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The study addresses the need to identify specific gene mutation(s) and map the exomic mutational landscape in Indian TNBC patients to support discovery of actionable therapeutic target(s). Whole-exome sequencing was performed on 15 TNBC cases plus 5 adjacent normal control tissues, followed by alignment, mutation calling, and signature and pathway analyses.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/whole-exome-sequencing-for-identification-of-specific-gene-mutations-in-an-indian-cohort-of-triple-negative-breast-cancer-patients/450361/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/whole-exome-sequencing-for-identification-of-specific-gene-mutations-in-an-indian-cohort-of-triple-negative-breast-cancer-patients/450361.png","ImageObject",300,407,{"name":92,"@type":93},"Rhys","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-05","2026-09-30",true,{"@type":102,"interactionType":103,"userInteractionCount":8},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What was the main goal of this study?","Question",{"text":112,"@type":113},"To identify specific gene mutations and characterize the exomic mutational landscape in an Indian cohort of triple-negative breast cancer patients, supporting discovery of potential therapeutic targets.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How were samples and sequencing performed?",{"text":117,"@type":113},"Whole-exome sequencing was conducted on 15 TNBC patients and 5 adjacent normal control tissue specimens. Sequencing data were aligned to the hg19 reference genome, and mutations were called using standard bioinformatics tools.",{"name":119,"@type":110,"acceptedAnswer":120},"Which recurrent somatic mutations were most significant in the TNBC genomes?",{"text":121,"@type":113},"MutSig2CV identified recurrent somatic mutations including CTNNB1 (47%), TP53 (33%), SLC7A8 (27%), AMOT (20%), CLEC11A (20%), and ECHDC1 (13%) with a q value of ≤ 0.1.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},450361,1791177889,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":8,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":36},687207024643,"https://ap-avatar.wpscdn.com/davatar_3d24733baf745e90a7e4bdd5f77d97b2","Preeti et al. Discover Oncology (2026) 17:20 [https://doi.org/10.1007/s12672-025-03921-1](https://doi.org/10.1007/s12672-025-03921-1)  \nDiscover Oncology  \nRESEARCH Open Access  \nWhole-exome sequencing for identification  of specific gene mutations in an Indian cohort of triple-negative breast cancer patients  \nP. Preeti 1†, Ankan Mukherjee Das2†, Prabhat Kumar3, Ajay Gogia4, Lalit Kumar5, S. V. S. Deo6, Sandeep Mathur7, Rajiv Janardhanan8*, Kamal Rawal 1, Manoj Garg3 and Bhudev C. Das3*  \n†P. Preeti and Ankan Mukherjee Das have equal 1st authorship.  \n*Correspondence:  \nRajiv Janardhanan [rajivj@srmist.edu.in](rajivj@srmist.edu.in)  \nBhudev C. Das [bcdas48@hotmail.com](bcdas48@hotmail.com); bcdas@ [amity.edu](amity.edu)  \n1Amity Institute of Biotechnology, Amity University Uttar Pradesh, Sector-125, Noida 201301, India 2Laboratory of Disease Dynamicsand Molecular Epidemiology, Amity Institute of Public Health, Amity University Uttar Pradesh, Sector-125, Noida 201313, India 3Amity Institute of Molecular Medicine and Stem Cell Research, Amity University Uttar Pradesh, Sector-125, Noida 201313, India 4Department of Medical Oncology, All India Institute of Medical Sciences, Institute Rotary Cancer Hospital, New Delhi, India 5Artemis Cancer Centre, Artemis Hospitals, Gurugram, Haryana, India 6Department of Surgical Oncology, All India Institute of Medical Sciences, Institute Rotary Cancer Hospital, New Delhi, India 7Department of Pathology, All India Institute of Medical Sciences, New Delhi, India  \n8Faculty of Medical and Health Sciences, SRM Institute of Science and Technology, Kattankulathur, Chennai, Tamil Nadu, India  \nAbstract  \nBackground/Objectives Triple-negative breast cancers (TNBCs) are the  \nmost aggressive, heterogeneous subtype of breast carcinoma with increased chemoradioresistance and a high rate of relapse. A compelling need exists to discover specific gene mutation(s) and the exomic mutational landscape associated with Indian TNBC patients to identify potential therapeutic target(s) for effective treatment ofTNBC. Methods Whole-exome sequencing (WES) was performed on 15 TNBC patients along with 5 random adjacent normal control tissue (ANCT) specimens. WES data alignment and mapping to the reference human genome (hg19) were done using BWA, SAMtools, and Picard tools. The data analysis and mutation calling were performed using the Genome Analysis Toolkit. The Signal Analyze and PANTHER pathways tools were utilized for mutational signature(s) and pathway(s) analysis, respectively.  \nResults Our data revealed that the TNBC genomes carried an average of ~ 106 mutations per sample. MutSig2CV analysis showed the most significant recurrent somatic mutations in CTNNB1 (47%; 7/15), TP53 (33%; 5/15), SLC7A8 (27%; 4/15), AMOT (20%; 3/15), CLEC11A (20%; 3/15), and ECHDC1 (13%; 2/15) with a q value of ≤ 0.1. We also observed somatic recurrent mutations in other important cancer-associated genes such as ABCC3, BRCA1, BRCA2, BIRC6, CDH7, CSMD3, MUC12, MUC16, NT5C1B, PIK3CA, POLE, STK31, TTN, and ZFHX4 . Moreover, we have noticed germline mutations in TP53, BIN1, MLH1, PIK3CA, and GPSM2 . Interestingly, the TNBC genomes exhibited a predominance of signature 1, which is associated with spontaneous deamination of 5-methylcytosine; signature 3 represented the failure of DNA double-strand break repair by homologous recombination; and signature 5 correlated with transcriptional strand bias. Interestingly, the high tumor mutational burden was observed specifically inTNBC patients with signature 3. Furthermore, these mutations were involved in several major signaling pathways, including the Wnt, p53, PDGF, cadherin, DNA replication, integrin, and apoptosis signaling pathways.  \nConclusions Together, the findings indicated that the crucial role played by these key genetic mutations could be utilized in screening and developing potential targeted therapeutics forTNBC patients.  \n© The Author(s) 2025. Open Access This article is licensed ","cbCaicrTDyQHEvpI","https://ap.wps.com/l/cbCaicrTDyQHEvpI","pdf",1723272,16,"English","# Abstract\n## Background/Objectives\n## Methods\n## Results\n## Conclusions\n# Introduction\n## Background on breast cancer and TNBC","[{\"question\":\"What was the main goal of this study?\",\"answer\":\"To identify specific gene mutations and characterize the exomic mutational landscape in an Indian cohort of triple-negative breast cancer patients, supporting discovery of potential therapeutic targets.\"},{\"question\":\"How were samples and sequencing performed?\",\"answer\":\"Whole-exome sequencing was conducted on 15 TNBC patients and 5 adjacent normal control tissue specimens. Sequencing data were aligned to the hg19 reference genome, and mutations were called using standard bioinformatics tools.\"},{\"question\":\"Which recurrent somatic mutations were most significant in the TNBC genomes?\",\"answer\":\"MutSig2CV identified recurrent somatic mutations including CTNNB1 (47%), TP53 (33%), SLC7A8 (27%), AMOT (20%), CLEC11A (20%), and ECHDC1 (13%) with a q value of ≤ 0.1.\"}]","Whole-exome sequencing for identification of specific gene mutations in an Indian cohort of triple-negative breast cancer patients | PDF",1790732969]