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      Tumor mutational burden is associated with poor outcomes in diffuse glioma

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          Abstract

          Background

          Tumor mutational burden (TMB) is a potential biomarker for immune checkpoint therapy and prognosis. The impact of TMB on clinical outcomes and the correlation coefficient between exome sequencing and targeted sequencing in glioma have not yet been explored.

          Methods

          Somatic mutations in the coding regions of 897 primary gliomas and the clinical and RNA-seq data of 654 patients in The Cancer Genome Atlas (TCGA) database were analyzed as a training set, while another 286 patients in the Chinese Glioma Genome Atlas (CGGA) database were used for validation. Descriptive and correlational analyses were conducted with TMB. Enrichment map analysis and gene set enrichment analysis (GSEA) were also performed.

          Results

          TMB was higher for the group of mutant genes that are frequently mutated in glioblastomas (GBMs) and lower for the group of mutant genes that are frequently mutated in lower-grade gliomas (LGGs). Patients with a higher TMB exhibited shorter overall survival. TMB was associated with grade, age, subtype and mutations affecting genomic structure. Moreover, univariate and multivariate analyses showed that TMB was an independent prognostic factor for glioma. The signaling pathways of the cell cycle were enriched in the TMB High group. TMB was higher in the mismatch repair (MMR) gene mutant group than in the wild-type group, but the MMR pathway was enriched in the TMB High group of gliomas without mutations in classical MMR genes. The correlation between TMBs calculated through exome sequencing and targeted sequencing was moderate, and panel-based TMB was not correlated with prognosis.

          Conclusions

          TMB is associated with poor outcomes in diffuse glioma. The high proliferative activity in the TMB High group could account for the shorter survival of these patients. This association was not reflected by a pan-cancer targeted sequencing panel.

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          Most cited references8

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          Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal.

          The cBioPortal for Cancer Genomics (http://cbioportal.org) provides a Web resource for exploring, visualizing, and analyzing multidimensional cancer genomics data. The portal reduces molecular profiling data from cancer tissues and cell lines into readily understandable genetic, epigenetic, gene expression, and proteomic events. The query interface combined with customized data storage enables researchers to interactively explore genetic alterations across samples, genes, and pathways and, when available in the underlying data, to link these to clinical outcomes. The portal provides graphical summaries of gene-level data from multiple platforms, network visualization and analysis, survival analysis, patient-centric queries, and software programmatic access. The intuitive Web interface of the portal makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries. Here, we provide a practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics.
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            GlioVis data portal for visualization and analysis of brain tumor expression datasets

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              Mutational burden, immune checkpoint expression, and mismatch repair in glioma: implications for immune checkpoint immunotherapy

              Background. Despite a multiplicity of clinical trials testing immune checkpoint inhibitors, the frequency of expression of potential predictive biomarkers is unknown in glioma. Methods. In this study, we profiled the frequency of shared biomarker phenotypes. To clarify the relationships among tumor mutational load (TML), mismatch repair (MMR), and immune checkpoint expression, we profiled patients with glioma ( n = 327), including glioblastoma (GBM) ( n = 198), whose samples had been submitted for analysis from 2009 to 2016. The calculation algorithm for TML included nonsynonymous mutation counts per tumor, with germline mutations filtered out. Immunohistochemical analysis and next-generation sequencing were used to determine tumor-infiltrating lymphocyte expression positive for programmed cell death protein 1 (PD-1), PD ligand 1 (PD-L1) expression on tumor cells, MMR ( MLH1 , MSH2 , MSH6 , and PMS2 ) protein expression and mutations, and DNA polymerase epsilon ( POLE ) mutations. Results. High TML was only found in 3.5% of GBM patients (7 of 198) and was associated with the absence of protein expression of mutL homolog 1 (MLH1) ( P = . 0345), mutS homolog 2 (MSH2) ( P = . 0099), MSH6 ( P = . 0022), and postmeiotic segregation increased 2 (PMS2) ( P = . 0345) and the presence of DNA MMR mutations. High and moderate TML GBMs did not have an enriched influx of CD8+ T cells, PD-1+ T cells, or tumor-expressed PD-L1. IDH1 mutant gliomas were not enriched for high TML, PD-1+ T cells, or PD-L1 expression. Conclusions. To clarify the relationships among TML, MMR, and immune checkpoint expression, we profiled the frequency of shared biomarker phenotypes. On the basis of a variety of potential biomarkers of response to immune checkpoints, only small subsets of glioma patients are likely to benefit from monotherapy immune checkpoint inhibition.
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                Author and article information

                Contributors
                lty3169@163.com
                Journal
                BMC Cancer
                BMC Cancer
                BMC Cancer
                BioMed Central (London )
                1471-2407
                12 March 2020
                12 March 2020
                2020
                : 20
                : 213
                Affiliations
                [1 ]GRID grid.419897.a, ISNI 0000 0004 0369 313X, Institute of Pathology and Southwest Cancer Center, Southwest Hospital, , Third Military Medical University (Army Medical University) and Key Laboratory of Tumor Immunopathology, Ministry of Education of China, ; Chongqing, 400038 China
                [2 ]GRID grid.410570.7, ISNI 0000 0004 1760 6682, Bio-Bank of Southwest Hospital, , Third Military Medical University (Army Medical University), ; Chongqing, 400038 China
                Article
                6658
                10.1186/s12885-020-6658-1
                7069200
                32164609
                0f789dd6-2055-430c-aa85-b59c88f3ea67
                © The Author(s). 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 15 July 2019
                : 20 February 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 81602196,81874087
                Award Recipient :
                Funded by: National Key R&D Program of China
                Award ID: 2016YFA0101200, 2016YFC1201801
                Award Recipient :
                Funded by: Chongqing Basic Research Project
                Award ID: cstc2016jcyjA2194
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2020

                Oncology & Radiotherapy
                tmb,glioma,prognosis,pan-cancer targeted sequencing
                Oncology & Radiotherapy
                tmb, glioma, prognosis, pan-cancer targeted sequencing

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