On the Horizon: Immuno-Oncology (I-O) Combinations

Home , Durvalumab, Mogamulizumab, Pidilizumab, Relatlimab, Ulocuplumab, Varlilumab

Immuno-Oncology (I-O) Combinations

• Jeffrey A. Sosman, MD • Robert H. Lurie Comprehensive Cancer Center of Northwestern University

The Cancer–Immunity Cycle

Daniel Chen and Ira Mellman Immunity, Volume 39, Issue 1, 2013, 1 - 10 The Cancer–Immunity Cycle

Daniel Chen and Ira Mellman Immunity, Volume 39, Issue 1, 2013, 1 - 10 Stimulatory and Inhibitory Factors in the Cancer-Immunity Cycle Each step of the Cancer-Immunity Cycle requires the coordination of numerous factors, both stimulatory and inhibitory in nature. Stimulatory factors shown in green promote immunity, ... Where will Improvements come from?

• Combinations: – Based on Template: anti-PD-1/PD-L1 or with anti-PD- 1/anti-CTLA-4 • Signal Inhibition, BRAF directed (BRAFi+MEKi), MEKi, PI3K inhibition (PTEN effects) • Cytokines- IL-2, IFN a,b,g,, Directed cytokines (FAP-IL-2v or CEA-IL-2v) • Epigenetic modulation- gene expression and EVR expression • Microbiome modification- fecal transplants • Chemotherapy other cytotoxics • Localized Irradiation SBRT, SRS T cells in Tumors Express Multiple Immunoinhibitory Receptors These regulate the balance between T cell activation and tolerance and are druggable targets for tumor immunotherapy

CD137 OX40 GITR TIGIT CD40 VISTA ICOS CD73 CAR-T cell (Adenosine R) NKG2D CD19, CD33, BMSA, IL13R IL2v-FAP or TCR ag spec-transf T cell CEA-IL-2v TIL TCR-CD3

TLR agonist IODi CSF1R ab or sm CXCR2 CXCR4 STAT3i PI3Kd ANG2 Anti-VEGF TKI PI3Kg,d inh NeoAg vac TVEC G Freeman and A Sharpe PARPinh Glutaminase inh Nature Immunol 2012; 13:113 NTRK-14 Anti-KIR T cells can coexpress multiple inhibitory receptors

Resolved acute LCMV Chronic LCMV

Degree of dysfunction:

Blackburn et al., 2009 Nature Immunology 10: 29-37

Co-blockade enables better rescue of exhausted T cells and therapeutic efficacy than blockade of a single inhibitory pathway, but ONLY anti-PD-1 monotherapy has substantial effects

9 Cancer immunotherapy-based combination studies underway in 2016

Chen and Mellman, Nature 2017

A dramatic and unprecedented increase in clinical cancer immunotherapy combination studies (across Phase I, II and III trials) has occurred in recent years. The studies in this figure represent many of the current studies that include a PD-L1/PD-1 pathway inhibitor in combination with other immune modulators, targeted therapy, chemotherapy and/or radiation therapy. These studies are designed to characterize the efficacy, safety and biology related to combinability, synergy or antagonism associated with these combinations. Adapted from Vanessa Lucey of the Cancer Research Institute. Enhancing Efficacy of anti-PD-1/L1

Anti-PD-1/anti- PD-L1

+ anti-CTLA4 Bring T + TLR agonists or cells into oncolytic viruses tumors: + IDO or macrophage inhibitors

Modified from Ribas, Cancer Discovery 2016 Blocking CTLA-4 and PD-1

Tumor Microenvironment

Activation (cytokines, lysis, proliferation, migration to tumor)

TCR TCR MHC MHC +++ Dendritic +++ cell B7 CD28 Tumor cell +++ T cell T cell PD-1 PD-L1 B7 CTLA-4 ------anti-PD-1 anti-CTLA-4 PD-1 PD-L2 - - - anti-PD-1 CTLA-4 Blockade (ipilimumab) PD-1 Blockade (nivolumab) Overall Survival in All Randomized Melanoma Patients : 067 Ipi+ Nivo vs Nivo vs Ipi

58%

52%

34% Can PD-L1 IHC Determine Cohort that Benefits from Combination Therapy vs Single agent Therapy?

PD-L1 Expression Level <1% PD-L1 Expression Level ≥1%

NIVO+IPI NIVO IPI NIVO+IPI NIVO IPI <1% PD-L1 ≥1% PD-L1 NR 23.5 18.6 22.1 Median OS, Median OS, (26.5– (13.0– (13.7– NR NR (17.1– mo (95% CI) mo (95% CI) NR) NR) 23.2) 29.7) 100 100 0.74 1.03 HR (95% CI) HR (95% CI) (0.52– ─ ─ (0.72– ─ ─ 90 vs NIVO 90 vs NIVO 1.06) 1.48) 80 80

70 70 67% 60% 60 60 67% 49% 50 50 41% OS (%) OS OS (%) OS 40 40 48%

30 30

20 20

10 • ORR of 54.5% for NIVO+IPI and 35.0% for NIVO 10 • ORR of 65.2% for NIVO+IPI and 55.0% for NIVO

0 0 0 3 6 9 12 15 18 21 24 27 30 33 36 39 0 3 6 9 12 15 18 21 24 27 30 33 36 39 Months Months

Patients at risk: Patients at risk: NIVO+IPI 123 113 102 91 82 82 79 74 74 72 66 18 4 0 NIVO+IPI 155 144 132 127 116 112 105 102 101 99 85 27 3 0

NIVO 117 103 86 76 73 65 62 59 57 55 50 16 2 0 NIVO 171 165 158 148 139 131 122 117 112 109 98 36 1 0

IPI 113 96 87 79 71 61 57 50 44 43 32 10 1 0 IPI 164 155 138 126 115 102 89 83 77 74 64 21 2 0

14 Where will Improvements come from?

• Combinations: – Based on Template: anti-PD-1/PD-L1 or with anti-PD- 1/anti-CTLA-4 • Block other co-inhibitory: LAG3, TIM3, KIR, VISTA • Activate co-stimulatory: 4-1BB, OX-40, GITR, CD27, ICOS • Block inhibitory molecules- IDOi, TGFbi, CSF1Ri, anti-IL-6 or anti- IL-10 • Effect trafficking- anti-VEGF, CCL5, CXCR4i • Vaccines- TVEC- oncolytic virus, Neoantigen, other cellular • Adoptive Cellular therapy- TIL, CAR-T cells, TCR T-cells Potential Role of LAG-3 in T-Cell Exhaustion and Anti–PD-1 Resistance • LAG-3 regulates a checkpoint pathway that limits the activity of T cells1 • LAG-3 and PD-1 receptors are overexpressed and/or co-expressed on tumor-infiltrating lymphocytes in melanoma2,3

+ Nivolumab Tumor or other + Relatlimab infiltrating cell I-O therapy naive: PD-1 PD-L1 LAG-3 may limit I-O response

LAG-3 MHC II Effector CD4+/CD8+ + Antigen PD-L1 MHC II T cell PD-1 LAG-3 PD-1 I-O therapy experienced: + Nivolumab + Nivolumab LAG-3 may contribute to + Relatlimab resistance Acquired resistance

Nivolumab I-O, immuno-oncology; MHC II, major histocompatibility complex class II; PD-1, programmed death-1; PD-L1, Relatlimab programmed death ligand 1. (BMS-986016/anti–LAG-3) 1. Grosso JF et al. J Clin Invest. 2007;117:3383‒3392. 2. Goding SR et al. J Immunol. 2013;190:4899–4909. 3. Taube JM et al. Clin Cancer Res. 2015;21:3969–3976.

Ascierto P etal, ESMO 2017 Antitumor Activity of Relatlimab (anti-LAG3) + Nivolumab Change in Tumor Size by LAG-3 Expression

LAG-3 ≥ 1% LAG-3 < 1% LAG-3 Unknown 100 n = 29 100 n = 17 100 n = 8

a,b 80 80 80

60 60 60 45% with tumor 24% with tumor 13% with tumor aseline 40 reduction 40 reduction 40 reduction

in sum of targetof in sum 20 20 20 from b from 0 0 0

-20 -20 -20

-40 -40 -40 iameters d -60 -60 -60

esion -80 -80 -80 l

Best percent c hange percent Best -100 -100 -100

Pink: PD-L1 ≥ 1% Blue: PD-L1 < 1% Gray: PD-L1 unknown aSix patients with clinical progression prior to their first scan and 1 with PD due to a new symptomatic brain metastasis prior to getting full scans were not included. 17 bOne patient with best change from baseline > 30% had a best response of SD.

17 Where will Improvements come from?

• Combinations: – Based on Template: anti-PD-1/PD-L1 or with anti-PD- 1/anti-CTLA-4 • Block other co-inhibitory: LAG3, TIM3, KIR, VISTA • Activate co-stimulatory: 4-1BB, OX-40, GITR, CD27, ICOS • Block inhibitory molecules- IDOi, TGFbi, CSF1Ri, anti-IL-6 or anti- IL-10 • Effect trafficking- anti-VEGF, CCL5, CXCR4i • Vaccines- TVEC- oncolytic virus, Neoantigen, other cellular • Adoptive Cellular therapy- TIL, CAR-T cells, TCR T-cells Rationale for IDO1 Inhibitor Plus Anti– PD-1 Combination Therapy

• IDO1 enzyme inhibits T-cell function through local depletion of tryptophan and production of immunosuppressive kynurenine and downstream metabolites1

• High IDO1 expression is associated with a decrease in immune cell tumor infiltration and an increase in regulatory T cells1,2

• IDO1 expression in tumors has also been associated with poor prognosis, increased progression, and reduced survival1,2

T cell • Anti–PD-1 treatment upregulates IDO1 expression in patients3,4

IDO+ Adapted from Moon YW et al. J Immunother Cancer. 2015;3:51. Published DC under Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).

IFNγR, interferon gamma receptor; MHC, major histocompatibility complex; PD-L1, programmed death-1 ligand. 1. Moon YW et al. J Immunother Cancer. 2015;3:51. 2. Godin-Ethier J et al. Clin Cancer Res. 2011;17:6985–6991. 3. Urba WJ et al. Presented at the AACR 2015 Annual Meeting; April 18–22, 2015: Philadelphia, Pennsylvania [oral 4886]. 4. Choueiri TK et al. Presented at the AACR 2015 Annual Meeting; April 18–22, 2015: Philadelphia, Pennsylvania [poster 5].

19 Recent Results of anti-PD-1 + IDOi

• Phase I/II results from the KEYNOTE-37 trial, the combination Pembrolizumab and Epecadostat induced objective responses in 29 of 53 (55%) treatment-naïve patients, including seven CRs • 22 of 38 evaluable patients (58%) responded to the recommended phase II dose of epacadostat (100 mg).

• Median progression-free survival (PFS) of 22.8 months in the treatment-naïve pts, and NR in the patients who received the phase II dose of epacadostat Where will Improvements come from?

• Combinations: – Based on Template: anti-PD-1/PD-L1 or with anti-PD- 1/anti-CTLA-4 • Block other co-inhibitory: LAG3, TIM3, KIR, VISTA • Activate co-stimulatory: 4-1BB, OX-40, GITR, CD27, ICOS • Block inhibitory molecules- IDOi, TGFbi, CSF1Ri, anti-IL-6 or anti- IL-10 • Effect trafficking- anti-VEGF, CCL5, CXCR4i • Vaccines- TVEC- oncolytic virus, Neoantigen, other cellular • Adoptive Cellular therapy- TIL, CAR-T cells, TCR T-cells Oncolytic Virus Injection Promotes Intratumoral T Cell Infiltration to Improve Anti-PD-1 Immunotherapy

Ribas etal, CELL 2017 Talimogene Laherparepvec Increases Tumor-Infiltrating Lymphocyte Density and PD-L1 Expression in Tumors

Ribas etal, CELL 2017 Where will Improvements come from?

• Combinations: – Based on Template: anti-PD-1/PD-L1 or with anti-PD- 1/anti-CTLA-4 • Block other co-inhibitory: LAG3, TIM3, KIR, VISTA • Activate co-stimulatory: 4-1BB, OX-40, GITR, CD27, ICOS • Block inhibitory molecules- IDOi, TGFbi, CSF1Ri, anti-IL-6 or anti- IL-10 • Effect trafficking- anti-VEGF, CCL5, CXCR4i • Vaccines- TVEC- oncolytic virus, Neoantigen, other cellular • Adoptive Cellular therapy- TIL, CAR-T cells, TCR T-cells Cancer exome–based identification of neoantigens.

Summary

• What’s required for effective Cancer Immunotherapy • Combination Therapy – – Underway in full gear – Rationale for many combinations- selection • IDOi • Anti-LAG-3 • Vaccines • Adoptive Cell Therapy • Improving Patient Selection • Biomarker Development- Too many- how to simplify • Use to select the most effective • Use to select the least toxic

Cancer-immune phenotypes.

Chen and Mellman, Nature 2017 Biomarker Model

CD8 Density Mutational PDL1 Expression Load Histology

IFNγ signature

• All inter-related • Some tumors may have a larger sweet spot

M Atkins with permission. 33 CD8+T cell Density within the Tumor and at Invasive Margin Importance Somatic mutations by tumor type

MS Lawrence et al. Nature 2013 Hypothesis: PD-1 Blockade works in patients with most “mutated” / “immunogenic” cancers.

This data supports hypothesis

B Fox CFDA T cell-inflamed tumor microenvironment by tumor type in increasing frequency

Presented By Jason Luke at 2016 ASCO Annual Meeting Expanded Gene Signatures Identified During Discovery LAG3 GZMB

Analysis Reveal Biology of GZMA CD27 Complex Immune Synapse T cells LCK GZMK

HLA- E T cell PRF1 PD-1 PD-L1 PD-L2 TCR Discovery analysis of TIGIT TCR entire NanoString B2 HLA melanoma data set led M to identification of HLA- CD74 DRA CCR5 IFNγ new genes: CXCL9 STAT STAT1 1 Tumor CXCL10 PD-L1 CIITA CCR5 CXCL11 PD-L2 IDO1 - IFNγ signaling - MHC class I and II antigen presentation HLA-E machinery Endothelial, - T-cell activation Macrophage/APC Fibroblast markers Signature Expanded in Validation Set (While Blinded to Clinical Outcome)

Melanoma Melanoma Discovery Set Validation Set

62 Patients IL2Rg 19 Patients Independent CXCR6 CD3d Data Set CD2 ITGAL TAGAP “Preliminary Expanded CIITA HLA-DRA Immune” (28-gene) PTPRC signature: coherent set CXCL9 CCL5 correlated with the 10- NKG7 gene “Preliminary GZMA PRF1 IFNγ” signature genes CCR5 (in red) CD3e GZMK IFNγ HLA-E GZMB PDCD1 SLAMF6 CXCL13 CXCL10 IDO1 LAG3 Correlation Matrix of Top Significant Genes in the Discovery STAT1 Set Evaluated in the Validation Set CXCL11 Overall Survival in All Randomized Patients : 067 Ipi+ Nivo vs Nivo vs Ipi

58 % 52 % 34 % Can PD-L1 IHC Determine Cohort that Benefits from Combination Therapy vs Single agent Therapy?

PD-L1 expression level ≥1% PD-L1 expression level <1% Outcomes Observed at a 1% Cutoff PD-L1 Expression Level <1% PD-L1 Expression Level ≥1%

70 70 67% 60% 60 60 67% 49% 50 50 41% OS (%) OS OS (%) OS 40 40 48%

30 30

20 20

10 • ORR of 54.5% for NIVO+IPI and 35.0% for NIVO 10 • ORR of 65.2% for NIVO+IPI and 55.0% for NIVO

0 0 0 3 6 9 12 15 18 21 24 27 30 33 36 39 0 3 6 9 12 15 18 21 24 27 30 33 36 39 Months Months

Patients at risk: Patients at risk: NIVO+IPI 123 113 102 91 82 82 79 74 74 72 66 18 4 0 NIVO+IPI 155 144 132 127 116 112 105 102 101 99 85 27 3 0

NIVO 117 103 86 76 73 65 62 59 57 55 50 16 2 0 NIVO 171 165 158 148 139 131 122 117 112 109 98 36 1 0

IPI 113 96 87 79 71 61 57 50 44 43 32 10 1 0 IPI 164 155 138 126 115 102 89 83 77 74 64 21 2 0

42 Tumor Type ICOS Intratumoral PD-L1 FOXP3 & IDO Mellman et al. Nature 2011 TCR Clonality Treg

Intratumoral Mutation CD8+/FOXP3+ Burden

NY-ESO-1 Microbiota Ku et al Cancer 2010; Menard et al Clin Cancer Res 2008; Absolute Weber et al JCO 2009; Yuan et al, PNAS 2011; IL-17 CD4+ lymphocyte Hodi et al PNAS 2008; DiGiacom lo et al Cancer Hamid et al JCO 2009; Immunol Immunother 2013; cells count Ng et al Cancer Immuno Queirolog et al,Cancer Invest Res 2013; 2013; Tarhini et al PLoS One Wolchok et al,Cancer Immun Prior “Inflamed” 2014; 2010; microenvironment Kitano et al Cancer Tumeh et al Nature 2105; Therapies? Immunol Res 2013; Snyder et al NEJM 2014; MDSC Spranger et al Sci Transl Rizvi et al Science 2015; CD45RO Med 2013; Van Allen et al Science 2105; Kitano et al Cancer Sivan et al Science 2015; Immunol Res 2014; Vetizou et al Science 2015; Ji RR et al, Cancer Rosenberg et al Lancet 2016 Presented by: Alexandra Snyder, M.D. Immunol Immunother 2012; Tumor Type ICOS Intratumoral PD-L1 FOXP3 & IDO TCR Clonality Treg

Intratumoral Mutation CD8+/FOXP3+ Data Burden

Integration? NY-ESO-1 Microbiota

Absolute IL-17 CD4+ lymphocyte cells count “Inflamed” Prior microenvironmen Therapies? t MDSC CD45RO Action?

Presented by: Alexandra Snyder, M.D. Tumor Interactions to Suppress the Immune System Overcome Tumor -Induced Immune Suppression The Barriers

• Cell Populations • Soluble Factors • Immune checkpoints • Loss of Tumor Antigens anti-PD-1/L1 plus anti-CTLA4 checkpoint blockade plus cancer vaccines Durvalumab + tremelimumab Nivolumab + anti-CTLA4 plus DC vaccine Nivolumab + ipilimumab anti-PD-1/L1 plus anti- anti-PD-1/L1 plus DC vaccine Pembrolizumab + ipilimumab BMS986156 GITR anti-PD-1/L1 plus peptide vaccine anti-PD-1 plus anti-PD-L1 PDR001 + GWN323 anti-PD-1/L1 plus neoantigen vaccine MEDI0680 + durvalumab Durvalumab + ADXS11-001 PDR001 + FAZ053 anti-PD-1/L1 plus anti- Durvalumab + TPIV200/huFR-1 combination checkpoint blockade anti-PD-1/L1 plus anti-TIM 3 Nivolumab + JTX-2011 Ipilimumab + GVAX Nivolumab + TSR022 ICOS Nivolumab + GVAX + CRS207 PDR001 + MBG453 Nivolumab + CIMAvax Nivolumab+ CV301 anti-PD-1/L1 plus anti-LAG 3 Nivolumab + NEO-PV-01 Nivolumab + BMS 986016 Atezolizumab + GDC0919 Ipilimumab + epacadostat PDR001 + LAG525 anti-CTLA-4 plus IDO inhibitors Nivolumab + Viagenpumatucel-L (HS-110) Ipilimumab + indoximid Pembrolizumab + IMP321 anti-PD-1/L1 plus IDO inhibitors Pembrolizumab + ADXS31-142 REGN2810 + REGN3767 Nivolumab + BMS986205 checkpoint blockade plus Durvalumab ± tremelimumab + IMCgp100 Avelumab + utomilumab Pembrolizumab+ epacadostat metabolic modulators anti-PD-1/L1 plus anti-41BB/CD137 Nivolumab + urelumab checkpoint blockade plus adoptive cell transfer (ACT) Pembrolizumab + utomilumab Atezolizumab + CPI-444 anti-CTLA4 plus ACT anti-PD-1/L1 plus A2AR inhibitors or anti- Atezolimumab + MOXR0916 ± bevacizumab Durvalumab + MEDI9447 Avelumab + PF-04518600 CD73 anti-PD-1/L1 plus ACT anti-CTLA4 plus anti-OX40 PDR001+ PBF509 Durvalumab + MEDI0562 anti-PD-1/L1 plus anti-OX40 Pembrolizumab + GSK3174998 Tremelimumab + anti-PD-1/L1 plus anti-CD137 plus ACT anti-CTLA4 plus Anti-PD-1/L1 plus anti-OX40 checkpoint blockade plus immune- durvalumab + MEDI6469 Tremelimumab + Nivolumab + LY2157299 Atezolimuamb + KTE-C19 anti-41BB/CD137 plus anti-OX40 anti-PD-1/L1 plus TGFb inhibitors stimulatory agents MEDI0562 PDR001 + NIS793 Utomilumab + PF-04518600 Ipilimumab + NYESO TCR ACT Nivolumab + ulocuplumab anti-CTLA4 plus anti-CD40 anti-PD-1/L1 plus anti- Atezolimumab + RO7009789 Tremelimumab + anti-PD-1/L1 plus CXCR4 inhibitors CD40 CP870893 Durvalumab + LY2510924 Nivolumab + NYESO TCR ACT Nivolumab + BMS986156 anti-PD-1/L1 plus anti-GITR Nivolumab + urelumab + TIL ACT PDR001 + GWN323 anti-PD-1/L1 plus CCR4 inhibitors Nivolumab + mogamulizumab Pembrolizumab + TIL ACT anti-PD-1/L1 plus anti-ICOS Nivolumab + JTX-2011 Ipilimumab + modified CD8 T cell ACT Atezolizumab + GDC0919 Pembrolizumab + modified CD8 T cell ACT Ipilimumab + epacadostat Nivolumab + varlilumab anti-CTLA-4 plus IDO inhibitors anti-PD-1/L1 plus anti-CD27 Ipilimumab + indoximid Atezolizumab + varlilumab anti-PD-1/L1 plus IDO inhibitors Nivolumab + BMS986205 checkpoint blockade plus checkpoint blockade plus anti-CTLA4 plus BRAF+MEK inhibitors Pembrolizumab+ epacadostat metabolic modulators other immune modulators anti-PD-1/L1 plus CD122-biased cytokine Nivolumab + NKTR-214 anti-CTLA4 plus VEGF inhibitors Atezolizumab + CPI-444 anti-PD-1/L1 plus BRAF+MEK inhibitors anti-PD-1/L1 plus A2AR inhibitors or anti-CD73 Durvalumab + MEDI9447 anti-PD-1/L1 plus EGFR inhibitors anti-PD-1/L1 plus yeast-derived soluble PDR001+ PBF509 Pembrolizumab + Imprime PGG anti-PD-1/L1 plus VEGF inhibitors Nivolumab + LY2157299 b-glucan anti-PD-1/L1 plus TGFb inhibitors anti-PD-1/L1 plus PI3K delta inhibitor PDR001 + NIS793 Atezolizumab + bevacizumab versus sunitinib Nivolumab + ulocuplumab Atezolizumab + trametinib anti-PD-1/L1 plus CXCR4 inhibitors anti-PD-1/L1 plus anti- TRAIL-DR5 Nivolumab + DS-8273a Durvalumab + LY2510924 Atezolizumab + vemurafenib ± cobimetinib anti-PD-1/L1 plus CCR4 inhibitors Nivolumab + mogamulizumab Durvalumab + ensartinib (ALK inhibitor) Nivolumab + varlilumab Durvalumab + gefitinib anti-PD-1/L1 plus anti-CD27 anti-PD-1/L1 plus glutaminase inhibitor Nivolumab + CB839 checkpoint blockade plus other Atezolizumab + varlilumab checkpoint blockade plus targeted therapies Durvalumab + trametinib ± dabrafenib immune modulators anti-PD-1/L1 plus CD122-biased cytokine Nivolumab + NKTR-214 Ipilimumab + bevacizumab Ipilimumab + anti-PD-1/L1 plus IAP inhibitor PDR001 + LCL161 dabrafenib ± trametinib Ipilimumab anti-PD-1/L1 plus yeast-derived soluble b-glucan Pembrolizumab + Imprime PGG +vemurafenib Nivolumab + sunitinib or pazopanib anti-PD-1/L1 plus anti- TRAIL-DR5 Nivolumab + DS-8273a Nivolumab + trametinib ± dabrafenib Durvalumab + Pexidartinib (PLX3397) anti-PD-1/L1 plus glutaminase inhibitor Nivolumab + CB839 PDR001 + sorafenib Durvalumab + LY3022855 anti-PD-1/L1 plus IAP inhibitor PDR001 + LCL161 Pembrolizumab + dabrafenib + trametinib checkpoint blockade plus anti-CTLA4 plus CSF1R inhibitors Nivolumab + FPA008 Durvalumab + Pexidartinib (PLX3397) Durvalumab Pembrolizumab + lenalidomide Pembrolizumab macrophage inhibitors anti-PD-1/L1 plus CSF1R inhibitors Pembrolizumab + Pexidartinib + LY3022855 + nintedarnib PDR001 + BLZ945 checkpoint blockade plus anti-CTLA4 plus CSF1R inhibitors macrophage inhibitors Nivolumab + FPA008 Pidilizumab + lenalidomide Tremelimumab + Tremelimumab + LY3022855 anti-PD-1/L1 plus CSF1R inhibitors Pembrolizumab + Pexidartinib sunitinib Nivolumab + SYM004 PDR001 + BLZ945 Tremelimumab + LY3022855 anti-CTLA-4 plus oncolytic viruses Durvalumab + Pexidartinib (PLX3397) Durvalumab + LY3022855 Ipilimumab + Talimogene Laherparepvec Nivolumab + FPA008 checkpoint blockade plus anti-CTLA4 plus CSF1R inhibitors macrophage anti-PD-1/L1 plus oncolytic viruses Pembrolizumab + Pexidartinib inhibitors anti-PD-1/L1 plus CSF1R inhibitors Nivolumab + Talimogene Laherparepvec PDR001 + BLZ945 Pembrolizumab + DNX2401 Tremelimumab + LY3022855 Pembrolizumab + Talimogene Laherparepvec checkpoint blockade plus injectable therapies anti-CTLA4 plus TLR agonists Ipilimumab + MGN1703 anti-CTLA4 plus BRAF+MEK inhibitors anti-CTLA4 plus VEGF inhibitors anti-PD-1/L1 plus TLR agonists anti-PD-1/L1 plus BRAF+MEK inhibitors Pembrolizumab + CMP001 anti-PD-1/L1 plus EGFR inhibitors Pembrolizumab + SD101 anti-PD-1/L1 plus VEGF inhibitors Tremelimumab + PF-3512676 anti-PD-1/L1 plus PI3K delta inhibitor Atezolizumab + bevacizumab versus sunitinib Atezolizumab + trametinib checkpoint blockade plus cancer vaccines Atezolizumab + vemurafenib ± cobimetinib Durvalumab + ensartinib (ALK inhibitor) Durvalumab + gefitinib anti-CTLA4 plus DC vaccine Durvalumab + trametinib ± dabrafenib Ipilimumab + bevacizumab Ipilimumab + dabrafenib ± trametinib anti-PD-1/L1 plus DC vaccine Ipilimumab +vemurafenib checkpoint blockade plus targeted therapies anti-PD-1/L1 plus peptide vaccine Nivolumab + sunitinib or pazopanib anti-PD-1/L1 plus neoantigenvaccine Nivolumab + trametinib ± dabrafenib PDR001 + sorafenib Durvalumab + ADXS11-001 Pembrolizumab + dabrafenib + trametinib Durvalumab + TPIV200/huFR-1 Pembrolizumab + lenalidomide Pembrolizumab + nintedarnib Ipilimumab + GVAX Pidilizumab + lenalidomide Tremelimumab + sunitinib Nivolumab + SYM004 Nivolumab + GVAX + CRS207 anti-PD-1/L1 plus PARP inhibitors Atezolizumab + Veliparib Durvalumab + olaparib BGB-A317 + BGB-290 Nivolumab + CIMAvax Nivolumab+ CV301 anti-PD-1/L1 plus mTOR inhibitor PDR001 + everolimus Nivolumab + NEO-PV-01 anti-PD-1/L1 plus pan RAF inhibitor PDR001 + LXH254 Nivolumab + Viagenpumatucel-L (HS-110) anti-PD-1/L1 plus glutaminase inhibitor Nivolumab + CB839 Pembrolizumab + ADXS31-142 checkpoint blockade plus anti-CTLA4 plus RT radiation therapy (RT) anti-PD-1/L1 plus RT Durvalumab ± tremelimumab + IMCgp100 anti-CTLA4 plus Anti-PD-1/L1 plus RT Atezolizumab + stereotactic radiation therapy Pembrolizumab + cisplatin/radiotherapy Pembrolizumab + sterotactic body radiotherapy Pembrolizumab + hypofractionated radiotherapy