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      Development of tumor mutation burden as an immunotherapy biomarker: utility for the oncology clinic

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          Abstract

          Background

          Treatment with immune checkpoint blockade (ICB) with agents such as anti-programmed cell death protein 1 (PD-1), anti-programmed death-ligand 1 (PD-L1), and/or anti-cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) can result in impressive response rates and durable disease remission but only in a subset of patients with cancer. Expression of PD-L1 has demonstrated utility in selecting patients for response to ICB and has proven to be an important biomarker for patient selection. Tumor mutation burden (TMB) is emerging as a potential biomarker. However, refinement of interpretation and contextualization is required.

          Materials and methods

          In this review, we outline the evolution of TMB as a biomarker in oncology, delineate how TMB can be applied in the clinic, discuss current limitations as a diagnostic test, and highlight mechanistic insights unveiled by the study of TMB. We review available data to date studying TMB as a biomarker for response to ICB by tumor type, focusing on studies proposing a threshold for TMB as a predictive biomarker for ICB activity.

          Results

          High TMB consistently selects for benefit with ICB therapy. In lung, bladder and head and neck cancers, the current predictive TMB thresholds proposed approximate 200 non-synonymous somatic mutations by whole exome sequencing (WES). PD-L1 expression influences response to ICB in high TMB tumors with single agent PD-(L)1 antibodies; however, response may not be dependent on PD-L1 expression in the setting of anti-CTLA4 or anti-PD-1/CTLA-4 combination therapy. Disease-specific TMB thresholds for effective prediction of response in various other malignancies are not well established.

          Conclusions

          TMB, in concert with PD-L1 expression, has been demonstrated to be a useful biomarker for ICB selection across some cancer types; however, further prospective validation studies are required. TMB determination by selected targeted panels has been correlated with WES. Calibration and harmonization will be required for optimal utility and alignment across all platforms currently used internationally. Key challenges will need to be addressed before broader use in different tumor types.

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          Most cited references112

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          The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.

          Next-generation DNA sequencing (NGS) projects, such as the 1000 Genomes Project, are already revolutionizing our understanding of genetic variation among individuals. However, the massive data sets generated by NGS--the 1000 Genome pilot alone includes nearly five terabases--make writing feature-rich, efficient, and robust analysis tools difficult for even computationally sophisticated individuals. Indeed, many professionals are limited in the scope and the ease with which they can answer scientific questions by the complexity of accessing and manipulating the data produced by these machines. Here, we discuss our Genome Analysis Toolkit (GATK), a structured programming framework designed to ease the development of efficient and robust analysis tools for next-generation DNA sequencers using the functional programming philosophy of MapReduce. The GATK provides a small but rich set of data access patterns that encompass the majority of analysis tool needs. Separating specific analysis calculations from common data management infrastructure enables us to optimize the GATK framework for correctness, stability, and CPU and memory efficiency and to enable distributed and shared memory parallelization. We highlight the capabilities of the GATK by describing the implementation and application of robust, scale-tolerant tools like coverage calculators and single nucleotide polymorphism (SNP) calling. We conclude that the GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.
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            The blockade of immune checkpoints in cancer immunotherapy.

            Among the most promising approaches to activating therapeutic antitumour immunity is the blockade of immune checkpoints. Immune checkpoints refer to a plethora of inhibitory pathways hardwired into the immune system that are crucial for maintaining self-tolerance and modulating the duration and amplitude of physiological immune responses in peripheral tissues in order to minimize collateral tissue damage. It is now clear that tumours co-opt certain immune-checkpoint pathways as a major mechanism of immune resistance, particularly against T cells that are specific for tumour antigens. Because many of the immune checkpoints are initiated by ligand-receptor interactions, they can be readily blocked by antibodies or modulated by recombinant forms of ligands or receptors. Cytotoxic T-lymphocyte-associated antigen 4 (CTLA4) antibodies were the first of this class of immunotherapeutics to achieve US Food and Drug Administration (FDA) approval. Preliminary clinical findings with blockers of additional immune-checkpoint proteins, such as programmed cell death protein 1 (PD1), indicate broad and diverse opportunities to enhance antitumour immunity with the potential to produce durable clinical responses.
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              Pembrolizumab versus Chemotherapy for PD-L1–Positive Non–Small-Cell Lung Cancer

              Pembrolizumab is a humanized monoclonal antibody against programmed death 1 (PD-1) that has antitumor activity in advanced non-small-cell lung cancer (NSCLC), with increased activity in tumors that express programmed death ligand 1 (PD-L1).
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                Author and article information

                Journal
                Ann Oncol
                Ann. Oncol
                annonc
                Annals of Oncology
                Oxford University Press
                0923-7534
                1569-8041
                January 2019
                05 November 2018
                05 November 2018
                : 30
                : 1 , Tumor mutation burden as an immunotherapy biomarker
                : 44-56
                Affiliations
                [1 ]Human Oncology and Pathogenesis Program
                [2 ]The Immunogenomics and Precision Oncology Program, Memorial Sloan Kettering Cancer Center, New York
                [3 ]Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, USA
                [4 ]Translational Cancer Therapeutics Laboratory, Francis Crick Institute, London
                [5 ]Cancer Immunology Unit, Research Department of Haematology, University College London Cancer Institute, London, UK
                [6 ]Institute of Pathology, University Hospital Heidelberg, Heidelberg
                [7 ]Germany and German Cancer Consortium (DKTK), Heidelberg Partner Site, Heidelberg, Germany
                [8 ]Department of Oncology, Centre Hospitalier Universitaire Vaudois (CHUV), Lausanne, Switzerland
                Author notes
                Correspondence to: Dr Timothy A. Chan, 1275 York Avenue, Memorial Sloan Kettering Cancer Center, NY 10065, USA. Tel: 646-888-2765; E-mail: chant@ 123456mskcc.org
                Prof. Solange Peters, Centre Hospitalier Universitaire Vaudois (CHUV), 1011 Lausanne, Switzerland. Tel: +41795560192; E-mail: solange.peters@ 123456chuv.ch
                Author information
                http://orcid.org/0000-0002-0412-7143
                Article
                mdy495
                10.1093/annonc/mdy495
                6336005
                30395155
                e3878dc7-a3cd-4cdf-9219-2d4298a57671
                © The Author(s) 2018. Published by Oxford University Press on behalf of the European Society for Medical Oncology.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                Page count
                Pages: 13
                Funding
                Funded by: NIH 10.13039/100000002
                Funded by: NCI Cancer Center Support
                Award ID: P30 CA008748
                Funded by: NIH 10.13039/100000002
                Award ID: R35 CA232097
                Funded by: Mellnikoff Precision Immunotherapy Kidney Cancer Fund
                Funded by: Exelixis, Merck, and Bristol-Myers Squibb
                Categories
                Reviews

                Oncology & Radiotherapy
                mutation,immunotherapy,immune checkpoint,cancer
                Oncology & Radiotherapy
                mutation, immunotherapy, immune checkpoint, cancer

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