on binding energies between RANKL and RANK,

RANKL variants antagonizing osteoclastogenesis we decided to focus on and construct a subset of RANKL mutants. I248Y was chosen because of the conserved tyrosine at the same position in the DE-loop of TNF-ligands and its calculated large difference in ΔΔGi (Fig. 1C); I248K because this mutation also has a predicted large effect on the ΔΔGi, plus it is homologous to the arginine found at this position in TNF ligand family member CD40L; and finally I248D was chosen as it was previously reported to have an eight-fold lower ED50 compared to WT RANKL [12]. As the interaction between the DE-loop of RANKL and RANK is mainly hydrophilic, all the hydrophobic mutations including I248W were not taken into consideration.

Fig 1. Structural representation of the binding interface of the RANKL DE loop with RANK and binding energy predictions for I248 mutants, made using Discovery Studio 4.5 A) Refined structure of RANKL (orange) in complex with RANK (shown in hydrophilicity contact surface). The various strands and loops of RANKL are shown in orange and the DE loop of RANKL is shown in yellow. The model was derived from the 3D structure of the murine RANKL-RANK complex (PDB code 4GIQ). B) Detailed view of RANK residues in close proximity to residue I248 of RANKL. C) Predicted differences in binding energy (ΔΔGi) of I248 variants binding to RANK when compared with WT RANKL. The change in energy is measured in kcal/mol. A negative

ΔΔGi value indicates an improvement in receptor binding, whereas a positive ΔΔGi value indicates a deterioration in receptor binding.

Chapter 3

RANKL mutations I248Y and I248K show increased binding affinity to RANK

After expression, purification and characterization of WT RANKL and mutants, we determined their affinities to RANK by surface plasmon resonance (SPR). Using a CM4 sensor chip and a low density of RANK-Fc (< 60 response units [RU]), we were able to measure the interaction between one trimeric RANKL molecule binding to one RANK-Fc monomer [8]. Indeed, the sensorgrams for WT RANKL, I248Y, I248K and I248D all show a ~1:1 binding ratio (varying between 0.9-1.2) (Fig. 2). Hence, the data could be fitted with a 1:1 Langmuir fitting model and the kinetic parameters were calculated [8]. As shown in Table 1, I248Y and I248K showed approximately three- to four-fold higher affinities to the target receptor in comparison to WT RANKL. This was mainly caused by an increase in the association rate constant (ka). The dissociation rate constants (kd) of I248Y and I248K were comparable to WT RANKL. Mutant I248D showed a lower affinity to RANK-Fc compared to WT RANKL, which is mainly due to a much higher dissociation rate. Taken together, these results are consistent with the previous in silico predictions and they further confirm that the I248 residue indeed plays an important role in RANKL-RANK binding.

Table 1: Binding kinetics of the RANKL variants and WT RANKL to murine RANK-Fc as measured by Surface Plasmon Resonance

-6 -1 -1 4 -1 ka·10 (M s ) kd·10 (s ) KD (pM)

WT 4.3 ± 1.5 1.5 ± 0.4 38 ± 2

I248Y 15.7 ± 7.7 1.3 ± 0.7 8 ± 3

I248K 17.1 ± 1.1 1.5 ± 0.4 9 ± 2

I248D 8.0 ± 0.9 4.2 ± 0.6 53 ± 7

RANKL variants antagonizing osteoclastogenesis

Fig 2. Typical SPR sensorgrams obtained for binding between RANK-Fc and RANKL variants. The sensorgrams are obtained at receptor density <60 RU to establish a 1:1 binding ratio. Depicted are A) WT RANKL, B) RANKL variant I248Y, C) RANKL variant I248K and D) RANKL variant I248D. Injection of RANKL (0-20.48 nM) is marked with a double-headed arrow. After injection a buffer effect is visible for the higher concentrations used. Dissociation is followed for 1000 s.

RANKL mutants compete for binding of WT RANKL to RANK and form high order complexes with their receptor

To further assess whether the mutants compete with WT RANKL for binding, we performed a competitive ELISA assay, in which wells coated with RANK-Fc were incubated with both WT RANKL and RANKL variants. Our competitive ELISA results (Fig. 3) showed that increasing concentrations of both I248K and I248Y can efficiently compete with WT RANKL for RANK-Fc binding at physiological concentrations. However, RANKL I248D could only partially compete with WT RANKL at concentrations over 1000 nM, which is in accordance with the lowered affinity of RANKL I248D to RANK-Fc compared to WT RANKL.

Chapter 3

Fig 3. Competitive ELISA performed with 10 nM sfGFP-WT RANKL and increasing concentrations (0-8000 nM) of variants I248Y (red circles), I248K (blue squares) and I248D (orange triangles). Bound sfGFP-WT RANKL was detected by incubation with a murine anti-GFP antibody and a secondary anti-mouse HRP- conjugated antibody. The signal was quantified using the One-step Turbo TMB reagent and absorbance was measured at 450 nm using a spectrophotometer. The percentage of sfGFP-WT RANKL bound was measured relative to the binding of 10 nM sfGFP WT RANKL alone. The log concentration of the RANKL variants is displayed on the x-axis. The error bars reflect the standard deviation (SD) of three independent experiments.

Given that signaling of several TNF cytokines has been shown to require receptor oligomerization, we also tested whether mutants I248Y, I248K and I248D could form multimeric complexes with RANK using high densities of RANK-Fc in SPR. As shown in Fig. 4, using the number of RU of bound RANK-Fc we could estimate the ratio of complex formation (the number of trimeric RANKL units bound to monomeric RANK-Fc) using equation 1 (see Experimental Procedures). A binding ratio of 1:3.07 ± 0.01 was found for WT RANKL. For RANKL mutants I248Y, I248K and I248D, mean binding ratios were 1:3.03 ± 0.04, 1:2.99 ± 0.02 and 1:3.12 ± 0.01, respectively. These results imply that the mutants, as WT RANKL, form a trimer-trimer complex with the RANK receptor.

RANKL variants antagonizing osteoclastogenesis

Fig 4. Typical SPR sensorgrams to check trimer-trimer binding of RANKL and RANK-Fc. Depicted are the injection phases of RANK-Fc followed by the injection phase of WT RANKL or mutants. Regeneration (reg.) is visible at the end. With the number of response units (RU) bound, the ratio of complex formation, i.e., the number of trimeric RANKL units bound to monomeric RANK-Fc was estimated. Shown are the injections of A) WT RANKL, B) I248Y, C) I248Y and D) I248D, leading to binding to RANK-Fc.

RANKL mutants antagonize the biological activity of WT RANKL

We next tested the effect of RANKL mutants I248D, I248K and I248Y on osteoclastogenesis by assessing their ability to induce multinucleation (three or more nuclei per cell) in osteoclast precursor murine RAW 264.7 cells and by testing their capability to inhibit WT RANKL (Fig. 5A). Microscopic photographs of osteoclasts from different treatment with RANKL variants (50 ng/mL) only, WT RANKL (50 ng/mL) or a combination of both are shown in Fig. 5A. Single treatment with WT RANKL caused osteoclast formation to a large extent and induced formation of giant multinucleated cells (two or more clusters of multinuclei per cell) which can cover large areas of the wells. RANKL variants themselves were also capable of inducing osteoclast formation, although the number of osteoclasts formed was lower than that induced

Chapter 3 by WT RANKL. Competition of either RANKL I248Y or I248K with 50 ng/mL WT RANKL led to a reduction in both number and size of osteoclasts, while the competitive effect of RANKL I248D was less than that of I248Y and I248K. Importantly, single treatment with each of the three mutants induced less osteoclastogenesis compared to treatment with WT RANKL at all concentrations measured (Fig. 5B, C and D). The high affinity mutants I248Y and I248K reached a maximum level at approximately 50 ng/mL, which is 70 and 80% of that of WT RANKL, respectively (Fig. 5B, C). In contrast, the low affinity mutant I248D only reached up to 40% of the osteoclastogenic effect of WT RANKL even at the highest concentration of 150 ng/mL (Fig. 5D). Co-treatment of RAW 264.7 cells with WT RANKL and high affinity mutants I248Y or I248K led to a reduction in the level of osteoclastogenesis by 30-40% already at low concentration of mutant RANKL, with no further reduction at higher concentrations (Fig. 5B, C). In contrast, the low affinity mutant I248D only showed a reduction of the osteoclastic potential of WT RANKL at high concentrations (>50 ng/mL) (Fig. 5D).

Fig 5. Relative number of osteoclasts obtained after treatment of murine RAW 264.7 cells with RANKL variants, WT RANKL or a combination of both. A) Microscope images and absolute numbers of normal and giant osteoclasts from different treatments with RANKL variants (50 ng/mL) only, WT RANKL (50 ng/mL) or a combination of both at 200× magnification. The yellow bars represent the absolute numbers of normal osteoclasts, while the green bars represent the absolute numbers of giant osteoclasts; B) Relative number of osteoclasts for variant I248Y compared to WT RANKL; C) Relative number of osteoclasts for variant I248K compared to WT RANKL; D) Relative number of osteoclasts for variant I248D compared to WT RANKL. The red bars represent the relative numbers of osteoclasts treated with RANKL variant alone, and the blue bars represent the combination treatment of RANKL variants with WT RANKL (50 ng/mL). The number of osteoclasts in the well treated with 50 ng/mL WT RANKL only was set to 100%. Significance was calculated using a Student‘s t-test compared to untreated cells: (*) is p<0.05 and (**) is p<0.001. The error bars reflect the SD of three independent experiments in triplicate. For WT RANKL alone the error bar is the average SD over all separate experiments.

RANKL variants antagonizing osteoclastogenesis

Chapter 3

Does exchange of RANKL subunits play a role in inhibition of WT RANKL induced osteoclastogenesis?

In our studies, we showed inhibition of WT RANKL-induced osteoclastogenesis in the murine RAW 264.7 cell line by RANKL variants I248K and I248Y (Fig. 5). Although they themselves can also cause osteoclast formation, the numbers of osteoclasts are lower than those of WT RANKL (50 ng/mL). The increased affinities of these mutants can explain the results of the inhibition experiments: both mutants showed higher affinities to RANK-Fc than WT RANKL (Fig. 2), which can make them compete efficiently with WT RANKL to occupy RANK and induce less osteoclastogenesis. An alternative explanation may be that the subunits of RANKL are interchanged, allowing the formation of heterotrimeric RANKL molecules that are no longer able to activate RANK. To confirm or refute this hypothesis, we mixed purified sfGFP-WT RANKL with WT RANKL at the equimolar ratio and incubated this for either 24h at 37°C or 44h at 4°C. The protein samples were loaded onto a size exclusion column while the absorbance was followed at 280 and 475/488 nm (Fig. 6). The trimeric fusion protein sfGFP-WT RANKL with its higher molecular weight eluted at approximately 12 mL showing absorbance at both wavelengths, whereas WT RANKL eluted at approximately 14.8 mL, showing only absorbance at 280 nm. Mixing of the two trimeric proteins did not result in shifting peaks, demonstrating that no exchange occurred during the incubation (Fig. 6).

RANKL variants antagonizing osteoclastogenesis

Fig 6. Size exclusion chromatography for the determination of the potential exchange of RANKL subunits. A) Chromatogram of WT RANKL at 0 h; B) Chromatogram for a mixture of WT RANKL and sfGFP-WT RANKL at concentrations of 12 μM each at 0 h; C) Chromatogram for a mixture of WT RANKL and sfGFP-WT RANKL after incubation for 24 h at 37°C and D) for 44 h at 4°C. Elution was monitored in mAU at 280 nm (all proteins), 475 nm and 488 nm (sfGFP fusion proteins).

Discussion

Bone homeostasis is achieved by continuously renewing the tissue [6]. Loss of bone remodeling homeostasis can lead to a range of disorders, including osteoporosis [6], bone lesions associated with rheumatoid arthritis [25], Paget‘s disease [26] and malignancy- induced bone diseases [27]. Due to the important role of the RANK-RANKL pathway in the bone remodeling process [5], interfering with their interaction is a promising strategy for therapeutic intervention. Initially, OPG-Fc was developed as a RANKL scavenger [28]; as OPG cross reacts with TRAIL, recently OPG variants lacking TRAIL binding were developed, showing significantly reduced osteoclastogenesis [29]. RANKL-targeted peptides were also

Chapter 3 developed and confirmed to prevent bone loss and inflammation in rheumatoid arthritis in vivo [19,30]. Finally, denosumab, an FDA-approved RANKL-specific antibody, was developed and is currently used in the treatment of osteoporosis and bone metastases [19]. Denosumab inhibits osteoclastogenesis by scavenging RANKL thus inhibiting receptor interaction. In contrast, we focused on novel RANKL variants, which will be of interest as these are blocking the receptor directly.

3D structures of TNF-TNF-R1 and TRAIL-DR5 complexes show a conserved tyrosine residue in the DE loop of ligands, which induces a hydrophobic interaction with loop 1 of the receptors [15,31]. Mukai et al. created a series of receptor-selective TNF-α mutants with full bioactivity by using the phage display technique; the results showed that all active TNF-R1- selective mutants retained Y87, suggesting that Y87 is an essential residue for receptor binding [32]. Furthermore, TNF-α mutation Y87H was generated as a part of a TNF-R1- selective antagonist and Y87H was found to change the binding mode of the DE-loop from a hydrophobic to an electrostatic interaction [13]. In silico calculation of the effects of mutations of RANKL residue I248, which is homologous to TNF-α Y87, on the interaction with its receptor RANK, suggested that mutagenesis of the I248 residue of RANKL has strong effect on binding of RANKL to RANK.

We have focused on three mutations on position 248: I248Y, I248K and I248D. Detailed analysis of the interaction of RANKL proteins with RANK using SPR showed an increased affinity for mutants I248K and I248Y and a decreased affinity for I248D (Fig. 2 and Table 1). In accordance, competitive ELISA confirmed that RANKL I248Y and I248K can efficiently compete with WT RANKL for binding to RANK, whereas I248D cannot (Fig. 3). In line with these results, structural analysis of the impact of these mutations shows that the positively charged lysine on position 248 may interact with the negatively charged E54 residue on the RANK surface. Mutation I248Y could also result in an extra hydrogen bond and strengthened van der Waals forces, also reinforcing the binding of RANKL and RANK. The lower affinity for RANK that we measured for I248D can be explained by an electrostatic repulsion with E54 residue in RANK.

High affinity mutants RANKL I248Y and I248K are still able to induce osteoclastogenesis but to a 20-30% lower maximum than WT RANKL, whereas low affinity mutant I248D does not even reach 40% of this maximum activation level even at 150 ng/mL (Fig. 5). Interestingly, the high affinity mutants were able to reduce WT RANKL-mediated

RANKL variants antagonizing osteoclastogenesis osteoclastogenesis already at low concentrations, whereas I248D shows a dose-dependent reduction of the WT RANKL signal up to the concentration of 150 ng/mL (Fig. 5). All three mutants showed higher association rate constants (Table 1) allowing them to bind faster to the receptor than WT RANKL. Whereas high affinity mutants I248K and I248Y have similar dissociation rate constants as WT RANKL, low affinity mutant I248D has a higher dissociation rate constant (Table 1). The latter one leads to a less stable complex with RANK, which can explain why this mutant in itself is not very biologically active and why it reduces WT RANKL activity only at high concentrations (Fig. 5D). A similar explanation was formulated for antagonistic TNF-α mutation Y87H [13].

Our RANKL mutants can reduce WT RANKL activity by competing in binding to RANK, 3 resulting in a reduction in biological activity to the level of the mutants themselves. What could be an explanation for this lower biological activity? In a molecular dynamics study on binding between TNF-ligand family member TRAIL and its death receptor DR5, Wassenaar et al. proposed that through binding to TRAIL the conformational freedom of extracellular binding domains of DR5 was strongly restricted; this might also influence the stability of the intracellular death complex [33]. Furthermore, Neumann et al. showed that the signaling capabilities of the death receptors DR4 and DR5 do not only depend on binding of TRAIL: the transmembrane domains together with their adjacent stalk regions also control the signaling strength [34]. Likewise, the transmembrane domain and adjacent extracellular stalk regions of RANK could play a similar role. RANKL may also play a role in controlling the conformational freedom of the extracellular domains of RANK. Mutants RANKL I248Y and I248K may slightly change the conformation of the RANKL-RANK complex, thus influencing the conformational freedom of RANK extracellular domains and subsequently the orientation of intracellular domains, which further influences the recruitment of downstream effector proteins.

In conclusion, our data show that the DE-loop is of importance for osteoclastogenesis and can be explored for the creation of new ligands with inhibitory properties. Given the importance of the DE-loop for RANK-RANKL signaling, the newly created mutants I248Y and I248K can form a starting point for novel therapeutic proteins in new osteoporosis treatments.

Chapter 3

Materials and Methods

In silico calculations of the interaction energy of RANK in complexes with RANKL I248 mutants

Simulations were performed using the available 3D structure of murine RANKL in complex with RANK (Protein Data Bank accession code 4GIQ) [4]. All calculations and predictions were performed using BIOVIA Discovery studio 4.5. Briefly, the structures of RANKL and the I248 mutants were refined using the CHARMm force field. For the minimization of the receptor-ligand complex, the Smart Minimizer was used with maximum steps of 2000 and RMS gradient of 0.1, and Generalized born with molecular volume (GBMW) was used as implicit solvation model. Predicted differences in RANK-binding energy (ΔΔGi) of the RANKL I248 mutants compared to WT RANKL were determined through interaction energy calculation. The change in energy was calculated in kcal/mol and applies to a single binding interface. A negative ΔΔGi value indicates an increase in receptor binding energy, whereas a positive ΔΔGi value indicates a decrease in receptor binding energy.

Site-directed mutagenesis, production and purification of the RANKL variants cDNA encoding murine soluble RANKL (aa 160-316) was introduced in a pET15b expression plasmid (Novagen, Darmstadt, Germany) using the restriction sites NcoI and BamHI (Fermentas, Lithuania). Mutations at position 248 were introduced using megaprimers [35]. The PCR product was digested using DpnI (Fermentas, Lithuania) to remove template DNA and used for transformation of Escherichia coli DH5α cells. Plasmid DNA was purified from an overnight culture (Nucleospin, Macherey-Nagel, Germany). After confirming the introduction of mutations by DNA sequencing, the plasmids were used for transformation of Escherichia coli BL21(DE3). Transformants selected using ampicillin (Duchefa, Haarlem, The Netherlands) were grown overnight at 37°C in 1 x LB medium (Trypton, NaCl and Yeast extract all from Duchefa, Haarlem, The Netherlands) containing 100 μg/mL ampicillin. This culture was used to inoculate a larger culture (1:100 dilution), which was grown for approximately 2 h to OD600 0.5, after which protein production was initiated by adding 1 mM IPTG (Duchefa, Haarlem, The Netherlands), and continued for 16 h at 20°C.

After harvesting cells by centrifugation and resuspending at 3 mL/g wet cells in buffer A containing 50 mM MES pH 5.8 (Duchefa, Haarlem, The Netherlands), 10% v/v glycerol

RANKL variants antagonizing osteoclastogenesis

(Duchefa, Haarlem, The Netherlands), and 2 mM dithiothreitol (Sigma, Saint Louis, USA), the cells were lysed by sonication. The RANKL proteins were mainly soluble. Supernatants were firstly loaded on a 5 mL cation exchange column (SP column, GE Healthcare, USA) using buffer A. Buffer B, similar to A but containing 2 M NaCl (Duchefa, Haarlem, The Netherlands), was used to elute the protein. Elution of the fractions containing RANKL occurred with 300-400 mM NaCl. The presence of proteins was confirmed by Western blotting using an anti-mRANKL antibody (R&D Systems, USA) and corresponding anti goat- Horse Radish Peroxidase (HRP) antibody (Biosource, UK).

The obtained protein-containing fractions were pooled and loaded onto a HiLoad Superdex75 16/60 size exclusion chromatography column (GE Healthcare, USA), using buffer A. The 3 retention volumes of the RANKL proteins corresponded to the hydrodynamic radius of a trimeric complex. The proteins were checked by SDS-PAGE to determine the purity which was estimated to be more than 90% pure. Concentrations were determined with the Coomassie Bradford protein assay kit (Pierce, Rockford, USA) using bovine serum albumin (BSA, ThermoScientific, Rockford, USA) as a standard. The final yield of the variants was approximately 2 mg purified protein per liter culture. When calculating molarity, we used the molecular weight of trimeric RANKL proteins. sfGFP was amplified from pQE30_sfGFP [36] by PCR, digested with NcoI / NcoI site and ligated into the vector pET15b_WT RANKL to encode sfGFP fused to the N-terminus of WT RANKL. sfGFP-WT RANKL was produced in BL21(DE3) cells similar to our variants. For the purification of sfGFP-WT RANKL, cleared cell lysate was firstly loaded onto a 5 mL anion exchange column (Q column, GE Healthcare, USA), using a buffer of 20 mM Tris pH 8.5, 2 mM dithiothreitol and 10% v/v glycerol. Buffer B, similar to A but containing 2 M NaCl, was used to elute the protein. Elution of the fractions containing sfGFP-WT RANKL occurred at 300-500 mM NaCl. The obtained protein-containing fractions were pooled and loaded onto a 5 mL cation exchange column, followed by a HiLoad Superdex200 16/60 size exclusion chromatography column (GE Healthcare, USA), and the purification steps were similar with that of WT RANKL.

Kinetic analysis of complex formation between trimeric RANKL and monomeric RANK-Fc

Chapter 3

Binding between RANKL and RANK-Fc was determined using a Biacore 3000 system (GE Healthcare, USA). A CM4 chip was directly coated with 70 μg/mL protein A (Sigma, Saint Louis, USA), making use of the amine coupling kit (GE Healthcare, USA) according to manufacturer‘s instructions. The amount of immobilized protein A was typically around 1000 RU. Next, murine RANK-Fc (R&D Systems) was captured at a low density, never exceeding 60 RU. The flow rate used for immobilization was 50 μL/min. RANKL was injected at a flow rate of 50 μL/min in concentrations between 0.01 nM and 20.48 nM for 3 minutes. Dissociation of the formed complex was followed for 1000 seconds. HBS-N buffer (GE Healthcare, USA) with 0.005% v/v surfactant P20 (GE Healthcare, Uppsala, Sweden) was used as a running buffer. The chip surface was regenerated between cycles with two injections of 10 mM glycine (Duchefa, Haarlem, The Netherlands) pH 1.5 for 30 seconds each. The responses were corrected for buffer effect and binding to the protein A chip surface [8]. At low receptor densities the data could be fitted to a 1:1 Langmuir model using the BIAevaluation software version 4.2 (GE Healthcare, USA) [8].

Determination of trimer-trimer complexes using SPR

To confirm whether a trimer - trimer complex could be formed between RANKL and RANK, an SPR experiment was set up as previously described [8]. RANK-Fc was captured at high density, >1000 RU, on the surface of a CM5 chip by immobilized protein A. RANKL was injected at a high concentration of 5000 nM with a flow rate of 10 μL/min. After each cycle the chip surface was regenerated as described above. With equation 1, the ratio of the complex formation, n, can be calculated by measuring the maximal response (Rmax) that can be reached by formation of the complex ABn between trimeric RANKL (A; with molecular weight MWA = 52.7 kDa) and monomeric RANK-Fc (B; with molecular weight MWB = 60 kDa) captured at density RUcaptured [8].

Equation 1: Rmax=[MWA/(n∙MWB)] ∙ RUcaptured

Competitive ELISA

Competition between selected RANKL mutants and WT RANKL was determined using a competitive Enzyme-Linked Immuno Sorbent Assay (ELISA). Murine RANK-Fc (Sigma,

RANKL variants antagonizing osteoclastogenesis

Saint Louis, USA) was immobilized on a 96-well Microlon 600 plate (Greiner, Frickenhausen,

Germany) by incubating the wells with 25 nM RANK-Fc in 0.1 M NaHCO3 (Merck, Darmstadt, Germany) buffer pH 8.6 overnight at 4°C. Subsequently, the wells were washed with Tris-buffered saline (TBS) buffer including 0.05% v/v Tween 20 (TBST, Duchefa, Haarlem, The Netherlands), pH 7.4, followed by a 2-hour incubation at room temperature with 2% w/v BSA (Roche, Mannheim, Germany) in phosphate-buffered saline (PBS), pH 7.4. After washing with TBST buffer, the wells were incubated for 30 minutes at room temperature with the RANKL variants I248K, I248Y and I248D at concentrations in the range of 0-8000 nM, mixed with 10 nM sfGFP-WT RANKL. After washing with TBST buffer, bound sfGFP-WT RANKL was detected by incubation with a murine anti-GFP antibody 3 (Sigma, Saint Louis, USA) and a secondary anti-mouse HRP-conjugated antibody (Millipore, USA). The signal was quantified using the One-step Turbo TMB reagent (ThermoScientific, Rockford, USA) and absorbance was measured at 450 nm. The percentage of sfGFP-WT RANKL bound was measured relative to the binding of 10 nM sfGFP WT RANKL alone.

Inhibition of osteoclastogenesis

Cells from the murine leukemic monocyte macrophage cell line RAW 264.7 were cultured as described before [37]. Cells were subcultured every third or fourth day using a 1:10 dilution in fresh DMEM medium (Life Technologies, USA) containing 10% v/v Fetal Calf Serum (FCS, Life Technologies, USA) and 2 mM penicillin/streptomycin (Life Technologies, USA). Cells were seeded at a density of 1,000 cells/well in a 96-well plate (Greiner, Frickenhausen, Germany). At day three the medium was changed to Alpha-MEM (Invitrogen, Carlsbad, USA) containing 2 mM penicillin/streptomycin and 10% v/v FCS (Invitrogen, Carlsbad, USA); different concentrations of RANKL were added, ranging from 3.1 to 150 ng/mL. Inhibition of WT RANKL-induced osteoclastogenesis by RANKL mutants was assessed via treatment of RAW 264.7 cells with 50 ng/mL WT RANKL and a concentration range (3.1-150 ng/mL) of a determined RANKL mutant. At day 5 the medium was exchanged, and both WT RANKL and RANKL mutants were added using the same concentrations as described for day 3. At day 7 osteoclastogenesis was determined using the tartrate resistance acid phosphatase (TRAP) assay (Sigma, Saint Louis, USA) according to the manufacturer‘s instructions. The number of osteoclasts in the wells containing 50 ng/mL WT RANKL was set to 100% and the number of osteoclasts in all other wells was calculated relative to this reference well. Multinucleated

Chapter 3

(three or more nuclei) TRAP-positive cells were considered as osteoclasts. Osteoclasts with two or more clusters of multinuclei were considered as giant osteoclasts.

Determination of exchange of RANKL subunits

The exchange of RANKL subunits was determined using size exclusion chromatography. WT RANKL and sfGFP-WT RANKL at concentrations of 12 μM were incubated together in a 1:1 ratio for 24 h at 37°C or for 44 h at 4°C. After incubation, samples were loaded onto a Superdex 200 10/30 column (GE Healthcare, Uppsala, Sweden) using buffer E (20 mM sodium phosphate buffer pH 7.4, 10% v/v glycerol,). Elution was monitored at 280 nm (all proteins) and at 475/488 nm (sfGFP-WT RANKL); the chromatograms were compared to that of a mixture of sfGFP-WT RANKL and WT RANKL at 0 h.

Acknowledgements

Murine RAW 264.7 cells were a kind gift from J. Doktor, Department of Pathology and Medical Biology, University Medical Center Groningen, Groningen, The Netherlands. This work was performed within the framework of the Dutch Top Institute Pharma project TNF- ligands in cancer (project nr. T3-112) and STW grant 11056. YW is a recipient of a scholarship from the Chinese Scholarship Council (CSC).

Author contributions

YW, AHGA, CRR, RS, RM and RHC performed experiments and analyzed data; YLB, RHC and WJQ planned the research and supervised the study; YW, AHGA, YLB, RHC and WJQ wrote the paper.

References

1 Kim J & Kim N (2016) Signaling Pathways in Osteoclast Differentiation. Chonnam Med J 52, 12–17.

RANKL variants antagonizing osteoclastogenesis

2 Boyce BF & Xing L (2007) Biology of RANK, RANKL, and osteoprotegerin. Arthritis Res Ther 9, S1. 3 Tanaka S, Nakamura K, Takahasi N & Suda T (2005) Role of RANKL in physiological and pathological bone resorption and therapeutics targeting the RANKL-RANK signaling system. Immunol Rev 208, 30–49. 4 Nelson CA, Warren JT, Wang MWH, Teitelbaum SL & Fremont DH (2012) RANKL employs distinct binding modes to engage RANK and the osteoprotegerin decoy receptor. Structure 20, 1971–1982. 5 Trouvin AP & Goëb V (2010) Receptor activator of nuclear factor-κB ligand and osteoprotegerin: maintaining the balance to prevent bone loss. Clin Interv Aging 5, 345– 354. 6 Rachner T, Khosla S, Hofbauer L & Manuscript A (2011) New horizons in osteoporosis. 3 Lancet 377, 1276–1287. 7 Bodmer JL, Schneider P & Tschopp J (2002) The molecular architecture of the TNF superfamily. Trends Biochem Sci 27, 19–26. 8 Reis CR, van Assen AHG, Quax WJ & Cool RH (2011) Unraveling the binding mechanism of trivalent tumor necrosis factor ligands and their receptors. Mol Cell Proteomics 10, M110.002808. 9 Walsh NC, Alexander KA, Manning CA, Karmakar S, Karmakar SK, Wang JF, Weyand CM, Pettit AR & Gravallese EM (2013) Activated human T cells express alternative mRNA transcripts encoding a secreted form of RANKL. Genes Immun 14, 336–45. 10 Ikeda T, Kasai M, Utsuyama M & Hirokawa K (2001) Determination of three isoforms of the receptor activator of nuclear factor-kappaB ligand and their differential expression in bone and thymus. Endocrinology 142, 1419–26. 11 Liu C, Walter TS, Huang P, Zhang S, Zhu X, Wu Y, Wedderburn LR, Tang P, Owens RJ, Stuart DI, Ren J & Gao B (2010) Structural and functional insights of RANKL-RANK interaction and signaling. J Immunol 184, 6910–9. 12 Lam J, Nelson CA, Ross FP, Teitelbaum SL & Fremont DH (2001) Crystal structure of the TRANCE/RANKL cytokine reveals determinants of receptor-ligand specifity. J Clin Invest 108, 971–979. 13 Shibata H, Yoshioka Y, Ohkawa A, Minowa K, Mukai Y, Abe Y, Taniai M, Nomura T, Kayamuro H, Nabeshi H, Sugita T, Imai S, Nagano K, Yoshikawa T, Fujita T, Nakagawa S, Yamamoto A, Ohta T, Hayakawa T, Mayumi T, Vandenabeele P, Aggarwal BB, Nakamura T, Yamagata Y, Tsunoda S, Kamada H & Tsutsumi Y (2008) Creation and X-ray structure analysis of the tumor necrosis factor receptor-1-selective mutant of a tumor necrosis factor-alpha antagonist. J Biol Chem 283, 998–1007. 14 Luan X, Lu Q, Jiang Y, Zhang S, Wang Q, Yuan H, Zhao W, Wang J & Wang X (2016) Crystal structure of human RANKL complexed with its decoy receptor opsteoprotegerin. J Immunol 189, 245–252. 15 Hymowitz SG, Christinger HW, Fuh G, Ultsch M, O‘Connell M, Kelley RF, Ashkenazi A & de Vos AM (1999) Triggering cell death: the crystal structure of Apo2L/TRAIL in a

Chapter 3

complex with death receptor 5. Mol Cell 4, 563–571. 16 Jones EY, Stuart DI & Walker NPC (1989) Structure of tumour necrosis factor. Nature 338, 225–228. 17 Liang S, Dai J, Hou S, Su L, Zhang D, Guo H, Hu S, Wang H, Rao Z, Guo Y & Lou Z (2013) Structural basis for treating tumor necrosis factor α (TNFα)-associated diseases with the therapeutic antibody infliximab. J Biol Chem 288, 13799–13807. 18 Mongkolsapaya J, Grimes JM, Chen N, Xu XN, Stuart DI, Jones EY & Screaton GR (1999) Structure of the TRAIL-DR5 complex reveals mechanisms conferring specificity in apoptotic initiation. Nat Struct Biol 6, 1048–53. 19 Ta HM, Nguyen GTT, Jin HM, Choi J, Park H, Kim N, Hwang H-Y & Kim KK (2010) Structure-based development of a receptor activator of nuclear factor-kappaB ligand (RANKL) inhibitor peptide and molecular basis for osteopetrosis. Proc Natl Acad Sci U S A 107, 20281–6. 20 Ito S, Wakabayashi K, Ubukata O, Hayashi S, Okada F & Hata T (2002) Crystal structure of the extracellular domain of mouse RANK ligand at 2.2-Å resolution. J Biol Chem 277, 6631–6636. 21 Ito S & Hata T (2004) Crystal structure of RANK ligand involved in bone metabolism. Vitam Horm 67, 19–33. 22 Reis CR, Van der Sloot AM, Szegezdi E, Natoni A, Tur V, Cool RH, Samali A, Serrano L & Quax WJ (2009) Enhancement of antitumor properties of rhTRAIL by affinity increase toward its death receptors. Biochemistry 48, 2180–2191. 23 Tur V, Van der Sloot AM, Reis CR, Szegezdi E, Cool RH, Samali A, Serrano L & Quax WJ (2008) DR4-selective tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) variants obtained by structure-based design. J Biol Chem 283, 20560–20568. 24 Van der Sloot AM, Tur V, Szegezdi E, Mullally MM, Cool RH, Samali A, Serrano L & Quax WJ (2006) Designed tumor necrosis factor-related apoptosis-inducing ligand variants initiating apoptosis exclusively via the DR5 receptor. Proc Natl Acad Sci U S A 103, 8634–8639. 25 Mori H, Kitazawa R, Mizuki S, Nose M, Maeda S & Kitazawa S (2002) RANK ligand, RANK, and OPG expression in type II collagen-induced arthritis mouse. Histochem Cell Biol 117, 283–292. 26 Whyte MP (2006) Paget‘s disease of bone and genetic disorders of RANKL/OPG/RANK/NF-kappaB signaling. Ann N Y Acad Sci 1068, 143–64. 27 Lipton A, Uzzo R, Amato RJ, Ellis GK, Hakimian B, Roodman GD & Smith MR (2009) The science and practice of bone health in oncology: managing bone loss and metastasis in patients with solid tumors. J Natl Compr Canc Netw 7 Suppl 7, S1–29; quiz S30. 28 Body J-J, Greipp P, Coleman RE, Facon T, Geurs F, Fermand J-P, Harousseau J-L, Lipton A, Mariette X, Williams CD, Nakanishi A, Holloway D, Martin SW, Dunstan CR & Bekker PJ (2003) A phase I study of AMGN-0007, a recombinant osteoprotegerin construct, in patients with multiple myeloma or breast carcinoma related bone metastases. Cancer 97, 887–92.

RANKL variants antagonizing osteoclastogenesis

29 Higgs JT, Jarboe JS, Lee JH, Chanda D, Lee CM, Deivanayagam C & Ponnazhagan S (2015) Variants of osteoprotegerin lacking TRAIL binding for therapeutic bone remodeling in osteolytic malignancies. Mol cancer Res 33, 395–401. 30 Naidu VGM, Dinesh Babu KR, Thwin MM, Satish RL, Kumar P V. & Gopalakrishnakone P (2013) RANKL targeted peptides inhibit osteoclastogenesis and attenuate adjuvant induced arthritis by inhibiting NF-κB activation and down regulating inflammatory cytokines. Chem Biol Interact 203, 467–479. 31 Banner DW, D‘Arcy A, Janes W, Gentz R, Schoenfeld HJ, Broger C, Loetscher H & Lesslauer W (1993) Crystal structure of the soluble human 55 kd TNF receptor-human TNFβ complex: Implications for TNF receptor activation. Cell 73, 431–445. 32 Mukai Y, Shibata H, Nakamura T, Yoshioka Y, Abe Y, Nomura T, Taniai M, Ohta T, Ikemizu S, Nakagawa S, Tsunoda S ichi, Kamada H, Yamagata Y & Tsutsumi Y (2009) Structure-function relationship of tumor necrosis Factor (TNF) and its receptor 3 interaction based on 3D structural analysis of a fully active TNFR1-selective TNF mutant. J Mol Biol 385, 1221–1229. 33 Wassenaar TA, Quax WJ & Mark AE (2008) The conformation of the extracellular binding domain of Death Receptor 5 in the presence and absence of the activating ligand TRAIL: A molecular dynamics study. Proteins 70, 333–343. 34 Neumann S, Bidon T, Branschädel M, Krippner-Heidenreich A, Scheurich P & Doszczak M (2012) The transmembrane domains of TNF-related apoptosis-inducing ligand (TRAIL) receptors 1 and 2 co-regulate apoptotic signaling capacity. PLoS One 7. 35 Miyazaki K & Takenouchi M (2002) Creating random mutagenesis libraries using megaprimer PCR of whole plasmid. Biotechniques 33, 1033–4, 1036–8. 36 Boersma YL, Chao G, Steiner D, Wittrup KD & Plückthun A (2011) Bispecific Designed Ankyrin Repeat Proteins (DARPins) targeting epidermal growth factor receptor inhibit A431 cell proliferation and receptor recycling. J Biol Chem 286, 41273–41285. 37 Duan L, de Vos P, Fan M & & Ren Y (2008) Notch is activated in RANKL-induced osteoclast differentiation and resorption. Front Biosci 13, 7064–7071.

Abbreviations

Chapter 3

TNF-R2 - Tumor Necrosis Factor receptor 2 TRAIL - Tumor Necrosis Factor Related Apoptosis Inducing Ligand sfGFP-RANKL - superfolder green fluorescent protein-RANKL fusion protein SPR - surface plasmon resonance

Chapter 4

Creation of RANKL mutants with low affinity for decoy receptor OPG and their potential anti-fibrosis activity

Yizhou Wang, Timo Michiels, Rita Setroikromo, Ronald van Merkerk, Robbert H. Cool and Wim J. Quax#

Department of Chemical and Pharmaceutical Biology, Groningen Research Institute of Pharmacy, University of Groningen, A. Deusinglaan 1, 9713 AV Groningen, The Netherlands

Published in FEBS. J. 2019, 286(18): 3582-3593.

Chapter 4

Abstract

Fibrosis is characterized by progressive alteration of the tissue structure due to the excessive production of extracellular matrix (ECM). The signaling system encompassing Receptor Activator of Nuclear factor NF-κB Ligand (RANKL)/RANK/Osteoprotegerin (OPG) was discovered to play an important role in the regulation of ECM formation and degradation in bone tissue. However, whether and how this signaling pathway plays a role in liver or pulmonary ECM degradation is unclear up to now. Interestingly, increased decoy receptor OPG levels are found in fibrotic tissues. We hypothesize that RANKL can stimulate RANK on macrophages and initiate the process of ECM degradation. This process may be inhibited by highly expressed OPG in fibrotic conditions. In this case, RANKL mutants that can bind to RANK without binding to OPG might become promising therapeutic candidates. In this study, we built a structure-based library containing 44 RANKL mutants and found that the Q236 residue of RANKL is important for OPG binding. We show that RANKL_Q236D can activate RAW cells to initiate the process of ECM degradation and is able to escape from the obstruction by exogenous OPG. We propose that the generation of RANKL mutants with reduced affinity for OPG is a promising strategy for the exploration of new therapeutics against fibrosis.

Keywords: RANK, OPG, fibrosis, liver, lung

RANKL variants escape obstruction of OPG

Introduction

The cytokine system consisting of receptor activator of nuclear factor NF-κB ligand (RANKL), RANK and Osteoprotegerin (OPG), plays a key role in bone homeostasis by controlling the balance between bone producing and bone resorbing activity [1]. RANKL is expressed on osteoblasts and its receptor RANK is expressed on osteoclast precursors cells [2]. As a member of the Tumor Necrosis Factor (TNF) superfamily, RANKL is a type II transmembrane protein with a C-terminal extracellular region [3–5]. The binding between RANKL and RANK on osteoclast precursors induces the expression of osteoclast‐specific genes, including tartrate ‐ resistant acid phosphatase (TRAP), cathepsin K, matrix metallopeptidase 9 (MMP9), which will further trigger osteoclast maturation and bone extracellular matrix (ECM) degradation [6,7]. Osteoprotegerin (OPG) is produced by 4 osteoblasts and acts as a natural decoy receptor for RANKL thereby inhibiting osteoclast activation and bone ECM degradation [8]. Imbalances in the RANK/RANKL/OPG pathway can differently regulate the orientation of bone remodeling to either bone formation or resorption, therefore lead to diseases such as osteoporosis with a high RANKL/OPG ratio and osteopetrosis with a low RANKL/OPG ratio [9–12].

Fibrosis is a chronic disease characterized by excessive accumulation of ECM and the destruction of tissue structure in response to injury [13,14]. With a high mortality rate, fibrotic diseases cause more than 800,000 deaths every year worldwide [14]. However, there is no effective therapy to reverse chronic fibrosis currently. Taking pulmonary fibrosis as an example, lung transplantation is the only effective way to treat lung fibrosis at present [13,15,16]. Fibroblasts and myofibroblasts are the most important cells involved in the production of ECM [17]. Macrophages, which are also abundantly present in fibrotic tissue, however, have been shown to possess both profibrotic and antifibrotic properties leading to different phenotypes [18,19]. They have been identified to secrete inflammatory and growth factors such as transforming growth factor beta (TGF-β), IL-13 and TNF, which promote the fibrotic process [14,15]. On the other hand, macrophages in fibrotic tissues also possess antifibrotic properties by producing secreted matrix metalloproteinases (MMPs) and cathepsins that degrade fibrotic ECM [20]. However, how antifibrotic macrophages are activated and induced to degrade ECM still remains to be understood.

Interestingly, many tissue macrophages express RANK, and through RANKL stimulation, proteases are released which can degrade ECM [20]. In bone, osteoclasts are derived from

Chapter 4 macrophage/monocyte and can produce MMPs and other proteolytic enzymes to degrade bone ECM [21,22]. In fibrotic tissue, the stimulation of the RANKL/RANK axis may also be a possible way to activate antifibrotic macrophages and reverse fibrosis [20]. Notably, OPG, as a decoy receptor of RANKL, was shown to be an inducer of fibrogenesis to promote vascular fibrosis in vascular smooth muscle cells [23]. High expression of OPG was found to be related to the formation of fibrous tissues in diseases like liver, vasculature and cystic fibrosis [24,25], suggesting that OPG may be important in the fibrosis process, which is a further support for the role of the RANKL/RANK/OPG axis in fibrosis.

In the present research, we hypothesized that RANKL could stimulate RANK on macrophages and initiate the process of ECM degradation. This process may be inhibited by the decoy activity of highly expressed OPG in fibrotic conditions. As a consequence, RANKL mutants that can bind to RANK without binding to OPG are becoming promising agonists to stimulate RANK on macrophages and reduce ECM without being hampered by high OPG production. Therefore, in this research, through comparing the 3D structures of murine RANKL-RANK and RANKL-OPG, we have built a structure based RANKL mutants library containing 44 RANKL mutants. Our results show that RANKL_Q236D is very effective in activating murine RAW 264.7 macrophage cells and to escape from the obstruction by exogenous OPG. The generation of RANKL mutants with reduced binding to OPG is a promising strategy for the exploration of new therapeutics against fibrosis.

Results

RANKL-RANK and RANKL-OPG binding interface analysis and structure-based design of the mutants

The available 3D structures of murine RANKL-RANK and RANKL-OPG complexes (Protein Data Bank accession codes 4GIQ and 4E4D) were used to perform binding simulations. As shown in Fig. 1A, via analysis of all interactions -including hydrogen bonds, electrostatic and hydrophobic properties- between RANKL-RANK and RANKL-OPG, all residues of RANKL that show interactions with one or both receptors were identified. These residues are marked from light to dark purple according to the number of interactions they were involved in (Fig. 1A). RANKL_Q236, I248 and K256 were selected for mutation because they show interactions with OPG, but not RANK (Fig. 1B, C and Table. 1). Therefore it is supposed that

RANKL variants escape obstruction of OPG these can change the binding of RANKL to OPG without influencing the binding of RANKL to RANK. In addition, RANKL_R190, R222, H252 and E268 were selected, because these four residues show more interactions with OPG than RANK (Fig. 1B, C and Table. 1), suggesting that the effect on RANKL-RANK interactions by replacing them might be minimal.

Fig 1. Structural comparison of RANKL/OPG and RANKL/RANKmade using Discovery Studio. 4.5 A) Structural comparison between RANKL/OPG (upper sequence) and RANKL/RANK (bottom sequence). The color represents the residue shows interaction with receptor and the range of color form light blue to dark blue indicates the number of interactions. B) and C) Detailed view of selected RANKL residues (R190, R222, I248, Q236, H252, K256 and E268) and their interactions with OPG and RANK.

Chapter 4

Table 1. Interaction analysis between RANKL-OPG and RANKL-RANK complexes.

RANKL-OPG RANKL-RANK

Interaction Category Interaction Category K256 RANKL:K256:NZ - OPG1:E95:OE2 Electrostatic RANKL:K256:HZ2 - OPG1:E95:OE1 Hydrogen Bond

Q236 RANKL:Q236:HE21 - OPG1:E93:O Hydrogen Bond OPG1:E95:HN - RANKL:Q236:OE1 Hydrogen Bond

I248 OPG1:V60 - RANKL:I248 Hydrophobic OPG1:H54 - RANKL:I248 Hydrophobic

R190 RANKL:R190:HD1 - OPG2:Y61:OH Hydrogen Bond RANKL:R190 - RANK2:L59 Hydrophobic RANKL:R190:HD2 - OPG2:Y61:OH Hydrogen Bond RANKL:R190:NH1 - OPG2:H47 Electrostatic OPG2:Y61 - RANKL:R190 Hydrophobic

H252 RANKL:H252:HD1 - OPG1:S63:OG Hydrogen Bond RANKL:H252:HE1 - RANK1:Y47:OH Hydrogen Bond OPG1:Y49:HH - RANKL:H252:NE2 Hydrogen Bond RANKL:H252 - RANK1:L58 Hydrophobic RANKL:H252:HE1 - OPG1:Y61:O Hydrogen Bond RANKL:H252:HE1 - OPG1:S63:O Hydrogen Bond RANKL:H252 - OPG1:V60 Hydrophobic

E268 OPG2:R90:HH12 - RANKL:E268:OE2 Hydrogen Bond;Electrostatic RANK2:R99:NH1 - RANKL:E268:OE2 Electrostatic OPG2:K99:NZ - RANKL:E268:OE2 Electrostatic RANK2:R100:HN - RANKL:E268:OE2 Hydrogen Bond OPG2:R90:HH21 - RANKL:E268:OE1 Hydrogen Bond RANK2:R100:NH1 - RANKL:E268:OE2 Electrostatic OPG2:K99:HE1 - RANKL:E268:OE1 Hydrogen Bond OPG2:K99:HE2 - RANKL:E268:OE1 Hydrogen Bond

R222 RANKL:R222:NH1 - OPG2:E68:OE2 Electrostatic RANKL:R222:HH11 - RANK2:D64:OD2 Hydrogen Bond;Electrostatic RANKL:R222:NH1 - OPG2:E95:OE2 Electrostatic RANKL:R222:HD1 - RANK2:D64:OD2 Hydrogen Bond RANKL:R222:HE - OPG2:E68:OE2 Hydrogen Bond RANKL:R222:HD2 - RANK2:G66:O Hydrogen Bond RANKL:R222:HH12 - OPG2:E95:OE1 Hydrogen Bond RANKL:R222 - RANK2:K67 Hydrophobic RANKL:R222:HH21 - OPG2:E68:OE1 Hydrogen Bond RANKL:R222:HH22 - OPG2:E95:O Hydrogen Bond RANKL:R222:NH1 - OPG2:F96 Electrostatic

In silico mutagenesis at positions Q236, I248, K256, R190, R222, H252 and E268 was performed to estimate differences between RANKL mutants and RANKL_WT in ΔΔGi binding to receptors (Fig. 2). A more negative ΔΔGi value indicates a predicted increase in receptor binding energy, and vice versa. Based on the outcome, we decided to select and construct a subset of RANKL mutants. Two residues, RANKL_Q236 and K256, were subjected to full saturation mutagenesis, because for these two positions all the other 19 amino acids were predicted to give a decrease in affinity for OPG (Fig. 2A, B). Other single substitutions of RANKL_I248W, H252W, H252L, H252R, E268D and E268N were selected on the basis of their predicted lowered affinity for OPG or their large difference of predicted affinities for OPG and RANK. In total 44 variants were proposed.

RANKL variants escape obstruction of OPG

Fig 2. Heatmap of the binding energy predictions for RANKL_ mutants. Predicted differences in binding energy (ΔΔGi) of RANKL_K256, Q236, I248, R190, H252, E268 and R222 variants binding to RANK (A) and OPG (B) when compared with RANKL_WT are shown in the heatmap, respectively. A negative ΔΔGi value indicates an improvement in receptor binding, whereas a positive ΔΔGi value indicates a decrease in receptor binding.

Pre-screen of RANKL mutants with reduced binding to OPG

After construction, expression and purification using cation exchange chromatography, 28 out of these 44 variants were obtained successfully. Most RANKL_K256 variants, however, were produced in inclusion bodies. On hindsight, this can be explained by the role this residue plays in RANKL trimerization, which forms a polar interaction with D303 within the neighbor monomer [4]. Changing this lysine into any other amino acid might prevent the formation of the RANKL trimer. The double mutant RANKL_K256D/D303K could not rescue the folding of the protein as well. Apparently, no changes are tolerated at this position

Chapter 4 and therefore the 256 variants were not used for further investigations. To assess the binding of RANKL variants to immobilized RANK-Fc and OPG-Fc, an ELISA assay was performed (Fig. 3). Several RANKL_236 variants RANKL_Q236N, Q236S, Q236D, Q236H, Q236P and Q236A showed an increase in the binding ratio of RANK versus OPG. Compared to RANKL_WT, they all showed higher binding to RANK and 40%-60% lower binding to OPG. Especially, RANKL_Q236D was of interest as it displayed a low binding to OPG, which is at 25% of that of RANKL_WT. Variant RANKL_Q236K was also selected for further analysis as it showed a large decrease in binding to OPG with, however, a concomitant lower ELISA signal in binding to RANK.

Fig 3. Comparison of the relative bindings of RANKL mutants towards mOPG-Fc and RANK-Fc, as determined by ELISA. Receptor binding to mOPG-Fc and RANK-Fc was performed in Duplo and calculated relative to the response of RANKL_WT (100%) at 0.5 nM.

Receptor binding affinity of RANKL variants as determined by SPR

Seven promising candidates, which maintained the binding to RANK-Fc and showed decreased binding to OPG-Fc were selected following the ELISA data. These variants were purified to homogeneity as described before [10]. Affinities of the purified RANKL variants to RANK and OPG receptors were determined using Surface Plasmon Resonance (SPR). By using the CM4 sensorchip, with a low density of receptor, we were able to achieve complexes of RANKL-RANK and RANKL-OPG in the form of mixtures of trimer-monomer and trimer-

RANKL variants escape obstruction of OPG dimer [26]. All the data were fitted with a 1 : 1 Langmuir fitting model and the kinetic parameters were calculated and shown in Table 2. All these seven RANKL mutants showed much lower affinities to OPG-Fc with the best one RANKL_Q236D showing around three times decrease in the association rate constant (ka) and ten folds increase in dissociation rate constant (kd), which taken together is a 30 times decrease in affinity to OPG-Fc (Fig. 4). Importantly, this same mutant maintained its affinity to RANK-Fc. RANKL_Q236K, however, has a much lowered affinity to RANK-Fc as suggested by its lower ELISA signal. RANKL mutants Q236N, Q236S, Q236H, Q236P and Q236A, all showed affinities to RANK-Fc that are in the same range or slightly lower than RANK_WT, between 50% and 100%, which is mainly due to higher dissociation rates. Taken together, these results are consistent with the previous pre-screen ELISA result and they further confirm that the RANKL_Q236 residue indeed plays an important role in RANKL-OPG binding with 4 RANKL_Q236D showing the most promising properties.

Table 2. Binding kinetics of the RANKL variants and RANKL_WT to mRANK-Fc and mOPG-Fc by surface plasmon resonance.

OPG-Fc RANK-Fc Protein

-7 -1 -1 4 -1 -6 -1 -1 4 -1 ka•10 (M s ) kd·10 (s ) KD (pM) ka·10 (M s ) kd·10 (s ) KD (pM)

RANKL_WT 1.8 ± 0.7 0.7 ± 0.1 4.3 ± 1.6 8.4 ± 0.6 1.0 ± 0.1 11.9 ± 1.5

RANKL_Q236N 1.5 ± 0.2 3.1 ± 0.9 20.7 ± 3.7 7.9 ± 0.9 1.7 ± 0.3 22.1 ± 2.9

RANKL_Q236H 1.3 ± 0.2 2.2 ± 0.5 16.6 ± 1.6 6.7 ± 0.0 1.3 ± 0.2 18.7 ± 2.8

RANKL_Q236S 1.4 ± 0.2 3.1 ± 0.4 23.3 ± 4.5 7.0 ± 0.6 1.8 ± 0.5 24.9 ± 5.1

RANKL_Q236D 0.6 ± 0.1 7.0 ± 1.0 112.3 ± 24.4 6.4 ± 0.8 0.9 ± 0.2 15.0 ± 3.2

RANKL_Q236A 1.6 ± 0.3 3.3 ± 0.4 20.5 ± 2.2 8.9 ± 2.0 1.8 ± 0.3 21.5 ± 6.6

RANKL_Q236K 1.1 ± 0.5 14.6 ± 2.7 142.7 ± 44.6 8.0 ± 1.3 9.5 ± 0.8 119.3 ± 10.5

RANKL_Q236P 1.1 ± 0.3 2.2 ± 0.3 21.3 ± 8.2 6.1 ± 0.5 1.2 ± 0.4 19.8 ± 6.0

Chapter 4

Fig 4. Typical SPR sensorgrams obtained for binding between RANK-Fc/OPG-Fc and RANKL_WT/RANKL_Q236D. Depicted are the binding between (A) OPG-Fc and RANKL_WT, (B) OPG-Fc and RANKL_Q236D, (C) RANK-Fc and RANKL_WT, and (D) RANK-Fc and RANKL_Q236D. Injection of RANKL is marked with a double-headed arrow. After injection, the dissociation was followed for 1000 s.

Effect of RANKL variants on ECM-degradation enzymes expression in RAW 264.7 cells

In bone regulation process, the binding between RANKL and the RANK on osteoclast precursors will induce the expression of osteoclast-specific genes, such as TRAP and MMP9, which will stimulate osteoclast maturation and bone ECM degradation [22]. In fibrosis, MMPs have been shown to be responsible for collagen degradation and ECM breakdown, which is actually beneficial for fibrosis recovery [14,19]. Furthermore, MMP9 is particularly expressed in macrophages within lung and liver [20]. Therefore, we chose monocyte-derived RAW 264.7 macrophage as a cell model to detect the biological effects caused by RANKL variants. Real-time quantitative PCR was performed to detect the TRAP and MMP9 gene expressions in presence of RANKL variants with or without exogenous OPG. As shown in Fig. 5, RANKL_WT (50 ng/ml) stimulation could significantly induce the expressions of

RANKL variants escape obstruction of OPG

MMP9 and TRAP, which was totally blocked by adding exogenous mOPG-Fc at the concentration of 400 ng/ml. Interestingly, addition of mOPG-Fc did have much less influence on the activation by RANKL variants as compared to that by RANKL_WT. Activation by RANKL_Q236D was not inhibited at all by the presence mOPG-Fc indicating that this variant is capable to restore MMP9 activity in fibrotic tissues.

Fig 5. mRNA levels of different ECM degrading enzymes, A) MMP 9 and B) TRAP, after treatment with RANKL_WT and mutants, determined by Real-time quantitative PCR. Significance was calculated using a Student‘s t-test compared to cells treated with RANKL_WT (50 ng/ml) plus mOPG-Fc (400 ng/ml): (**) is P < 0.01 and (***) is P < 0.0001. The error bars reflect the standard deviation (SD) of three independent experiments.

Effect of RANKL variants on RANKL induced osteoclastogenesis in RAW 264.7 cells

To further confirm the role of RANKL variants, we next tested their effects on osteoclastogenesis in presence of mOPG-Fc. RAW 264.7 cells were treated with RANKL_WT and variants with or without the presence of mOPG-Fc. After 4 days, the cells were measured for TRAP activity and osteoclasts formation, respectively. As shown in Fig. 6A and 6B, RANKL_WT could significantly induce both TRAP activation and osteoclasts formation. This activation was totally blocked by the addition of mOPG-Fc. Treatments with RANKL variants Q236N, Q236S, Q236H, Q236P and Q236A could induce TRAP activity at a level comparable with RANKL_WT (Fig. 6A). Interestingly, these RANKL variants exhibited less inhibition by the addition of OPG-Fc and they were capable to retain from 50% to 80% of TRAP activity in the presence of OPG-Fc. RANKL_Q236K could no longer induce TRAP activity because of its lower affinity to RANK. Fascinatingly, RANKL_Q236D could almost completely escape from the inhibition by OPG and kept approximately 95% of TRAP

Chapter 4 activity. Consistently, in the osteoclasts formation assay (Fig. 6B), RANKL_Q236N, Q236S, Q236H, Q236P and Q236A showed from 18% to 54% capability to induce osteoclast formation in presence of 400 ng/ml of mOPG-Fc, while RANKL_Q236D still showed complete activation in the presence of this amount of mOPG-Fc (Fig. 6B). Microscope photographs of osteoclasts from treatments with RANKL_WT (50 ng/ml) and RANKL_Q236D (50 ng/ml), both in the presence and absence of mOPG-Fc are shown in Fig. 6C. Both single treatments with RANKL_WT and RANKL_Q236D instigated a massive osteoclast formation. Addition of 400 ng/ml of mOPG-Fc could completely block osteoclast formation caused by RANKL_WT, but showed no influence on that caused by RANKL_Q236D.

Fig 6. Effect of RANKL variants on RANKL induced osteoclastogenesis in RAW 264.7 cells. A) TRAP activity and B) relative number of osteoclasts obtained after treatment of murine RAW 264.7 cells with RANKL variants (50 ng/ml) and RANKL_WT (50 ng/ml) with or without mOPG-Fc (400 ng/ml). C) Microscope images of RAW 264.7 cells treated with RANKL_WT and RANKL_Q236D with or without mOPG-Fc. Scale 100 μm. Significance was calculated using a Student‘s t-test: (**) is P < 0.01 and (***) is P < 0.0001. The error bars reflect the standard deviation (SD) of three independent experiments.

RANKL variants escape obstruction of OPG

Discussion

The RANKL/RANK/OPG system was discovered decades ago and is most prominently known for its role in regulating bone density [27,28]. Nowadays this system is known to be more versatile and is also thought to be involved in the process of fibrosis [20,29,30]. High expression of OPG was found to be related to fibrosis diseases like liver, vascular and cystic fibrosis, suggesting an important role of OPG in fibrosis [23–25]. Recently, it was suggested that inefficient RANKL stimulation occurs in lung tissues of human and mice with pulmonary fibrosis [20] supporting the idea that the decoy activity of OPG plays a role in fibrosis. In this study, we hypothesized that RANKL could stimulate RANK on macrophages and initiate the process of ECM degradation, which may be inhibited by high OPG levels in fibrotic conditions. Therefore, RANKL mutants, which can bind to RANK without binding to OPG, are becoming of interest to solely stimulate RANK on macrophages and reduce ECM without 4 binding to OPG present in fibrotic tissue. Notably, OPG also acts as the decoy receptor of tumor necrosis factor-related apoptosis-inducing ligand (TRAIL), the other member of TNF superfamily, and recently TRAIL variant DHER lacking binding to OPG was developed [31,32], which indicates the possibility of making RANKL variants as well.

The available 3D structures of murine RANKL-RANK and RANKL-OPG complexes (Protein Data Bank accession codes 4GIQ and 4E4D) were used as the starting point for inspecting the binding surface. Several residues of mRANKL, Q236, I248, K256, R190, R222, H252 and E268, stand out from the analysis as they show more interactions with OPG than RANK. In silico calculation of differences in ΔΔGi binding to receptors helped us to further reduce the range of selection. The selected residues are located in the C-D loop, D-E loop, E strand and F strand of RANKL, respectively. This is consistent with a previous analysis by Nelson et al. that the contacts made by OPG are limited to the E-strand and DE-loop region of RANKL [33]. Upon expression, unfortunately, RANKL K256 variants were not being properly folded and insoluble aggregates were formed. Lam et al. discussed that position 256 is involved in the trimeric interface of RANKL and it forms an ionic interaction with D303 of the neighboring monomer [4]. Our attempt to restore the ionic bond by making the reciprocal double mutation K256D/D303K could not rescue the folding of the protein. More refined studies on position mRANKL_K256 might still be of interest as Luan et al. suggested that hRANKL_K257, which is the equivalent to mRANKL_K256, interacts with the E95 residue of hOPG-CRD [34].

Chapter 4

Computational Protein Design (CPD) methods have been successfully used for analyzing and modifying protein-protein interactions by us [32,35]. Compared to traditional directed evolution, which produces and evaluates mutations at many positions, CPD can guide us directly to focus on certain key amino acids in a much shorter time. Therefore, the combination of CPD and focused mutagenesis and screening is efficient as exemplified by the mutant Q236D. However, there are limitations in the predictions given by CPD and the factual results can differ from predictions as exemplified by the mutants of residue K256.

Receptor binding experiments using pre-screen ELISA and SPR confirmed the predictions from the design that residue Q236 is one of the most important residues for OPG binding. On the basis of the ELISA results we purified RANKL_Q236N, Q236S, Q236H, Q236D, Q236P, Q236K and Q236A and using SPR all were shown to have decreased affinity for OPG in accordance with the in silico predictions. All of them, except Q236K, have affinities for RANK comparable to RANKL_WT (Table 2). RANKL_Q236D is the best among them to have approximately 30 times decreases in affinity to OPG-Fc. In line with these results structural analysis of this mutation (Figs. 7A and 7B) shows that the single substitution at 236 position from glutamine to aspartate reduces the length of the side chain. Therefore the distance from RANKL 236 to OPG E93 and E95 becomes larger, and two hydrogen bonds might disappear that are normally present between RANKL Q236 and OPG residues E93 and E95. On the other hand, the negatively charged aspartate on position 236 may have repulsion to the negatively charged E93 and E95 residues on the OPG surface. Interestingly, Warren et al. previously selected RANKL_Q236H from an error prone PCR library using yeast display to have a decrease binding to OPG [36]. Here we used saturation mutagenesis and among others also selected RANKL_Q236H to show a lower affinity to OPG. Thanks to the saturation mutagenesis, we selected a superior variant, RANKL_Q236D, which has a 6.8 times decrease affinity to OPG compared to RANKL_Q236H. This novel variant shows superior properties to initiate the process of ECM degradation in fibrotic tissue, which is typified by an excess of OPG [20,24]. In the further development of this variant towards a therapeutic drug it should be noted that the RANKL/RANK/OPG pathway also plays an important role in bone remodeling. Therefore, a tissue specific delivery of RANKL_Q236D is needed to achieve targeting of fibrotic organs directly without influencing the bone remodeling. As fibrosis can occur in many different organs showing a common pathogenic pathway and the presence of matrix proteins is highly similar, it is suggested that promoting ECM degradation could be a common way for organ repair [37]. Drug delivery systems that

RANKL variants escape obstruction of OPG can target these different organs will be the topic of our future research. As it is crucial and essential to identify alternative therapeutic strategies for fibrosis treatment [16,38], we think our approach is worthwhile pursuing.

Fig 7. Predicted area of interaction of RANKL and OPG receptor around position 236. A) RANKL_WT and B) RANKL_Q236D variant.

In conclusion, we have built a structure based RANKL mutants library containing 44 RANKL mutants and the Q236 residue of RANKL is of importance for OPG binding. RANKL_Q236D was found to maintain activating RAW 264.7 cells and to escape from the obstruction by exogenous OPG. Notably, the anti-fibrotic effect of RANKL_Q236D is deserved to be evaluate in vivo. In our study, the importance of RANKL Q236 residue in RANKL-OPG binding and the discovery of RANKL_Q236D variant form a starting point for the exploration of new therapeutics against fibrosis.

Methods and Materials

In silico calculation

Binding simulations were performed using the available 3D structures of murine RANKL- RANK and RANKL-OPG complexes (Protein Data Bank accession codes 4GIQ and 4E4D). BIOVIA Discovery studio 4.5 was used to perform all the calculations and predictions. Briefly, homotrimer structures of RANKL-RANK and RANKL-OPG were prepared and minimized based on CHARMm force field as previously described [10]. Generalized Born

Chapter 4 with molecular volume (GBMW) was used as implicit solvation model. Interactions including hydrogen bond, electrostatic and hydrophobic effects between one ligand and two receptors of each complex were analyzed. Residues of RANKL that showed more interactions with OPG than RANK were selected to do further calculations on mutation binding energy difference.

Predicted differences in RANK or OPG binding energy (ΔΔGi) of the RANKL mutants compared to RANKL_WT were determined through interaction energy calculation as previously described [10].

Site-directed mutagenesis, production, and purification of the RANKL variants cDNA corresponding to mouse soluble RANKL (aa 160-316) was cloned in pET15b (Novagen) using NcoI and BamHI restriction sites. Mutants were constructed by QuikChange PCR method using Phusion high-fidelity DNA polymerase (New England Biolabs). For full randomization of each residue, the small-intelligent method was used by mixing four pairs of complementary primers with degenerate codons NDT, VMA, ATG, and TGG at a ratio of 12:6:1:1 [39,40]. The PCR products were digested with DpnI (Fermentas) enzymes and then transformed into Escherichia coli DH5a cells. The colonies were transferred to 96 well Luria- Bertani (LB) agar plate with 100 μg/ml ampicillin and sequenced by GATC Biotech. After confirming the sequences of mutations, the plasmids were transformed into E. coli BL21(DE3) cells individually. Homotrimeric RANKL proteins were produced and purified as described before [10]. For prescreen using ELISA assay, the purities of the RANKL samples after cation exchange column (SP column, GE Healthcare, Uppsala, Sweden) were sufficient.

Prescreen ELISA

Murine RANK-Fc (R&D Systems) and murine OPG-Fc (Bio Legends) (100 ul, 10 nM) were immobilized on a 96-well high binding plate (Greiner, Frickenhausen, Germany) by in 0.1 M NaHCO3 (Merck, Darmstadt, Germany) buffer pH 8.6 overnight at 4 °C, respectively. The wells were subsequently washed with phosphate-buffered saline (PBS) buffer including 0.05% v/v Tween 20 (PBST, Duchefa), pH 7.4, and the remaining binding places were blocked with 2% w/v BSA (Roche, Mannheim, Germany) in PBS, pH 7.4 for 2 h. After washing for three times, 100 ul of 0.5 nM one-step purified RANKL_WT or mutants were added and incubated at room temperature for 1 h. After washing with TBST buffer, a 1:1000 dilution of goat anti-

RANKL variants escape obstruction of OPG

RANKL antibody (R&D Systems, Cat # BAF462, Lot # CLR0412011) was added and incubated for 1 h, and after washing, subsequently incubated with a 1:1000 anti-goat HRP- conjugated antibody (Millipore, Billerica,MA, USA). The signal was quantified using the One-step Turbo TMB reagent (ThermoScientific) and stopped by 100 µl of 1 M sulfuric acid solution. The absorbance was measured at 450 nm. The percentage of RANKL mutants bound to RANK-Fc or OPG-Fc was measured relative to the binding of RANKL_WT.

Kinetic analysis by Surface Plasmon Resonance

Binding experiments were determined using a Biacore 3000 system (GE Healthcare) at 25 °C. HBS-P buffer (10 mM HEPES, pH 7.4, 150 mM NaCl, 0.005% (v/v) surfactant P20; GE Healthcare) was used as a running buffer. A CM4 sensor chip (Biacore) was coated with 4 protein A (Sigma) in 10mM NaAc, pH 4.5. To achieve trimer-monomer complexes between ligand and receptors, RANK-Fc (sigma) and OPG-Fc (R&D Systems) were captured at a low density, not exceeding 60 RU, with a flow rate of 50 μl/min. RANKL was injected subsequently at in concentrations between 0.01 nM and 160 nM for 3 min, followed by a disassociation period for 1000 s. The chip surface was regenerated by two injections of 10 mM glycine, pH 1.5-2.0 (30 s). The response data was corrected for buffer effect and was fitted to a 1: 1 Langmuir model using the BIAEVALUATION software version 4.2.

Real-time quantitative PCR

Murine RAW 264.7 cells were a kind gift obtained from J. Doktor (University Medical Center Groningen, Groningen, The Netherlands). Cells were cultured in Dulbecco’s modified Eagle’s medium (Life Technologies, Carlsbad, CA, USA) with 10% v/v fetal calf serum (FCS, Life Technologies) and 2 mM penicillin/streptomycin (Life Technologies). RAW 264.7 cells were seeded at a density of 2×105 cells per well in a 12-well plate (Greiner) and allowed to adhere for overnight. On day 2, 50 ng /ml RANKL_WT, combination of 50 ng /ml RANKL_WT plus 400 ng /ml mOPG-Fc (R&D) and combinations of 50 ng /ml RANKL mutants plus 400 ng /ml mOPG-Fc were added to the cells for 24 h.

Cells of each treatment were harvested and total mRNA was extracted using Maxwell LEX simply RNA Cells/Tissue kit (Promega, Madison, WI) according to instruction described. The

Chapter 4 concentration of mRNA was measured using Nanodrop ND-100 spectrophotometer (Nanodrop Technologies, Wilmington, DE). cDNA was obtained through a reverse transcription reaction using M-MLV reverse transcriptase (Promega, Madison, WI) and random primers (Promega, Madison, WI).The quantitative real-time PCR was performed using SensiMixTM SYBR kit (Bioline, Taunton, MA) with the following specific primer sequences: GAPDH, 5’- ACAGTCCATGCCATCACTGC -3’ (forward) and 5’- GATCCACGACGGACATTG -3’ (reverse); MMP-9, 5’- GTCCAGACCAAGGGTACAGC -3’ (forward) and 5’- GCCTTGGGTCAGGCTTAGAG -3’ (reverse); TRAP, 5’- ACTTCCCCAGCCCTTACTACCG -3’ (forward) and 5’-TCAGCACATAGCCCACACCG - 3’ (reverse). Thermal cycling and fluorescence detection were performed using QuantStudio real time PCR System (Thermo Fischer) and Ct values were calculated using QuantStudio real time PCR software v1.3 (Thermo Fischer). For each sample, mRNA expression was normalized to GAPDH and calculated with the 2−ΔΔCt method.

Osteoclast differentiation assay

The biological activities of RANKL_WT and mutants were evaluated using trap activity assay. RAW 264.7 cells were seeded into a 96 well plate with a density of 2500 cells per well. On day 2, cells were treated with 25 ng/ml of RANKL with or without 200 ng/ml of mOPG-Fc. After 4 days treatment, cells were washed with PBS buffer and fixed with 4% formaldehyde (Sigma) at 37 °C for 1 h. After washing with PBS buffer, the cells were then lysed for 5 min with lysis buffer containing 0.2 M Sodium acetate, 20mM tartaric acid and 1% triton X-100. After lysis, the plate was centrifuged for 5 min at 1000 rpm and the supernatants were removed. The cells were then incubate with para-nitrophenylphosphate (pNPP) solution containing 20 mM pNPP, 0.2 M Sodium acetate, 20 mM tartaric acid and 30 mM potassium chloride (100 μl/well) at 37 °C for 1 h. The reaction was stopped with 1 M NaOH (100 μl/well) and the absorbance was measured at 405/410 nm using a microplate reader (Thermo Labsystems). The absorbance in the wells containing 25 ng/ml RANKL_WT was set to 100%.

The osteoclast differentiation assay was performed as well. As previously described [10], RAW 264.7 cells were seeded with a density of 1000 cells per well in a 96-well plate. At day 3 and day 5, cells were treated with 50 ng/ml of RANKL with or without 500 ng/ml of mOPG-Fc. At day 7, osteoclast formation was determined using the tartrate resistance acid phosphatase (TRAP) staining kit (Sigma) according to the manufacturer’s instructions.

RANKL variants escape obstruction of OPG

Multinucleated (three or more nuclei) TRAP-positive cells were treated as osteoclasts and counted under the microscope. The number of osteoclasts in the wells containing 50 ng/ml RANKL_WT was set to 100%.

Acknowledgements

This work was performed within the framework of the Dutch Top Institute Pharma project TNF-ligands in cancer (project nr. T3-112) and STW grant 11056. YW is a recipient of a scholarship from the Chinese Scholarship Council (CSC). We thank prof. B.N. Melgert and H. Habibie from Department of Molecular Pharmacology, Groningen Research Institute of Pharmacy, University of Groningen for their guidance and assistance in Real-time quantitative PCR measurement and TRAP activity assay. 4

Author contributions

YW, TM, RS, RM and RHC performed experiments and analyzed data; WJQ planned the research and supervised the study; YW and WJQ wrote the paper.

References

1 Trouvin AP & Goëb V (2010) Receptor activator of nuclear factor-κB ligand and osteoprotegerin: maintaining the balance to prevent bone loss. Clin Interv Aging 5, 345– 354. 2 Naidu VGM, Dinesh Babu KR, Thwin MM, Satish RL, Kumar P V. & Gopalakrishnakone P (2013) RANKL targeted peptides inhibit osteoclastogenesis and attenuate adjuvant induced arthritis by inhibiting NF-κB activation and down regulating inflammatory cytokines. Chem Biol Interact 203, 467–479. 3 Douni E, Rinotas V, Makrinou E, Zwerina J, Penninger JM, Eliopoulos E, Schett G & Kollias G (2012) A RANKL G278R mutation causing osteopetrosis identifies a functional amino acid essential for trimer assembly in RANKL and TNF. Hum Mol Genet 21, 784–798. 4 Lam J, Nelson CA, Ross FP, Teitelbaum SL & Fremont DH (2001) Crystal structure of the RANCE/RANKL cytokine reveals determinants of receptor ligand specificity. J Clin Investig 108, 971–979. 5 Ito S, Wakabayashi K, Ubukata O, Hayashi S, Okada F & Hata T (2002) Crystal structure

Chapter 4

of the extracellular domain of mouse RANK ligand at 2.2-Å resolution. J Biol Chem 277, 6631–6636. 6 Chaweewannakorn W, Ariyoshi W, Okinaga T, Fujita Y, Maki K & Nishihara T (2019) Ameloblastin attenuates RANKL-mediated osteoclastogenesis by suppressing activation of nuclear factor of activated T-cell cytoplasmic 1 (NFATc1). J Cell Physiol 234, 1745– 1757. 7 Rachner TD, Khosla S & Hofbauer LC (2011) Osteoporosis: now and the future. Lancet 377, 1276–1287. 8 Holen I & Shipman CM (2006) Role of osteoprotegerin (OPG) in cancer. Clin Sci 110, 279– 291. 9 Ta HM, Nguyen GTT, Jin HM, Choi J, Park H, Kim N, Hwang H-Y & Kim KK (2010) Structure-based development of a receptor activator of nuclear factor- B ligand (RANKL) inhibitor peptide and molecular basis for osteopetrosis. Proc Natl Acad Sci 107, 20281– 20286. 10 Wang Y, van Assen AHG, Reis CR, Setroikromo R, van Merkerk R, Boersma YL, Cool RH & Quax WJ (2017) Novel RANKL DE-loop mutants antagonize RANK-mediated osteoclastogenesis. FEBS J 284, 2501–2512. 11 Liu C, Walter TS, Huang P, Zhang S, Zhu X, Wu Y, Wedderburn LR, Tang P, Owens RJ, Stuart DI, Ren J & Gao B (2010) Structural and Functional Insights of RANKL-RANK Interaction and Signaling. J Immunol 184, 6910–6919. 12 Szalay F, Hegedus D, Lakatos PL, Tornai I, Bajnok E, Dunkel K & Lakatos P (2003) High serum osteoprotegerin and low RANKL in primary biliary cirrhosis. J Hepatol 38, 395– 400. 13 Todd NW, Luzina IG & Atamas SP (2012) Molecular and cellular mechanisms of pulmonary fibrosis. Fibrogenesis Tissue Repair 5, 11. 14 Murtha LA, Schuliga MJ, Mabotuwana NS, Hardy SA, Waters DW, Burgess JK, Knight DA & Boyle AJ (2017) The processes and mechanisms of cardiac and pulmonary fibrosis. Front Physiol 8, 1–15. 15 Wynn TA (2011) Integrating mechanisms of pulmonary fibrosis. J Exp Med 208, 1339– 1350. 16 Raghu G & Richeldi L (2017) Current approaches to the management of idiopathic pulmonary fibrosis. Respir Med 129, 24–30. 17 Florez-Sampedro L, Song S & Melgert BN (2018) The diversity of myeloid immune cells shaping wound repair and fibrosis in the lung. Regeneration, 3–25. 18 Beljaars L, Schippers M, Reker-Smit C, Martinez FO, Helming L, Poelstra K & Melgert BN (2014) Hepatic localization of macrophage phenotypes during fibrogenesis and resolution of fibrosis in mice and humans. Front Immunol 5, 430. 19 Boorsma CE, Draijer C & Melgert BN (2013) Macrophage heterogeneity in respiratory diseases. Mediators Inflamm 2013.

RANKL variants escape obstruction of OPG

20 Adhyatmika A, Putri KSS, Beljaars L & Melgert BN (2015) The elusive antifibrotic macrophage. Front Med 2, 1–11. 21 Tosi P (2013) Diagnosis and treatment of bone disease in multiple myeloma: spotlight on spinal involvement. Scientifica (Cairo) 2013, 1–12. 22 Okamoto K, Nakashima T, Shinohara M, Negishi-Koga T, Komatsu N, Terashima A, Sawa S, Nitta T & Takayanagi H (2017) Osteoimmunology: The conceptual framework unifying the immune and skeletal systems. Physiol Rev 97, 1295–1349. 23 Toffoli B, Pickering RJ, Tsorotes D, Wang B, Bernardi S, Kantharidis P, Fabris B, Zauli G, Secchiero P & Thomas MC (2011) Osteoprotegerin promotes vascular fibrosis via a TGF-β1 autocrine loop. Atherosclerosis 218, 61–68. 24 Ambroszkiewicz J, Sands D, Gajewska J, Chelchowska M & Laskowska-Klita T (2013) Bone turnover markers, osteoprotegerin and RANKL cytokines in children with cystic fibrosis. Adv Med Sci 58, 338–343. 25 García-Valdecasas-Campelo E, González-Reimers E, Santolaria-Fernández F, De la Vega- Prieto MJ, Milena-Abril A, Sánchez-Pérez MJ, Martínez-Riera A & De Los Ángeles 4 Gómez-Rodríguez M (2006) Serum osteoprotegerin and rankl levels in chronic alcoholic liver disease. Alcohol Alcohol 41, 261–266. 26 Reis CR, van Assen AHG, Quax WJ & Cool RH (2011) Unraveling the binding mechanism of trivalent tumor necrosis factor ligands and their receptors. Mol Cell Proteomics 10, M110.002808. 27 Eriksen EF (2010) Cellular mechanisms of bone remodeling. Rev Endocr Metab Disord 11, 219–227. 28 Kim J & Kim N (2016) Signaling Pathways in Osteoclast Differentiation. Chonnam Med J 52, 12–17. 29 Feng W, Li W, Liu W, Wang F, Li Y & Yan W (2009) IL-17 induces myocardial fibrosis and enhances RANKL/OPG and MMP/TIMP signaling in isoproterenol-induced heart failure. Exp Mol Pathol 87, 212–218. 30 Renema N, Navet B, Heymann M-F, Lezot F & Heymann D (2016) RANK-RANKL signalling in cancer. Biosci Rep 36, e00366. 31 Bosman MCJ, Reis CR, Schuringa JJ, Vellenga E & Quax WJ (2014) Decreased affinity of recombinant human tumor necrosis factor-related apoptosis-inducing ligand (rhTRAIL) D269H/E195R to osteoprotegerin (OPG) overcomes trail resistance mediated by the bone microenvironment. J Biol Chem 289, 1071–1078. 32 Van der Sloot AM, Tur V, Szegezdi E, Mullally MM, Cool RH, Samali A, Serrano L & Quax WJ (2006) Designed tumor necrosis factor-related apoptosis-inducing ligand variants initiating apoptosis exclusively via the DR5 receptor. Proc Natl Acad Sci U S A 103, 8634–8639. 33 Nelson C a, Warren JT, Wang MWH, Teitelbaum SL & Fremont DH (2013) RANKL employs distinct binding modes to engage RANK and the OPG decoy receptor Christopher. Structure 20, 1971–1982.

Chapter 4

34 Luan X, Lu Q, Jiang Y, Zhang S, Wang Q, Yuan H, Zhao W, Wang J & Wang X (2016) Crystal structure of human RANKL complexed with its decoy receptor opsteoprotegerin. J Immunol 189, 245–252. 35 Tur V, Van der Sloot AM, Reis CR, Szegezdi E, Cool RH, Samali A, Serrano L & Quax WJ (2008) DR4-selective tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) variants obtained by structure-based design. J Biol Chem 283, 20560–20568. 36 Julia T. Warren, Wei Zou, Corinne E. Decker, Nidhi Rohatgi, Christopher A. Nelson1, Daved H. Fremont and SLT (2015) Correlating RANK Ligand/RANK Binding Kinetics with Osteoclast Formation and Function. J Cell Biochem 116, 2476–2483. 37 Rockey DC, Bell PD & Hill JA (2015) Fibrosis - a common pathway to organ injury and failure. N Engl J Med 372, 1138–1149. 38 Said A & Lucey MR (2008) Liver transplantation: an update 2008. Curr Opin Gastroenterol 24, 339–345. 39 Tang L, Gao H, Zhu X, Wang X, Zhou M & Jiang R (2012) Construction of ―small- intelligent‖ focused mutagenesis libraries using well-designed combinatorial degenerate primers. Biotechniques 52, 149–158. 40 Abdallah II, Van Merkerk R, Klumpenaar E & Quax WJ (2018) Catalysis of amorpha- 4,11-diene synthase unraveled and improved by mutability landscape guided engineering. Sci Rep 8, 1–11.

Abbreviations

OPG - Osteoprotegerin RANK - Receptor Activator of Nuclear Factor-κB RANKL - Receptor Activator of Nuclear Factor-κB-ligand mRANK - murine RANK mRANKL - murine RANK-ligand TNF - Tumor Necrosis Factor TRAIL - Tumor Necrosis Factor Related Apoptosis Inducing Ligand ECM - extracellular matrix TRAP – tartrate resistant acid phosphatase MMP - matrix metallopeptidase TGF-β - transforming growth factor beta

Chapter 5

Long term secretion of adenovirally-expressed RANKL WT/ Q236D for treatment of fibrosis

Yizhou Wang*, Olivia Adaly Diaz Arguello*, Rita Setroikromo, Fengzhi Suo, Hidde J. Haisma and Wim J. Quax#

Department of Chemical and Pharmaceutical Biology, Groningen Research Institute of Pharmacy, University of Groningen, A. Deusinglaan 1, 9713 AV Groningen, The Netherlands

* Both authors equally contributed to this manuscript

Manuscript to be submitted

Chapter 5

Abstract

Fibrosis is a pathological process characterized by excessive accumulation of extracellular matrix (ECM) in an organ and is a leading cause of morbidity and mortality in chronic inflammatory diseases. The receptor activator of nuclear factor NF-κB ligand (RANKL)/ RANK/Osteoprotegerin (OPG) cytokine system was first discovered to provide a major role in bone homeostasis. Alveolar macrophages express RANK and binding of its ligand RANKL, induces ECM degradation. We have demonstrated the potential anti-fibrosis activity of RANKL variant RANKL_Q236D with a decreased affinity to OPG. In the present study, we constructed replication-deficient adenoviruses Ad-RANKL WT and Ad-RANKL Q236D to achieve a targeting delivery system by directly delivering RANKL_Q236D to the fibrotic tissues without influencing other tissues. Virally produced RANKL_WT and RANKL_Q236D activated RAW 264.7 macrophages and RANKL_Q236D escaped from inhibition by exogenous OPG. Secreted RANKL protein was detected up to 19 days after infection with protein levels up to 30 nM. The generation of Ad-RANKL Q236D is a powerful new tool for the treatment of fibrosis.

Keywords: Adenovirus, fibrosis, OPG, RANKL

Potential anti-fibrosis activity of Adenovirally-expressed RANKL Q236D

Introduction

Fibrosis is a pathological process characterized by excessive accumulation of extracellular matrix (ECM) in an organ and this scarring process causes up to 45% of total deaths worldwide [1]. Although fibrosis is recognized to be a major cause of morbidity and mortality in individuals with chronic inflammatory diseases, there are few treatment strategies and hardly any that specifically target fibrogenesis [2–4]. In most cases, fibrosis is initiated by primary injury to the organ and followed by the activation of effector cells, the deposition of the ECM and finally by organ failure [2]. Fibroblasts and myofibroblasts, which are involved in the production of ECM, are the key mediators to the pathogenesis of all fibrotic diseases [3]. Therefore, research is focused on the deactivation and elimination of myofibroblasts. Degradation of ECM including the activation of matrix metalloproteinases (MMPs), which digest the collagen and other ECM proteins, is also one of the important principles of fibrosis regression and resolution [5,6]. 5 The cytokine system, consisting of the receptor activator of nuclear factor NF-κB ligand (RANKL), RANK and Osteoprotegerin (OPG), was first discovered to provide a major role in controlling osteoclast differentiation and activation in bone homeostasis [7]. The binding between RANKL, which is expressed on osteoblasts, and RANK on osteoclast precursors induces the recruitment of TNF receptor-associated factors (TRAFs) [8]. Notably, TRAF6 transmits the RANKL/RANK signal to downstream targets to induce the expression of osteoclast-specific genes, including tartrate-resistant acid phosphatase (TRAP), cathepsin K, and matrix metallopeptidase 9 (MMP9), which will further trigger osteoclast formation and bone ECM degradation [7–9]. As the natural decoy receptor of RANKL, OPG inhibits the RANKL/RANK interaction and blocks the maturation of osteoclasts [10]. Interestingly, apart from bone, RANK is also expressed on macrophages in many other tissues, and RANKL stimulation could induce proteases release [11]. Therefore, the RANKL/RANK axis may also play a role in fibrotic tissue to activate macrophages and reverse fibrosis [11].

Notably, OPG was shown to have pro-fibrotic effects on the vasculature [12,13] and increased levels of OPG were found to be related to fibrotic tissue formation in liver and cystic fibrosis [14,15]. Therefore, in our previous research, we hypothesized that RANKL could stimulate RANK on macrophages and trigger ECM degradation in fibrotic conditions, which may be blocked by highly expressed OPG [9]. Based on the hypothesis, we generated a structure- based mutant RANKL_Q236D, which could activate murine RAW 264.7 macrophage cells

Chapter 5 effectively while escaping from the inhibition by exogenous OPG. The anti-fibrotic effect of RANKL_Q236D should be evaluated in vivo. However, as the RANKL/RANK/OPG system is also important in other tissues, a targeted delivery system is needed to supply RANKL_Q236D directly to fibrotic tissues without influencing the bone remodeling and homeostasis of other normal tissues.

Adenovirus has received tremendous attention as a gene delivery vehicle for therapeutic use due to its high genetic stability, high transduction efficiency and easy production [16,17]. Recombinant replication-defective adenoviruses show increased biological safety and further improved the use of gene therapy [18]. Among all the vectors registered in clinical gene therapy trials up to 2017 all over the world, adenoviral vectors occupied the most with approximately 21% of all registry [17]. Adenoviral vectors with intravenous administration predominantly target and infect hepatic Kupffer cells in the liver [19], which could be a natural advantage for adenoviral vectors encoding RANKL_Q236D to target liver fibrotic tissue. Related research showed that a single injection of adenoviral vectors expressing BMP- 7 could suppress the development of hepatic fibrosis in rats [20]. This strengthens the use of the adenovirus system in fibrosis treatment. On the other hand, local administration to the tissue of interest could also be achieved, for example, intranasal administration or inhalation may directly bring the adenoviral vectors to the lung tissue.

In the present study, to achieve a targeting delivery system that can directly deliver RANKL_Q236D to the fibrotic tissues, we constructed replication-deficient adenoviruses Ad- RANKL WT and Ad-RANKL Q236D, and evaluated virally produced RANKL_WT and RANKL_Q236D. Virally produced RANKL_Q236D activated RAW 264.7 macrophages and escaped from the inhibition by exogenous OPG.

Results

Construction and characterization of adenoviral vectors expressing RANKL WT/Q236D

We constructed the soluble form of mouse RANKL WT/Q236D containing the C terminal 157 amino acids of full-length sequence previously [22]. To encourage the correct folding and secretion of RANKL WT/Q236D in a eukaryotic expression system, an Igκ signal peptide sequence was fused with the RANKL fragment. This was predicted to allow efficient removal of the signal sequence and leave six amino acids, AAQPAG, at the N-terminal of RANKL. A

Potential anti-fibrosis activity of Adenovirally-expressed RANKL Q236D recombinant adenoviral vector expressing this soluble form of mouse RANKL WT/Q236D was constructed with the AdEasy system (Fig. 1A) [18], and Ad-RANKL WT/Q236D were obtained successfully with virus titers of 6.31×109 and 3.10×1010 pfu/ml, respectively (Suppl. Fig. 1). Mouse lung epithelial C10 cells showed increased GFP signals after 48 h infection, indicating that Ad-RANKL WT/Q236D were effectively transduced to C10 cells (Fig. 1B). The production and secretion of RANKL_WT and RANKL_Q236D were confirmed by western blot, shown in Fig. 1C. For both RANKL_WT and RANKL_Q236D, two bands at approximately 17 KD and 20 KD were detected, which can be explained by a difference in glycosylation [23]. To further confirm the trimerization of the secreted RANKL_WT/Q236D, the supernatants of C10 cells after Ad-RANKL WT/Q236D infection were loaded to a size exclusion chromatography column (Superdex 75 16/60), and the elution time of RANKL_WT/Q236D indicated the trimeric complex formation (Suppl. Fig. 2). Together, this indicates that Ad-RANKL WT /Q236D was constructed successfully and virally produced RANKL_WT and RANKL_Q236D was secreted by C10 cells. 5

Fig 1. Construction and characterization of adenoviral vectors expressing RANKL WT/Q236D. A) Construction of Ad-RANKL WT/Q236D by using the AdEasy system. LITR and RITIR: Inverted terminal repeats (Left and right), PacI and PmeI: endonuclease restriction sites; B) Transduction efficiency of AdTL (the control virus) and Ad-RANKL WT/Q236D monitored by GFP signals after 48 h infection; C) Production of RANKL WT/Q236D determined by western blot (1-non treated control; 2-AdTL; 3-Ad-RANKL WT; 4-Ad-RANKL Q236D).

Chapter 5

Long-term production of adenoviral vectors expressing RANKL WT/Q236D

To further determine the long-term production of protein by adenoviral vectors expressing RANKL WT/Q236D, we have traced the production levels of both proteins for 19 days. After infection of Ad-RANKL WT/Q236D (25 MOI) of C10 cells, the medium was changed every 3 to 4 days, and the production of RANKL_WT and RANKL_Q236D from each fraction was determined by western blot. As shown in Fig. 2, after infection, C10 cells kept producing RANKL proteins. Both RANKL_ WT and RANKL_Q236D could be detected until day 19 after infection with protein levels up to 30 nM, and the highest production levels were found on day 5. This indicates the long-term effects of delivering the proteins via Ad-RANKL WT/Q236D.

Fig 2. Long-term production of adenoviral vectors expressing RANKL WT/Q236D. The production of adenoviral vectors expressing RANKL WT/Q236D from each fraction was determined by western blot of supernatant fractions.

Binding activity of adenoviral vectors expressing RANKL WT/Q236D to different receptors

Binding and specificity of the virally produced RANKL_WT or RANKL_Q236D to the immobilized RANK-Fc and OPG-Fc receptors were assessed by using ELISA. The 96 well plates were immobilized with 10 nM of RANK-Fc or OPG-Fc respectively. Virally produced RANKL_WT or RANKL_Q236D was first quantified by Western Blot, and then added to the plate at a concentration of 100 nM. As shown in Fig. 3, RANKL_WT and RANKL_Q236D could bind to RANK-Fc properly (Fig. 3A), while RANKL_Q236D showed a 70% lower

Potential anti-fibrosis activity of Adenovirally-expressed RANKL Q236D binding to OPG-Fc compared to RANKL_WT (Fig. 3B). The supernatants from C10 cells non-transduced or transduced with AdTL were added as negative controls and there was no signal detected. This demonstrates that the binding of virally produced RANKL_WT or RANKL_Q236D to RANK-Fc and OPG-Fc receptors is consistent with the values obtained by previous ELISA experiments for purified bacterially-expressed RANKL_WT or RANKL_Q236D [9]. The RANKL_Q236D mutation has no influence on the binding to RANK-Fc and it escapes from binding to the decoy receptor OPG.

Fig 3. Binding activity of adenoviral vectors expressing RANKL WT/Q236D to different receptors. ELISA was performed to show the binding of adenoviral vectors expressing RANKL WT/Q236D to RANK-Fc (A) and OPG-Fc (B). The group with only receptors was served as the negative control, and the binding of adenoviral vectors expressing RANKL WT to the receptors was served as 100%. Groups were compared using a Student‘s t-test: (***) is P < 0.001. The error bars reflect the standard deviation (SD) of three independent experiments.

Biological activity of adenovirally-expressed RANKL WT/Q236D

To confirm that infected C10 cells produced biologically active proteins, we used RAW macrophage reporter cell line (RAW-Blue cell) to examine the effect of the virally produced RANKL_WT or RANKL_Q236D on the NF-κB pathway, where the SEAP reporter gene is integrated into the chromosome and driven by an NF-κB-inducible promoter (Fig. 4A). As shown in Fig. 4B, after 24 h treatment, C10 supernatants containing virally produced RANKL_WT and RANKL_Q236D at a concentration of 50 ng/ml increased SEAP release by

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3.5 and 4 fold over untreated control cells, respectively, while pure RANKL_WT protein caused a comparable induction of SEAP (5 fold) at the same concentration. The supernatants from C10 cells with non-transduced or transduced with AdTL showed no induction of SEAP activity. This indicates that infected C10 cells produced and secrete biologically active RANKL_WT and RANKL_Q236D proteins.

Fig 4. Biological activity of adenoviral vectors expressing RANKL WT/Q236D. A) NF-κB signaling pathway in SEAP expression; B) Relative NF-κB-SEAP activity was determined by a colorimetric enzyme assay and absorbance was measured at 650 nm. The signal caused by the RAW-Blue cells without any treatment served as the negative control. NC represents the negative control group that cells treated with only medium; (-) represents the group treated with the medium from C10 cells with non-virus infection. Groups were compared using a Student‘s t-test: (***) is P < 0.001. The error bars reflect the SD of three independent experiments.

Effect of adenovirally-expressed RANKL WT/Q236D on TRAP activity of RAW 264.7 cells and blocking by OPG-Fc

A high level of OPG was found to be related to fibrosis formation in different tissues like liver vasculature and heart [12,15,24]. Therefore, to further confirm the potential of adenoviral vectors expressing RANKL WT/Q236D, we next tested their effects on TRAP activity in the presence of OPG-Fc. RAW 264.7 cells were treated with virally produced RANKL_WT or RANKL_Q236D, which were first quantified by western blot. After 4 days of incubation, the cells were evaluated for TRAP activity. As shown in Fig. 5, both virally produced RANKL_WT and RANKL_Q236D could significantly induce TRAP activation,

Potential anti-fibrosis activity of Adenovirally-expressed RANKL Q236D which was comparable to the activity induced by pure RANKL_WT/ Q236D protein. Interestingly, after the addition of OPG-Fc, virally produced RANKL_WT exhibited less TRAP activity, which dropped 50% and 90% in the presence of 100 ng/ml and 200 ng/ml of OPG-Fc, respectively. With the addition of OPG-Fc in the same concentrations, virally produced RANKL_Q236D fully maintained the TRAP activity by escaping from the inhibition by OPG-Fc. On the other hand, the supernatants from C10 cells non-transduced or transduced with AdTL showed no induction of TRAP activity, which is comparable with the effect caused by the medium control. Taken together, virally produced RANKL_Q236D maintained activation of RAW 264.7 cells and escaped from the inhibition by exogenous OPG.

Fig 5. Effect of adenoviral vectors expressing RANKL WT/Q236D on TRAP activity of RAW 264.7 cells in the presence of OPG-Fc. TRAP activity obtained after treatment of murine RAW 264.7 cells with adenoviral vectors expressing RANKL WT/Q236D or pure RANKL_WT/ Q236D protein with different amounts of mOPG-Fc. The signal caused by the RAW 264.7 cells treated with only virally produced RANKL WT was considered as 100%. Graph is mean ± SD from two independent experiments performed in triplicate.

Co-incubation system

To further mimic the process of adenovirus infection in vivo, we set up a co-incubation transwell system, where C10 cells were cultured in the lower chamber and infected with Ad- RANKL WT/Q236D or AdTL. RAW 264.7 macrophages were seeded in the insert separated

Chapter 5 by a polycarbonate membrane, which allowed the free diffusion of the RANKL WT/Q236D proteins (Fig. 6A). After co-incubation for 44 h, RAW 264.7 cells were collected and real- time quantitative PCR was performed to detect the MMP9 gene expressions. As shown in Fig. 6B, RANKL WT protein produced by C10 cells after Ad-RANKL WT infection could stimulate and significantly induce the expression of MMP9 in the target RAW 264.7 cells, which was blocked by adding exogenous mOPG-Fc (400 ng/ml). Notably, the activation of MMP9 was not inhibited by the presence of mOPG-Fc in the Ad-RANKL Q236D infection group. At the same conditions using Ad-TL infection with or without mOPG-Fc, no MMP9 activity was induced. Taken together, in the co-incubation system, Ad-RANKL Q236D infection is capable of activating MMP9 gene expression in RAW 264.7 cells, which indicates a potential role of Ad-RANKL Q236D in treating fibrotic tissue.

Fig 6. mRNA levels of ECM-degrading enzyme MMP-9, after the co-incubation transwell system, determined by real-time quantitative PCR. A) Co-incubation transwell system; B) MMP-9 gene expression. Graph is mean ± SD from two independent experiments performed in triplicate.

Discussion

Fibrosis is an out of control wound-healing response, which results from chronic inflammatory reactions [25]. Long term inflammation, tissue destruction and repair processes cause an extra accumulation of ECM, which leads to pathogenic fibrosis formation [25]. Facing that fibrosis is the leading cause of morbidity and mortality among chronic inflammatory diseases, the demand for antifibrotic drugs is enormous. However, up to now, there are only two antifibrotic drugs, pirfenidone and nintedanib, that have been approved for

Potential anti-fibrosis activity of Adenovirally-expressed RANKL Q236D treating idiopathic pulmonary fibrosis [6], and no specific therapy for other organ fibrosis like liver, kidney or heart fibrosis exists [5]. It is challenging to translate the experimental research in fibrosis into clinical practice, partly because most of the antifibrotic targets are tested in a single organ type or species, and most cases bring negative results or limited effects in human fibrosis [26]. Therefore, it is still needed to fully understand the mechanisms of fibrosis, and the demand for effective antifibrotic therapies remains enormous.

In 2011, the concept ―core mechanisms of fibrosis‖ came up, which stipulates the pathways crucial to converting the initial stimulus in fibrosis development to different organs [5,26]. ECM remodeling is one of these core mechanisms. Collagens are the major components of ECM, which are regulated by collagen synthesis (myofibroblasts) and collagen catabolism (proteolytic enzymes such as MMPs) [25]. Previous research showed that macrophage depletion in the fibrosis recovery phase caused a failure of matrix degradation, suggesting that macrophages might be important for ECM degradation [27]. Interestingly, many tissue macrophages express RANK, and RANKL-RANK binding could stimulate proteolytic 5 enzymes release, which further degrades ECM [11]. In fibrotic tissue, the decoy receptor OPG is highly expressed, which may block the RANKL-RANK axis and thereby the degradation of ECM [12,14,15]. The generation of structure-based mutant RANKL_Q236D with decreased affinity to OPG is a promising strategy for developing a novel antifibrotic drug [9]. However, as the cytokine system RANKL/RANK/OPG also plays an important role in other tissues, an organ-specific delivery system for RANKL_Q236D is essential and necessary.

In this study, we constructed replication-deficient adenoviruses Ad-RANKL WT and Ad- RANKL Q236D, and the functionality of virally produced RANKL_WT and RANKL_Q236D was analyzed (Figs. 3 and 4). Previous research, which established a murine model of hypercalcemia with anorexia by using an adenovirus vector to overexpress RANKL offered us the feasibility to generate functional virally produced RANKL_Q236D [28]. Adenovirus-mediated expression of the bone morphogenetic protein (BMP)-7 suppressed liver fibrosis development in rats, which further confirmed the possibility of using an adenoviral delivery system for fibrosis treatment [20]. As fibrosis results from chronic inflammation and is considered as a long term chronic disease, a long term administration is required for the treatment. Protein therapies usually show short half-lives. Taking the other TNF superfamily member TRAIL as an example, the half-life of rhTRAIL is only 3-5 minutes in rodents and a half-hour in non-human primates [29]. By generating an adenovirus Ad-scFv425:sTRAIL, which encodes the cDNA of fused scFv425 and sTRAIL, only single

Chapter 5 i.v. injection of Ad-scFv425:sTRAIL in tumor-free nu/nu mice could achieve high blood plasma levels of scFv425:sTRAIL even after 64 days [19]. We also achieved long term production of virally expressed RANKL WT/Q236D and both proteins could be detected until day 19 after a single infection (Fig. 2). This indicates the long-term potential of Ad-RANKL WT/Q236D. Notably, the antifibrotic effect of Ad-RANKL Q236D needs to be evaluated in vivo, which will be one of our future activities.

Another advantage of the adenoviral delivery system is the organ-specific delivery without influencing other tissues. Adenoviral vectors after intravenous administration predominantly target and infect hepatic Kupffer cells in the liver [19], which could help adenoviral vectors encoding RANKL_Q236D to directly target liver fibrotic tissue. On the other hand, targeting other organs should be achieved by local administration or virus modification. The deposition of viruses by inhalation in the lung might be evaluated as a treatment for lung fibrosis.

In conclusion, we have constructed replication-deficient adenoviruses Ad-RANKL WT and Ad-RANKL Q236D, and showed functional expression of virally produced RANKL_WT and RANKL_Q236D. Virally produced RANKL_Q236D activated the NF-κB pathway in RAW 264.7 cells and was insensitive to inhibition by exogenous OPG. The generation of Ad- RANKL Q236D may be a powerful new tool for the treatment of fibrosis.

Materials and Methods

Cell lines and cell culture

RAW 264.7 cell and HEK293T cell lines were purchased from American Type Culture Collection (ATCC, Wesel, Germany). Murine RAW-Blue cells are derived from RAW 264.7 macrophages, where the Secreted Embryonic Alkaline Phosphatase (SEAP) reporter gene is integrated into the chromosome and driven by an NF-κB-inducible promoter, were obtained from InvivoGen (San Diego, CA). Non-transformed C10 cells are alveolar type II epithelial cells derived from normal BALB/c mouse lungs, were kindly provided by Dr. B. N. Melgert (Groningen Research Institute of Pharmacy, Groningen, the Netherlands). RAW 264.7, RAW- Blue and HEK293T cells were maintained in DMEM (Life Technologies, Carlsbad, CA, USA), while C10 cells were cultured in PRMI1640 medium(Life Technologies, Carlsbad, CA, USA), both supplemented with 10% v/v FBS (Life Technologies) and 2 mM

Potential anti-fibrosis activity of Adenovirally-expressed RANKL Q236D penicillin/streptomycin (Life Technologies). Cells were cultured at 37 °C in a 5% CO2 atmosphere.

Construction and production of Ad vector containing RANKL WT/Q236D

Ad-RANKL WT/Q236D was generated by introducing the gene encoding mouse soluble RANKL WT/Q236D into the E1- and E3-deleted replication-incompetent Ad-5 adenovirus using the Ad-Easy system [18]. Briefly, cDNA encoding mRANKL WT/Q236D (aa 160–316) was first cloned in pSecTag (Invitrogen, Groningen, The Netherlands) using SfiI and NotI restriction sites. A fragment containing the immunoglobulin κ chain leader sequence (Igκ) and the mRANKL WT/Q236D sequence was excised from pSecTag-RANKL WT/Q236D and cloned into pAdTRACK-CMV using HindIII and EcoRV restriction sites.

Then the vector was linearized by PmeI restriction endonuclease and transformed by electroporation into E.coli strain BJ5183pAdEasy1. The homologous recombination between 5 pAdTRACK-CMV-RANKL WT/Q236D and AdEasy1 assembled the full length of the adenovirus genome. Individual colonies were selected and the plasmids were isolated. Next, the vectors were transformed into E. coli strain DH5 to generate a large stock of plasmid that was analyzed by restriction fragment length analysis with PacI to confirm the right recombinants[18]. After the screening, the linearized vector was transfected into HEK293 cells to generate the recombinant adenoviruses.

Purification and Quantification of Ad vector containing RANKL WT/Q236D

HEK293T cells (25 000 cells/cm2; 5× T175 flasks) were infected with adenoviral particles containing RANKL WT/Q236D, and then incubated until complete cytotoxicity from penton base (CPE). The cells were harvested, resuspended in 2 ml buffer A (50 mM Tris-HCl, pH

8.00; 1 mM MgCl2) and lysed by 3-4 freeze-thaw-vortex cycles. After spinning for 10 min at 100 g, the supernatants were diluted 5 times with application buffer (50 mM Tris-HCl, 0.1 mM MgCl, pH 8) and loaded on a 5 mL HiTrap Q XL column (GE Healthcare; Illinois, USA). After washing the column with washing buffer (application buffer plus 0.3 M NaCl), the virus was then eluted with elution buffer (application buffer plus 0.6 M NaCl). Finally, the column was cleaned by cleaning buffer (application buffer plus 1 M NaCl) and cleaning solution (0.1

Chapter 5

M NaOH). The fractions from each step were collected during the chromatography. 10 l of each fraction was treated with lysis buffer (PBS, 20% SDS, 0.5 M EDTA) and incubated at 56ºC for 10 min, followed by measuring the absorbance at 260/280 nm. Once that the fractions containing virus were identified, the viruses were concentrated and the buffer was replaced by storage buffer (20 mM Tris-HCl, pH 8.00; 25 mM NaCl, 5% v/v glycerol) by using a VivaSpin 2 (300,000 MWCO, Sartorius; Göttingen, Germany). The viruses were aliquoted and stored at -80ºC; The quantification of virus was done by using a serial limiting dilution of the viruses where HEK293T cells were used to detect the plaque-forming units (PFU/ml).

Infection of C10 cells with Ad-RANKL WT/Q236D

Cells were seeded at a density of 2.5×105 cells per well in a 6-well plate and were allowed to adhere overnight. Infections with Ad-RANKL WT/Q236D and the control virus AdTL were performed by transducing cells with 50 multiplicity of infection (MOI). Green fluorescent protein (GFP) served as a marker for infection. After 48 hours of incubation medium was collected and analyzed.

To measure the long-term protein production by adenoviral vectors in vitro, C10 cells were seeded at a density of 1.5×105 cells per well in a 6-well plate overnight and then treated with Ad-RANKL WT/Q236D at 25 MOI. After infection for 1.5 h, medium containing virus was removed and the cells were washed twice with PBS. The cells were then cultured with 2% FBS for 19 days. The medium was collected and changed every 3 or 4 days. 20 l of each fraction was used to test the expression of RANKL_WT/Q236D.

Western Blot

The secretion of protein RANKL WT/Q236D from C10 cells after Ad- RANKL WT/Q236D infection was detected by Western Blot. An equal volume of each collected medium sample was mixed with sample buffer (4×) and boiled for 10 min. Twenty microliters of each sample were separated by 12% SDS-PAGE and transferred to a polyvinylidene difluoride (PVDF) membrane. The membrane was blocked with 10% skimmed milk in PBST for 1 h at room temperature (RT) and followed by the incubation with Goat-anti-mRANKL antibody 4°C

Potential anti-fibrosis activity of Adenovirally-expressed RANKL Q236D overnight. After washing with PBST, anti-goat HRP-conjugated secondary antibody was added with a dilution of 1:1000 and incubated at RT for half-hour. The protein bands were visualized by Western Lightning Plus-ECL kit (GE Healthcare, Buckinghamshire, UK) and subsequently, the membrane was exposed using GeneSnap Image machine (SynGene, Frederick, MD, USA). To calculate the concentrations of the secreted RANKL WT/Q236D by C10 cells after Ad- RANKL WT/Q236D infection, pure mRANKL protein produced by E. coli BL21(DE3) cells with different dilutions were loaded as standards and the protein bands were quantified by Image J software.

ELISA

The binding activity of secreted RANKL WT/Q236D in the supernatants of C10 cells transduced with Ad-RANKL WT/Q236D was detected by ELISA as previously described [9]. Murine RANK-Fc (Sigma) and murine OPG-Fc (R&D) at a concentration of 10 nM were 5 immobilized on a 96-well high binding plate (Greiner, Frickenhausen, Germany) at 4 °C overnight, respectively. After washing with PBST buffer, the plate was blocked with 2% w/v BSA (Roche, Mannheim, Germany) in PBST for 2 h at RT. Subsequently, 100 μl of each collected medium was added and incubated at RT for 1 h. After washing with PBST buffer, the goat-anti-mRANKL antibody at a dilution of 1:1000 was added and incubated for 1 h, and after washing, the plate was incubated with a 1: 1000 anti-goat HRP-conjugated secondary antibody. The signal was detected by adding 100 μl of the One-step Turbo TMB reagent and stopped by 100 μl of 1 M sulfuric acid solution. The absorbance was measured at 450 nm. The supernatants from cells with non-transduced or transduced with AdTL served as negative controls. The binding of supernatant containing RANKL WT to RANK-Fc and OPG-Fc was set to 100%.

Quanti-blue assay

The activation of NF-κB pathway caused by virally produced RANKL WT and RANKL Q236D were detected by the Quanti-blue assay, where a SEAP colorimetric detection medium was used according to the manufacturer‘s instruction [21]. RAW blue cells were plated in 96- well plates at the concentration of 1×105 cells/well. The collected medium from Ad-RANKL WT/Q236D infected C10 cells was first diluted to 50 ng/ml and then added to the plate (100

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μl/well). The medium from C10 cells with the non-virus infection or control virus infection was also added to the plate as negative controls. Escherichia coli produced mouse RANKL protein at 50 ng/ml was added as the positive control. After 24 h treatment, 100 μl of supernatants were transferred to a new 96-well plate and incubated with 100 μl pre-warmed Quanti-Blue™ reagent for 30 min at 37°C, and OD 650 nm was measured.

Tartrate-resistant acid phosphatase (TRAP) activity assay

In order to evaluate the effect of virally produced RANKL WT and RANKL Q236D on the activation of TRAP, which is an ECM degradation enzyme, RAW 264.7 cells were seeded at a 96-well plate with the amount of 2500 cells per well. On day 2, the collected medium from C10 cells after the infection of Ad-RANKL WT/Q236D at 25 ng/ml was added to RAW 264.7 cells with or without 200 ng/ml of mOPG-Fc. Escherichia coli produced mouse RANKL_WT of RANKL_Q236D at a concentration of 25 ng/ml was added as control. After 4 days of treatment, cells were fixed with 4% formaldehyde (Sigma) at 37 °C for 1 h and lysed with lysis buffer (0.2 M Sodium acetate, 20 mM tartaric acid, and 1% Triton X-100) for 5 min, in between washed with PBS. After centrifugation at 1000 rpm for 5 min, the supernatants were removed and 100 μl para-nitrophenylphosphate (pNPP) solution (20 mM pNPP, 0.2 M Sodium acetate, 20 mM tartaric acid, and 30 mM potassium chloride) was added to each well and incubated at 37 °C for 1 h. The reaction was stopped with 1 M NaOH and the absorbance was measured at 405/410 nm using a microplate reader (Thermo Labsystems, Beverly, MA, USA).

Transwell experiment

A transwell was used to build up a co-culture system. RAW 264.7 cells were seeded in the insert of a 12-well plate at a density of 1×105 cells/well. C10 cells were seeded in a separate 12-well plate at a density of 1 ×105 cells/well and infected with Ad-RANKL WT/Q236D (35 MOI). After 1.5 h infection, C10 cells were washed twice with PBS and replaced with fresh medium. Then the inserts were gently transferred to the plate containing RAW 264.7 cells. After incubation at 37 °C for 44 h with or without 400 ng/ml of mOPG-Fc, RAW 264.7 cells were harvested for detection of ECM degradation enzymes expression.

Potential anti-fibrosis activity of Adenovirally-expressed RANKL Q236D

Real-time quantitative PCR

The expression of osteoclast-specific genes was examined by real-time quantitative PCR as previously described [9]. After cells of each treatment were harvested, total mRNA was extracted by Maxwell LEX simply RNA Cells/Tissue kit (Promega, Madison, WI, USA) and cDNA was obtained from a reverse transcription reaction using AMV reverse transcriptase (Promega). The real-time quantitative PCR was performed using the Sensi MixTM SYBR kit (Bioline, Taunton, MA, USA) and QuantStudio real-time PCR System. For each sample, mRNA expression was normalized to GAPDH. The specific primer sequences are provided as follows: GAPDH, 5‘-ACAGTCCATGCCATCACTGC-3‘ (forward) and 5‘- GATCCACGACGGACATTG-3‘ (reverse); MMP-9, 5‘-GTCCAGACCAAGGGTACAGC-3‘ (forward) and 5‘-GCCTTGGGTCAGGCTTAGAG-3‘ (reverse).

5 Acknowledgements

This study was supported by the Dutch Science Foundation (NWO/STW) (grant 11056), European Fund for Regional Development (KOP/EFRO) (grants 068 and 073), the Chinese Scholarship Council, and the Mexican National Council for Science and Technology (CONACyT).

Conflict of interest

The authors declare no conflict of interest.

References

1 Murtha LA, Schuliga MJ, Mabotuwana NS, Hardy SA, Waters DW, Burgess JK, Knight DA & Boyle AJ (2017) The processes and mechanisms of cardiac and pulmonary fibrosis. Front. Physiol. 8, 1–15. 2 Rockey DC, Bell PD & Hill JA (2015) Fibrosis - a common pathway to organ injury and failure. N. Engl. J. Med. 372, 1138–1149.

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3 Wynn TA & Ramalingam TR (2012) Mechanisms of fibrosis: Therapeutic translation for fibrotic disease. Nat. Med. 18, 1028–1040. 4 Ho YY, Lagares D, Tager AM & Kapoor M (2014) Fibrosis—a lethal component of systemic sclerosis. Nat. Rev. Rheumatol. 10, 390–402. 5 Weiskirchen R, Weiskirchen S & Tacke F (2019) Organ and tissue fibrosis: Molecular signals, cellular mechanisms and translational implications. Mol. Aspects Med. 65, 2–15. 6 Jun J Il & Lau LF (2018) Resolution of organ fibrosis. J. Clin. Invest. 128, 97–107. 7 Kim J & Kim N (2016) Signaling Pathways in Osteoclast Differentiation. Chonnam Med. J. 52, 12–17. 8 Lacey DL, Boyle WJ, Simonet WS, Kostenuik PJ, Dougall WC, Sullivan JK, Martin JS & Dansey R (2012) Bench to bedside: Elucidation of the OPG-RANK-RANKL pathway and the development of denosumab. Nat. Rev. Drug Discov. 11, 401–419. 9 Wang Y, Michiels T, Setroikromo R, van Merkerk R, Cool RH & Quax WJ (2019) Creation of RANKL mutants with low affinity for decoy receptor OPG and their potential anti- fibrosis activity. FEBS J. 286, 3582–3593. 10 Nelson CA, Warren JT, Wang MW, Teitelbaum SL, Fremont DH & Engage R (2012) RANKL employs distinct binding modes to enage RANK and the osteoprotegerin decoy receptor. Structure 20, 1971–1982. 11 Adhyatmika A, Putri KSS, Beljaars L & Melgert BN (2015) The elusive antifibrotic macrophage. Front. Med. 2, 1–11. 12 Toffoli B, Pickering RJ, Tsorotes D, Wang B, Bernardi S, Kantharidis P, Fabris B, Zauli G, Secchiero P & Thomas MC (2011) Osteoprotegerin promotes vascular fibrosis via a TGF-β1 autocrine loop. Atherosclerosis 218, 61–68. 13 Bernardi S, Bossi F, Toffoli B & Fabris B (2016) Roles and Clinical Applications of OPG and TRAIL as Biomarkers in Cardiovascular Disease. Biomed Res. Int. 2016. 14 Ambroszkiewicz J, Sands D, Gajewska J, Chelchowska M & Laskowska-Klita T (2013) Bone turnover markers, osteoprotegerin and RANKL cytokines in children with cystic fibrosis. Adv. Med. Sci. 58, 338–343. 15 García-Valdecasas-Campelo E, González-Reimers E, Santolaria-Fernández F, De la Vega- Prieto MJ, Milena-Abril A, Sánchez-Pérez MJ, Martínez-Riera A & De Los Ángeles Gómez-Rodríguez M (2006) Serum osteoprotegerin and rankl levels in chronic alcoholic liver disease. Alcohol Alcohol. 41, 261–266. 16 Haisma HJ & Rita Bellu A (2011) Pharmacological interventions for improving adenovirus usage in gene therapy. Mol. Pharm. 8, 50–55. 17 Lee CS, Bishop ES, Zhang R, Yu X, Farina EM, Yan S, Zhao C, Zeng Z, Shu Y, Wu X, Lei J, Li Y, Zhang W, Yang C, Wu K, Wu Y, Ho S, Athiviraham A, Lee MJ, Wolf JM, Reid RR & He TC (2017) Adenovirus-mediated gene delivery: Potential applications for gene and cell-based therapies in the new era of personalized medicine. Genes Dis. 4, 43– 63.

100

Potential anti-fibrosis activity of Adenovirally-expressed RANKL Q236D

18 Luo J, Deng ZL, Luo X, Tang N, Song WX, Chen J, Sharff KA, Luu HH, Haydon RC, Kinzler KW, Vogelstein B & He TC (2007) A protocol for rapid generation of recombinant adenoviruses using the AdEasy system. Nat. Protoc. 2, 1236–1247. 19 Bremer E, van Dam GM, de Bruyn M, van Riezen M, Dijkstra M, Kamps G, Helfrich W & Haisma H (2008) Potent systemic anticancer activity of adenovirally expressed EGFR- selective TRAIL fusion protein. Mol. Ther. 16, 1919–1926. 20 Kinoshita K, Iimuro Y, Otogawa K, Saika S, Inagaki Y, Nakajima Y, Kawada N, Fujimoto J, Friedman SL & Ikeda K (2007) Adenovirus-mediated expression of BMP-7 suppresses the development of liver fibrosis in rats. Gut 56, 706–714. 21 Walachowski S, Tabouret G & Foucras G (2016) Triggering dectin-1-pathway alone is not sufficient to induce cytokine production by murine macrophages. PLoS One 11, 1–26. 22 Wang Y, van Assen AHG, Reis CR, Setroikromo R, van Merkerk R, Boersma YL, Cool RH & Quax WJ (2017) Novel RANKL DE-loop mutants antagonize RANK-mediated osteoclastogenesis. FEBS J. 284, 2501–2512. 23 Willard D, Chen WJ, Barrett G, Blackburn K, Bynum J, Consler T, Hoffman C, Horne E, Iannone MA, Kadwell S, Parham J & Ellis B (2000) Expression, purification, and characterization of the human receptor activator of NF-κB ligand (RANKL) extracellular domain. Protein Expr. Purif. 20, 48–57. 5 24 Feng W, Li W, Liu W, Wang F, Li Y & Yan W (2009) IL-17 induces myocardial fibrosis and enhances RANKL/OPG and MMP/TIMP signaling in isoproterenol-induced heart failure. Exp. Mol. Pathol. 87, 212–218. 25 Wynn TA & Wynn TA (2007) Common and unique mechanisms regulate fibrosis in various fibroproliferative diseases Find the latest version : Review series introduction Common and unique mechanisms regulate fibrosis in various fibroproliferative diseases. J. Clin. Invest. 117, 524–529. 26 Mehal WZ, Iredale J & Friedman SL (2011) Scraping fibrosis. Nat. Med. 17, 552–553. 27 Duffield JS, Forbes SJ, Constandinou CM, Clay S, Partolina M, Vuthoori S, Wu S, Lang R & Iredale JP (2005) Selective depletion of macrophages reveals distinct, opposing roles during liver injury and repair. J. Clin. Invest. 115, 56–65. 28 Miyazaki J, Yasuda H, Mori K, Enomoto T, Furuya Y & Tomimori Y (2010) Establishment of a new murine model of hypercalcemia with anorexia by overexpression of soluble receptor activator of NF-κB ligand using an adenovirus vector. J. Bone Miner. Metab. 29, 414–421. 29 Wang H, Davis JS & Wu X (2014) Immunoglobulin Fc domain fusion to TRAIL significantly prolongs its plasma half-life and enhances its antitumor activity. Mol. Cancer Ther. 13, 643–650.

Abbreviations

OPG - Osteoprotegerin

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RANK - Receptor Activator of Nuclear Factor-κB RANKL - Receptor Activator of Nuclear Factor-κB-ligand Ad-RANKL WT - Adenovirus RANKL wild type TRAIL - Tumor Necrosis Factor Related Apoptosis Inducing Ligand ECM - extracellular matrix TNF - Tumor Necrosis Factor TRAF - TNF receptor-associated factors TRAP - tartrate‐resistant acid phosphatase MMP - matrix metallopeptidase SEAP - Secreted Embryonic Alkaline Phosphatase MOI - multiplicity of infection

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Supplementary

Supplemental Fig. 1

Supple. Fig. 1. Purification and Quantification of Ad vector containing RANKL WT/Q236D. A) Chromatograms of Ad-RANKL WT and Ad-RANKL Q236D; B) Quantification of Ad-RANKL WT and Ad-RANKL Q236D by using a serial limiting dilution of the viruses where HEK293T cells were used to detect the plaque-forming units 5 (pfu/ml).

Supplemental Fig. 2

Supple. Fig. 2. Trimer verification of adenoviral vectors expressing RANKL WT/Q236D.

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Overcoming senescent cancer cell resistance to extrinsic apoptosis using a death receptor 5 (DR5) selective TNF- related apoptosis inducing ligand (TRAIL) variant

Abel Soto-Gamez 1, 2, *, Yizhou Wang 1, *, Lorina Seras 1, Marco Demaria2, and Wim Quax 1, #

1 University of Groningen, Groningen Research Institute of Pharmacy, Chemical and Pharmaceutical Biology, Groningen, Netherlands.

2 European Institute for the Biology of Aging (ERIBA), University Medical Center Groningen (UMCG), Groningen, Netherlands.

Manuscript to be submitted

Chapter 6

Abstract

Cellular senescence is treated as a potent tumor suppressive mechanism and used as a common therapeutic outcome in cancer treatment. Senescent cells have been shown to be resistant to extrinsic apoptosis mediated via TNF-related apoptosis inducing ligand (TRAIL). The use of recombinant TRAIL is an anti-cancer strategy currently in development, and a major question remains whether senescent cancer cells might also develop resistance to this treatment. In this study, we compared the sensitivity of senescent and proliferating breast cancer cells, as well as ovarian and lung cancer cells. Changes in sensitivity were partly dependent on the pre-existing resistance observed for each cell line prior to senescence induction. Specifically, therapy-induced senescence following doxorubicin treatment or ionizing radiation resulted in an increased expression of the pro-apoptotic TRAIL receptor Death Receptor 5 (DR5) on the one hand, as well as an increase in TRAIL decoy receptors DcR1, DcR2, and soluble decoy receptor osteoprotegerin (OPG) on the other hand. Indicative of a protective role for decoy receptors, a DR5 selective TRAIL variant (DHER) unable of binding to OPG or DR4, was found to be more effective in inducing apoptosis of senescent breast cancer cells compared to wild-type TRAIL. Our findings suggest agonistic stimulation of DR5 may be a therapeutic strategy for the elimination of therapy-induced senescent cancer cells.

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Introduction

Cellular senescence is a stable cell cycle arrest that arises in response to various stressors. Senescent cells undergo morphological, structural and functional changes influenced by multiple variables, including the type of stressor, the time elapsed, and tissue or cell type. Cellular senescence represents an important barrier to tumorigenesis by limiting the growth of oncogenic cells. Chemotherapy and radiation are widely used as anti-cancer therapies for their ability to induce apoptosis and therapy-induced senescence in cancer cells [1]. However, aberrant persistence of senescent cells and subsequent escape from apoptosis contributes to the adverse effects of chemotherapy and facilitates cancer relapse [2] by fueling the proliferation of bystander cells through an altered secretome known as the senescence- associated secretory phenotype (SASP) [3].

Prolonged persistence of senescent cells is partially the consequence of mechanisms that enhance their survival and resistance to cell death (reviewed in [4]). Senescent cells have been shown to be more resistant to apoptosis compared to normal proliferating cells, in response to damaging agents, such as UV radiation [5], oxidative stress [6], and cytotoxic drugs [7]. Similarly, a higher resistance of senescent cells to extrinsic apoptosis via death receptors has 6 also been reported [8,9]. The tumor necrosis factor related apoptosis inducing ligand (TRAIL) signals extrinsic apoptosis via death receptors 4 and 5 (DR4/TRAIL-R1, and DR5/TRAIL- R2). On the other hand, decoy receptors 1 and 2 (DcR1/ TRAIL-R3, and DcR2/TRAIL-R4) are homologous to death receptors but are incapable of transducing an apoptotic signal. Because DcR1 and DcR2 retain their ability to bind to TRAIL they compete for ligand binding and limit extrinsic apoptosis.

Interestingly, upregulation of DcR1 [3,10,11] (Gene: TNFRSF10C), and DcR2 [12–16] (Gene: TNFRSF10D) is often reported in senescent cells. Additionally, the secretory phenotype of senescent cells also includes soluble DcRs such as osteoprotegerin (OPG) [3,17], capable of binding to TRAIL extracellularly and thus preventing death receptor stimulation. Despite senescence-associated increases in DcR1, DcR2, and OPG, a protective role in senescent cells is only reported for DcR2, where silencing of DcR2 increased susceptibility of TRAIL- induced extrinsic apoptosis in senescent fibroblasts [8]. However, as non-transformed fibroblasts are generally resistant to TRAIL-induced apoptosis due to multiple redundant pathways [18], acquired resistance to extrinsic apoptosis in TRAIL-sensitive cell lines following senescence induction remains to be described.

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TRAIL is believed to play an important role in tumor immune surveillance [19] and has been previously shown to be a promising anti-cancer therapeutic agent for its ability to induce apoptosis in a variety of tumor cells without affecting normal cells [18,20–22]. A recombinant human TRAIL (aa 114-281) has been mostly used and developed as a clinical anti-cancer drug [23,24]. Given the therapeutic implications of acquired resistance to extrinsic apoptosis in therapy-induced senescent cells, we decided to study changes in TRAIL sensitivity of breast cancer cells before and after senescence induction. Our findings suggest acquired resistance to extrinsic apoptosis is linked to an upregulation of decoy receptors and point to DR5 stimulation as a therapeutic option for the elimination of senescent cancer cells.

Results

Therapy-induced senescence in breast cancer cells

Breast cancer cell lines with varying sensitivities to TRAIL were chosen: MDA-MB-231 (high sensitivity), MDA-MB-436 (medium sensitivity), and MCF-7 (resistant). Therapy- induced senescence was created by doxorubicin treatment as previously described [25] (250 nM, 24 hours). After doxorubicin removal (Day 1), cells were allowed to senesce for 7 additional days before treatment with recombinant wild-type TRAIL (Day 8). As shown in Fig. 1, senescent breast cancer cells displayed typical markers of senescence such as enlarged morphology, tested positive for senescence-associated β-galactosidase (SA-β-gal), displayed less EdU incorporation, failed to form viable colonies, had increased SASP gene expression (IL-6, IL-8, MMP1) with the exception of MDA-MB-436 which lacked an increase of the SASP components IL-6 and IL-8, all cell lines showed increased cyclin- dependent kinase inhibitor p21Cip1 (p21) and decreased Lamin B1 expression (LMNB1).

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Figure 1. Therapy-induced senescence of doxorubicin treated breast cancer cells. (A) Breast cancer cells were treated with doxorubicin (250 nM) for 24 hours. After drug removal, fresh medium was added and cells were routinely inspected for morphological changes. (B) After 8 days in culture, cells were stained for SA-β- galactosidase activity, revealing significant increases in doxorubicin treated cells compared to untreated cells. (C) Doxorubicin treated cells displayed lower levels of EdU incorporation, indicative of a senescence- associated growth arrest. (D) Quantitative real-time PCR (qRT-PCR) analysis of mRNA isolated from doxorubicin treated cells or control cells (untreated, D0). Graphs are mean ± SD data from one experiment

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Chapter 6 performed in triplicate. The heatmap shows the fold change of mRNAs encoding the indicated protein relative to 2 reference genes (tubulin and vinculin). Mean and SD of pooled samples from at least n=2 independent experiments (Fig. S1).

Heterogeneous response to TRAIL-induced extrinsic apoptosis is observed in therapy- induced senescent cancer cells

Senescent or proliferating breast cancer cells were re-seeded and treated with recombinant human TRAIL to induce extrinsic apoptosis. Increased resistance to TRAIL-induced extrinsic apoptosis was observed in senescent MDA-MB-231 cells compared to proliferating cells (Fig. 2A and Fig. S2A). In contrast, increased sensitivity to TRAIL was observed in MDA-MB-436 cells following senescence induction (Fig. 2B and Fig. S2B), while no change in sensitivity was observed in resistant MCF-7 cells (Fig. 2C and Fig. S2C). We further tested the sensitivity change to TRAIL in ovarian and lung cancer tumor types. Similarly, an increased sensitivity after senescence was observed in ovarian cancer cell A2780 and lung cancer cell H1650; no effect was observed in senescent H1299 cells (Fig. S3). Taken together, increased resistance to extrinsic apoptosis was not a common feature of therapy induced senescent cancer cells, unlike previously shown for senescent fibroblasts [12]. Instead, changes in sensitivity were heterogeneous. No changes in sensitivity in cell lines already resistant prior to therapy-induced senescence induction. Increased sensitivity in mild sensitive cell lines and decreased sensitivity was observed in high sensitive TNBC cell line MDA-MB-231.

Using lower concentrations of TRAIL in senescent MDA-MB-231 cells induced by ionizing radiation (10 Gy) the decreased sensitivity was confirmed (Fig. 2D). Furthermore, complete rescue of cell viability was observed upon TRAIL treatment in the presence of the caspase inhibitor Q-VD-Oph (QVD), while no effect was observed using the necroptosis inhibitor Necrostatin 1 (Nec-1), suggesting the effects observed in senescent cells upon TRAIL addition are caspase dependent apoptotic cell death (Fig. 2E).

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Figure 2. Sensitivity of senescent breast cancer cells to TRAIL-induced apoptosis. Doxorubicin-induced senescent or untreated cells (normal) were incubated with human recombinant TRAIL for 24 hours. A dose dependent decrease in cell viability was observed upon cell treatment in TRAIL sensitive cells (MDA-MB-231 6 (A), MDA-MB-436 (B)) but not in TRAIL resistant MCF-7 cells (C). Increased resistance to TRAIL induced apoptosis was also observed in senescent MDA-MB-231 compared to ‗normal‘ MDA-MB-231 in both doxorubicin-induced and ionizing radiation-induced senescence (D). TRAIL induced apoptosis was completely rescued by the caspase inhibitor Q-VD-OPh (QVD), while no effect was observed using the necroptosis inhibitor Necrostatin 1 (Nec-1) (E). Graphs are mean ± SD data from one experiment performed in triplicate. Data from another independent experiment can be found in Fig. S2.

Both pro-apoptotic and anti-apoptotic TRAIL receptors were upregulated in senescent breast cancer cells

The decreased sensitivity of senescent MDA-MB-231 was only apparent at low concentrations of TRAIL, where we hypothesized increased levels of decoy receptors or secreted OPG, could reduce apoptosis by competing for TRAIL binding. In order to explain the differences in sensitivities upon senescence induction, we further looked at the mRNA levels of known TRAIL receptors (DR4, DR5, DcR1, DcR2 and OPG) in MDA-MB-231 and MDA-MB-436 cell lines. Interestingly, upregulation of DcR1/2 and OPG, as well as DR5 but not DR4, was observed across the different cell lines upon senescence induction, although to

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Chapter 6 varying degrees (Fig. 3A and Fig. S4). Equally, at the protein level, FACS analysis revealed increased surface levels of DR5 but not DR4 in therapy-induced senescent breast cancer cells (Fig. 3C), as well as increased secretion of OPG measured in the supernatant of the therapy- induced senescent cell lines (Fig. 3B). Therefore, both pro-apoptotic and anti-apoptotic receptors were upregulated in senescent breast cancer cells MDA-MB-231 and MDA-MB- 436.

Figure 3. Increased expression of selected TRAIL receptors upon senescence induction of breast cancer cells. (A) The mRNA levels of TRAIL death and decoy receptors were analyzed by qPCR. The changes were also assessed at the protein level using B) ELISA for the soluble TRAIL receptor OPG and C) flow cytometry for DR4/5 receptors. The heatmap shows the fold change of mRNAs encoding the indicated protein relative to 2

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Overcoming senescent cancer cell resistance to extrinsic apoptosis using DR5 selective TRAIL variant reference genes (tubulin and GAPDH). The graph of OPG secretion is mean ± SD data from one independent experiment performed in duplicate, which is still needed to repeat. The graph of FACS analysis is representative data from one of three experiments.

DR5 selective TRAIL variant (DHER) enhances apoptosis of senescent breast cancer cells

Based on these findings, we hypothesized that treatment with a DR5-selective TRAIL variant would result in improved cell death of senescent cancer cells. Previously, the Computational Protein Design (CPD) method has been successfully used to generate DR5-selective variant TRAIL D269H/E195R (DHER), which selectively binds to DR5, but has impaired binding to DR4, DcR1 and OPG [26,27]. Accordingly, as shown in Figs. 4A, B, D and E, treatment with TRAIL variant (DHER) resulted in increased cytotoxicity against therapy-induced senescent breast cancer cells MDA-MB-231 and MDA-MB-436. Furthermore, caspase-3/7 activity was found to be increased by the treatment of TRAIL variant DHER compared to wild type TRAIL, indicating that cytotoxicity is caused by caspase-dependent apoptotic pathways (Figs. 4C and 4F). 6

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Figure 4. Effect of DR5 selective TRAIL variant (DHER) on inducing apoptosis of senescent breast cancer cells. Doxorubicin-induced senescent were incubated with human recombinant wild type TRAIL or TRAIL DHER for 24 hours. TRAIL DHER showed increased cytotoxicity compared to wild type TRAIL in (A) MDA- MB-231 and (D) MDA-MB-436 cells. A real-time detection of cell death (PI incorporation) with Incucyte confirmed the increased cell death caused by TRAIL DHER in (B) MDA-MB-231 and (E) MDA-MB-436 cells. Caspase-3/7 activity was also found to be increased by the treatment of TRAIL variant DHER compared to wild type TRAIL in both (C) MDA-MB-231 and (F) MDA-MB-436 cells. Graphs A and D are mean ± SD data from three experiments performed in triplicate; graphs B, C, E and F are mean ± SD from one experiment performed in triplicate.

TRAIL-induced apoptosis in a senescent 3D Spheroid Model

To mimic the actual tumor microenvironment, we decided to use a 3D spheroid model for the TRAIL sensitive cell lines MDA-MB-231 and MDA-MB-436. 3D spheroids were generated by seeding the cells into ultra-low attachment plates and incubated for 7 days. As shown in Fig. 5A, after treatment with doxorubicin (250 nM), the sizes of both MDA-MB-231 and MDA-MB-436 spheroids remained unchanged indicating senescence, while the untreated spheroids remained proliferative-capable and grew in size over time. After TRAIL treatment, the edges of the spheroids became loose and irregular, while the inner layers appeared to lose integrity as apoptotic cells detached from one another. We further tested for differences in 3D cell viability between proliferating and senescent spheroids (Figs. 5A-C). For MDA-MB-231 spheroids, increased resistance to TRAIL-induced extrinsic apoptosis was observed in senescent spheroids compared to proliferating spheroids, similar to our observations in 2D monolayer cultures. In comparison, increased sensitivity was confirmed in senescent MDA- MB-436 spheroids compared to proliferating, similar to 2D monolayers. Importantly, treatment with TRAIL DHER resulted in increased cytotoxicity in both MDA-MB-231 and MDA-MB-436 senescent spheroids, compared to treatment with wild type TRAIL. In accordance, TRAIL DHER showed an advantage over wild type TRAIL in caspase 3/7 activation in both MDA-MB-231 and MDA-MB-436 senescent spheroids (Figs. 5D and 5E).

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MDA-MB-231

D3 D6 D13 D14 + TRAIL (WT)(DHER)

Figure 5. TRAIL-induced extrinsic apoptosis in 3D Spheroid Models. (A) 3D spheroids of MDA-MB-231 6 and MDA-MB-436 were constructed. After treated with doxorubicin (250 nM), the sizes of both MDA-MB-231 and MDA-MB-436 spheroids remained unchanged while the untreated spheroids continued to grow and became enlarged over time. TRAIL DHER resulted in increased cytotoxicity in both (B) MDA-MB-231 and (C) MDA- MB-436 senescent spheroids, compared to treatment with wild type TRAIL. TRAIL DHER also showed an advantage over wild type TRAIL in caspase 3/7 activation in both (D) MDA-MB-231 and (E) MDA-MB-436 senescent spheroids. Graphs are mean ± SD data from one experiment performed in triplicate.

Discussion

Breast cancer has the highest incidence and mortality rate of all cancers in women [28]. Triple-negative breast cancers are particularly aggressive forms of breast cancers that are extremely challenging to treat. Neoadjuvant (preoperative) chemotherapy, such as doxorubicin, continues to be used for the treatment of breast cancers around the world [29]. However, chemotherapeutics are not only able to eliminate cancer cells but are also capable of inducing cellular senescence at lower doses, which may exacerbate side effects by promoting the proliferation of non-responder cells through the SASP [2]. On the other hand, senescent cancer cells might be a risk of escaping growth arrest because of their genomic instability and

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Chapter 6 the possibility to accumulate further mutations [30]. Therefore, the elimination of therapy- induced senescent cancer cells may be desired. TRAIL can induce extrinsic apoptosis of a variety of cancer cells, however, the sensitivity of senescent cancer cells to TRAIL remains unclear. In this study, we compared the sensitivity of senescent breast cancer cells to TRAIL- induced apoptosis, prior to and after senescence induction.

Upon senescence induction, we observed a heterogeneous response to TRAIL-induced apoptosis. For MDA-MB-231 cells, increased resistance was observed at low concentrations of recombinant TRAIL, where we hypothesized the influence of decoy receptors is substantial. In contrast, increased sensitivity was observed in senescent MDA-MB-436 cells compared to their proliferating counterparts. No changes in resistance were observed in MCF-7 cells. Within the cell lines tested, MDA-MB-231 cells showed the highest secretion of OPG following senescence induction, an increase that is also previously described for the secretome of radiation-induced senescent tumor cells [17], and that may partly explain a decreased sensitivity to TRAIL induced apoptosis. This also explains the increased susceptibility for the DR5 specific TRAIL variant (DHER), which can bypass OPG binding but is still capable of stimulating DR5. An increased resistance to TRAIL induced apoptosis was observed in the 3D spheroid model in terms of viability, despite absolute caspase activity appearing higher in senescent cells. In MDA-MB-436 cells, an upregulation of DR5 was observed following doxorubicin treatment, which partly explains its increased sensitivity to TRAIL-induced apoptosis. Lastly, MCF-7 cells do not have functional caspase 3, and therefore the lack of changes in sensitivity may be partly explained by this deficiency in the apoptotic signaling pathway.

By comparing the sensitivity of senescent and proliferating breast cancer cells, we conclude that changes in sensitivity to TRAIL-induced extrinsic apoptosis are heterogeneous in senescent cancer cells. We also found that therapy-induced senescence resulted in an increased expression of death receptor 5 (DR5), as well as an increase in TRAIL decoy receptors DcR1, DcR2, and OPG. A DR5-selective TRAIL variant (DHER) was more effective in inducing apoptosis of senescent breast cancer cells compared to wild-type TRAIL, both in 2D and 3D spheroid models. The increased activity of TRAIL DHER compared to wild type TRAIL suggests selective DR5 stimulation may become a viable strategy for the elimination of therapy-induced senescent cancer cells.

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Materials and methods

Cell lines and reagents

Human breast cancer cell lines MDA-MB-231, MDA-MB-436 and MCF-7, human ovarian cancer cell lines A2780, human lung cancer cell lines (H1299, H1650) were all obtained from American Type Culture Collection (ATCC, Wesel, Germany). The cells were cultured in DMEM (MDA-MB-231, MDA-MB-436, MCF-7) or RPMI-1640 (A2780) containing 2 mM penicillin/streptomycin supplemented with 10% fetal bovine serum (Costar Europe,

Badhoevedorp, The Netherlands) at 37 °C with 5% CO2.

Induction of senescence

For doxorubicin-induced senescence, cells were seeded at a density of 2×106 cells per T75 flask overnight and then treated with doxorubicin at a concentration of 250 nM for 24 h. The medium was replaced by the fresh medium with 10% FBS every 2 days. Cells were harvested on day 8 after treatment. For ionizing radiation-induced senescence, cells were subjected to 10 6 gray (Gy) of ionizing gamma irradiation. The medium was refreshed every 2 days, and cells were harvested on day 8 after irradiation.

Senescence-associated β-galactosidase staining

The senescence-associated β-galactosidase Staining was performed as previously described [31]. Cells were seeded in a 24-well plate at a concentration of 20,000 cells/ml overnight. Then, the cells were fixed in a mixture of glutaraldehyde (0.2%, v/v) and formaldehyde (2%, v/v) for 5 min and stained with an X-Gal solution pH 6.0 (Biovision). The number of positive- blue stained cells was counted under a light microscope and compared to the total number of cells in each view. Biological replicates were stained in triplicate, and counting was made in blind.

EdU incorporation assay

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Cells were seeded in a 24-well plate at a concentration of 20,000 cells/ml overnight. After incubation with EdU for 24h, cells were fixed and stained using a commercial kit (Click-iT EdU Alexa Fluor 488 Imaging kit; Thermo Fisher Scientific). Visualization was made by using a Leica DM 6000 fluorescent microscope.

Clonogenic survival assay

Cells were seeded in the 6-well plates at a concentration of 5000 cells/ml in 2 ml medium and cultured for six days. The medium was then removed and cells were washed twice with PBS. Then, cells were fixed with 4% formaldehyde (Sigma-Aldrich, Saint Louis, USA) for 5 min and stained with a 0.5% (w/v) crystal violet (Sigma-Aldrich, Saint Louis, USA) solution for 15 minutes. The quantification was made by using the ImageJ software. Experiments were performed in triplicate and repeated at least three times.

RNA isolation and quantitative reverse transcriptase PCR

Total mRNA was isolated using Maxwell LEV simply RNA Cells/Tissue Kit (Promega, Madison, WI, USA) according to the instruction described. The concentrations of mRNA were measured by NanoDrop ND-100 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). cDNA was obtained through a reverse transcription reaction using Reverse Transcription Kit (Promega, Madison, WI, USA). A panel of SASP factors consisting of mouse p21, IL6, IL-8, MMP1, LMNB1, and a panel of TRAIL-receptor genes including DR4, DR5, DcR1, DcR2, OPG was detected by qRT-PCR using either commercially available Taqman (Applied Biosystems) or SensiMix SYBR kit (Bioline). mRNA levels of α-tubulin and GAPDH were measured and used as a reference for data normalization. The specific primer sequences are shown in Table S1.

Cell viability assay (MTS assay)

Cells were seeded at a density of 10,000 cells per well in a 96-well plate overnight. rhTRAIL WT or DHER with the different concentrations ranging from 1- 90 ng/ml was added, with or without the apoptosis inhibitor Q-VD-Oph (Sigma Aldrich, SML0063-1MG) and the

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Overcoming senescent cancer cell resistance to extrinsic apoptosis using DR5 selective TRAIL variant necroptosis inhibitor Necrostatin-1 (Cayman Chemical, Michigan, USA). After 24 h incubation, 20 µl of MTS (Promega, Madison, WI, USA) reagent was added. Cell viability was determined after 1-2 h of incubation by measuring the absorption at 490 nm using a microplate reader (BMG LABTECH, De Meern, Utrecht, The Netherlands).

3D spheroid viability assay

3D spheroids were constructed as described before [32]. Cells were seeded at a density of 1000 cells per well in an ultra-low attachment 96-well plate (Corning Incorporated, Kennebunk, ME, USA). Plates were centrifuged at 1000 rpm for 5 min to form the 3D spheroid. After 7 days of incubation, spheroids were constructed and ready for performing experiments. The viability of 3D spheroids was determined using the 3D CellTiter-Glo® kit (Promega). Spheroids were first treated with rhTRAIL WT or DHER with concentrations of 2.5 and 5 ng/ml for 24 h and transferred to a new 96-well plate with white walls. 100 µl of luminescence reagent was added to each well according to the manufacturer‘s instructions. After 30 min incubation at room temperature, the luminescence values were measured using a 6 Synergy™H1 plate reader (BioTek, Winooski, VT, USA).

Caspase activity assay (2D, 3D)

Caspase 8 and 3/7 activities were determined using Caspase-Glo 8 and Caspase-Glo 3/7 kits (Promega). Briefly, cells were seeded in a 96-well plate with white walls at a density of 30,000 cells/ml overnight. Subsequently, rhTRAIL WT or DHER (2.5 or 5 ng/ml) was added. After 8 h incubation, 100 µl of the reagent was added to each well according to the manufacturer‘s protocol, and luminescence was recorded after30 min by using a Synergy™H1 plate reader (BioTek, Winooski, VT, USA). For the 3D spheroids, the spheroids were transferred to a new 96-well plate with white walls before adding the Caspase- Glo reagents.

TRAIL receptors expression analysis

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Total numbers of 5 × 105 cells per sample were harvested and incubated with primary antibodies for DR4 (Abcam, Cambridge, UK), DR5 (EXBIO Praha, Nad Safinou, Czech Republic) DcR1 (Abcam, Cambridge, UK) or DcR2 (Abcam, Cambridge, UK) on ice for 1 h, respectively. Subsequently, cells were washed and incubated with R-Phycoerythrin (PE) conjugated goat anti-rabbit antibody (Southern Biotech, Birmingham, AL, USA) or Fluorescein (FITC) conjugated donkey anti-mouse antibody (Jackson ImmunoResearch Europe, Cambridge, UK) on ice for 1 h. The receptor expression was detected using a FACS Calibur flow cytometer (BD Bioscience, Franklin Lakes, NJ, USA) and data was analyzed with the FlowJo V10 software (BD Bioscience, Franklin Lakes, NJ, USA).

ELISA

ELISA kit to detect OPG was from R&D systems and was used according to the manufacturer‘s instructions. For doxorubicin-treated cells, media were collected in 1, 4 and 8 days after treatment. ELISA results were normalized to total cell numbers on the day of collection.

Incucyte ® ZOOM time-resolved assays

® Cells were maintained at 37°C with 5% CO2 atmosphere and imaged using an IncuCyte ZOOM (Essen BioScience) with a 4× magnification. For real-time caspase 3/7 activity measurements, cells were treated with rhTRAIL WT or DHER in the presence of CellEvent™ Caspase-3/7 Green Detection Reagent (Thermo scientific). The confluence and the fluorescent signal from each well were recorded by the IncuCyte® ZOOM every 2 h. For cell death determination propidium iodide was added with rhTRAIL WT or DHER, and the red fluorescent signal for each well was recorded using the IncuCyte® ZOOM.

Acknowledgements

This work was supported by the University of Groningen (ASG, YW, MD, WQ). This work was performed within the framework of the Dutch Top Institute Pharma project TNF-ligands in cancer (project nr. T3-112) and STW grant 11056. YW is a recipient of a scholarship from

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Overcoming senescent cancer cell resistance to extrinsic apoptosis using DR5 selective TRAIL variant the Chinese Scholarship Council (CSC). AS is a fellow of the Mexican National Council of Science and Technology (CONACYT). We thank H. Habibie from Department of Molecular Pharmacology, Groningen Research Institute of Pharmacy, University of Groningen for his assistance in ELISA assay.

References

1 Ewald JA, Desotelle JA, Wilding G & Jarrard DF (2010) Therapy-induced senescence in cancer. J. Natl. Cancer Inst. 102, 1536–46. 2 Demaria M, O‘Leary MN, Chang J, Shao L, Liu S, Alimirah F, Koenig K, Le C, Mitin N, Deal AM, Alston S, Academia EC, Kilmarx S, Valdovinos A, Wang B, de Bruin A, Kennedy BK, Melov S, Zhou D, Sharpless NE, Muss H & Campisi J (2017) Cellular Senescence Promotes Adverse Effects of Chemotherapy and Cancer Relapse. Cancer Discov. 7, 165–176. 3 Coppé JP, Patil CK, Rodier F, Sun Y, Muñoz DP, Goldstein J, Nelson PS, Desprez PY & Campisi J (2008) Senescence-associated secretory phenotypes reveal cell- nonautonomous functions of oncogenic RAS and the p53 tumor suppressor. PLoS Biol. 6. 4 Soto-Gamez A, Quax WJ & Demaria M (2019) Regulation of Survival Networks in 6 Senescent Cells: From Mechanisms to Interventions. J. Mol. Biol. 431, 2629–2643. 5 Marcotte R, Lacelle C & Wang E (2004) Senescent fibroblasts resist apoptosis by downregulating caspase-3. Mech. Ageing Dev. 125, 777–783. 6 Sanders YY, Liu H, Zhang X, Hecker L, Bernard K, Desai L, Liu G & Thannickal VJ (2013) Histone Modifications in Senescence-Associated Resistance to Apoptosis by Oxidative Stress. Redox Biol. 1, 8–16. 7 Tepper CG, Seldin MF & Mudryj M (2000) Fas-Mediated Apoptosis of Proliferating, Transiently Growth-Arrested, and Senescent Normal Human Fibroblasts. Exp. Cell Res. 260, 9–19. 8 Sagiv A, Burton DGA, Moshayev Z, Vadai E, Wensveen F, Ben-Dor S, Golani O, Polic B & Krizhanovsky V (2016) NKG2D ligands mediate immunosurveillance of senescent cells. Aging (Albany. NY). 8, 328–44. 9 Ovadya Y, Tokarsky-Amiel R, Cohen S, Yosef R, Krizhanovsky V, Vadai E, Condiotti R, Dassa L, Pilpel N, Shahar E, Ben-Porath I & Biran A (2016) Directed elimination of senescent cells by inhibition of BCL-W and BCL-XL. Nat. Commun. 7, 1–11. 10 Shah PP, Donahue G, Otte GL, Capell BC, Nelson DM, Cao K, Aggarwala V, Cruickshanks HA, Rai TS, McBryan T, Gregory BD, Adams PD & Berger SL (2013) Lamin B1 depletion in senescent cells triggers large-scale changes in gene expression and the chromatin landscape. Genes Dev. 27, 1787–99.

121

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11 Wiley CD, Flynn JM, Morrissey C, Lebofsky R, Shuga J, Dong X, Unger MA, Vijg J, Melov S & Campisi J (2017) Analysis of individual cells identifies cell-to-cell variability following induction of cellular senescence. Aging Cell 16, 1043. 12 Sagiv A, Biran A, Yon M, Simon J, Lowe SW & Krizhanovsky V (2013) Granule exocytosis mediates immune surveillance of senescent cells. Oncogene 32, 1971–1977. 13 Collado M, Gil J, Efeyan A, Guerra C, Schuhmacher AJ, Barradas M, Benguría A, Zaballos A, Flores JM, Barbacid M, Beach D & Serrano M (2005) Senescence in premalignant tumours. Nature 436, 642–642. 14 Xue W, Zender L, Miething C, Dickins RA, Hernando E, Krizhanovsky V, Cordon-Cardo C & Lowe SW (2007) Senescence and tumour clearance is triggered by p53 restoration in murine liver carcinomas. Nature 445, 656–660. 15 Binet R, Ythier D, Robles AI, Collado M, Larrieu D, Fonti C, Brambilla E, Brambilla C, Serrano M, Harris CC & Pedeux R (2009) WNT16B Is a New Marker of Cellular Senescence That Regulates p53 Activity and the Phosphoinositide 3-Kinase/AKT Pathway. Cancer Res. 69, 9183–9191. 16 Madsen SD, Russell KC, Tucker HA, Glowacki J, Bunnell BA & O‘Connor KC (2017) Decoy TRAIL receptor CD264: a cell surface marker of cellular aging for human bone marrow-derived mesenchymal stem cells. Stem Cell Res. Ther. 8, 201. 17 Hwang HJ, Jung SH, Lee HC, Han NK, Bae IH, Lee M, Han Y-H, Kang Y-S, Lee S-J, Park HJ, Ko Y-G & Lee J-S (2016) Identification of novel therapeutic targets in the secretome of ionizing radiation-induced senescent tumor cells. Oncol. Rep. 35, 841–850. 18 van Dijk M, Halpin-McCormick A, Sessler T, Samali A & Szegezdi E (2013) Resistance to TRAIL in non-transformed cells is due to multiple redundant pathways. Cell Death Dis. 4, e702–e702. 19 Takeda K, Smyth MJ, Cretney E, Hayakawa Y, Kayagaki N, Yagita H & Okumura K (2002) Critical Role for Tumor Necrosis Factor–related Apoptosis-inducing Ligand in Immune Surveillance Against Tumor Development. J. Exp. Med. 195, 161–169. 20 Pitti RM, Marsters SA, Ruppert S, Donahue CJ, Moore A & Ashkenazi A (1996) Induction of apoptosis by Apo-2 ligand, a new member of the tumor necrosis factor cytokine family. J. Biol. Chem. 271, 12687–12690. 21 Ashkenazi A, Pai RC, Fong S, Leung S, Lawrence DA, Marsters SA, Blackie C, Chang L, McMurtrey AE, Hebert A, DeForge L, Koumenis IL, Lewis D, Harris L, Bussiere J, Koeppen H, Shahrokh Z & Schwall RH (1999) Safety and antitumor activity of recombinant soluble Apo2 ligand. J. Clin. Invest. 104, 155–162. 22 Lawrence D, Shahrokh Z, Marsters S, Achilles K, Shih D, Mounho B, Hillan K, Totpal K, DeForge L, Schow P, Hooley J, Sherwood S, Pai R, Leung S, Khan L, Gliniak B, Bussiere J, Smith CA, Strom SS, Kelley S, Fox JA, Thomas D & Ashkenazi A (2001) Differential hepatocyte toxicity of recombinant Apo2L/TRAIL versions. Nat. Med. 7, 383–384.

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23 Yu R, Albarenque SM, Cool RH, Quax WJ, Mohr A & Zwacka RM (2014) DR4 specific TRAIL variants are more efficacious than wild-type TRAIL in pancreatic cancer. Cancer Biol. Ther. 15, 1658–1666. 24 Herbst RS, Eckhardt SG, Kurzrock R, Ebbinghaus S, O‘Dwyer PJ, Gordon MS, Novotny W, Goldwasser MA, Tohnya TM, Lum BL, Ashkenazi A, Jubb AM & Mendelson DS (2010) Phase I dose-escalation study of recombinant human Apo2L/TRAIL, a dual proapoptotic receptor agonist, in patients with advanced cancer. J. Clin. Oncol. 28, 2839–2846. 25 Hernandez-Segura A, Brandenburg S & Demaria M (2018) Induction and Validation of Cellular Senescence in Primary Human Cells. J. Vis. Exp., e57782. 26 Van der Sloot AM, Tur V, Szegezdi E, Mullally MM, Cool RH, Samali A, Serrano L & Quax WJ (2006) Designed tumor necrosis factor-related apoptosis-inducing ligand variants initiating apoptosis exclusively via the DR5 receptor. Proc. Natl. Acad. Sci. U. S. A. 103, 8634–8639. 27 Bosman MCJ, Reis CR, Schuringa JJ, Vellenga E & Quax WJ (2014) Decreased affinity of recombinant human tumor necrosis factor-related apoptosis-inducing ligand (rhTRAIL) D269H/E195R to osteoprotegerin (OPG) overcomes trail resistance mediated by the bone microenvironment. J. Biol. Chem. 289, 1071–1078. 28 Han H, Zhou H, Li J, Feng X, Zou D & Zhou W (2017) TRAIL DR5-CTSB crosstalk participates in breast cancer autophagy initiated by SAHA. Cell Death Discov. 3. 6 29 Hess KR, Anderson K, Symmans WF, Valero V, Ibrahim N, Mejia JA, Booser D, Theriault RL, Buzdar AU, Dempsey PJ, Rouzier R, Sneige N, Ross JS, Vidaurre T, Gómez HL, Hortobagyi GN & Pusztai L (2006) Pharmacogenomic Predictor of Sensitivity to Preoperative Chemotherapy With Paclitaxel and Fluorouracil, Doxorubicin, and Cyclophosphamide in Breast Cancer. J. Clin. Oncol. 24, 4236–4244. 30 Loaiza N & Demaria M (2016) Cellular senescence and tumor promotion: Is aging the key? Biochim. Biophys. Acta - Rev. Cancer 1865, 155–167. 31 Hernandez-Segura A, de Jong T V., Melov S, Guryev V, Campisi J & Demaria M (2017) Unmasking Transcriptional Heterogeneity in Senescent Cells. Curr. Biol. 27, 2652– 2660.e4. 32 Zhang B, Liu B, Chen D, Setroikromo R, Haisma HJ & Quax WJ (2019) Histone Deacetylase Inhibitors Sensitize TRAIL-Induced Apoptosis in Colon Cancer Cells. Cancers (Basel). 11, 645.

Abbreviations

TNF - Tumor Necrosis Factor TRAIL - Tumor Necrosis Factor Related Apoptosis Inducing Ligand OPG - Osteoprotegerin DR - Death Receptor

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DcR - Decoy Receptor CPD - Computational Protein Design SASP - senescence-associated secretory phenotype SA-β-gal - senescence-associated β-galactosidase IL-6/8 - Interleukin-6/8 MMP1 - matrix metallopeptidase 1 LMNB1 - Lamin B1 QVD - Q-VD-OPh Nec-1 - Necrostatin 1 Doxo - Doxorubicin IR - Ionizing Irradiation

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Supplementary

Supplemental Table S1. List of the primers sets used for qRT-PCR

Name Strand Sequence

IL-8 hIL8 #72 -F 5‘-GAGCACTCCATAAGGCACAAA-3‘ hIL8 #72 -R 5‘-ATGGTTCCTTCCGGTGGT-3‘ IL-6 hIL6 #45 -F 5‘-CAGGAGCCCAGCTATGAACT-3‘ hIL6 #45 -R 5‘-GAAGGCAGCAGGCAACAC-3‘ MMP1 hMMP1 #7 -F 5‘-GCTAACCTTTGATGCTATAACTACGA-3‘ hMMP1 #7 -R 5‘-TTTGTGCGCATGTAGAATCTG-3‘ LMNB1 hLMNB1 #3 -F 5‘-GTGCTGCGAGCAGGAGAC-3‘ hLMNB1 #3 -R 5‘-CCATTAAGATCAGATTCCTTCTTAGC-3‘ p16 hp16 #67 -F 5‘-GAGCAGCATGGAGCCTTC-3‘ hp16 #67 -R 5‘-CGTAACTATTCGGTGCGTTG-3‘ p21 hp21 #32 -F 5‘-TCACTGTCTTGTACCCTTGTGC-3‘ hp21 #32 -R 5‘-GGCGTTTGGAGTGGTAGAAA-3‘ Vinculin hVinculin1 #28 -F 5‘-GATGAAGCTCGCAAATGGTC-3‘ hVinculin1 #28 -R 5‘-TCTGCCTCAGCTACAACACCT-3‘ Tubulin hTubulin #40 -F 5‘-CTTCGTCTCCGCCATCAG-3‘ hTubulin #40 -R 5‘-CGTGTTCCAGGCAGTAGAGC-3‘ 6 DR4 Forward 5‘-CAGAACGTCCTGGAGCCTGTAAC-3‘ Reverse 5‘-ATGTCCATTGCCTGATTCTTTGTG-3‘ DR5 Forward 5‘-TGCAGCCGTAGTCTTGATTG-3‘ Reverse 5‘-GCACCAAGTCTGCAAAGTCA-3‘ DcR1 Forward 5‘-CACCAACGCTTCCAACAATGAACC-3‘ Reverse 5‘-TCCGGAAGGTGCCTTCTTTACACT-3‘ DcR2 Forward 5‘-CTTTTCCGGCGGCGTTCATGTCCTTC-3‘ Reverse 5‘-GTTTCTTCCAGGCTGCTTCCCTTTGTAG-3‘ OPG Forward 5‘-CCTGGCACCAAAGTAAACGC-3‘ Reverse 5‘-TGCTCGAAGGTGAGGTTAGC-3‘ GAPDH Forward 5‘-ACCCAGAAGACTGTGGATGG-3‘ Reverse 5‘-TCTAGACGGCAGGTCAGGTC-3‘

Supplemental Fig. 1 SASP expression

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Supplemental Fig. 1 SASP expression changes in mRNA levels after doxorubicin treatment. Quantitative real-time PCR (qRT-PCR) analysis of mRNA isolated from doxorubicin treated cells or control cells (untreated,

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D0) in (A) MDA-MB-231, (B) MDA-MB-436 and (C) MCF-7 cells. The values shown are represented as mean ± SD from two independent experiments performed in triplicates.

Supplemental Fig. 2

Supplemental Fig. 2. Sensitivity of senescent breast cancer cells to TRAIL-induced apoptosis. Doxorubicin- induced senescent or untreated cells (normal) were incubated with human recombinant TRAIL for 24 hours. A dose dependent decrease in cell viability was observed upon cell treatment in TRAIL sensitive cells (MDA-MB- 6 231 (A), MDA-MB-436 (B)) but not in TRAIL resistant MCF-7 cells (C). Graphs are mean ± SD from one experiment performed in triplicate.

Supplemental Fig. 3 MTS

Supplemental Fig. 3. Sensitivity of senescent cancer cells to TRAIL-induced apoptosis. Doxorubicin- induced senescent or untreated cells (normal) were incubated with human recombinant TRAIL for 24 hours. (A)

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A2780 cell line, (B) H1650 cell line and (C) H1299 cell line. Graphs are mean ± SD from one experiment performed in triplicate.

Supplemental Fig. 3 Receptor expression in mRNA level

Supplemental Fig. 3 Receptor expression in mRNA level. Quantitative real-time PCR (qRT-PCR) analysis of mRNA isolated from doxorubicin treated cells or control cells (untreated, D0) in (A) MDA-MB-231, (B) MDA- MB-436 and (C) MCF-7 cells. The values shown are represented as mean ± SD from two independent experiments performed in triplicates.

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Novel TRAIL variants with reduced binding to decoy receptor OPG overcome TRAIL resistance in breast cancers

Yizhou Wang1, Fengzhi Suo1, Patiwat Kongdang, Euphemia Amelia in het Veld, Rita Setroikromo, Ronald van Merkerk, Robbert H. Cool and Wim J. Quax#

Department of Chemical and Pharmaceutical Biology, Groningen Research Institute of Pharmacy, University of Groningen, A. Deusinglaan 1, 9713 AV Groningen, The Netherlands

Manuscript to be submitted

Chapter 7

Abstract

Breast cancer has the highest incidence and mortality rate of all cancers in women. Tumor necrosis factor (TNF)-related apoptosis inducing ligand (TRAIL) is a potential anti-cancer agent as it is able to induce apoptosis via the death receptors in a variety of cancer cells while leaving healthy cells unharmed. Osteoprotegerin (OPG), as the decoy receptor of TRAIL, can block the induction of apoptosis through sequestering the available TRAIL. OPG was discovered to show tumor-promoting effects in breast cancer, mainly due to the high expression of OPG by breast tumor cells inhibiting the TRAIL-induced apoptosis. Therefore, TRAIL variants that can efficiently bind to death receptors without binding to OPG are of interest for targeting breast cancer cells without the obstruction of high OPG production. Here, a structural model of TRAIL-OPG complex was created, and through comparing the 3D structures of TRAIL- DR4, TRAIL-DR5 and TRAIL-OPG, we have built a structure-based TRAIL mutants library. Our results show that TRAIL_D269 residue is important for OPG binding. Through computational protein design and a combination strategy, we found that the double mutant TRAIL_D269H/Y209M and the triple mutant TRAIL_D269H/Y209M/K179P showed lowered binding to OPG and these variants can induce apoptosis in breast cancer cells MDA- MB-231 and MDA-MB-436 in the presence of OPG. The generation of TRAIL mutants with reduced binding to OPG is a promising approach for targeting breast tumors in high OPG microenvironments.

Keywords: TRAIL, OPG, breast cancer, apoptosis

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Introduction

Breast cancer, with the highest incidence of all cancers in women, has a serious impact on women‘s health including a high mortality rate [2]. Worldwide, it occupies 30% of all cancers diagnosed in women with more than 1,677,000 new cases and over 520,000 deaths each year [3]. Metastasis in the early stages causes a major risk in the prognosis and survival of breast cancer [4]. Despite the recent improvements in breast cancer detection and treatment, the lack of understanding of the molecular mechanisms and its pathogenesis limits the treatment effects and prognosis [2,4,5].

Tumor necrosis factor (TNF)-related apoptosis inducing ligand (TRAIL), also known as Apo2 ligand (Apo2L), is an important ligand of the TNF superfamily that selectively induces apoptosis in a variety of tumor cells [6]. TRAIL binds to five cognate receptors: death receptor 4 (DR4/TRAIL-R1), death receptor 5 (DR5/TRAIL-R2), decoy receptor 1 (DcR1/TRAIL-R3), decoy receptor 2 (DcR2/TRAIL-R4), and the soluble receptor osteoprotegerin (OPG) [7]. Only upon binding to DR4 and DR5, TRAIL can activate the extrinsic pathway through the recruitment of the Fas-associated death domain and the activation of the initiator caspase-8 [8,9]. Binding of TRAIL to DcR1 or DcR2 does not induce apoptosis because they lack a functional death domain [10]. OPG, as a soluble protein, can also block the induction of apoptosis through sequestering the available TRAIL. 7

Interestingly, a number of studies have shown the role of OPG in cancers including prostate cancer, breast cancer and colon carcinoma, demonstrating that OPG production from tumor cells could lead to tumor growth and metastasis [1,11,12]. This may be caused by the overexpression of OPG to block the TRAIL-induced apoptosis [13]. Especially in breast cancer, OPG is reported to be expressed in 40% of breast cancers, but not in normal breast tissue [5]. Moreover, OPG was found highly expressed in breast cancer cell lines like MCF-7 and MDA-MB-231 [12], and TRAIL-induced apoptosis could be considerably inhibited by the accumulation of OPG produced by MDA-MB-436 cell [5,13]. Therefore, TRAIL variants that can efficiently bind to DR4 and/or DR5 without binding to OPG are of interest for targeting breast cancer cells without the obstruction of high OPG production.

Previously, a Computational Protein Design (CPD) method has been successfully used to generate DR5-selective variant TRAIL_D269H/E195R (DHER) and DR4-selective variant TRAIL_4C7 [7,14]. TRAIL_DHER was also reported to show a decreased affinity to OPG and can overcome TRAIL resistance in bone microenvironment with high OPG expression

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[15], however, the lowered binding of TRAIL_DHER to OPG was obtained without rational structure analysis. Therefore, through structure-based analysis, it is still possible to achieve new TRAIL variants with a lowered affinity to OPG. OPG also acts as the decoy receptor of receptor activator of nuclear factor NF-κB Ligand (RANKL), and recently a RANKL variant Q236D lacking binding to OPG was developed through comparing the crystal structure complexes RANKL-RANK and RANKL-OPG, which indicates the possibility of making TRAIL variants using the same approach [16].

In the present study, a model of the TRAIL-OPG complex was created, and through comparing the 3D structures of TRAIL-DR4, TRAIL-DR5 and TRAIL-OPG, we have built a structure-based TRAIL mutants library aimed at lowering the affinity for OPG. Our results show that TRAIL_D269 residue is important for OPG binding. Through computational protein design and a combination strategy, we found the double mutant TRAIL_D269H/Y209M and the triple mutant TRAIL_D269H/Y209M/K179P showing lowered binding to OPG compare to TRAIL_DHER, and these variants could induce apoptosis in breast cancer cells in the presence of OPG. The generation of TRAIL mutants with reduced binding to OPG is a promising strategy for targeting breast tumors in high OPG microenvironments.

Results

Design of TRAIL-OPG complex

Several 3D structures of TRAIL in complex with the DR4 or DR5 receptor are available [17– 19], while the crystal structure of TRAIL in complex with the OPG receptor has still not been resolved. The available 3D structure of human RANKL-OPG complex (PDB code 3URF) offered us the possibility to build the complex model of TRAIL and OPG [20]. As shown in figures 1A and 1B, we extracted the structures of hTRAIL dimer and hOPG monomer from hTRAIL-DR5 and hRANKL-OPG complexes (Protein Data Bank codes 1D4V and 3URF), respectively. Docking of proteins was performed using ZDOCK module in BIOVIA DISCOVERY STUDIO 4.5 software, where TRAIL_Y216 was selected as filtered binding residue because of its conservation in receptor binding, and TRAIL_S165, located far away from the receptor-binding interface, was set as a blocked residue [7]. 5000 poses from 362 clusters passed the filters after ZDOCK process. Through comparing all the poses with the

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Novel TRAIL variants with reduced binding to decoy receptor OPG structure of hRANKL-OPG, 23 poses from 7 clusters were selected manually. Afterward, the selected poses were refined by using the RDOCK module for energy minimization and evaluation [21]. Seven top poses from each cluster were further selected as candidates. We further compared the protein interfaces of these 7 poses to the structure of the hRANKL-OPG complex (3URF), and pose 2569 was selected as the highest-confident model because it showed the most conserved interactions with hRANKL-OPG complex (Fig. 1C).

Fig 1. Molecular modeling of TRAIL and OPG. A) The top view of the hTRAIL-DR5 trimer-trimer complex (PDB code: 1D4V); B) The side view of the hRANKL-OPG monomer-monomer complex (PDB code: 3URF); C) The model of TRAIL-OPG complex where TRAIL dimer and OPG monomer were extracted from hTRAIL-DR5 and hRANKL-OPG complexes, respectively.

TRAIL-DR4/DR5/OPG binding interface analysis leads to the structure-based design of mutants

For the computational screening, the binding interfaces of TRAIL-DR4 (5CIR), TRAIL-DR5 (1D4V) and TRAIL-OPG (pose 2569) complexes were analyzed. As shown in suppl. Table. 1, via analyzing all the interactions including hydrogen bonds, electrostatic, and hydrophobic

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Chapter 7 properties among TRAIL-DR4, TRAIL-DR5 and TRAIL-OPG complexes, all residues of TRAIL that show interactions with any of the three receptors were identified. Positions K145, G148, K179, Y209, E252 were selected for full mutation because they show interactions with OPG, but not DR4 and DR5. Therefore, it is supposed that these can change the binding of TRAIL to OPG without influencing the binding of TRAIL to DR4 and DR5. TRAIL_R130 was also selected because it shows interactions with both OPG and DR5, but not DR4, which may achieve DR4-selective TRAIL mutants. On the other hand, other single substitutions of TRAIL_K251D, K251E, D269H, D269R and D269K were selected on the basis of the interactions with OPG and DR4. Taken together, as shown in figure 2, in total 102 variants were proposed and constructed for further evaluation.

Fig 2. Mutation library of TRAIL. The wild-type amino acid residue at each position is indicated by black bolder, and white squares represent variants that are not present in the library. The colors represent different properties of amino acid group: yellow (non-polar), blue (polar), green (positive charge) and red (negative charge).

Prescreen of TRAIL mutants with reduced binding to OPG

After expression and purification using His-affinity chromatography in 96-well plates, 70 out of these 102 variants were obtained successfully. Most TRAIL_G148 and Y209 variants were produced in inclusion bodies, which could be explained by the importance of these residues for the TRAIL structure. To assess the binding of TRAIL variants to immobilized OPG-Fc, DR4-Fc and DR5-Fc, a prescreen ELISA assay was performed. The bindings of TRAIL variants to OPG-Fc, DR4-Fc and DR5-Fc were calculated relative to the response of TRAIL_WT. DR4-specific TRAIL_4C7 and DR5-specific TRAIL_DHER were reported before and used as control [14,15]. Several variants, displayed in figure 3, showed less

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Novel TRAIL variants with reduced binding to decoy receptor OPG binding to OPG-Fc compared to TRAIL_WT and these were further analyzed. Among these variants, TRAIL_D269H and D269R kept the binding to DR5 while showing approximately 60% lower binding to OPG. However, they also lost the binding to DR4 receptor indicating the importance of this position to both OPG and DR4 binding. TRAIL_Y209M, Y209F and K145W were also selected because of their lowered binding to OPG. TRAIL_K179T, K179T and K179M, although showing comparable binding to OPG as TRAIL_WT, were selected due to their increased DR4 binding and therefore decreased OPG/DR4 binding ratio.

Fig 3. Comparison of the relative bindings of TRAIL mutants towards mOPG-Fc, hDR4-Fc and hDR5-Fc, as 7 determined by ELISA. Receptor binding to mOPG-Fc and DR4-Fc was calculated relative to the response of TRAIL_WT (100%) at 0.2 nM, and the binding to DR5-Fc was calculated relative to the response of TRAIL_WT (100%) at 0.1 nM.

Combination of single variants

From the prescreen ELISA, several amino acid substitutions resulted in a lowered OPG binding relative to TRAIL_WT. However, none of them is better than TRAIL_DHER, which contains two mutations D269H and E195R. TRAIL_DHER was constructed to achieve a DR5-specific variant and had been found to have lowered binding to OPG as well [15]. Therefore, we combined the single mutants selected from the prescreen ELISA. The most promising variants TRAIL_D269H and D269R were combined with one of the three variants, TRAIL_ Y209M, Y209F and K145W. Interestingly, as shown in figure 4A, the six double mutants, TRAIL_D269H/Y209M, D269H/Y209F, D269H/K145W, D269R/Y209M, D269R/Y209F and D269R/K145W, all showed lowered binding to OPG compared to the

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Chapter 7 single mutants, and they also showed increased binding to DR5 compared to TRAIL_DHER. Unfortunately, the double mutants also lost the binding to the DR4 receptor, like TRAIL_DHER, confirming that D269 is crucial for the interaction with DR4. The triple mutant TRAIL_D269H/Y209M/K179P, which included the increased-DR4-binding single mutant, could not help to rescue the binding to DR4.

To further determine the bindings of TRAIL variants to OPG, DR4 and DR5, these variants were purified to homogeneity and subsequently, ELISA was performed with serial dilutions of TRAIL proteins. The binding curves were recorded using TRAIL concentrations ranging from 0.001 to 10 nM per well. As shown in figures 4B-4D, the results further confirm the decrease in bindings between the selected TRAIL variants to OPG and DR4, while they show similar binding to DR5, compared to TRAIL_WT. Interestingly, the double mutant TRAIL_D269H/Y209M and the triple mutant TRAIL_ D269H/Y209M/K179P even showed lowered binding to OPG, when compared with TRAIL_DHER. Therefore, these two TRAIL variants were taken for further biological evaluation.

Fig 4. Receptor binding of TRAIL_WT and selected TRAIL double and triple mutants to mOPG-Fc, DR4-Fc and DR5-Fc, as determined by ELISA. A) Comparison of the relative bindings of TRAIL double and triple

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Novel TRAIL variants with reduced binding to decoy receptor OPG mutants towards mOPG-Fc, DR4-Fc and DR5-Fc. Receptor binding to mOPG-Fc and DR4-Fc was calculated relative to the response of TRAIL_WT (100%) at 0.2 nM, and the binding to DR5-Fc was calculated relative to the response of TRAIL_WT (100%) at 0.1 nM. Receptor binding of TRAIL_WT and selected TRAIL mutants to B) mOPG-Fc, C) DR4-Fc and D) DR5-Fc were also performed with serial dilutions of TRAIL proteins. This was performed in three independent experiments and calculated relative to the response of TRAIL_WT at 10 nM. The error bars reflect the SD of three independent experiments.

Biological activity of the variants

The biological activities of TRAIL_WT and the variants TRAIL_D269H/E195R, TRAIL_D269H/Y209M and TRAIL_ D269H/Y209M/K179P were measured in the breast cancer cell lines MDA-MB-231 and MDA-MB-436. As shown in figures 5, for TRAIL sensitive cell line MDA-MB-231, at low concentration (5 ng/ml), the variants were better inducers of apoptosis when compared with TRAIL_WT, while at high concentrations, TRAIL_WT could induce more than 80% cell death and the variants caused 50%-60%. For MDA-MB-436 cell line, which is intermediate-sensitive to TRAIL, TRAIL_WT could induce 25% cell death at the highest concentration 100 ng/ml, and the TRAIL variants behaved better to cause 25% to 40% cell death. To assess the biological consequences of the variants toward OPG, we analyzed the survival of the breast cancer cell lines in the presence of 100 ng/ml OPG-Fc upon the addition of TRAIL_WT, TRAIL_D269H/E195R, TRAIL_D269H/Y209M 7 and TRAIL_ D269H/Y209M/K179P. Both cell lines became less sensitive to apoptosis when treated with TRAIL_WT, while the addition of OPG-Fc did not block these two cell lines from apoptosis induced by the variants TRAIL_D269H/E195R, TRAIL_D269H/Y209M and TRAIL_ D269H/Y209M/K179P.

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Fig 5. Biological activity of TRAIL_WT, D269H/E195R, D269H/Y209M, and D269H/Y209M/K179P in breast cancer cells with or without the addition of OPG. A) – D) MDA-MB-231 cells and E) – H) MDA-MB-436 cells were treated with TRAIL_WT, D269H/E195R, D269H/Y209M, and D269H/Y209M/K179P for 24 h in the presence or absence of 100 ng/ml OPG. The error bars reflect the SD from one independent experiments performed in triplicate.

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Discussion

OPG was first discovered and identified through sequence homology to the TNF receptor superfamily [22]. As the natural decoy receptor of RANKL, OPG inhibits the RANKL/RANK interaction, blocks osteoclast maturation and regulates bone remodeling system by sequestering RANKL [23]. Therefore, early studies about OPG and breast cancer were focused on bone metastases. In bone microenvironment, tumor cells form osteolytic metastases and OPG could prevent bone loss by blocking RANKL/RANK interaction [24]. However, primary breast tumors and breast cancer cells also express OPG, indicating the role of OPG in breast tumorigenesis [12]. Notably, as a ligand, OPG was found to have direct effects on tumor cells through binding to different receptors on cell surfaces such as Syndecan-1, αVβ5 integrin, and β-catenin. These bindings trigger different pathways such as PI3K/Akt, ERK or Wnt pathways, which results in the expression of various cell survival genes and causes cell survival, proliferation and angiogenesis [5]. On the other hand, as a decoy receptor of TRAIL, OPG can exert an anti-apoptotic effect on breast tumors by preventing the interactions of TRAIL and death receptors [12,13]. Therefore, TRAIL variants that can efficiently bind to death receptors without binding to OPG are of interest to trigger the apoptosis of breast cancer cells without being obstructed by high OPG production.

Previously we used CPD method to construct a structure-based RANKL mutant 7 RANKL_Q236D with decreased affinity to OPG [16]. This stimulated us to design a TRAIL variant with lowered binding to OPG as well, despite the lack of a crystal structure complex for TRAIL-OPG. Therefore, in this study, we first built up a model of the TRAIL-OPG complex by using DISCOVERY STUDIO 4.5 software. Through ZDOCK, which is an initial-stage protein-protein docking algorithm, we accomplished to search all possible binding modes; followed by RDOCK for minimization, and protein interface analysis, we finally got a model of the TRAIL-OPG complex (pose 2569). To confirm the accuracy of this model, we used the same way to build up the TRAIL-DR4 complex and then compared it to the published 3D TRAIL-DR4 structure (PDB code: 5CIR). It turned out that 70% of the residues involved in the interactions and 50% of the interactions in the published TRAIL-DR4 structure were predicted in our model, indicating the accuracy of the modeling method.

The model of TRAIL-OPG complex was used as the starting point for analyzing the binding surface. Several residues of TRAIL, K145, G148, K179, Y209, E252, K251 and D269, stand out as they show more interactions with OPG than DR4 and/or DR5. Receptor binding

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Chapter 7 experiments using a prescreen ELISA revealed that only several mutants showed lowered binding to OPG. However, it also confirmed the predictions that residue TRAIL_D269 is one of the most important residues for OPG binding. Like it was explained previously [7,15], TRAIL_D269 interacts with a conserved lysine in all the receptors, except for DR5 where it is D120. Changing this TRAIL_D269 to another amino acid with the opposite charge (D269H) would break the interaction of TRAIL-D269 and OPG_K67; however, it breaks the interaction between TRAIL_D269 and DR4_K120 as well. This may explain that if we use TRAIL_D269 as a start point to design TRAIL variants that do not bind to OPG, these might also lose the binding to DR4.

TRAIL_D269H/E195R was reported to show decreased affinity to OPG [15]. However, from the modeling structure (figure 6A), it can be seen that TRAIL_E195 is too far away to make an interaction with OPG. Therefore, it is hard to understand any contribution of TRAIL_E195R in decreasing the affinity to OPG. This led us to ignore position E195 for further improving TRAIL variants that do not bind to OPG. Through a combination strategy, we found the double mutant TRAIL_D269H/Y209M and the triple mutant TRAIL_ D269H/Y209M/K179P, which even show lowered binding to OPG, when compared with TRAIL_DHER. In line with these results, structural analysis shown in figures 6B-6D explains the importance of position Y209. In TRAIL_WT Y209 shows a hydrogen bond with OPG_I94. Although the single mutant TRAIL_D269H breaks the interactions between TRAIL_D269 and OPG_K67, it brings new electrostatic interaction between TRAIL_D269H and OPG_E95, which is located next to OPG_I94. When we combine the mutation Y209M with D269H, the two interactions (TRAIL_Y209-OPG_I94; TRAIL_D269H-OPG_E95) may all disappear because of the slight shift of the structure and the larger distances from TRAIL_Y209M and TRAIL_D269H to OPG_I94 and OPG_E95.

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Fig 6. Structural analysis and comparison of TRAIL_D269H/E195R and TRAIL_D269H/Y209M. A) The side view of TRAIL-OPG complex, indicating the location of TRAIL_E195; Predicted area of interactions of TRAIL 7 and OPG around position 269 and 209 in B) TRAIL_WT, C) TRAIL_D269H and D) TRAIL_D269H/Y209M.

In conclusion, we have found that the double mutant TRAIL_D269H/Y209M and the triple mutant TRAIL_D269H/Y209M/K179P showed decreased binding to OPG compare to TRAIL_DHER. These variants can efficiently target breast cancer cells by bypassing the interference caused by decoy receptor OPG. The generation of TRAIL mutants with reduced binding to OPG forms the available option for therapeutic intervention in breast cancers.

Methods and Materials

Modeling of TRAIL-OPG complex

Docking of hTRAIL-OPG complex was performed by using BIOVIA DISCOVERY STUDIO 4.5 software (Accelrys, CA, USA). The 3D structures of hTRAIL and hOPG were extracted

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Chapter 7 from hTRAIL-DR5 and hRANKL-OPG complexes (Protein Data Bank codes 1D4V and 3URF), respectively. The crystal water in these proteins was deleted. Then the proteins were cleaned and prepared by building missing loops and being protonated. Docking of proteins was proposed using ZDOCK module where TRAIL_Y216 was selected as filtered binding residue because of its conservation in receptor binding, and TRAIL_S165, located far away from the receptor-binding interface, was set as a blocked residue [7]. The region on the hOPG from OPG_G127 to H168 was also set as blocked residues. 5000 poses from maximum of 500 clusters passed the filters and promising poses were selected manually by comparing with the structure of hRANKL-OPG. Selected poses were refined by using the RDOCK module based on the CHARMm simulations program and the top poses from each cluster were further selected as candidates. We selected the highest-confidence model through analyzing and comparing the protein interface to the structure of the hRANKL-OPG complex (3URF). Interactions including hydrogen bond, electrostatic and hydrophobic effects between TRAIL- OPG. TRAIL-DR4 and TRAIL-DR5 complexes were analyzed.

Site-directed mutagenesis of selectivity Mutants cDNA corresponding to rhTRAIL (aa 114-281) was cloned in pET15b (Novagen, Darmstadt, Germany) using NcoI and BamHI restriction sites. For saturation mutation of each residue, the small-intelligent method was used to design primers by mixing four pairs of complementary primers with codons NDT, VMA, ATG, and TGG at a ratio of 12 : 6 : 1 : 1 [25]. Mutants were obtained by the QuikChange PCR method using Phusion DNA polymerase (New England Biolabs, Ipswich, MA, USA) as previously described [16]. The PCR products were digested with DpnI (Fermentas, St. Leon, Lithuania) restriction enzymes and then transformed into Escherichia coli DH5a cells. The produced colonies were sequenced by GATC Biotech (Constance, Germany).

Expression and purification of selectivity Mutants

After confirming the mutations by DNA sequencing, the plasmids were transformed into E. coli BL21(DE3). Homotrimeric TRAIL proteins were produced and purified as described before [10]. For prescreen using ELISA assay, proteins were purified using His MultiTrap™ Fast Flow GE Healthcare 96-well plates (Thermo). The purities of the TRAIL samples after

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Novel TRAIL variants with reduced binding to decoy receptor OPG this one step purification were sufficient. Briefly, cells were harvested from 10 ml culture and lysed by sonication. Supernatants were loaded to the 96-well His trap column with binding buffer (50 mM Tris-HCl, 100 mM NaCl, 20 µM ZnSO4 and 25 mM imidazole, 10% glycerol, pH 8.0). After washing, TRAIL proteins were eluted by elution buffer containing 250 mM imidazole.

ELISA

For the prescreen ELISA, the 96-well high binding plate was immobilized with 10 nM of hDR4-Fc, hDR5-Fc and murine OPG-Fc (100 μl/well) (R&D Systems, Minneapolis, MN, USA) in 0.1 M NaHCO3 buffer pH 8.6 overnight at 4 °C, respectively. After washing the plate with PBS buffer including 0.05% v/v Tween 20 (PBST), pH 7.4, the remaining binding places were blocked with 2% w/v BSA (Roche, Mannheim, Germany) for 2 h at room temperature (RT). The wells were washed with PBST three times, 100 μl of diluted one-step purified TRAIL_WT or mutants were added and incubated at RT for 1 h. For the binding to OPG-Fc and DR4-Fc, 0.2 nM of TRAIL_WT or mutants were added; for the binding to DR5- Fc, 0.1 nM was added. After washing with PBST buffer for three times, a 1 : 500 - 1 : 1000 dilution of Rabbit anti-TRAIL antibody (Cell signaling) was added and incubated at 4 °C overnight, and after washing, the plate was subsequently incubated with a 1 : 1000 anti-rabbit 7 HRP-conjugated antibody (Dako). After washing, the signal was quantified by adding 100 μl of One-step Turbo TMB reagent (ThermoScientific, Rockford, IL, USA) and stopped by 100 μl of 1 M sulfuric acid solution. The absorbance was measured at 450 nm. The percentage of TRAIL mutants bound to OPG-Fc, DR4-Fc or DR5-Fc was measured relative to the binding of TRAIL_WT.

Cell lines and reagents

Human breast cancer cell lines MDA-MB-231 and MDA-MB-436 were obtained from American Type Culture Collection (ATCC, Wesel, Germany). The cells were maintained in Dulbecco‘s modified Eagle‘s medium (Life Technologies, Carlsbad, CA, USA) supplemented with 10% fetal bovine serum (Costar Europe, Badhoevedorp, The Netherlands) and 2 mM penicillin/streptomycin at 37 °C with 5% CO2.

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Cell viability assay

Cells were seeded in 96-well plates at a density of 10,000 cells/well and maintained overnight prior to the treatment. Subsequently, cells were treated with 0-100 ng/ml of TRAIL_WT, TRAIL_DHER or other selected variants with or without OPG-Fc (Bio Legends, San Diego, CA, USA). For the treatment combined with OPG-Fc, rhTRAIL proteins were preincubated with OPG-Fc for 1h at 37 °C and then added to the plates. After 24 h incubation, 20 µl of MTS reagent (Promega, Madison, WI, USA) was added to each well according to the manufacturer‘s instruction. Cell viability was determined by measuring the absorption at 490 nm.

References

1 Holen I & Shipman CM (2006) Role of osteoprotegerin (OPG) in cancer. Clin. Sci. 110, 279–291. 2 Han H, Zhou H, Li J, Feng X, Zou D & Zhou W (2017) TRAIL DR5-CTSB crosstalk participates in breast cancer autophagy initiated by SAHA. Cell Death Discov. 3, 17052. 3 Siegel RL, Miller KD & Jemal A (2018) Cancer statistics, 2018. CA Cancer J Clin. 68, 7-30. 4 Gao W, Mei X, Wang J, Zhang X & Yuan Y (2015) ShRNA-mediated knock-down of CXCR7 increases TRAIL-sensitivity in MCF-7 breast cancer cells. Tumor Biol. 36, 7243–7250. 5 Goswami S & Sharma-Walia N (2016) Osteoprotegerin rich tumor microenvironment: implications in breast cancer. Oncotarget 7, 42777-42791. 6 Van Roosmalen IAM, Quax WJ & Kruyt FAE (2014) Two death-inducing human TRAIL receptors to target in cancer: Similar or distinct regulation and function? Biochem. Pharmacol. 91, 447–456. 7 Van der Sloot AM, Tur V, Szegezdi E, Mullally MM, Cool RH, Samali A, Serrano L & Quax WJ (2006) Designed tumor necrosis factor-related apoptosis-inducing ligand variants initiating apoptosis exclusively via the DR5 receptor. Proc. Natl. Acad. Sci. U. S. A. 103, 8634–8639. 8 Bodmer J-L, Holler N, Reynard S, Vinciguerra P, Schneider P, Juo P, Blenis J & Tschopp J (2000) TRAIL receptor-2 signals apoptosis through FADD and caspase-8. Nat. Cell Biol. 2, 241–243. 9 Kischkel FC, Lawrence DA, Chuntharapai A, Schow P, Kim KJ & Ashkenazi A (2000) Apo2L/TRAIL-Dependent Recruitment of Endogenous FADD and Caspase-8 to Death

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Receptors 4 and 5. Immunity 12, 611–620. 10 Reis CR, Van der Sloot AM, Szegezdi E, Natoni A, Tur V, Cool RH, Samali A, Serrano L & Quax WJ (2009) Enhancement of antitumor properties of rhTRAIL by affinity increase toward its death receptors. Biochemistry 48, 2180–2191. 11 Pettersen I, Bakkelund W, Smedsrød B & Sveinbjørnsson B (2005) Osteoprotegerin is expressed in colon carcinoma cells. Anticancer Res. 25, 3809–3816. 12 Holen I, Cross SS, Neville-Webbe HL, Cross NA, Balasubramanian SP, Croucher PI, Evans CA, Lippitt JM, Coleman RE & Eaton CL (2005) Osteoprotegerin (OPG) expression by breast cancer cells in vitro and breast tumours in vivo - A role in tumour cell survival? Breast Cancer Res. Treat. 92, 207–215. 13 Weichhaus M, Chung STM & Connelly L (2015) Osteoprotegerin in breast cancer: Beyond bone remodeling. Mol. Cancer 14, 1–7. 14 Reis CR, Van Der Sloot AM, Natoni A, Szegezdi E, Setroikromo R, Meijer M, Sjollema K, Stricher F, Cool RH, Samali A, Serrano L & Quax WJ (2010) Rapid and efficient cancer cell killing mediated by high-affinity death receptor homotrimerizing TRAIL variants. Cell Death Dis. 1, e83-10. 15 Bosman MCJ, Reis CR, Schuringa JJ, Vellenga E & Quax WJ (2014) Decreased affinity of recombinant human tumor necrosis factor-related apoptosis-inducing ligand (rhTRAIL) D269H/E195R to osteoprotegerin (OPG) overcomes trail resistance mediated by the bone microenvironment. J. Biol. Chem. 289, 1071–1078. 16 Wang Y, Michiels T, Setroikromo R, van Merkerk R, Cool RH & Quax WJ (2019) Creation of RANKL mutants with low affinity for decoy receptor OPG and their potential anti-fibrosis activity. FEBS J. 286, 3582–3593. 7 17 Ramamurthy V, Yamniuk AP, Lawrence EJ, Yong W, Schneeweis LA, Cheng L, Murdock M, Corbett MJ, Doyle ML & Sheriff S (2015) The structure of the death receptor 4– TNF-related apoptosis-inducing ligand (DR4–TRAIL) complex. Acta Crystallogr. Sect. F Struct. Biol. Commun. 71, 1273–1281. 18 Mongkolsapaya J, Grimes JM, Chen N, Xu XN, Stuart DI, Jones EY & Screaton GR (1999) Structure of the TRAIL-DR5 complex reveals mechanisms conferring specificity in apoptotic initiation. Nat. Struct. Biol. 6, 1048–53. 19 Cha S-S, Sung B-J, Kim Y-A, Song Y-L, Kim H-J, Kim S, Lee M-S & Oh B-H (2000) Crystal Structure of TRAIL-DR5 Complex Identifies a Critical Role of the Unique Frame Insertion in Conferring Recognition Specificity. J. Biol. Chem. 275, 31171–31177. 20 Luan X, Lu Q, Jiang Y, Zhang S, Wang Q, Yuan H, Zhao W, Wang J & Wang X (2016) Crystal structure of human RANKL complexed with its decoy receptor opsteoprotegerin. J. Immunol. 189, 245–252. 21 Li L, Chen R & Weng Z (2003) RDOCK: Refinement of Rigid-body Protein Docking Predictions. Proteins Struct. Funct. Genet. 53, 693–707. 22 Lacey DL, Boyle WJ, Simonet WS, Kostenuik PJ, Dougall WC, Sullivan JK, Martin JS & Dansey R (2012) Bench to bedside: Elucidation of the OPG-RANK-RANKL pathway and the development of denosumab. Nat. Rev. Drug Discov. 11, 401–419.

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23 Nelson CA, Warren JT, Wang MW, Teitelbaum SL, Fremont DH & Engage R (2012) RANKL employs distinct binding modes to enage RANK and the osteoprotegerin decoy receptor. Structure 20, 1971–1982. 24 Renema N, Navet B, Heymann M-F, Lezot F & Heymann D (2016) RANK-RANKL signalling in cancer. Biosci. Rep. 36, e00366. 25 Tang L, Gao H, Zhu X, Wang X, Zhou M & Jiang R (2012) Construction of ―small- intelligent‖ focused mutagenesis libraries using well-designed combinatorial degenerate primers. Biotechniques 52, 149–158.

Abbreviations

TNF - Tumor Necrosis Factor TRAIL - Tumor Necrosis Factor Related Apoptosis Inducing Ligand OPG - Osteoprotegerin DR - Death Receptor DcR - Decoy Receptor CPD - Computational Protein Design RANKL - Receptor Activator of Nuclear Factor-κB-ligand PI3K - Phosphoinositide 3-kinase ERK - Extracellular signal-regulated kinases

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Supplementary

Supple Table. 1. Interaction analysis between TRAIL-OPG, TRAIL-DR4 and TRAIL- DR5 complexes

TRAIL-OPG TRAIL-DR4/DR5

Interaction Category Interaction Category K145 TRAIL1:K145:NZ - OPG:E85:OE2 Electrostatic TRAIL1:K145:CE - OPG:E85:OE2 Hydrogen Bond TRAIL1:K145 - OPG:V83 Hydrophobic

G148 OPG:R117:HE - TRAIL1:G148:O Hydrogen Bond OPG:R117:HH21 - TRAIL1:G148:O Hydrogen Bond

K179 TRAIL1:K179:NZ - OPG:D57:OD2 Electrostatic TRAIL1:K179:NZ - OPG:E58:OE2 Electrostatic TRAIL1:K179:CE - OPG:D57:OD2 Hydrogen Bond

OPG:I94:HN - TRAIL1:Y209:OH Hydrogen Bond Y209

OPG:K22:NZ - TRAIL1:E252:OE2 Electrostatic E252 OPG:T55:HG1 - TRAIL1:E252:OE1 Hydrogen Bond

R130 TRAIL2:R130:NH1 - OPG:E95:OE2 Electrostatic TRAIL2:R130:HD1 - DR5:C116:O Hydrogen Bond

K251 TRAIL1:K251:HZ1 - OPG:S56:OG Hydrogen Bond TRAIL 1:K251:HZ1 - DR4:N160:O Hydrogen Bond TRAIL1:K251:HZ1 - OPG:E58:O Hydrogen Bond TRAIL 1:K251:HZ3 - DR4:N160:O Hydrogen Bond TRAIL1:K251:HZ2 - OPG:S56:OG Hydrogen Bond

TRAIL1:K251:HZ3 - OPG:E58:O Hydrogen Bond

TRAIL1:K251 - OPG:L60 Hydrophobic 7 OPG:H54 - TRAIL1:K251 Hydrophobic

D269 OPG:K67:HZ1 - TRAIL2:D269:OD2 Hydrogen Bond;Electrostatic DR4:K171:HZ3 - TRAIL2:D269:OD2 Hydrogen Bond;Electrostatic OPG:K67:HZ2 – TRAIL2:D269:OD2 Hydrogen Bond;Electrostatic DR4:K171:HE2 - TRAIL2:D269:OD1 Hydrogen Bond

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Summary and future perspectives

Chapter 8

During the last two decades, research has shown that the tumor necrosis factor (TNF) superfamily is of importance in numerous biological activities, such as mediating cellular apoptosis, survival, differentiation or proliferation. The binding between the TNF superfamily ligands and receptors regulates normal physiological processes, while the deregulation may cause harmful effects [1]. Therefore, targeting TNF superfamily ligands or receptors with either agonistic or antagonistic molecules may provide novel approaches for therapy. The work described in this thesis is focused on the ligand-receptor interface of TNF super family members Ligand of Receptor Activator of Nuclear Factor κB (RANKL) and TNF-Related Apoptosis Inducing Ligand (TRAIL), to design and characterization novel recombinant RANKL and TRAIL variants for their use as potential therapeutics.

Chapter 2 of this thesis provides a review on the RANKL/RANK pathway as a therapeutic target for bone diseases. This pathway is inhibited by the RANKL-specific monoclonal antibody Denosumab, which is clinically used to treat osteoporosis, but also by the natural, soluble decoy receptor of RANKL, osteoprotegerin (OPG). Alternatively, the receptor RANK can be inhibited by RANKL variants with antagonistic properties. Finally, the possibility to create antagonistic molecules by changing the stoichiometry of the receptor is discussed, which can further break the signal transduction. Taken together, interfering with the RANKL/RANK/OPG pathway is a promising strategy to develop therapeutics for bone diseases.

In Chapter 3, antagonistic variants of RANKL have been designed by the introduction of mutations at position I248 in the mRANKL DE-loop, and their effects on the binding to mRANK and subsequent osteoclastogenesis is investigated. Two single mutants, RANKL I248Y and I248K, show increased binding affinity to RANK compared to RANKL WT, which is mainly caused by an increase in the association rate constant (ka). Competitive ELISA results also show both RANKL I248K and I248Y can efficiently compete with RANKL WT for RANK-Fc binding. Interestingly, although RANKL I248Y and I248K are still able to induce osteoclastogenesis at a 20-30% lower rate than RANKL WT, these two variants are able to reduce RANKL WT-mediated osteoclastogenesis already at low concentrations. Taken together (shown in Figure 1), our data show that the DE-loop of RANKL is of importance for RANK binding and RANKL mutants I248Y and I248K can reduce RANKL WT-induced osteoclastogenesis. These two RANKL mutants may form a starting point for the development of novel therapeutic proteins in osteoporosis treatments.

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Figure 1. Novel RANKL DE-loop mutants I248Y and I248K reduce RANKL WT-induced osteoclastogenesis.

Recent studies show that the RANKL-RANK pathway has physiological and pathological effects on tissues other than bone. Interestingly, this system may play a role in fibrosis [2]. In Chapter 4, we hypothesized that RANKL could stimulate RANK on macrophages and activate the process of extracellular matrix (ECM) degradation in fibrotic tissue, which might 8 be inhibited by highly expressed OPG. Therefore, the aim of this study was to create RANKL mutants that bind to RANK but not to OPG, and thus reduce ECM. We compared the 3D structures of RANKL-RANK and RANKL-OPG and built up a structure-based RANKL mutant library containing 44 RANKL mutants. Our results show that the RANKL Q236 position is of importance for OPG binding. One single mutant RANKL_Q236D has approximately a 30-time decrease in affinity to OPG-Fc compared to RANKL_WT. Pleasingly, RANKL_Q236D is also very effective in activating murine RAW 264.7 macrophages and to escape from the blockade by exogenous OPG (shown in Figure 2). RANKL mutants with reduced binding to OPG show potential anti-fibrosis activity, which offers a promising strategy to explore new therapeutics against fibrosis.

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Figure 2. RANKL_Q236D is able to escape from the blockade by exogenous OPG and activate RAW cells to initiate the ECM degradation process.

As a continuation of the study on RANKL mutants with low affinity for OPG and their potential anti-fibrosis activity, in Chapter 5, we constructed adenoviruses Ad-RANKL WT and Ad-RANKL Q236D (shown in Figure 3). The aim of this study was to achieve a targeting delivery system by directly produce RANKL_Q236D in the fibrotic tissues without influencing other tissues. We found that by infecting C10 cells with Ad-RANKL WT/Q236D, secreted RANKL protein can be detected up to 19 days with protein levels up to 30 nM, which shows the long-term potential of delivering the proteins via an adenovirus system. Virally produced RANKL_Q236D maintains the activation of RAW 264.7 cells and escapes from the blocking of exogenous OPG-Fc. In a co-incubation system to mimic the process of adenovirus infection in vivo, we also found that Ad-RANKL Q236D infected C10 cells were capable of activating MMP9 gene expression in RAW 264.7 cells. Taken together, the generation of Ad-RANKL Q236D could be a powerful new tool for the treatment of fibrosis.

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Figure 3. Virally produced RANKL_Q236D can activate RAW 264.7 cells and escape from the blocking of exogenous OPG-Fc.

Since OPG also acts as the decoy receptor of TRAIL, in Chapter 6 and 7 we further investigated the ligand-receptor interface of TRAIL and its receptors, and TRAIL resistance caused by its decoy receptors. In Chapter 6, we focused on the extrinsic apoptosis of senescent breast cancer cells caused by TRAIL. We compared the sensitivity to TRAIL of senescent and proliferating cancer cells. It turns out that changes in sensitivity to TRAIL are dependent on the pre-existing resistance observed for each cell line before senescence induction. We also found that therapy-induced senescence, by either doxorubicin treatment or ionizing radiation, results in an increased expression of death receptor 5 (DR5), as well as an increase in TRAIL decoy receptors DcR1, DcR2, and OPG. A DR5-selective TRAIL variant 8 (DHER) is more effective in inducing apoptosis of senescent breast cancer cells compared to wild-type TRAIL, both in 2D and 3D spheroid models (shown in Figure 4). This suggests that targeting DR5 might be a therapeutic strategy for the elimination of therapy-induced senescent cancer cells.

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Figure 4. DR5-selective TRAIL variant (DHER) is more effective than wild-type TRAIL in inducing apoptosis in senescent breast cancer cells.

In Chapter 7, we focused on resistance of breast cancer cells to TRAIL due to high expression of decoy receptor OPG. The aim was to create TRAIL variants that can efficiently bind to death receptors with decreased binding to OPG. In this study, we built a model of complex TRAIL-OPG through Discovery Studio software and subsequently a TRAIL mutant library was created based on this 3D model. This mutant library is screened by ELISA, and points at TRAIL_D269 residue be of importance for OPG binding. Through a combination strategy, double mutant TRAIL_D269H/Y209M and triple mutant TRAIL_D269H/Y209M/K179P are shown to have lower binding to OPG compared to TRAIL_D269H/E195R. These variants also induce apoptosis in breast cancer cells MDA- MB-231 and MDA-MB-436 in the presence of OPG. Thus, the generation of TRAIL mutants with reduced binding to OPG may be promising for targeting breast tumors in high OPG microenvironments.

Conclusion and future perspectives

As described in this thesis, we focused on probing the ligand-receptor interface of TNF superfamily members RANKL and TRAIL. Through the combination of Computational Protein Design (CPD) and targeted mutagenesis with screening and characterization assays,

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Summary and future perspectives we obtained receptor-specific, agonistic or antagonistic variants of RANKL and TRAIL, thereby providing novel approaches for the treatment of osteoporosis, fibrosis or cancer.

In Chapter 3, two RANK-antagonists, RANKL I248Y and I248K, are described to reduce WT RANKL-induced osteoclastogenesis by competing for binding to RANK. However, the mechanism of RANKL I248Y and I248K showing less osteoclastogenesis is still not clear. Therefore, it is interesting to look into how RANKL I248Y and I248K change the conformation of the RANKL-RANK complex, and subsequently influence the orientation of intracellular domains of RANK and the recruitment of downstream effector proteins. In Chapter 4 and 5, we focused on the potential role of the RANKL/RANK/OPG system in fibrosis. RANKL_Q236D maintains activation of RAW 264.7 macrophages and escapes the blockade by exogenous OPG. The adenovirus-mediated expression of RANKL_Q236D is shown to achieve long term targeted delivery. Notably, the antifibrotic effects of Adenovirally-expressed RANKL_Q236D deserve to be evaluated in vivo.

In Chapter 6 and 7, the ligand-receptor interface of TRAIL and its receptors is investigated, and TRAIL resistance caused by its decoy receptors. The DR5 selective TRAIL variant (DHER) with decreased binding to OPG or DR4 is found to be more effective in inducing apoptosis of senescent breast cancer cells compared to wild-type TRAIL. On the other hand, TRAIL D269H/Y209M and TRAIL D269H/Y209M/K179P show decreased binding to OPG compared to TRAIL DHER. Since TRAIL resistance occurs in approximately half of the tumor cells, there is a need to overcome resistance and sensitize TRAIL-induced apoptosis. 8 Therefore, receptor-specific TRAIL variants, as single treatment or in combination strategies, could become promising for the treatment of cancers.

Overall, our work shows that the combination of CPD and focused mutagenesis with screening is a powerful approach to modify protein-protein interactions. We produced and evaluated recombinant RANKL and TRAIL mutants, which showed improved receptor selectivity and might overcome decoy receptor related resistance. Gene therapy approaches using Adenovirus may result in a sustained level of these recombinant proteins, thereby providing potential approaches for the treatments of osteoporosis, fibrosis or cancer. Additional efficacy and safety studies in vivo deserve to be conducted in the future.

References:

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1 Aggarwal BB (2003) Signalling pathways of the TNF superfamily: A double-edged sword. Nat. Rev. Immunol. 3, 745–756. 2 Adhyatmika A, Putri KSS, Beljaars L & Melgert BN (2015) The elusive antifibrotic macrophage. Front. Med. 2, 1–11.

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In de afgelopen twee decennia is er aangetoond dat de superfamilie van tumornecrosefactor (TNF) van belang is bij tal van biologische activiteiten, zoals het mediëren van cellulaire apoptose, overleving, differentiatie of proliferatie. De binding tussen de liganden van de TNF- superfamilie en hun receptoren reguleert normale fysiologische processen, terwijl de deregulering schadelijke effecten kan veroorzaken [1]. Daarom kan het richten op TNF- superfamilieliganden of -receptoren met agonistische of antagonistische moleculen nieuwe benaderingen voor therapie opleveren. Het werk dat in dit proefschrift wordt beschreven, richt zich op de ligand-receptor-interface van TNF-superfamilieleden Ligand van Receptor Activator of Nuclear Factor κB (RANKL) en TNF-gerelateerde Apoptosis Inducing Ligand (TRAIL), om nieuwe recombinante RANKL en TRAIL varianten te ontwerpen en karakteriseren voor hun gebruik als potentiële therapeutica.

Hoofdstuk 2 van dit proefschrift geeft een overzicht van de RANKL/RANK-route als therapeutisch doelwit voor botziekten. Deze route kan worden geremd door het gebruik van het RANKL-specifieke monoklonale antilichaam Denosumab, dat klinisch wordt gebruikt voor de behandeling van osteoporose, maar ook door de natuurlijke, oplosbare ―lokaasreceptor‖ van RANKL, osteoprotegerin (OPG). Als alternatief kan de receptor RANK worden geremd door RANKL-varianten met antagonistische eigenschappen. Tenslotte wordt de mogelijkheid besproken om antagonistische moleculen te creëren door de stoichiometrie van de receptor te veranderen, en daarmee de signaaltransductie te verbreken. Alles bij elkaar is het interfereren van de RANKL/RANK-route een veelbelovende strategie om therapeutica voor botziekten te ontwikkelen.

In Hoofdstuk 3 zijn antagonistische varianten van RANKL ontworpen door de introductie van mutaties op positie I248 in de mRANKL DE-loop, en zijn hun effecten op de binding aan mRANK en daaropvolgende osteoclastogenese onderzocht. Twee mutanten, RANKL I248Y en I248K, vertonen een verhoogde bindingsaffiniteit voor RANK in vergelijking met RANKL WT, wat voornamelijk wordt veroorzaakt door een toename in de associatiesnelheidconstante (ka). Competitie-ELISA experimenten tonen ook aan dat zowel RANKL I248K als I248Y efficiënt kunnen concurreren met RANKL WT voor RANK-Fc-binding. Interessant is dat hoewel RANKL I248Y en I248K nog steeds in staat zijn osteoclastogenese te induceren met een 20-30% lager percentage dan RANKL_WT, deze twee varianten in staat zijn om RANKL_WT-gemedieerde osteoclastogenese al bij lage concentraties te verminderen. Alles

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Samenvatting en toekomstperspectieven bij elkaar genomen (weergegeven in figuur 1), laten onze gegevens zien dat de DE-lus van RANKL van belang is voor RANK-binding en dat RANKL-mutanten I248Y en I248K in staat zijn de RANKL WT-geïnduceerde osteoclastogenese te verminderen. Deze twee RANKL-mutanten kunnen een startpunt vormen voor de ontwikkeling van nieuwe therapeutische eiwitten bij osteoporosebehandelingen.

Figuur 1. Nieuwe RANKL DE-loop-mutanten I248Y en I248K verminderen RANKL WT-geïnduceerde osteoclastogenese.

Recente studies tonen aan dat de RANKL-RANK-route fysiologische en pathologische effecten heeft op andere weefsels dan bot. Interessant is dat dit systeem een rol kan spelen bij fibrose [2]. In hoofdstuk 4 veronderstelden we dat RANKL de receptor RANK op macrofagen zou kunnen stimuleren en het proces van afbraak van extracellulaire matrix (ECM) in fibrotisch weefsel zou kunnen activeren, een proces dat zou kunnen worden geremd door sterk tot expressie gebracht OPG. Daarom was het doel van deze studie om RANKL- mutanten te creëren die wel aan RANK binden maar niet aan OPG, en dus ECM kunnen reduceren. We vergeleken de 3D-structuren van RANKL-RANK en RANKL-OPG en bouwden een op structuur gebaseerde RANKL-mutantenbibliotheek met 44 RANKL- mutanten. Onze resultaten laten zien dat de positie van RANKL Q236 van belang is voor

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OPG-binding. Eén enkele mutant RANKL_Q236D vertoont een 30-voudige afname in affiniteit met OPG-Fc in vergelijking met RANKL_WT. RANKL_Q236D blijkt ook zeer effectief is bij het activeren van de muis macrofaag RAW 264.7 cellen- en wordt daarbij niet geremd door exogene OPG (weergegeven in figuur 2). RANKL-mutanten met verminderde binding aan OPG vertonen potentiële anti-fibrose-activiteit, wat een veelbelovende strategie biedt om nieuwe therapeutica tegen fibrose te onderzoeken.

Figuur 2. RANKL_Q236D kan uit de blokkade van exogene OPG ontsnappen en RAW-cellen activeren om het ECM-afbraakproces te starten.

Als vervolg op het onderzoek naar RANKL-mutanten met een lage affiniteit voor OPG en hun potentiële anti-fibrose-activiteit, hebben we in hoofdstuk 5 adenovirussen Ad-RANKL WT en Ad-RANKL Q236D geconstrueerd (weergegeven in figuur 3). Het doel van deze studie was om een gericht toedieningssysteem te bereiken door RANKL_Q236D rechtstreeks in de fibrotische weefsels te produceren zonder andere weefsels te beïnvloeden. We ontdekten dat door C10-cellen te infecteren met Ad-RANKL WT / Q236D, uitgescheiden RANKL-eiwit tot 19 dagen kan worden gedetecteerd met eiwitniveaus tot 30 nM, wat het langetermijnpotentieel laat zien van het afleveren van de eiwitten via een adenovirussysteem. Viraal geproduceerde RANKL_Q236D handhaaft de activering van RAW 264.7-cellen en ontsnapt uit de blokkering van exogene OPG-Fc. In een co-incubatiesysteem om het proces van adenovirusinfectie in vivo na te bootsen, vonden we ook dat met Ad-RANKL Q236D geïnfecteerde C10-cellen MMP9-genexpressie in RAW 264.7-cellen konden activeren. Alles

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Samenvatting en toekomstperspectieven bij elkaar genomen kan de generatie van Ad-RANKL Q236D een krachtig nieuw hulpmiddel zijn voor de behandeling van fibrose.

Figuur 3. Viraal geproduceerde RANKL_Q236D kan RAW 264.7-cellen activeren en ontsnappen aan de blokkering van exogene OPG-Fc.

Aangezien OPG ook fungeert als de lokaasreceptor van TRAIL, hebben we in Hoofdstuk 6 en 7 de ligand-receptor interface van TRAIL en zijn receptoren en TRAIL-resistentie veroorzaakt door de lokaasreceptoren verder onderzocht. In Hoofdstuk 6 hebben we ons gericht op de extrinsieke apoptose van verouderde borstkankercellen veroorzaakt door TRAIL. We vergeleken de gevoeligheid voor TRAIL tussen verouderde en prolifererende kankercellen. Het blijkt dat veranderingen in gevoeligheid voor TRAIL afhankelijk zijn van de reeds bestaande resistentie die voor elke cellijn werd waargenomen vóór inductie van veroudering. We ontdekten ook dat door therapie geïnduceerde veroudering, door behandeling met doxorubicine of ioniserende straling, leidt tot een verhoogde expressie van death receptor 5 (DR5), evenals een toename van TRAIL lokaasreceptoren DcR1, DcR2 en OPG. Een DR5-selectieve TRAIL-variant (DHER) is effectiever in het induceren van apoptose van verouderde borstkankercellen in vergelijking met wildtype TRAIL, zowel in 2D- als 3D-sferoïdemodellen (weergegeven in Figuur 4). Dit suggereert dat het richten op DR5 een therapeutische strategie kan zijn voor de eliminatie van door therapie verouderde kankercellen.

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Figuur 4. DR5-selectieve TRAIL-variant (DHER) is effectiever dan wildtype TRAIL bij het induceren van apoptose in verouderde borstkankercellen.

In hoofdstuk 7 hebben we ons gericht op resistentie van borstkankercellen tegen TRAIL als gevolg van hoge expressie van OPG. Het doel was om TRAIL-varianten te creëren die efficiënt kunnen binden aan pro-apoptosis receptoren, maar met verminderde binding aan OPG.

In deze studie hebben we een model van complex TRAIL-OPG gebouwd via Discovery Studio-software en vervolgens is een op TRAIL-mutantenbibliotheek gemaakt op basis van dit 3D-model. Deze mutantbibliotheek is gescreend middels ELISA, waaruit duidelijk werd dat positie TRAIL_D269van belang is voor OPG-binding. Door middel van een combinatiestrategie is aangetoond dat dubbele mutant TRAIL_D269H/Y209M en drievoudige mutant TRAIL_D269H/Y209M/K179P een lagere binding met OPG hebben in vergelijking met TRAIL_D269H/E195R. Deze varianten veroorzaken ook apoptose in borstkankercellen MDA-MB-231 en MDA-MB-436 in aanwezigheid van OPG. De generatie van TRAIL- mutanten met verminderde binding aan OPG zou dus veelbelovend kunnen worden voor het aanpakken van borsttumoren in micro-omgevingen met hoge OPG concentraties.

Conclusie en toekomstperspectieven

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Samenvatting en toekomstperspectieven

Zoals beschreven in dit proefschrift, hebben we ons gericht op het onderzoeken van de ligand- receptor interface van TNF superfamilieleden RANKL en TRAIL. Door de combinatie van Computational Protein Design (CPD) en gerichte mutagenese met screening- en karakterisatiebepalingen, hebben we receptorspecifieke, agonistische of antagonistische varianten van RANKL en TRAIL verkregen, waardoor we nieuwe benaderingen hebben geboden voor de behandeling van osteoporose, fibrose of kanker.

In Hoofdstuk 3 worden twee RANK-antagonisten beschreven, RANKL_I248Y en I248K, die WT RANKL-geïnduceerde osteoclastogenese kunnen verminderen door te strijden om binding aan RANK. Het mechanisme van RANKL_I248Y en I248K dat minder osteoclastogenese vertoont, is echter nog steeds niet duidelijk. Daarom is het interessant om te kijken hoe RANKL_I248Y en I248K de conformatie van het RANKL-RANK-complex veranderen en vervolgens de oriëntatie van intracellulaire domeinen van RANK en de rekrutering van stroomafwaartse effector-eiwitten beïnvloeden.In hoofdstuk 4 en 5 hebben we ons gericht op de potentiële rol van het RANKL/RANK/OPG-systeem bij fibrose. RANKL_Q236D is in staat tot activering van RAW 264.7-macrofagen en ontsnapt aan de blokkade door exogene OPG. Lange termijn productie van deze mutant is bereikt middels adenovirus gemedieerde expressie van RANKL_Q236D. Met name de antifibrotische effecten van adenoviraal tot expressie gebrachte RANKL_Q236D verdienen het om in vivo te worden beoordeeld.

In Hoofdstuk 6 en 7 wordt de ligand-receptor interface van TRAIL en zijn receptoren onderzocht, en TRAIL-resistentie veroorzaakt door de lokaasreceptoren. De DR5-selectieve TRAIL-variant (DHER) met verminderde binding aan OPG of DR4 blijkt effectiever te zijn bij het induceren van apoptose van verouderde borstkankercellen in vergelijking met wildtype TRAIL. Aan de andere kant vertonen TRAIL D269H/Y209M en TRAIL D269H/Y209M/K179P verminderde binding aan OPG in vergelijking met TRAIL DHER. Aangezien TRAIL-resistentie optreedt in ongeveer de helft van de tumorcellen, is het nodig om resistentie te overwinnen en TRAIL-geïnduceerde apoptose te sensibiliseren. Daarom kunnen receptorspecifieke TRAIL-varianten, ofwel als monotherapie of in combinatiestrategieën, veelbelovend worden voor de behandeling van kanker.

Al met al toont ons werk aan dat de combinatie van CPD en gerichte mutagenese met screening een krachtige benadering is om eiwit-eiwitinteracties te wijzigen. We produceerden en evalueerden recombinante RANKL- en TRAIL-mutanten, die een verbeterde

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Samenvatting en toekomstperspectieven receptorselectiviteit vertoonden en mogelijk resistentie tegen lokreceptoren konden overwinnen. Gentherapiebenaderingen met behulp van Adenovirus kunnen resulteren in een aanhoudend niveau van deze recombinante eiwitten, waardoor mogelijke benaderingen worden geboden voor de behandeling van osteoporose, fibrose of kanker. Bijkomend aanvullend onderzoek naar de werkzaamheid en veiligheid in vivo verdient het om in de toekomst te worden uitgevoerd

References:

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Appendices

Acknowledgements List of publications About the author

Achknowledgements

Acknowledgements

Today is my 30th birthday and it is a great opportunity to recall my PhD life in the Netherlands. In the last four and a half years, I have been so lucky to meet all of you and work in such a supportive environment. At this moment, I would like to express my gratitude to everyone who helped me with this journey.

First of all, I would like to express my deep thanks to my supervisor Prof. dr. Wim. J. Quax. Dear Wim, thank you for offering me the opportunity to study under your supervision and for supporting me through these years. I have learned a lot from your guidance, not only the broad knowledge but also scientific thinking and problem-solving skills. I cherish every opportunity to have the meeting with you because you can always solve problems that have troubled me for a long time, and you always cheer me up when I feel worried during my study. Besides, you encourage me to cooperate with other departments and support me to join the international conference, which allowed me to learn the frontiers of research on cell death. Apart from work, you are also very kind and patient to everyone. I appreciate your care for the ―elevator people‖ and your organization for the department during the Covid-19 lockdown. I wish you all the best.

I would like to thank my second supervisor Prof. dr. Hidde. J. Haisma. Dear Hidde, we have had frequent communications since Olivia and I started the project on adenoviral- expressed RANKL WT/ Q236D. I enjoy our discussions at every meeting, and I learned a lot of knowledge about adenovirus from you. Special thanks to you for your patience and time to help me revise my thesis in the end period of my PhD. My sincere thanks to Prof. dr. Gerrit J. Poelarends and Prof. dr. Frank J. Dekker for the kind comments and constructive suggestions for my PhD projects.

I would like to thank the members of my assessment committee: Prof. R.A. Bank, Prof. B.N. Melgert, and Prof. V.W. van Beusechem for taking the time to evaluate and comment on my thesis.

I would also like to thank Dr. Marco Demaria and Prof. Barbro. N. Melgert for helping me with my research projects. Dear Marco, thank you for the support and discussions on the ―TRAIL-senescent‖ story, from which I got a huge interest in the field of cellular senescence. Dear Barbro, thank you for the guidance on my RANKL project. In the meantime, I would also like to show my gratitude to you for the knowledge of statistics analysis.

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Dear Dr. Robbert. Cool, I don't know how to express my gratitude to you because you have given me too much help and support along the way in the past four and a half years. Thanks to you, I systematically learned protein-related knowledge and technologies. You spent a lot of time and effort teaching me to use the AKTA and Biacore machines. I destroyed the Biacore a thousand times, but you are always patient to help me ―kick off the devils.‖ Thanks for translating the Dutch Summary for my thesis and helping me write the recommendation letter. We have a lot of communications both at and out of the work. I appreciate your rigorous attitude towards scientific research and your optimism towards life. I will move forward with your encouragement and support.

Dear Ykelien, thank you for being my second supervisor in the first two years of my PhD. You gave me a lot of guidance on my projects and taught me the techniques to be a strong/confident woman. Thank you for inviting me to dinners with different interesting topics and for the best desserts in the world, especially the matcha ice-cream. Importantly, thank you for the daily hugs, which are the warmest gifts you gave to me.

Dear Rita, thank you for everything! You are always generous and ready to help others. Without you, I definitely could not finish this thesis smoothly. I feel lucky to meet you in a foreign country and I seem to be used to sharing my emotions with you. The conference trip to Dresden made us know each other better. I appreciate your honesty and bravery. Love you because you are unique Rita! Dear Ronald, thank you for introducing the Discovery studio software and some advanced/effective techniques to me. Thank you for always helping me to solve various problems efficiently. I enjoy our discussions about selecting RANKL and TRAIL mutants, although sometimes I am stubborn. Dear Pieter, thank you for helping me with ordering reagents and arranging lab issues. Thank you for your concern after the elevator accident. Dear Petra, thank you for your help and quick response when I came to you. I wish you all the best!

Dear Yvonne, Janita, and Gillian, thank you for your professional work, which allows me to conduct PhD study efficiently. I would also like to thank Anne and Cathy for helping me with PhD registration and extension related issues.

My dear officemates, Brenda, Magda, Abel, and Xinyu. We spent these years together in perfect harmony. I am very lucky to meet each of you. Brenda, we accompanied each other through many unforgettable moments. Thank you, my 小师姐，for your continuous support and encouragement to me. I admire your bravery and very happy for you to get a postdoc

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Achknowledgements position in Dublin. I wish you, Louis, and Xiaodong all the best. Magda, this world may sometimes be unfriendly, but the sunshine always comes after the rain. I appreciate your versatility and your passion for life. Thank you for the various interesting conversations, for the dinners and the living room concerts. You are amazing. I wish you all the best in Gdansk. Abel, my paranymph, I feel very lucky to have a close friend like you in my life. You are so smart with broad knowledge. You have the most beautiful heart, always thinking about others. I believe we will keep in touch! Xinyu, I enjoy chatting with you a lot. Thank you for so many smart tips both at and out of work. I wish your PhD study goes smoothly. I love you all!

My sincere gratitude to people who also help me with my research projects. Abel, it is so pleasant to work with you. Thank you for your patience and focus. Olivia, you are very kind and sweet. Thank you for the adenovirus related knowledge and techniques. I wish you a bright future. Patiwat, as an exchange student, although you have limited time to work here, it is very helpful for you for the progress of the TRAIL mutants project. I wish you all the best. Fengzhi, I am glad you could continue with the RANKL work. Good luck with the animal experiments! Habibie, we have had a lot of interesting discussions on each other‘s projects. We also provide relevant experimental materials to each other. I wish you good luck with your PhD and your family all the best. Besides, I would like to thank Bin and Lin for the discussions and support. Thank Catherina, Eduard, and Michela (ERIBA) for their guidance and assistance in Real-time quantitative PCR measurement. Of course, I would like to thank my lovely students, Timo, Amy, Naira, Federico, Lorina, Nora, and Maysam. I wish you all have a bright future!

My dear previous and current colleagues, thank you for creating an open, friendly and pleasant atmosphere in the department. Jielin, it is very funny that we came from the same hometown and university, but we started to know each other in Groningen. You are calm and thoughtful, and you always cheer me up when I am down. It‘s comfortable to stay with you and it was a wonderful trip with you in Portugal. I will always be your fan. Bin, Hao and Haigen, we started the PhD study on the same day in the department. Thank you for taking care of me over the years! Putri, thank you for your sweet and warm heart. I always feel cozy and relaxed with you. I wish you and Johannes a happy life! Yafeng, you are smart and hardworking, I am sure you will have a bright future. Thank you for your company in the past two years, which is my precious memory. Guangcai and Fangyuan, we used to have a study team with Yafeng and I miss the days that we work together. I wish you two a happy and sweet life! Siqi and Fengzhi, thank you for bringing me a lot of joy in the last period of my

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PhD. It was full of fun to gather with you girls! Ingy, thank you for sharing your experience of constructing the mutation library, and thanks for the delicious Egyptian food! Ele and Marie, it was pleasant to talk with you girls! Deng and Siwei, you are both doing excellent jobs. Good luck! Jan, thank you for arranging the group meetings and bringing a lot of joy to the department. Joko, I wish you success in your PhD study. It's almost there! My sincere thanks to Ingrid, Christel, Jane, Linda, Hegar, Tjie, Dan, Yan, Lieuwe, Alex, Saif, Saravanan, Zainal, Chao, Andreas, Michele, Laura, Shanshan, Fabiola, Hannah, Thea, Martijn, Zhangping, and Roberta, for your help and support in the department. I enjoyed the time with you and I wish you all the best! For the new coming people, Kristina, Sandy and Michael, I wish you a great time in the department!

Special thanks to my friends for their support and accompany outside the working life. Lin, my paranymph, you are gorgeous with forthright and sincerity. Thanks for being such strong support for me during the last period of my PhD. Bin, thank you for a lot of interesting conversations and for choosing the right foundation color for me. I wish you, Lin and Mengmeng an early reunion. Yana, this is the 13th year we have known each other, but it seems that I just started to know you in the past recent year. I miss those nights when we talked (and drank) until we lost track of time. See you in China! Keni, you are the best! Life is like a circle, the same as our friendship. Hao and Yu, thank you for your care in the last several years. I am sure we will keep in touch in the future. Shanshan, thank you for a lot of good memories. I wish you and Zhangping a happy life. Yehan, Wenxuan and Huala, I feel lucky to meet you girls! Su, you are intellectual and beautiful. I wish you, Naqin and your lovely baby a happy future! I am truly thankful to my other friends, Haigen & Xiaoxuan, Yang, Liwen, Xiaohong, Yuzhen, Mingming, Chengtao, Huatang, Zhenchen, Chengcheng, Chenxi, Lianghui, Wenjia, Xinhui, Kai, Chao, Qian, Jingyao , Xiaoxiang, Daozheng, Jingjing & Yuanze, Yuanyuan & Liqiang, Jiabao, Xiaoyin, Yingying & Changsen, Peng, Xin. It‘s so nice to meet you in Groningen!

Many thanks to my good friends far away in China, for their support and encouragement, even though we are a thousand miles away. They are Jing, Xuan, Xiaoting, Shuya, Xin Wang, Luting, Kexin and Feiran.

I sincerely thank the Chinese Scholarship Council for offering me this opportunity to pursue my PhD study abroad. Thank my supervisors at the master‘s degree, Dr. Hui Wang and Prof. Changlin Zhou, for their guidance and supervision.

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Special thanks to Yaoyao’s family. You made me feel at home in a foreign country. Yaoyao and Eason, Aunt Ning loves you forever!

My dear Qifeng, we have known each other for eight years and have been married for four years. Although it is often a long-distance relationship, I feel you are always by my side. Thank you for your unconditional tolerance, support and love. We will never be apart. Thanks a lot to my parents-in-law, for your kind support and warm regards during my stay in the Netherlands.

Dear Dad and Mom, I feel lucky to be your daughter. I love you!

亲爱的爸爸妈妈，很幸运成为你们的女儿，希望我们仨永远都走不散，我爱你们！

Yizhou

22-04-2020

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List of publications

1. Yizhou Wang, Timo Michiels, Rita Setroikromo, Ronald van Merkerk, Robbert H. Cool and Wim J. Quax#. (2019) Creation of RANKL mutants with low affinity for decoy receptor OPG and their potential anti-fibrosis activity. FEBS. J. 286(18): 3582-3593. 2. Yizhou Wang*, Aart H.G. van Assen*, Carlos R. Reis, Rita Setroikromo, Ronald van Merkerk, Ykelien L. Boersma, Robbert H. Cool and Wim J. Quax#. (2017) Novel RANKL DE-loop mutants antagonize RANK-mediated osteoclastogenesis. FEBS. J. 284(15), 2501- 2512. 3. Wim J. Quax#, Aart H.G. van Assen and Yizhou Wang. (2018) TNF-family member Receptor Activator of NF-κB (RANK) and RANK-Ligand (RANKL) in bone remodelling. IOP Conference Series: Earth and Environmental Science. IOP PUBLISHING LTD, 9 p. 012001. 4. Yizhou Wang*, Yikang Gu*, Kai Fang, Ke Mao, Jie Dou, Hongye Fan, Changlin Zhou and Hui Wang. (2018) Lactobacillus acidophilus and Clostridium butyricum ameliorate colitis in murine by strengthening the gut barrier function and decreasing inflammatory factors. Beneficial microbes. 9(5):775-787. 5. Mengyun Ke, Hui Wang, Min Zhang, Yuwei Tian, Yizhou Wang, Bing Li, Jie Yu, Jie Dou, Tao Xi and Changlin Zhou. (2014) The anti-lung cancer activity of SEP is mediated by the activation and cytotoxicity of NK cells via TLR2/4 in vivo. Biochem Pharmacol. 89 (1):119-30. 6. Hui Wang, Mengyun Ke, Yuwei Tian, Jing Wang, Bing Li, Yizhou Wang, Jie Dou and Changlin Zhou. (2013) BF-30 selectively inhibits melanoma cell proliferation via cytoplasmic membrane permeabilization and DNA-binding in vitro and in B16F10-bearing mice. Eur J Pharmacol, 707: 1-10.

Manuscripts in preparation

1. Yizhou Wang*, Olivia Adaly Diaz Arguello*, Rita Setroikromo, Fengzhi Suo, Hidde J. Haisma and Wim J. Quax#. Long term secretion of adenovirally-expressed RANKL WT/ Q236D for treatment of fibrosis. In preparation. 2. Abel Soto Gamez*, Yizhou Wang*, Lorina Seras, Rita Setroikromo, Marco Demaria and Wim J. Quax#. Overcoming senescent cancer cell resistance to extrinsic apoptosis using a death receptor 5 (DR5) selective TNF-related apoptosis inducing ligand (TRAIL) variant. In preparation. 3. Fengzhi Suo*, Yizhou Wang*, Patiwat Kongdang, Euphemia Amelia in het Veld, Rita Setroikromo, Ronald van Merkerk, Robbert H. Cool and Wim J. Quax#. Novel TRAIL variants with reduced binding to decoy receptor OPG overcome TRAIL resistance in breast cancers. In preparation.

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4. Yizhou Wang*, Bin Liu*, Deng Chen, Abel Soto Gamez, Rita Setroikromo, Hidde J. Haisma and Wim J. Quax#. Inhibition of CXCR7 sensitizes TRAIL-induced apoptosis in breast cancer cells. In preparation. 5. Bin Liu*, Deng Chen*, Jelle van den Bor, Yizhou Wang, Martine J. Smit, Frank J. Dekker, Hidde J. Haisma#. A novel interaction of EGF and CXCR7. In preparation. 6. Habibie, Shanshan Song, Kurnia S.S. Putri, Carian E Boorsma1, Robbert H Cool, Xinhui Wu, Reinoud Gossens, Yizhou Wang, Wim J Quax, Peter Olinga, Corry-Anke Brandsma, Wim Timens, Janette K Burgess, Barbro N Melgert#. RANKL contributes to lung tissue repair via promoting type II epithelial cell proliferation. In preparation.

Conferences

1. Chemistry as Innovating Science: The Dutch Chemistry Conference (Eindhoven, NL, Dec, 2016) 2. Chemistry as Innovating Science: The Dutch Chemistry Conference (Eindhoven, NL, Dec, 2017) Poster presentation: Novel RANKL DE-loop mutants antagonize RANK-mediated osteoclastogenesis. 3. Cell Death and Regeneration: The Conference of European Cell Death Organization (Dresden, Germany, Sep, 2019) Poster presentation: Creating structure-based RANKL mutants with low affinity for OPG to activate macrophage in fibrosis.

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About the author

Yizhou Wang was born on the 22nd of April 1990 in Hebei, China. In June 2012, she obtained her Bachelor‘s degree in Biotechnology from China Pharmaceutical University. In June 2015, she earned her Master‘s degree in Microbial and Biochemical Pharmacy in the same university under the supervision of Prof. Changlin Zhou. In October 2015, she moved to The Netherlands to pursue her doctoral degree in the Department of Chemical and Pharmaceutical Biology, University of Groningen, under the supervision of Prof. Wim. J. Quax. Her doctoral research focuses on probing the ligand-receptor interface of TNF ligand family members RANKL and TRAIL, of which the results are described in this thesis.

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