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      Insights into treatment-specific prognostic somatic mutations in NSCLC from the AACR NSCLC GENIE BPC cohort analysis

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          Abstract

          Background

          Treatment of non-small lung cancer (NSCLC) has evolved in recent years, benefiting from advances in immunotherapy and targeted therapy. However, limited biomarkers exist to assist clinicians and patients in selecting the most effective, personalized treatment strategies. Targeted next-generation sequencing–based genomic profiling has become routine in cancer treatment and generated crucial clinicogenomic data over the last decade. This has made the development of mutational biomarkers for drug response possible.

          Methods

          To investigate the association between a patient’s responses to a specific somatic mutation treatment, we analyzed the NSCLC GENIE BPC cohort, which includes 2,004 tumor samples from 1,846 patients.

          Results

          We identified somatic mutation signatures associated with response to immunotherapy and chemotherapy, including carboplatin-, cisplatin-, pemetrexed- or docetaxel-based chemotherapy. The prediction power of the chemotherapy-associated signature was significantly affected by epidermal growth factor receptor ( EGFR) mutation status. Therefore, we developed an EGFR wild-type–specific mutation signature for chemotherapy selection.

          Conclusion

          Our treatment-specific gene signatures will assist clinicians and patients in selecting from multiple treatment options.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12890-024-03124-4.

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          Most cited references44

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          Maftools: efficient and comprehensive analysis of somatic variants in cancer

          Numerous large-scale genomic studies of matched tumor-normal samples have established the somatic landscapes of most cancer types. However, the downstream analysis of data from somatic mutations entails a number of computational and statistical approaches, requiring usage of independent software and numerous tools. Here, we describe an R Bioconductor package, Maftools, which offers a multitude of analysis and visualization modules that are commonly used in cancer genomic studies, including driver gene identification, pathway, signature, enrichment, and association analyses. Maftools only requires somatic variants in Mutation Annotation Format (MAF) and is independent of larger alignment files. With the implementation of well-established statistical and computational methods, Maftools facilitates data-driven research and comparative analysis to discover novel results from publicly available data sets. In the present study, using three of the well-annotated cohorts from The Cancer Genome Atlas (TCGA), we describe the application of Maftools to reproduce known results. More importantly, we show that Maftools can also be used to uncover novel findings through integrative analysis.
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            AACR Project GENIE: Powering Precision Medicine through an International Consortium

            (2017)
            The AACR Project GENIE is an international data-sharing consortium focused on generating an evidence base for precision cancer medicine by integrating clinical-grade cancer genomic data with clinical outcome data for tens of thousands of cancer patients treated at multiple institutions worldwide. In conjunction with the first public data release from approximately 19,000 samples, we describe the goals, structure, and data standards of the consortium and report conclusions from high-level analysis of the initial phase of genomic data. We also provide examples of the clinical utility of GENIE data, such as an estimate of clinical actionability across multiple cancer types (>30%) and prediction of accrual rates to the NCI-MATCH trial that accurately reflect recently reported actual match rates. The GENIE database is expected to grow to >100,000 samples within 5 years and should serve as a powerful tool for precision cancer medicine.Significance: The AACR Project GENIE aims to catalyze sharing of integrated genomic and clinical datasets across multiple institutions worldwide, and thereby enable precision cancer medicine research, including the identification of novel therapeutic targets, design of biomarker-driven clinical trials, and identification of genomic determinants of response to therapy. Cancer Discov; 7(8); 818-31. ©2017 AACR.See related commentary by Litchfield et al., p. 796This article is highlighted in the In This Issue feature, p. 783.
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              ARID1A deficiency promotes mutability and potentiates therapeutic antitumor immunity unleashed by immune checkpoint blockade

              ARID1A (the AT-rich interaction domain 1A, also known as BAF250a) is one of the most commonly mutated genes in cancer1,2. The majority of ARID1A mutations are inactivating mutations and lead to loss of ARID1A expression 3 , which makes ARID1A a poor therapeutic target. Therefore, it is of clinical importance to identify molecular consequences of ARID1A deficiency that create therapeutic vulnerabilities in ARID1A-mutant tumors. In a proteomic screen, we found that ARID1A interacts with mismatch repair (MMR) protein MSH2. ARID1A recruited MSH2 to chromatin during DNA replication and promoted MMR. Conversely, ARID1A inactivation compromised MMR and increased mutagenesis. ARID1A deficiency correlated with microsatellite instability genomic signature and a predominant C>T mutation pattern and increased mutation load across multiple human cancer types. Tumors formed by an ARID1A-deficient ovarian cancer cell line in syngeneic mice displayed increased mutation load, elevated numbers of tumor-infiltrating lymphocytes, and PD-L1 expression. Notably, treatment with anti-PD-L1 antibody reduced tumor burden and prolonged survival of mice bearing ARID1A-deficient but not ARID1A-wild-type ovarian tumors. Together, these results suggest ARID1A deficiency contributes to impaired MMR and mutator phenotype in cancer, and may cooperate with immune checkpoint blockade therapy.
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                Author and article information

                Contributors
                doctorwangzhifei@163.com
                Journal
                BMC Pulm Med
                BMC Pulm Med
                BMC Pulmonary Medicine
                BioMed Central (London )
                1471-2466
                2 July 2024
                2 July 2024
                2024
                : 24
                : 309
                Affiliations
                [1 ]Department of Neurosurgery, the Third XiangYa Hospital of Central South University, ( https://ror.org/05akvb491) Changsha, 410013 PR China
                [2 ]Department of Nanoscience, The Joint School of Nanoscience and Nanoengineering, University of North Carolina Greensboro, ( https://ror.org/04fnxsj42) Greensboro, NC 27401 USA
                Article
                3124
                10.1186/s12890-024-03124-4
                11218090
                38956553
                c80cb8d9-b27b-4b34-8e78-0910b9cb9358
                © The Author(s) 2024

                Open Access This 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 March 2024
                : 23 June 2024
                Funding
                Funded by: Changsha Municipal Natural Science Foundation
                Award ID: kq2202431
                Award Recipient :
                Funded by: Hunan Provincial Natural Science Foundation of China
                Award ID: 2022JJ30904
                Award Recipient :
                Categories
                Research
                Custom metadata
                © BioMed Central Ltd., part of Springer Nature 2024

                Respiratory medicine
                clinocogenomic,nsclc,treatment response,mutational signature,genie
                Respiratory medicine
                clinocogenomic, nsclc, treatment response, mutational signature, genie

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