Mutational Landscape and Sensitivity to Immune Checkpoint Blockers

Chabanon, R; Pedrero, Marion; Lefèbvre, Céline; Marabelle, Aurélien; Soria, Jean‐Charles; Postel-Vinay, Sophie

doi:10.1158/1078-0432.ccr-16-0903

Cited by 183 publications

(153 citation statements)

References 105 publications

(69 reference statements)

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“…C or CD8 C T cells, amongst others; [251][252][253] (2) the circulating levels of multiple cytokines, such as interferon, gamma (IFNG; best known as IFN-g), 254 IL6, 255 and tumor necrosis factor (TNF); 256-258 (3) the amounts of TAA-specific T cells (via tetramer assays); 259,260 (4) the tumor mutational load and/or the abundance of predicted neo-antigens (via genome or whole-exome sequencing); 115,138,[261][262][263][264][265] and (5) the levels of circulating biomarkers of ICD (via proteomic or metabolomic assays).…”

Section: Ongoing Clinical Trialsmentioning

confidence: 99%

Trial watch: Immunogenic cell death induction by anticancer chemotherapeutics

et al. 2017

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The expression "immunogenic cell death" (ICD) refers to a functionally unique form of cell death that facilitates (instead of suppressing) a T cell-dependent immune response specific for dead cell-derived antigens. ICD critically relies on the activation of adaptive responses in dying cells, culminating with the exposure or secretion of immunostimulatory molecules commonly referred to as "damage-associated molecular patterns". Only a few agents can elicit bona fide ICD, including some clinically established chemotherapeutics such as doxorubicin, epirubicin, idarubicin, mitoxantrone, bleomycin, bortezomib, cyclophosphamide and oxaliplatin. In this Trial Watch, we discuss recent progress on the development of ICD-inducing chemotherapeutic regimens, focusing on studies that evaluate clinical efficacy in conjunction with immunological biomarkers.

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Section: Ongoing Clinical Trialsmentioning

confidence: 99%

Trial watch: Immunogenic cell death induction by anticancer chemotherapeutics

et al. 2017

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“…2,6 We gave due consideration to two currently described scenarios in this regard, i.e., (1) the "canonical" association between immunosuppressive Treg cells and immune checkpoints, considering that the function of Tregs and CTLA4, PD1 and IDO1 in enforcing immunosuppression is overlapping 2,6,17,34,35 ; and (2) the "paradoxical" association between immune checkpoints and T cell-effector markers (like IFNg, Granzyme B-perforin), since activation of T cells eventually causes upregulation of immune checkpoints as an auto-regulatory loop in later stages of effector function (to avoid autoimmunity and resolve inflammation). To this end, we first analyzed the correlation between CTLA4, PDCD1 or IDO1 expression levels and a previously established Treg-specific genetic signature or metagene.…”

Section: Ctla4 and Ido1 Show Association With Treg And Effector T-celmentioning

confidence: 99%

“…17,34,35 To this end, we decided to ascertain the prognostic impact of immune-checkpoint gene expression in TCGA and REMBRANDT GBM cohorts. The differential expression of CTLA4, PDCD1 and IDO1 did not show strong association with poor or prolonged overall survival (OS) in GBM patients, neither in TCGA (Figs.…”

Section: Differential Ctla4 Pdcd1 and Ido1 Expression Fail To Exhibimentioning

confidence: 99%

“…6 Such broad predictive biomarkers include (but are not limited to) the following: 6,17,18 (1) overall mutational burden, which is a surrogate marker for neoantigen burden (neoantigen-specific T cells are particularly active in tumors responding to ICIs thereby making high mutational/neoantigen burden crucial for ICI responsiveness), (2) differential expression of immune checkpoints, (3) pre-existing or basal levels of tumorinfiltrating T lymphocytes (TILs), (4) correlation of immune-checkpoint expression with particular TILs/Tregassociated polarization or effector function markers and (5) prognostic impact of differential immune-checkpoint expression. 2,6,17,18 In terms of consistency, current clinical data shows that high pre-existing/basal density of TILs and high mutational/neoantigen burden together predict positive responsiveness to ICIs. 2,6 These biomarkers are considered to be resulting from prolonged carcinogenic insults and mutagenic clonal evolution.…”

Section: Introductionmentioning

confidence: 99%

“…2,6 These biomarkers are considered to be resulting from prolonged carcinogenic insults and mutagenic clonal evolution. 6,17,18 Carcinogenic insults, in particular, are considered to be the predominant source of high mutational burden (i.e., non-synonymous somatic single-nucleotide variations). 19,20 In fact, some recent genetic analyses have shown that specific mutagens or carcinogens induce distinct mutational lesions in particular cancer types 21 like mutational signatures 4 and 29 (e.g., C>A or CC>AA mutations induced by tobacco mutagens, hence showing high presence in smokers and/or those who chew tobacco), signature 7 (e.g., CC>TT mutations induced by ultraviolet radiation), signature 22 (e.g., T>A mutations induced by aristolochic acid) and signature 24 (e.g., C>A mutations induced by aflatoxin).…”

Section: Introductionmentioning

confidence: 99%

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Preclinical efficacy of immune-checkpoint monotherapy does not recapitulate corresponding biomarkers-based clinical predictions in glioblastoma

et al. 2017

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Glioblastoma (GBM) is resistant to most multimodal therapies. Clinical success of immune-checkpoint inhibitors (ICIs) has spurred interest in applying ICIs targeting CTLA4, PD1 or IDO1 against GBM. This amplifies the need to ascertain GBM's intrinsic susceptibility (or resistance) toward these ICIs, through clinical biomarkers that may also "guide and prioritize" preclinical testing. Here, we interrogated the TCGA and/or REMBRANDT human patient-cohorts to predict GBM's predisposition toward ICIs. We exploited various broad clinical biomarkers, including mutational or predicted-neoantigen burden, pre-existing or basal levels of tumor-infiltrating T lymphocytes (TILs), differential expression of immune-checkpoints within the tumor and their correlation with particular TILs/Treg-associated functional signature and prognostic impact of differential immune-checkpoint expression. Based on these analyses, we found that predictive biomarkers of ICI responsiveness exhibited inconsistent patterns in GBM patients, i.e., they either predicted ICI resistance (as compared with typical ICI-responsive cancer-types like melanoma, lung cancer or bladder cancer) or susceptibility to therapeutic targeting of CTLA4 or IDO1. On the other hand, our comprehensive literature meta-analysis and preclinical testing of ICIs using an orthotopic GL261-glioma mice model, indicated significant antitumor properties of anti-PD1 antibody, whereas blockade of IDO1 or CTLA4 either failed or provided very marginal advantage. These trends raise the need to better assess the applicability of ICIs and associated biomarkers for GBM.

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Evaluation of Programmed Death Ligand 1 (PD-L1) Gene Amplification and Response to Nivolumab Monotherapy in Non–small Cell Lung Cancer

et al. 2020

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IMPORTANCE Robust predictors for response to anti-programmed death 1 and its ligand (PD-1/PD-L1) immunotherapy in non-small cell lung cancer (NSCLC) are not fully characterized. OBJECTIVE To evaluate whether PD-L1 (CD274) copy number gains (CNGs), comprising amplification and polysomy, in pretreatment specimens assessed by fluorescence in situ hybridization are associated with response to nivolumab monotherapy in NSCLC. DESIGN, SETTING, AND PARTICIPANTS This multicenter cohort study enrolled 200 patients, of whom 194 had assessable tumors, with advanced or recurrent NSCLC who were treated with nivolumab after progression following prior treatment at 14 institutions in Japan between July 2016 and December 2018. Median (interquartile range) duration of follow-up was 12.6 (5.6-20.4) months. Data were analyzed from December 2019 to February 2020. EXPOSURES Sequential nivolumab was given on day 1 of a 14-day cycle. Response was assessed every 4 cycles using Response Evaluation Criteria in Solid Tumors version 1.1. MAIN OUTCOMES AND MEASURES Overall response rate (ORR) according to the PD-L1 copy number status. Additional end points were progression-free survival, overall survival, and PD-L1 tumor proportion score (TPS) assessed by immunohistochemistry based on PD-L1 copy number status. RESULTS A total of 6 of the 200 patients were excluded because of poor-quality tumor specimens for the biomarker study, resulting in 194 assessable patients. Of these, 155 (79.9%) were men, with a median (range) age of 69 (43-83) years. PD-L1 CNGs were identified in 32 patients (16.5%), including 5 (2.6%) with amplification and 27 (13.9%) with polysomy. The ORR among patients with and without PD-L1 CNGs was 28.1% (95% CI, 13.7%-46.7%) and 17.9% (95% CI, 12.3%-24.7%), respectively. Although patients with PD-L1 polysomy did not demonstrate improved ORR (18.5% [95% CI, 6.3%-38.1%]) compared with those without PD-L1 CNGs, 4 of 5 patients (80.0% [95% CI, 28.4%-99.5%]) with PD-L1 amplification showed response, among whom median duration of response was not reached. Patients with PD-L1 amplification showed excellent survival outcomes for progression-free and overall survival. Overall, 3 PD-L1-amplified tumors (60.0%) showed PD-L1 TPS of at least 80%, but 2 (40.0%) had PD-L1 TPS of 15% or less. (continued) Key Points Question Is the copy number status of the programmed death ligand 1 (PD-L1) gene in non-small cell lung cancer associated with response to nivolumab monotherapy? Findings In this cohort study of 194 patients with non-small cell lung cancer who were treated with nivolumab monotherapy, the proportion of patients with PD-L1 amplification who achieved response was 80.0% vs 18.5% among those with PD-L1 polysomy and 17.9% among those with PD-L1 disomy. Responses among patients with PD-L1 amplification were long lasting, leading to excellent progression-free and overall survival outcomes. Meaning The findings of this study suggest that PD-L1 amplification in non-small cell lung cancer is associated with durable benefit from nivolumab trea...

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Mutational Landscape and Sensitivity to Immune Checkpoint Blockers

Cited by 183 publications

References 105 publications

Trial watch: Immunogenic cell death induction by anticancer chemotherapeutics

Trial watch: Immunogenic cell death induction by anticancer chemotherapeutics

Preclinical efficacy of immune-checkpoint monotherapy does not recapitulate corresponding biomarkers-based clinical predictions in glioblastoma

Evaluation of Programmed Death Ligand 1 (PD-L1) Gene Amplification and Response to Nivolumab Monotherapy in Non–small Cell Lung Cancer

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