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Mutational Landscape and Sensitivity to Immune Checkpoint Blockers Roman M

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Mutational Landscape and Sensitivity to Immune Checkpoint Blockers Roman M Published OnlineFirst July 7, 2016; DOI: 10.1158/1078-0432.CCR-16-0903 Review Clinical Cancer Research Mutational Landscape and Sensitivity to Immune Checkpoint Blockers Roman M. Chabanon1,2, Marion Pedrero2,Celine Lefebvre1,2, Aurelien Marabelle3,4, Jean-Charles Soria1,2,3, and Sophie Postel-Vinay1,2,3 Abstract Immunotherapy is currently transforming cancer treatment. from ICB. Thus, closely reflecting the DNA damage repair capacity Notably, immune checkpoint blockers (ICB) have shown unprec- of tumor cells and their intrinsic genomic instability, the muta- edented therapeutic successes in numerous tumor types, includ- tional load and its associated tumor-specific neoantigens appear ing cancers that were traditionally considered as nonimmuno- as key predictive paths to anticipate potential clinical benefits of genic. However, a significant proportion of patients do not ICB. In the era of next-generation sequencing, while more and respond to these therapies. Thus, early selection of the most more patients are getting the full molecular portrait of their sensitive patients is key, and the development of predictive tumor, it is crucial to optimally exploit sequencing data for the companion biomarkers constitutes one of the biggest challenges benefit of patients. Therefore, sequencing technologies, analytic of ICB development. Recent publications have suggested that the tools, and relevant criteria for mutational load and neoantigens tumor genomic landscape, mutational load, and tumor-specific prediction should be homogenized and combined in more inte- neoantigens are potential determinants of the response to ICB and grative pipelines to fully optimize the measurement of such can influence patients' outcomes upon immunotherapy. Further- parameters, so that these biomarkers can ultimately reach the more, defects in the DNA repair machinery have consistently been analytic validity and reproducibility required for a clinical imple- associated with improved survival and durable clinical benefit mentation. Clin Cancer Res; 22(17); 1–13. Ó2016 AACR. Introduction among all tumor types included, still do not respond to these drugs, highlighting the urge for developing robust predictive Since their first introduction into the clinic and first approval in biomarkers that would guide appropriate selection of patients. 2011 (1), immune checkpoint blockers (ICB) have transformed Recently, the tumor cell mutational burden has been correlated cancer treatment and allowed unprecedented improvements in with clinical benefits of anti–PD-1 and anti-CTLA-4 therapy in overall survival (OS), progression-free survival (PFS), or overall various tumor types, including malignant myeloma (4, 5), response rates (ORR) in many aggressive diseases (2, 3). Most NSCLC (6), and several DNA repair–deficient tumors (7–9). importantly, benefits of ICB have not been limited to the "tradi- Predicted neoantigen load has also emerged as an interesting tional" immunogenic cancers, malignant melanoma and renal selection biomarker for predicting clinical benefit of these agents. cell carcinoma (RCC), but have also been extended to other Overall, a direct link between DNA repair deficiency, mutational histologies classically described as "nonimmunogenic," such as landscape, predicted neoantigen load, and clinical activity of ICB non–small cell lung cancer (NSCLC) or mismatch-repair–defi- is suggested. cient colorectal cancer (MMR-deficient colorectal cancer; ref. 3). In this review, we discuss the significance and the relevance of Despite these clear clinical advances, the biological mechanisms this correlation in solid tumors. We also provide critical insight that underlie antitumor immunity and determine sensitivity to into the methods and techniques that have been used for per- these agents, notably anti-programmed death receptor-1/-ligand forming analyses of tumor mutational burden, predicted neoan- 1 [anti–PD-(L)1] are still poorly understood. Moreover, a statis- tigen load, and neopeptide formation. We further propose a tically significant proportion of patients, approximately 80%, comprehensive approach that would allow encompassing other potential predictive biomarkers for response to anti–PD-(L)1 inhibitors. 1FacultedeM edicine, Universite Paris Saclay, Universite Paris-Sud, Le Kremlin Bicetre,^ France. 2Inserm Unit U981, Gustave Roussy, Villejuif, France. 3DITEP (Departement d'Innovations Therapeutiques et Essais Immune Escape and Carcinogenesis Precoces), Gustave Roussy, Villejuif, France. 4Inserm Unit U1015, Gus- tave Roussy, Villejuif, France. The original concept of immune surveillance, hypothesized in 1957 (10), and formally established in 1970 (11), postulated that Note: Supplementary data for this article are available at Clinical Cancer the immune system alone could eliminate tumor cells in the early Research Online (http://clincancerres.aacrjournals.org/). stages of carcinogenesis. Since then, this theory has been further Corresponding Author: Sophie Postel-Vinay, Gustave Roussy, 114 Rue Edouard enriched by the "immunoediting" notion (12), which describes Vaillant, Villejuif 98105, France. Phone: 3301-4211-43 43; Fax: 3301-4211-6444; how both innate and adaptive immunity contribute to carcino- E-mail: [email protected] genesis, notably by exerting a Darwinian selection pressure. doi: 10.1158/1078-0432.CCR-16-0903 Immunoediting classically consists of three distinct steps: (i) Ó2016 American Association for Cancer Research. elimination: the innate and adaptive compartments coordinately www.aacrjournals.org OF1 Downloaded from clincancerres.aacrjournals.org on September 25, 2021. © 2016 American Association for Cancer Research. Published OnlineFirst July 7, 2016; DOI: 10.1158/1078-0432.CCR-16-0903 Chabanon et al. IL10 TGFb Arginase 1 MDSC Treg TAN TAM 3 – ++ ++ CXCL15 CCL2 IL4 GM-CSF CCL5 NK MHC CSF-1 CXCL1 CXCL2 CCL22 class I CXCL12 CXCL5 IL1 TNFa 1 – TCR PD-L1 Tumor cell – 5 CTL PD-1 PD-L2 iDC DR4/5 FAS PGE2 TRAIL – COX-2 4 FAS-L 2 mDC © 2016 American Association for Cancer Research Figure 1. Mechanisms of immune escape in the tumor microenvironment. Several mechanisms, involving multiple immune components, contribute to tumor immune escape. (1) Immune recognition can be impaired following reduced expression of MHC class I molecules in malignant cells, resulting in decreased antigen presentation and consequently reduced detection by cytotoxic CD8þ T lymphocytes. (2) Cancer cells can activate immunosuppressive mechanisms by inducing immune cells' apoptosis through the expression of death signals (including FAS- and TRAIL-ligands). (3) Tumor cells release in the microenvironment a variety of immune- modulatory molecules that inhibit the immune system, such as IL6 and IL10, by inducing immunosuppressive Treg cells and MDSC, whereas the activity of cytotoxic CD8þ T cells and NK cells is inhibited. (4) This cytokine imbalance, combined with the secretion of TGFb, COX-2, and PGE2, inhibits dendritic cell differentiation and maturation, thereby affecting antigen presentation and recognition by T cells. The release of additional immune modulators or metabolic regulators, such as IDO and arginase, also favors the establishment of an immunosuppressive tumor microenvironment. (5) Disrupted expression of immune checkpoint ligands by cancer cells provides coinhibitory signals to CD4þ and CD8þ T lymphocytes, preventing them from building a specific antitumor immune response. CCL, chemokine ligand; COX-2, cyclooxygenase-2; CXCL, chemokine (C-X-C motif) ligand; FAS-L, FAS-ligand; GM-CSF, granulocyte macrophage colony-stimulating factor; iDC, immature dentritic cell; IDO, indoleamine-2,3-deoxygenase; mDC, mature dentritic cell; MDSC, myeloid-derived suppressor cell; PD-1, programmed cell death 1; PD-L, programmed cell death ligand; PGE2, prostaglandin E2; TAN, tumor-associated neutrophil; TCR, T-cell receptor; Treg, regulatory T cells. drive immune rejection; (ii) equilibrium: through a clonal selec- CD86, and conversely inhibits T cells when CTLA-4 is engaged; tion process, the dynamic balance between tumor and immune and (ii) the PD-1 axis, which provides a strong inhibitory signal cells results in the emergence of specific tumor cell variants with following binding of PD-L1 or PD-L2 to the PD-1 receptor (22). increased resistance, which take advantage of acquired mutations; Contrary to CTLA-4, PD-1 is thought to act predominantly in the (iii) escape: the immune-resistant clones freely expand, circum- tumor microenvironment, where PD-L1 is overexpressed by mul- venting both innate and adaptive immune responses. tiple cell types, including dendritic cells, M2 macrophages, and A variety of mechanisms can facilitate tumor immune escape tumor-associated fibroblasts (23). (Fig. 1). Among them, deregulation of immune checkpoint sig- As opposed to historical immune-based approaches that were naling has been observed in multiple malignancies (13–21). developed in traditionally immunogenic cancers, ICBs have Immune checkpoints involve the interaction between a receptor allowed significant therapeutic successes in many solid tumors expressed on T cells and its ligand located at the surface of antigen- and hematologic malignancies. The anti-CTLA-4 ipilimumab presenting cells. This generates a costimulatory signal, which (Yervoy, Bristol-Myers Squibb) was the first ICB to improve OS triggers either the activation or inhibition of T cells. Two major in malignant melanoma patients (1). In 2012, anti–PD-(L)1 checkpoints regulate T-cell activation: (i) the CD28/CTLA-4 axis, therapies
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