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      Intrinsic features of the cancer cell as drivers of immune checkpoint blockade response and refractoriness

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          Abstract

          Immune checkpoint blockade represents the latest revolution in cancer treatment by substantially increasing patients’ lifetime and quality of life in multiple neoplastic pathologies. However, this new avenue of cancer management appeared extremely beneficial in a minority of cancer types and the sub-population of patients that would benefit from such therapies remain difficult to predict. In this review of the literature, we have summarized important knowledge linking cancer cell characteristics with the response to immunotherapy. Mostly focused on lung cancer, our objective was to illustrate how cancer cell diversity inside a well-defined pathology might explain sensitivity and refractoriness to immunotherapies. We first discuss how genomic instability, epigenetics and innate immune signaling could explain differences in the response to immune checkpoint blockers. Then, in a second part we detailed important notions suggesting that altered cancer cell metabolism, specific oncogenic signaling, tumor suppressor loss as well as tight control of the cGAS/STING pathway in the cancer cells can be associated with resistance to immune checkpoint blockade. At the end, we discussed recent evidences that could suggest that immune checkpoint blockade as first line therapy might shape the cancer cell clones diversity and give rise to the appearance of novel resistance mechanisms.

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          Most cited references165

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          The Immune Landscape of Cancer

          We performed an extensive immunogenomic analysis of more than 10,000 tumors comprising 33 diverse cancer types by utilizing data compiled by TCGA. Across cancer types, we identified six immune subtypes-wound healing, IFN-γ dominant, inflammatory, lymphocyte depleted, immunologically quiet, and TGF-β dominant-characterized by differences in macrophage or lymphocyte signatures, Th1:Th2 cell ratio, extent of intratumoral heterogeneity, aneuploidy, extent of neoantigen load, overall cell proliferation, expression of immunomodulatory genes, and prognosis. Specific driver mutations correlated with lower (CTNNB1, NRAS, or IDH1) or higher (BRAF, TP53, or CASP8) leukocyte levels across all cancers. Multiple control modalities of the intracellular and extracellular networks (transcription, microRNAs, copy number, and epigenetic processes) were involved in tumor-immune cell interactions, both across and within immune subtypes. Our immunogenomics pipeline to characterize these heterogeneous tumors and the resulting data are intended to serve as a resource for future targeted studies to further advance the field.
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            Pembrolizumab plus Chemotherapy in Metastatic Non–Small-Cell Lung Cancer

            First-line therapy for advanced non-small-cell lung cancer (NSCLC) that lacks targetable mutations is platinum-based chemotherapy. Among patients with a tumor proportion score for programmed death ligand 1 (PD-L1) of 50% or greater, pembrolizumab has replaced cytotoxic chemotherapy as the first-line treatment of choice. The addition of pembrolizumab to chemotherapy resulted in significantly higher rates of response and longer progression-free survival than chemotherapy alone in a phase 2 trial.
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              Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer.

              Immune checkpoint inhibitors, which unleash a patient's own T cells to kill tumors, are revolutionizing cancer treatment. To unravel the genomic determinants of response to this therapy, we used whole-exome sequencing of non-small cell lung cancers treated with pembrolizumab, an antibody targeting programmed cell death-1 (PD-1). In two independent cohorts, higher nonsynonymous mutation burden in tumors was associated with improved objective response, durable clinical benefit, and progression-free survival. Efficacy also correlated with the molecular smoking signature, higher neoantigen burden, and DNA repair pathway mutations; each factor was also associated with mutation burden. In one responder, neoantigen-specific CD8+ T cell responses paralleled tumor regression, suggesting that anti-PD-1 therapy enhances neoantigen-specific T cell reactivity. Our results suggest that the genomic landscape of lung cancers shapes response to anti-PD-1 therapy. Copyright © 2015, American Association for the Advancement of Science.
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                Author and article information

                Contributors
                Journal
                Front Immunol
                Front Immunol
                Front. Immunol.
                Frontiers in Immunology
                Frontiers Media S.A.
                1664-3224
                26 April 2023
                2023
                : 14
                : 1170321
                Affiliations
                [1] Institut de Recherche en Cancérologie de Montpellier (IRCM), Inserm U1194, Univ Montpellier, Institut du Cancer de Montpellier (ICM) , Montpellier, France
                Author notes

                Edited by: Andrey Zamyatnin, I.M. Sechenov First Moscow State Medical University, Russia

                Reviewed by: Rodabe N. Amaria, University of Texas MD Anderson Cancer Center, United States; Ming Yi, Zhejiang University, China

                *Correspondence: Julien Faget, julien.faget@ 123456inserm.fr

                This article was submitted to Cancer Immunity and Immunotherapy, a section of the journal Frontiers in Immunology

                Article
                10.3389/fimmu.2023.1170321
                10169604
                37180110
                c50eef6b-54b6-4ee3-9f76-786a41c0a0e5
                Copyright © 2023 Ursino, Mouric, Gros, Bonnefoy and Faget

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 20 February 2023
                : 11 April 2023
                Page count
                Figures: 2, Tables: 1, Equations: 0, References: 165, Pages: 17, Words: 8584
                Funding
                Funded by: Association pour la Recherche sur le Cancer , doi 10.13039/100007391;
                Funded by: Agence Nationale de la Recherche , doi 10.13039/501100001665;
                Funded by: Ligue Contre le Cancer , doi 10.13039/501100004099;
                Funded by: Labex , doi 10.13039/501100004100;
                Funded by: Bristol-Myers Squibb Foundation , doi 10.13039/100001009;
                This work was supported by the ligue nationale contre le cancer in the context of the ARN-therpeutiques call for proposal (grant number ATFHJ23534), the Association pour la recherche contre le cancer (ARC) (grant number PJA2019209423) and the BMS foundation (grant number R20024FF). The National Research Agnecy (ANR) also founded this research work in the context of its support to the project ANR-22-CE17-0004-01. All these supports were allowed to Julien Faget. The Labex Mabimprove supports Chiara Urcino’s salary.
                Categories
                Immunology
                Review

                Immunology
                immune checkpoint,plasticicity,immunogenicitiy,adjuvanticity,tumor micro environment (tme)

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