New direction of tumor microenvironment in ovarian cancer treatment Department of Gynecologic Oncology, School of Medicine, Keimyung University (Chi-Heum Cho, M.D., PhD.)

Introduction • One of the most lethal GY malignances and the 5th leading cause of cancer death in women in the United States • In 2015, an estimated 21,980 new cases of ovarian cancer and estimated 14,270 deaths in the United States • The majority (65–75 %) of women : the advanced stage disease (III and IV) • Only about 15–20% of these women : free of disease recurrence at 10 years Siegel, R.L. et al Cancer statistics, 2015. CA Cancer J. Clin. 2015, 65, 5–29 Aletti, G. D. et al 2007 Current management strategies for ovarian cancer, 82(6), 751–770

Current Standards of Care for Ovarian Cancer • Optimal debulking surgery + CTx (platinum- and taxane-based CTx)  effective in patients whose cancer is diagnosed at an early stage the cure rate : as high as 90% • In most patients, initial sensitivity to CTx  recur as chemo-resistant tumor within 12~24 months after initial Dx • To improve treatment effectiveness and survival of ovarian cancer patients : new therapeutic targets  tumor-supportive microenvironment

Tumor Microenvironment • Interactions between malignant cell and non-transformed cells : “tumor microenvironment” (TME)  High degree of genetic heterogeneity & form a complex society • Various non-transformed cells such as fibroblasts, endothelial cells, and inflammatory cells as well as extracellular matrix ↔ tumor cells • Consequence of collaboration of different types of malcontrolled cells

D.F. Quail et al Nat. Med. 19 (2013) 1423-1437.

Tumor Microenvironment

Bruno Sainz Jr. et al Mediators of Inflammation (2016)

Tumor & Inflammation & CSC phenotype

The Cells of Tumor Microenvironment

Weinberg RA Cell 144:662 (2011)

Inflammation & Cancer & Angiogenesis & Metastasis heterotypic molecular interaction

Weinberg RA, the biology of CANCER (2013)

Macrophage plasticity and characterization

Bruno Sainz Jr. et al Mediators of Inflammation (2016)

Signaling crosstalks between ovarian cancer cells and stromal CAFs promote tumor progression

Tsz-Lun Yeung. et al Biomolecules (2016)

Multiple approach can be used to target ovarian tumor microenvironment

Tsz-Lun Yeung. et al Biomolecules (2016)

Ovarian Tumor Microenvironment • Most current treatment option  target only ovarian cancer cells & overlook the importance of the tumor-supportive microenvironment

• In ovarian cancer, the tumor stroma contributes to 7%–83% : a median relative proportion of 50% • The major cell types in the tumor microenvironment : stromal fibroblasts, certain immune cell types, endothelial cells and cancer- associated adipocytes

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Labiche, A. et al Int. J. Gynecol. Cancer 2010, 20, 28–33

Ovarian Tumor Microenvironment • Endothelial cells : the basic building blocks of the tumor vasculature : tumor vasculature is the major gateway to metastasize  hematogenous • Microvessel density : a poor prognostic marker • Vascular endothelial growth factor (VEGF) : ascites formation in ovarian cancer patients : an independent predictor for patient survival • Pre-treatment VEGF level : a direct association with the CA125 level  a predictive indicator for refractoriness to CTx  Impact tumor growth, metastasis, and response to CTx Chavez-Macgregor, M. et al Clin. Cancer Res. 2005, 11, 5396–5400 Masoumi-Moghaddam, S. et al Oncotarget 2015, 6,28491–28501

Ovarian Tumor Microenvironment • Adipocyte (cancer-associated adipocytes)

: promote ovarian cancer cell proliferation, motility and resistance to chemotherapeutic agents

• Kato and colleagues : an assessment of an ovarian cancer patient cohort that consisted of 33 healthy weight and 37 overweight individuals  both OS and PFS in overweight patients ↓ • Adipose tissue-derived cytokines, termed adipokines  support tumor progression • Leptin was the first identified adipokine Dirat, B. et al Clin. Endocr. Dev. 2010, 19, 45–52. Kato, S. et al Oncotarget 2015, 6, 21100–21119

Ovarian Tumor Microenvironment • Leptin : ovarian cancer cell migration and invasion potential through the activation of JAK/Stat3, PI3K/Akt, and RhoA/ROCK signaling : ↓ apoptosis and ↑ cell division (suppressing p21 and up-regulating cyclin D, which controls the G1/S cell cycle checkpoint) • Cancer-associated adipocytes 1. Source of both tumor-promoting adipokines 2. Energy-rich fatty acids for cancer cells Clark, R. et al Am. J. Pathol. 2013, 183, 576–591 Chen, C. et al Int. J. Oncol. 2013, 42, 1113–1119

Ovarian Tumor Microenvironment • Cancer-Associated Fibroblasts (CAFs)

: fibroblasts within tumor stroma similar to those of fibroblasts associated with wound healing  CAFs : CAF-specific proteins, cytokines, and growth factors

• Common marker for CAFs : α-smooth muscle actin , stromal-derived factor 1 (SDF-1) fibroblast activation protein-1α (FAPα) and fibroblast-specific protein-1 • CAF-derived SDF-1 (CXCL12) : interacting with the CXCR4 receptors on cancer cell : ↑ tumor growth, motility, and tumor angiogenesis in multiple cancer types, including ovarian cancer Ryan, G.B. et al Lab. Investig. 1973, 29, 197–206 Chang, S.C. et al Ann. Surg. Oncol. 2009, 16, 2323–2330 Daly, A.J et al Oral. Oncol. 2008, 44, 646–651

Ovarian Tumor Microenvironment • FAPα : up-regulation of the ERK signaling pathway and engagement of α3β1 integrin receptor in ovarian cancer cells  ovarian cancer proliferation ↑ and invasion • Interacting with tumor cells through CAF-derived secretory factors : expression of adhesion molecules by stromal cells • McAndrews and colleagues : CAFs  more adherent to invasive ovarian cancer cells when compared to non-invasive ovarian cancer cells. : adhesion mediated by cadherin 11 and cadherin 2  highly expressed by invasive cancer cells and CAFs Ohira, S. et al Am. J. Pathol. 2006, 168, 1155–1168 McAndrews, K.M. et al ACS Chem. Biol. 2015, 10, 1932–1938

Ovarian Tumor Microenvironment • Yeung and colleagues : laser microdissection (LCM) on ovarian tumor tissues from cancer patients • TGF-β-rich ovarian tumor microenvironment  ↑ production of versican (VCAN), a large ECM proteoglycan, in CAFs  ↑ ovarian cancer cell migration and invasion by activating their NF-B signaling pathway • CAFs play crucial roles in TGF-β-induced ovarian cancer progression : Targeting TGF-β signaling in CAFs  impactful targeted therapy for ovarian cancer Yeung, T.L. et al Cancer Res. 2013, 73, 5016–5028 Yamada, S.D. et al Gynecol. Oncol. 1999, 75, 72–77

Ovarian Tumor Microenvironment • Leung and colleagues : Another member of the microdissected CAF-specific gene signature : Microfibrillar-associated protein 5 (MFAP5)  prognostic marker of poor survival rates in patients with ovarian cancer • Tumor-promoting roles of CAF-derived MFAP5  Activation of the calcium-dependent FAK/CREB/troponin C type 1 (TNNC1) signaling pathway by engaging the αVβ3 integrin receptors  F-actin cytoskeleton rearrangement & stress fiber formation in ovarian cancer cells • In vivo, targeting stromal MFAP5 using siRNA delivered by nanoparticles  reduced tumor growth and metastasis Leung, C.S. et al Nat. Commun. 2014

Ovarian Tumor Microenvironment

Ovarian cancer Microenvironment: role of tumor infiltrating immune cells • CD8 cytotoxic T lymphocytes (CTL)  Primary mediators of anti-tumor immune responses : major histocompatibility complex (HLA) class I molecules expressed on ovarian cancer cells • Sato and colleagues studied 117 ovarian cancer cases : ↑ survival in patients who had higher numbers of infiltrating CD8+ T cells compared to patients w/o infiltrating CD8 T cells (median survival 55 vs. 26 months)

Sato, E. et al Proceedings of the National Academy of Sciences of the United States of America, 102(51), 18538–18543

Ovarian cancer Microenvironment: role of tumor infiltrating immune cells • Natural killer (NK) cells 1) CD16− CD56bright NK cells : less cytolytic, found in the 2ndary lymphoid tissue 2) CD16+ CD56dim NK cells : highly cytolytic, found in the periphery • Activating (i.e., NKG2D) receptors : bind to stress ligands such as MICA, MICB and ULBP1-3 • Inhibitory (i.e., KIR) receptors : major histocompatibility complex class I and class I associated ligands  Balance between inhibitory and activating signals  Nearly all ovarian cancers express the NK ligands MICA, MICB, and ULBP2  numbers of NK cells ↑  associated with poor prognosis Perussia, B. et al Molecular Immunology, 42(4), 385–395. Gonzalez, S. et al Trends in Immunology, 29(8), 397–403

Ovarian cancer Microenvironment: role of tumor infiltrating immune cells • CD4+ regulatory T cell (Tregs)

• Well known immune-supppressor of lymphoid origin  immune-suppressive soluble mediators such as transforming growth factor-β (TGF-β) and IL-10  transform dendritic cell to a suppressive type & downregulate the activity of effector T cell, NK cell • Tumors  ↑ the numbers of Tregs in the peripheral blood of cancer patients for several tumor types, including ovarian cancer • Tumors  recruit or induce Tregs into tumor infiltration  Infiltration of Tregs (as assessed by CD4 and CD25 staining)  ass. with poor patient survival Knutson, K. L. et al Cancer Immunology, Immunotherapy, 56(3), 271–285. Bluestone, J. A., & Abbas, A. K. Nature Reviews Immunology, 3(3), 253–257 Curiel, T. J. et al Nature Medicine, 10(9), 942–949

Ovarian cancer Microenvironment: role of tumor infiltrating immune cells • Tumor-associated macrophages (TAM) • Hagemann et al first demonstrated that ovarian cancer cells can direct macrophages to become M2 phenotype  tissue regeneration responses & local immune suppression • CD163 and CD204 : markers for the pro-tumor M2 phenotype • ↑ CD163- or CD204- positive cells within the TAM infiltration  tumor progression and a worse clinical prognosis

Y. Komohara et al Cancer Sci. 105 (2014) 1–8. Hagemann, T. et al Journal ofImmunology, 176(8), 5023–5032

Tumor-associated macrophages • TM : Contribute to the recruitment of macrophage precursors, differentiation of pro-tumor and immunosuppressive macrophages • Macrophages predominantly into two major subsets depending on tissue microenvironments 1) Pro-inflammatory M1-type macrophages : multiple transcription factors such as IRF-1, Stat1 and nuclear factor-kappaB (NF-κB)  inflammatory responses 2) Anti-inflammatory M2-type macrophages : regulation of tissue remodeling, repair, and antifungal immunity under physiological conditions A.Mantovani et al, Immunity 23 (2005) 344–346 Y. Komohara et al, Cancer Sci. 105 (2014) 1–8.

Tumor-associated macrophages • Tumor-associated macrophages : macrophages infiltrating tumor tissues : bone marrow precursors, circulating and splenic monocytes : high plasticity and flexibility  adapt to different TM : polarize into immunosuppressive M2 macrophages upon exposure to M2 macrophage-differentiation factors produced by TM  reflect their interactions with tumor cells with heterogeneous oncogenic profiles  impacting tumorigenicity and responses to anticancer therapies P. Sinha et al, Cancer Res. 65 (2005) 11743–11751 T. Satoh et al., Nat. Immunol. 11 (2010) 936–944.

Tumor Microenvironment

Ovarian cancer Microenvironment: role of tumor infiltrating immune cells • Dendritic cells (DCs) 1) 2) • 

Plasmacytoid DCs (pDCs): CD123+, CD45RA+CD8+CD11c−ILT3+ILT1−Lin− Myeloid DCs (mDCs): CD11C+CD33+CD45RA−CD123− Upon detection of danger or pathogen mature and migrate to the lymph nodes to activate T helper cells and CTL

• Tumor-induced alterations in DC differentiation  ↓ the number of functional cells available for effective T cell activation • Ovarian cancers  large amounts of IL-10  redifferentiation of mDCs to an aberrant phenotype  T cell activation properties ↓ Chen, F. et al International Journal of Gynecological Cancer, 19(9), 1487–1493. Fricke, I., & Gabrilovich, D.I Immunological Inv es t i g a t i o n s , 35( 3 – 4 ) , 459– 4 8 3

Ovarian cancer Microenvironment: role of tumor infiltrating immune cells • Dendritic cells (DCs) • In murine modeling studies, suppressor mDCs within ovarian cancers  high levels of PD-1  suppresses expression of co-stimulatory molecules & blocks responsiveness to danger signals • In Recent work, PD-1 ligation of infiltrating mDCs suppresses IL-7 receptor expression on infiltrating T cells  limiting persistence of T cells in the tumor bed • Human ovarian cancers  recruit immature pDCS  release large amounts of IL-10 preventing local T cell activation Krempski, J. et al Journal of Immunology, 186(12), 6905–6913. Zou, W et al Nature Medicine, 7(12), 1339–1346

Ovarian cancer Microenvironment: role of tumor infiltrating immune cells • Indoleamine 2,3-dioxygenase (IDO) : mediates immune tolerance in T cells and NK cells by consuming tryptophan and forming kynurenine  inhibition of proliferation and functional impairment : promotes a Tregs phenotype : expressed by many tumor types, including ovarian cancer • Takao and colleagues : protein expression of IDO in serous (57.5 %), clear cell (49.2 %), and endometrioid (73.3 %) ovarian adenocarcinomas • An association between IDO staining in ovarian cancer and lower overall survival for serous ovarian cancer patients with advanced stage Uyttenhove, C. et al Nature Medicine, 9(10), 1269–1274 Munn, D. H. Current Opinion in Immunology,18(2), 220–225

Takao, M. et al Oncology Reports, 17(6), 1333–1339

Ovarian cancer Microenvironment: role of tumor infiltrating immune cells

Pathologic cytokine interactions: TNF-α, CXCL12 and IL-6 axis • “TNF network”— consisting of TNF, CXCL12, and IL-6 recently identified by Kulbe and colleagues in human ovarian cancer • Single, high-dose exposure of TNF-α  tumor regression • Chronic, low-dose expression of TNF-α  tumor promoting • In vitro studies of ovarian cancer, using RNAi to decrease expression of TNF-α  not result in any changes in proliferation or apoptosis • In vivo  tumor burden,distribution ↓ and apoptosis ↑ • TNF-α blockade in vivo  disruption of a multi-cytokine network constituted by TNF-α, CXCL12, and IL-6 (TNF network)  reduced angiogenesis, reduced infiltration of regulatory cells Kulbe, H. et al Cancer Research, 72(1), 66–75 Kulbe, H. et alCancer Research, 67(2), 585–59 Balkwill, F. Cytokine & Growth Factor Reviews, 13(2), 135–1412

Pathologic cytokine interactions: TNF-α, CXCL12 and IL-6 axis

• High-level expression of IL-6 in ovarian cancer

 promotes cancer growth and progression through several mechanisms : including activation of the growth promoting JAK/STAT, PI3K/Akt, and Ras/MEK/IRK pathways • Detected in the malig. ascites & ass. with shorter survival • Thought to be Important in the generation of thrombocytosis  IL-6 emerged as a logical candidate for targeted therapy

• CXCR4 its ligand, CXCL12 : secreted by cells in the tumor microenvironment at ovarian cancer : stimulation of proliferation, VEGR-mediated angiogenesis : blockade of the CXCL12/CXCR4 signaling  tumor cell apoptosis, survival ↑ Duan, Z. et al Clinical Cancer Research, 12(17), 5055–5063 Lo, C.W. Cancer Research, 71(2),424–434 Penson, R. T. et al International Journal of Gynecological Cancer, 10(1), 33–41

Pathologic cytokine interactions: TNF-α, CXCL12 and IL-6 axis

Targeted antigens in ovarian cancer Duan, Z. et al Clinical Cancer Research, 12(17), 5055–5063 Lo, C.W. Cancer Research, 71(2),424–434 Penson, R. T. et al International Journal of Gynecological Cancer, 10(1), 33–41 Barbieri, F. et al Journal of Oncology, 2010,426956

Targeted antigens in ovarian cancer • Human epidermal growth factor receptor 2(HER-2/neu protein) : A transmembrane glycoprotein (185 kDa) : Epidermal growth factor receptor family that also includes EGFR-1, HER-3, and HER-4  attractive immunologic target d/t low level expression in peripheral tissues • Variable, ranging from 5 to 66%  somewhat contradictory regarding to the prognostic relevance

Ioannides, C. G. et al Cellular Immunology, 151(1), 225–234 Bookman, M. A. et al Journal of Clinical Oncology, 21(2), 283–290 Camilleri-Broet, S. et al Annals of Oncology, 15(1), 104–112

Targeted antigens in ovarian cancer • MUC1, MUC4, and MUC16 : transmembrane mucins • MUC16 (CA 125) : The largest membrane-bound mucin protein : Expressed on the surface of ovarian cancer cells & shed to the bloodstream and peritoneal cavity : Overexpressed in 50–80 %  tumor marker for monitoring growth and recurrence of epithelial ovarian cancer Bafna, S. et al Cancer Research, 68(22), 9231–9238 Bast, R. C. et al The International Journal of Biological Markers, 13(4), 179–187 Yin, B.W.,& Lloyd, K. O. The Journal of Biological Chemistry, 276(29), 27371–27375

Targeted antigens in ovarian cancer • MUC4 : expressed in >90 % of malignant ovarian tumors : very low to an undetectable expression in the normal ovary • Recent study demonstrated pathological role of MUC4 : epithelial to mesenchymal transition which is involved in metastasis and enhanced tumor aggression  no association of expression with outcome • MUC1 : anti-MUC1 antibodies in healthy individuals as well as in ovarian cancer patients  correlate with ovarian cancer risk factors Ponnusamy, M. P. et al Oncogene, 29(42), 5741–5754 Terry, K. L. et al Cancer Epidemiology Biomarkers & Prevention, 16(1), 30–35 Oei, A. L et al International Journal of Cancer, 123(8), 1848–1853

Targeted antigens in ovarian cancer • Mutation of the p53 gene : one the most common single genetic alterations in ovarian cancer : overexpressed in nearly 50 % of ovarian cancers • Goodell showed the presence of p53 antibodies  independent predictor of survival • Median survival for antibody positive patients was 51 months compared with 24 months for patients without antibodies

Goodell, V et al Journal of Clinical Oncology, 24(5), 762–768 Corney, D. C et al Advances in Experimental Medicine and Biology, 622, 99–117 Lambeck, A. et al International Journal of Cancer,121(3), 606–614

Targeted antigens in ovarian cancer • Cancer testes antigens (CTAs) : CTA family  BAGE, GAGE, LAGE, MAGE, sperm protein 17 (SP17) NY-ESO-1, AKAP4, and the synovial sarcoma X (SSX) genes • NY-ESO-1 : best characterized and clinically targeted • Zhang and colleagues : moderate to high expression of MAGE-1 and MAGE-3 in ovarian cancer tissue  positively correlated with tumor differentiation and clinical stage

Valmori, D. et al Clinical Cancer Research, 12(2), 398–404 Zhang, S. et al BMC Cancer, 10, 163

Targeted antigens in ovarian cancer • Folate receptor alpha (FR-α) : a glycosyl - phosphatidylinositol-linked membrane protein overexpressed in many epithelial cancers : non-mucinous ovarian tumors ↑∼90-fold in comparison with normal epithelial cells • Expression relatively limited to a few tissues, notably the apical surface of kidney tubule epithelium

• Mesothelin : 40-kDa cell surface protein, expressed on normal mesothelial cells : the highest level, particularly on non-mucinous subtypes Parker, N. et al Analytical Biochemistry, 338(2), 284–293 Frierson, H. F. et al Human Pathology, 34(6), 605–609

Approaches to Targeting Tumor-Stroma Signaling Networks • Targeting the stroma-specific signaling networks for cancer Tx 1) Ongoing functions of stromal cells : core of tumor microenvironment  ↓ tumor progression indirectly 2) stromal cells : genetically stable than cancer cells  ↓ adaptive mutations during treatment

↓ acquire resistance to therapeutic agents • Nanotechnology • Antibodies • Small molecular inhibitor Micke, P. et al Lung Cancer 2004, 45, S163–S175 Jain, R.K. Science 2005, 307, 58–62

Nanotechnology • Nanomedicine : opportunities to improve current cancer Tx by targeted drug delivery ↑ and systemic toxicity ↓

• Nanoparticles : liposomes, polymeric nanoparticles, dendrimers, gold nanoparticles, carbon nanotubes, and quantum dots  drug or gene delivery • Several nanomedicine formulations approved by the FDA : a Pegylated liposomal doxorubicin (Doxil)  Tx of recurrent ovarian ca. : a polyamino acid-bound paclitaxel, paclitaxel poliglumex  in a phase III clinical trial for ovarian cancer Gharpure, K.M. et al Cancer Res. 2015, 21, 3121–3130

Nanotechnology • Rely on the passive accumulation of nanoparticles at the tumor sites  enhanced permeability and retention effect • One way to enhance tumor selectivity : Attach tumor-specific ligands (e.g., HER2 antibody, aptamers, and transferrin) to target signal transduction pathways in cancer • Other strategies to target the stromal populations ex> Chitosan nanoparticles  targeting CAF-derived tumorigenic factor, MFAP5, in vivo  chitosan nanoparticles labeled with RGD peptides localize to the tumor vasculature and exert anti-angiogenic effects Han, H.D. et al Clin. Cancer Res. 2010, 16,3910–3922; Leung, C.S. et al Nat. Commun. 2014

Antibodies • The discovery of antibodies “magic bullets” for cancer Dx and Tx • Antibody-based therapy : one of the most successful anti-tumor strategies • Antibodies’ mechanisms of tumor cell killing  Direct tumor Cell killing via receptor agonist or antagonist activity, immune-mediated cell killing and stromal cell inhibition

• Successful targets for antibody therapy  epidermal growth factor receptor (EGFR), VEGF, PD-1, and CTLA-4 Scott, A.M. et al Nat. Rev. Cancer 2012, 12, 278–287 Boland, W.K. et al Expert Opin. Biol. Ther. 2009, 9, 1199–1206 Weiner, L.M et al Nat. Rev. Immunol. 2010, 10, 317–327

Antibodies (bevacizumab) • Antibody-based antiangiogenic therapies : target tumor-derived angiogenic factor using bevacizumab (a VEGF alpha-targeting monoclonal antibody) • Despite the encouraging phase I and II trial results, phase III randomized trials of bevacizumab  as treatment for recurrent ovarian cancer demonstrated only modest improvement in PFS • Further discovery of pro-angiogenic factors as therapeutic targets, optimization of the treatment regimen  maximize the efficacy of therapeutic antibodies Burger, R.A. et al N. Engl. J. Med. 2011, 365, 2473–2483 Perren, T.J. et al N. Engl. J. Med. 2011, 365, 2484–2496 Pujade-Lauraine, E. et al J. Clin. Oncol. 2014, 32, 1302–1308

Antibodies (Trastuzumab) • Trastuzumab : a humanized monoclonal antibody  inhibits HER2-positive tumor growth by targeting HER2 receptor  currently targeted therapeutic agent for HER2-positive breast cancer • In a phase II trial of the GOG, Bookman and colleagues analyzed the HER2 expression levels in 837 tumor samples  11.4% of these samples exhibited overexpression of the receptor • 41 of them evaluate the clinical value of single-agent trastuzumab in recurrent ovarian cancer  overall low response rate of 7.3% and 2 months median PFS Bookman, M.A. et al J. Clin. Oncol. 2003, 21, 283–290 Slamon, D.J. et al Nscience1989, 244, 707–712

Antibodies (Trastuzumab) • In a phase II trial study, Combination with paclitaxel + carboplatin in 7 patients with taxane-/carboplatin-resistant ovarian cancer and HER-2 overexpression finding  a clinical response in 3 patients with a median PFS of 2.9 months and OS of 12.3 months • Another trial done in 33 patients with mucinous ovarian carcinoma  18 % HER-2 expression and 3 of the 6 patients treated with chemotherapy + trastuzumab  one had CR // another had PR • trastuzumab may be effective for this subset of individuals Ray-Coquard, I. et al Clinical Ovarian Cancer, 1(1), 54–59 McAlpine, J. N. et al BMC Cancer, 9, 433

Small molecule inhibitors • Accelerated by cancer genome sequencing and RNA interference based screening  development of small molecule cancer drugs • For example, the EGFR kinase inhibitors gefitinib and erlotinib : non-small cell lung cancer patients • The EGFR/ERBB2 inhibitor lapatinib : ERBB2-positive breast cancer patients • The VEGFR kinase inhibitor sorafenib : renal cancer • Bringing a new drug to market  costly and incredibly high rate of failure • The complexity of genetic alterations and heterogeneity  key driver mutations and the corresponding therapies challenging Yap, T.A et al Annu. Rev. Pharmacol. Toxicol. 2012, 52, 549–573. Sellers, W.R. Cell 2011, 147, 26–31

Small molecule inhibitors • In ovarian cancer, small molecule inhibitor of the bone morphogenetic protein pathway, DMH1 : tumor cell proliferation ↓ • Orally active small molecule inhibitors of gp130 and c-Met : tumor burden ↓ in mouse xenograft models • Despite effective approach to inhibit molecular targets, : cells under prolonged treatment of small molecular inhibitors  resistance via selection for mutant alleles or up-regulation of alternative signaling pathways • Identification and development of multiple inhibitors that target different pathways  the development of synergistic inhibitor combinations . Hover, L.D. et Cancer Lett. 2015, 368, 79–87

Drug Resistance Related to TME • The pleiotropic nature of cytokines in the microenvironment 1. promoting cancer cell proliferation 2. bypassing apoptosis 3. recruiting immune suppressor cells aggregating around the tumor 4. driving the development of drug resistance

• Many anticancer drugs  for targeting the crucial signal molecules overactivated in cancer cells  frustrating d/t the occurrence of drug resistance seems inevitable • “De novo mechanisms” : dynamic changes of the tumor surrounding microenvironment  new immortal signal or fundamentally alter some default signal pathways  cancer cells finally bypass the influence caused by the original drug

Drug Resistance Related to TME • For ex> Siltuximab (CNTO328) : a human-mouse chimeric IL-6 antibody : in multiple clinical trials for a variety of cancers, including ovarian, renal, and prostate  early stage monotherapy trial, which included 29 ovarian cancer patients, no objective responses, suggesting that ovarian cancer can easily evade the IL-6 blockade • IL-6 transmits major survival signals through various pathways, including PI3K/AKT, Ras/Raf/MEK-ERK1/2, JAK/STAT3, SHP2/RAFTK, and Src-family tyrosine kinase pathways  each of these pathways : the cancer cell alternative surviving reliance K. H. Shain and W. S. Dalton Expert Review of Hematology, vol. 2, no. 6, pp. 649–662, 2009 Angevin, E. et al Clinical Cancer Research, 20(8), 2192–2204

Drug Resistance Related to TME • Targeting the crucial contributing factor, VEGF TME  serve as a clonal selection niche or compensatory substance providing source and make the resistance happen • Anti-VEGF therapy : Play a selection pressure for selecting adapting tumor cells  regrowth of clonal populations with higher compensatory factors such as VEGF, fibroblast growth factor (FGF), placental growth factor (PGF), and platelet-derived growth factor (PDGF) K. H. Shain and W. S. Dalton Expert Review of Hematology, vol. 2, no. 6, pp. 649–662, 2009 Angevin, E. et al Clinical Cancer Research, 20(8), 2192–2204

Future Drug Development regarding the Importance of TME • TME : many aspects of carcinogenesis and cancer progression : understanding the TME  concept for drug development • Targeting cancer cells + key components of the TME : Tx outcome ↑ compared to chemotherapy  multitargeting drug or “cocktail” drug application strategy • Immunomodulation as an anticancer treatment modality • To narrow down the gap between the experimental and clinical application of anticancer drugs

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