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Exploring Therapeutic Combinations with anti-CTLA-4 Antibody Padmanee Sharma, MD, PhD Associate Professor GU Medical Oncology and Immunology M. D. Anderson Cancer Center iSBTc Hot Topic Symposium October 2010 Disclosures • Served on advisory board, BMS, received honorarium • Served on advisory board, Dendreon, received honorarium Improving on CTLA-4 blockade • CTLA-4 blockade has a consistent anti-tumor response rate of ~10% and survival benefit of ~20-30%; Phase III trial with documented survival benefit • Durable partial and complete regression of disease observed in a subset of patients • How can we do better? – Identify immunologic markers that predict which patients will benefit and provide therapy to those patients – Explore combination therapies to increase the numbers of patients who will benefit Part I Identification of immunologic markers: Pre-surgical clinical trial with anti-CTLA-4 monotherapy anti-CTLA-4 antibody Study Week 0 3 PreAfter therapy dose #1 blood* blood* Post-operative follow-up visits Surgery #1 #2 7 11-15 23-24 After dose #2 blood* Blood Blood *Blood drawn prior to antibody dose administered and prior to surgery Tissue Analysis RNA later Core biopsy (~ 1 cm x 1mm x 1mm) Core biopsy TIL expansion + Fine needle aspiration and chunks IF in frozen sections Histology sections IHC in paraffin sections Clinical Trial • Patients who are surgical candidates (N=12) – 6 patients dosed at 3mg/kg/dose and 6 patients dosed at 10 mg/kg/dose – Organ-confined localized disease; did not require any therapy other than surgery as treatment • Primary endpoint: safety • Secondary endpoint: immunologic correlates Choosing biomarkers for immune monitoring PD-l 10 0 100 70 0 10 mB7-H3 mB7h 91 ? hB7h 100 96 100 hB7x mB7-H2 100 mB7x hB7-H2 10 0 mB7-H1 hB7-H1 10 0 hB7-H3 mB7-2 hB7-2 hB7-1 mB7-1 CD28, CTLA-4 ICOS Immune Monitoring • Assessed T cell markers including: HLA-DR, CD69, CD45RA, CD45RO, PD-1, etc. and • Inducible costimulator (ICOS) -belongs to CD28 family -expression increased on activated T cells -plays a role in function of Th1, Th2, Th17, Tfh, Treg cells -is not a marker of a particular T cell subset but plays a role in the function of a given T cell subset that has been activated Increased frequency of ICOShi T cells in tumors from anti-CTLA-4 treated patients Non-malignant tissues: untreated Tumor tissues: untreated 16% ICOS 40% CD4 CD4 CD4 13% Tumor tissues: anti-CTLA-4 treated ICOS ICOS Liakou et al., Proc Natl Acad Sci, 2008 ICOS expression increases in tumor tissues of treated patients % CD4+ICOShi T cells 80 p < 0.05 70 60 50 40 30 20 10 0 Non-malignant tissues Tumor tissues untreated Tumor tissues anti-CTLA-4 treated Liakou et al., Proc Natl Acad Sci, 2008 FOXP3 expression is lower in tumor tissues from anti-CTLA-4 treated patients Non-malignant tissues: untreated Tumor tissues: untreated 95% FOXP3 8% CD4 CD4 CD4 3% Tumor tissues: anti-CTLA-4 treated FOXP3 FOXP3 Liakou et al., Proc Natl Acad Sci, 2008 % CD4+FOXP3+ T cells FOXP3 expression decreases in tumor tissues of treated patients 100 90 80 70 60 50 40 30 20 10 0 p < 0.05 Non-malignant tissues Tumor tissues untreated Tumor tissues anti-CTLA-4 treated Liakou et al., Proc Natl Acad Sci, 2008 Relative expression normalized to GAPDH Increased IFN- and T-bet mRNA in treated tissues with concomitant decrease in FOXP3 mRNA levels 120 Non-malignant tissues Cancer tissues: untreated 100 Cancer tissues: anti-CTLA-4 treated 80 60 40 20 0 CD3- IFN- IL-10 IL-4 IL-2 FOXP3 T-bet GATA-3 Liakou et al., Proc Natl Acad Sci, 2008 What is the function of ICOShi cells in tumors?: Expression of NY-ESO-1 antigen allowed for functional analyses of TILs H&E CD4 T cells NY-ESO-1 Chen et al., Proc Natl Acad Sci, 2009 Number of spots / 25,000 CD4 T cells Recognition of NY-ESO-1 by TILs 250 200 150 100 50 0 No Peptide NY-ESO-1 Peptides IFN- production 6% ICOS ICOS 2% TNF- MIP-1 Chen et al., Proc Natl Acad Sci, 2009 What about immunologic events in the systemic circulation? Do they correlate with observed changes in tumor tissues? ICOS expression significantly increases on T cells in peripheral blood after treatment with anti-CTLA-4 antibody Week 3 3% Week 7 14% ICOS 13% CD4 CD4 CD4 CD4 Baseline ICOS ICOS ICOS Liakou et al., Proc Natl Acad Sci, 2008 ICOShi T cells in peripheral blood from antiCTLA-4 treated patients produce IFN- 4 Healthy donors Pre-therapy patients Post-therapy patients pg/mL x 103 3.5 3 2.5 2 1.5 1 0.5 0 IFN-γ IL-10 CD4+ICOShi T cells IFN-γ IL-10 CD4+ICOSlow T cells Liakou et al., Proc Natl Acad Sci, 2008 Number of spots / 50,000 T cells ICOShi T cells from peripheral blood recognize NY-ESO-1 tumor antigen APCs pulsed w ithout peptide (no peptide) APCs pulsed w ith NY-ESO-1 peptides (all peptides) 300 250 200 150 100 50 0 Pt #2 Pretherapy Pt #2 Posttherapy Pt #4 Pretherapy Pt #4 Posttherapy Pt #6 Pretherapy CD4+ICOShi T cells Pt #6 Posttherapy Are changes in ICOS expression associated with clinical benefit? Pre-Operative CTLA-4 Blockade: Pathology and Cytology Data Patient Number Pre-Therapy Cytology Fluorescence in situ hybridization (FISH) Post-Therapy Cytology Fluorescence in situ hybridization (FISH) Pre-Therapy Pathology (UC, HighGrade) Post-Therapy Pathology 1 T1N0M0 T0N0M0 Positive Cytology, Positive FISH Negative Cytology, Negative FISH 2 T1N0M0 T4N0M0 Positive Cytology, Positive FISH Positive Cytology, Positive FISH 3 T1N0M0 TisN0M0 Negative Cytology, Positive FISH Negative Cytology, Negative FISH 4 T2N0M0 T3N1M0 Negative Cytology, Non-contributory FISH Negative Cytology 5 T1N0M0 TaN0M0 Positive Cytology Positive Cytology 6 T1N0M0 T0N0M0 Positive Cytology Negative Cytology, Negative FISH 7 T1N0M0 TaN0M0 Positive Cytology Positive Cytology 8 T2N0M0 T0N0M0 Negative Cytology, Negative FISH Negative Cytology, Negative FISH 9 T1N0M0 TisN0M0 Positive Cytology Positive Cytology 10 T2N0M0 T0N0M0 Positive Cytology Negative Cytology, Negative FISH 11 T1N0M0 pTXN0M1 Positive Cytology Positive Cytology 12 T2N0M0, UC & Micropapillary Disease T2N1M0, UC, Sarcomatoid & Micropapillary Disease Positive Cytology Positive Cytology, Positive FISH Carthon et al., Clinical Cancer Research, 2010 Metastatic Melanoma: Sustained elevation of CD4+ICOShi T cells correlates with survival ICOShi ICOSlow Carthon et al., Clinical Cancer Research, 2010 Part II Combination Therapies Why Combination Therapy? •Each tumor has multiple (90?) mutations resulting in coding changes (Vogelstein et al. Science 2006) •Many of these, depending on MHC type of host, will represent neoantigens Neoepitopes generated by genomic instability inherent in cancer •Algorithms predict 9/tumor for HLA-0201 •6 MHC alleles/tumor, so assuming even distribution predicts 54 total neoepitopes/tumor •Assuming algorithm is wrong 90% of time, would predict 5-6 neoepitopes/tumor Effective checkpoint blockade with anti-CTLA-4 therapy may turn 1 drug/therapy into 6-7, raising the possibility of combinatorial therapies to improve anti-tumor responses Segal N and Allison JP Rationale for Combination Therapy Agents that kill tumor cells (e.g. chemotherapy, radiation, hormone therapy, antibodies, “targeted” therapies) can be used to prime an immune response against multiple antigens In combination with checkpoint blockade, can unleash the immune system to maximize T cell responses to multiple targets Combination Studies with Ipilimumab • • • • • • • • • • Phase III study with Ipilimumab plus XRT in patients with metastatic prostate cancer Phase III study with Ipilimumab plus DTIC in patients with melanoma Phase II study with Ipilimumab plus Temozolamide in patients with metastatic melanoma Phase II study with Ipilimumab plus Taxol plus Paraplatin in patients with lung cancer Phase II study with Ipilimumab plus androgen blockade in patients with metastatic prostate cancer Pre-surgical Phase IIa study with Ipilimumab plus Lupron in patients with localized prostate cancer Phase I study with Ipilimumab plus MDX-1106 (anti-PD-1) in patients with melanoma Phase I/II study with Ipilimumab plus cryoablation in patients with breast cancer Planned study with Ipilimumab plus Sipuleucel-T in patients with prostate cancer Planned study with Ipilimumab plus BRAF inhibitor in patients with melanoma Phase III clinical trial with Ipilimumab + XRT vs. Placebo + XRT in CRPC 800 patients Bone Mets Estimate participation of 145 sites R A N D O M I Z E XRT + Placebo Overall Survival Immune Monitoring XRT + antiCTLA-4 antibody (administered within 2 days of XRT) No crossovers allowed Pre-surgical trial: Lupron + Ipilimumab Lupron Therapy Week - 4 to -1 Blood & Tumor 0 Blood Ipilimumab Dose (10 mg/kg) Surgery 1 4 8 Blood Blood Blood & Tumor Clinical Trial for Patients with Localized Prostate Cancer Conclusions • CTLA-4 blockade increases ICOS expression on T cells in tumor tissues and peripheral blood • ICOShi T cells from treated patients contain a population that are IFN-producing effector T cells and can recognize tumor antigen • ICOS may serve as a biologic marker of disease response but, this has to be tested in a larger cohort of patients • ICOS/ICOSL may serve as another immunotherapy target • Pre-surgical clinical trials provide a feasible platform to study biologic effects on tumor tissues thus providing data that can be applied to the metastatic disease setting and improve our understanding of mechanisms • Pre-clinical data supports the development of combination therapies with anti-CTLA-4 and any agent that is capable of killing tumor cells to prime a T cell response Sharma Lab Team – Derek Ng Tang – Hong Chen – Chrysoula Liakou – Jingjing Sun – Tihui Fu – Qiuming He – Abdol Hossein • GU Medical Oncology, Urology, Pathology – Chris Logothetis, Ashish Kamat, John Ward, Patricia Troncoso • MDACC Collaborators – Dimitra Tsavachidou, Sijin Wen • MSKCC and LICR Collaborators – Lloyd Old, Achim Jungbluth, Sacha Gnjatic (LICR) – Jim Allison, Jedd Wolchok, Jianda Yuan (LCCI, MSKCC) • BMS Team – Rachel Humphrey, Axel Hoos, Ramy Ibrahim •