---
title: "Genetic Diagnosis in Triple-Negative Breast Cancer via Exome-Based Testing"
id: "plos-one-13-exome-based-cancer-driver-gene-comprehensive-testing-can-provide-a-genetic"
canonical_url: "https://medichelpline.com/clinical-feed/plos-one-13-exome-based-cancer-driver-gene-comprehensive-testing-can-provide-a-genetic"
content_type: "clinical_feed_article"
specialty: "Oncology"
source_name: "PLOS ONE (Medicine)"
source_url: "https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356762"
published_at: "2026-08-24T14:00:00.000Z"
evidence_level: "Journal Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# Genetic Diagnosis in Triple-Negative Breast Cancer via Exome-Based Testing
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/plos-one-13-exome-based-cancer-driver-gene-comprehensive-testing-can-provide-a-genetic
- **Specialty:** [Oncology](https://medichelpline.com/clinical-feed/oncology.md)
- **Primary Source:** PLOS ONE (Medicine)
- **Source URL:** [Original Journal Publication](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0356762)
- **Published At:** 2026-08-24T14:00:00.000Z
- **Evidence Rating:** Journal Feed
## Executive GIST (TL;DR)
- **Triple-negative breast cancer (TNBC)** poses significant treatment challenges due to its aggressive nature and high recurrence rates. - Genetic diagnosis through **whole-exome sequencing (WES)** allows for precise treatments and recommendations for TNBC patients. - A study validated a **bioinformatics pipeline** to identify variants in cancer susceptibility genes in 24 TNBC patients. - The pipeline successfully identified **three pathogenic germline variants** in genes such as **ATM, RAD51D,** and **BRCA1.** - This approach enhances the understanding of hereditary cancer and can lead to better early intervention and treatment tailored to patients' genetic profiles.
## Clinical Analysis & Structured Key Points
Exome-based cancer driver gene comprehensive testing can provide a genetic diagnosis for individuals with triple-negative breast cancer | PLOS One Browse Subject Areas ? Click through the PLOS taxonomy to find articles in your field. For more information about PLOS Subject Areas, click here . Article Authors Metrics Comments Media Coverage Reader Comments Figures Figures Abstract Triple-negative breast cancer (TNBC) is characterized by aggressive behaviour, high tumor heterogeneity, and an increased likelihood of recurrence and early metastasis. These factors hinder successful treatment. Genetic diagnosis enables personalized clinical recommendations and treatment options. The objective of this study was to validate whole-exome sequencing (WES) and variant prioritization in cancer susceptibility genes (CSG) associated with hereditary cancer (HC) predisposition in TNBC patients (n = 24). We present the development of a reproducible bioinformatic pipeline and its technical validation in a validation cohort (n = 25). This cohort comprised individuals with diverse primary tumors who had a previously confirmed molecular diagnosis of a hereditary cancer syndrome, serving as gold-standard cases to assess the pipeline’s analytical accuracy. We consolidated a comprehensive panel of cancer genes and determined all variants in the TNBC discovery cohort (12.5% of patients), identifying three pathogenic germline variants (gPV) in ATM, RAD51D, and BRCA1 . These genes are involved in the molecular pathway of DNA repair by homologous recombination (HRD). Our results demonstrate that the developed bioinformatic pipeline provides reliable genetic diagnosis of cancer predisposition syndromes from exome data, applicable not only to TNBC patients but also to individuals with any cancer suspected of having a hereditary component. Citation: Alzate D, Sánchez AY, Pacheco Y, Isaza Ruget M, Sánchez R, Castillo C, et al. (2026) Exome-based cancer driver gene comprehensive testing can provide a genetic diagnosis for individuals with triple-negative breast cancer. PLoS One 21(8): e0356762. https://doi.org/10.1371/journal.pone.0356762 Editor: Klaus Brusgaard, Odense University Hospital, DENMARK Received: November 24, 2025; Accepted: August 7, 2026; Published: August 24, 2026 Copyright: © 2026 Alzate et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability: All relevant data are within the paper and its Supporting Information files. Funding: This work was supported by grants from the Colombian Ministry of Science, Technology, and Innovation (MinCiencias), Program 92191, Project 92268, Contract No. 800-2023, and by institutional funding from Fundación Salud de los Andes (Bogotá, Colombia). Additional support was provided by HERMES grants (Nos. 52457, 5607, 53654, and 6641), which fund the Personalized Cancer Medicine Program at the Universidad Nacional de Colombia School of Medicine. No additional external funding was received for this study. Competing interests: The authors have declared that no competing interests exist. Introduction Triple-negative breast cancer (TNBC) accounts for approximately 15% of all breast cancers and is generally very aggressive, with more frequent distant spread, high tumor heterogeneity, higher recurrence, and earlier metastasis, all of which hinder the success of new therapies [ 1 ]. TNBC often occurs in women under 40 years of age and has a mortality rate of 40% within the first 5 years after diagnosis, a median survival after metastasis of only 13.3 months, and a recurrence rate after surgery of 25% [ 2 ]. The predominant systemic therapy for most metastatic TNBC (mTNBC) is chemotherapy, but responses are often short-lived, and patients have a median overall survival of 12–18 months [ 3 ]. Hereditary cancer (HC) accounts for 5% to 10% of all cancers, although it may be underdiagnosed in less genetically studied populations [ 4 ]. Criteria for suspecting HC include the development of multiple primary tumors, clustering of affected family members with cancer, and/or early age at tumor onset [ 5 ]. Identifying variants in well-established cancer susceptibility genes (CSG) and in candidate genes that increase cancer risk is critical for understanding the pathophysiology and advancing the development of new precision therapies and early interventions. Therefore, it is urgent to conduct diagnostic testing actively to identify patients and family members who may carry a harmful variant associated with a hereditary cancer syndrome. This will help establish a personalized follow-up plan to detect cancer early, increasing the likelihood of successful treatment. Tests using smaller genetic panels have the drawback that the causal variant may be missed, especially when there is no clear phenotypic sign, which often occurs in individuals with different primary tumors. Conducting diagnoses based on the whole exome enables the identification of variants in well-established CSG, as well as in emerging candidate genes. This approach would enable the identification of pathogenic or likely pathogenic ( P/LP) causal variants and elucidate genotype-phenotype associations for other rare and less-studied genetic diseases [ 6 ]. In this study, we investigated germline genetic variants from the exome, focusing on a comprehensive and expanded panel of cancer genes that we consolidated (n = 813 genes). We validated a reproducible pipeline with a cohort of patients (n = 25) who had clinical and molecular diagnoses of HC (pipeline validation cohort), and we applied it to patients with TNBC (TNBC discovery cohort, n = 24). This tumor type was selected for its molecular heterogeneity, aggressive phenotype, and limited sensitivity of standard gene panels in detecting rare susceptibility variants, and as a proof of concept for the usefulness of whole-exome sequencing (WES) to overcome this limitation, particularly in underrepresented populations such as those of Latin American ancestry. Materials and methods Ethical approval and consent to participate All participants gave their informed consent, and the study was approved by the local ethics committee of the National University of Colombia (study number 2019–5738). Although in the present study the secondary findings report was not performed due to the approved protocol restrictions by the ethics committees, the technical and bioinformatics pipeline feasibility was demonstrated. This study was conducted in accordance with the ethical standards described in the Declaration of Helsinki. Study cohorts The first study cohort consists of 25 individuals with hereditary cancer syndromes who met clinical criteria and had a molecular diagnosis, i.e., a germline P/LP variant that explains the patients’ phenotype. A total of 25 cases meet these criteria and are hereafter referred to as the “pipeline validation cohort.” Our second group, called the “TNBC discovery cohort,” includes 24 patients with a confirmed pathological diagnosis of TNBC. Both groups underwent whole exome sequencing (WES) after signature and acceptance of written informed consent for research. Whole exome sequencing of germline DNA from blood Genomic DNA was extracted from peripheral blood, and the DNA sample was quantified by spectrophotometry (Nanodrop OneC) and fluorometry (Qubit 4) to normalize the DNA concentration across samples. Whole Exome Sequencing (WES) libraries were prepared using enrichment kits according to the manufacturer’s instructions ( Agilent SureSelect All Exon V6 for the TNBC discovery cohort and Illumina DNA Prep with Exome 2.5 Enrichment for the pipeline validation cohort ). Briefly, DNA was randomly fragmented into 180–280 bp fragments. The resulting fragments were end-repaired and ligated with Illumina molecular adapters. Adapter-containing fragments were amplified by PCR, size-selected, and purified. Hybridization capture of the libraries was performed using a buffer containing biotin-labelled probes, and streptavidin-coated magnetic beads were used to capture the gene exons. Subsequently, unhybridized fragments were washed away, and the probes were digested. The captured libraries were further enriched by PCR amplification. Libraries were analysed with Qubit and a fragment bioanalyzer to determine size distribution. They were then quantified, pooled, and sequenced on Illumina platforms using a 2x150 bp paired-end read strategy. Development of a pipeline for germline variant detection based on GATK best practices The study evaluates the feasibility and proof of concept for implementing an end-to-end bioinformatics pipeline. This workflow integrates the recommendations of GATK Best Practices [ 7 ] to establish a robust and reproducible pipeline for germline variant identification, covering everything from initial data quality assessment to variant annotation and prioritization. First, the quality assessment was performed with FastQC [ 8 ], which detects potential contamination or artifacts before proceeding with alignment. For sequence alignment, the cleaned data are mapped to the reference genome (hg38) using the Burrows-Wheeler Aligner BWA-MEM [ 9 ] software, and the output files are converted and sorted by chromosomal position (SAM/BAM) with Samtools (view, sort, index). GATK then performs critical steps for variant calling optimization, including duplicate marking ( MarkDuplicatesSpark) , alignment sorting ( SortSam) , base quality recalibration ( BaseRecalibrator, ApplyBQSR) , and finally, germline variant calling with HaplotypeCaller [ 10 ]. After separating SNPs and INDELs with SelectVariants, quality filters are applied using the VariantFiltration tool to obtain a set of reliable variants. The SNP and InDel filter parameters are shown below: SNP: QD 60.0, MQ 13.0, MappingQualityRankSum 200.0, ReadPosRankSum 20x and an allele frequency>15% were considered valid. In a complementary manner, alignment metrics ( CollectAlignmentSummaryMetrics) and library fragment size metrics ( CollectInsertSizeMetrics) are generated with GATK to evaluate the consistency of the process. The resulting variants are functionally annotated with Ensembl VEP [ 11 ] and the Franklin Genoox platform, incorporating information on the allele frequency of the variants, molecular effects, and clinical databases. *Databases used in variant annotation include: dbSNP, gnomAD (Exome), gnomAD (Genome), Sift, Polyphen2, Mut Taster, Mut Assessor, Fathmm, ClinVar, Gerp, Revel, SpliceAI, Vep, dbNSFP, dbscSNV. **Genomic variant classification criteria: The guidelines of the American College of Medical Genetics and Genomics (ACMG) [ 12 ] and the Association for Clinical Genomic Science (ACGS) [ 13 ] were followed. To ensure reproducibility, this workflow was implemented in a Docker container with specific versions of the aforementioned bioinformatics tools. Finally, we tested the bioinformatics pipeline using a validation set of independent samples previously sequenced and analysed, with platforms developed for a clinical diagnostic environment ( Euformatics Genomics Hub : https://www.euformatics.com , Emedgene : https://emg.emedgene.com , Franklin: https://franklin.genoox.com ), based on fastq files from patients for whom a germline variant previously identified, responsible for a hereditary cancer syndrome, had been previously identified. Then, we ran the raw data (fastq) from all these patients through the new germline pipeline, and 100% concordance was obtained in the results, confirming the variants previously identified with the pipeline and the clinical exome analysis platform. The concordance strictly refers to the ability of the bioinformatics pipeline to accurately detect and annotate the causal variants of the “gold standard” phenotype present in the pipeline validation cohort. These results confirm the robustness and reliability of this pipeline for germline variant identification in the context of precision genomic diagnosis. Code availability and hybrid Docker orchestration (high reproducibility): The exact versions of the bioinformatics tools, the complete source code, the command-line parameters, and the computational environments are available in the GitHub repository at https://github.com/GatoconBata-07/Germinal_Pipeline_GATK_BEST . Consolidation of an expanded and comprehensive panel of cancer susceptibility genes To prioritize germline variants with potential impact on cancer predisposition, genes were selected from a panel of cancer susceptibility genes (CSG) compiled from the literature [ 14 – 17 ], and from gene panels used in clinical diagnosis (Illumina TruSight Oncology, Pan-cancer panel CD Genomics). We selected the genes from the IntOGen database that were present in at least 1% of cancer patients. We also selected genes that were consensus in at least three sources in the OnkoKB database, and were cited as cancer drivers. We finally obtained a comprehensive and expanded panel of 813 genes ( pancancer panel ). Prioritization of germline variants After exome annotation, germline variants with a sequencing depth of ≥20 reads and an allelic frequency >15% were selected from the comprehensive panel.The following criteria were used for variant prioritization: i) variants predicted to cause loss of function (nonsense, frameshift, and canonical splice sites: + /-3 bp); ii) missense variants and in-frame indels; iii) synonymous variants. The terms were entered into the Franklin platform using the Human Phenotype Ontology (HPO) nomenclature: Tumor (HP:0002664), Carcinoma (HP:0030731), Breast cancer (HP:0003002). Finally, the prioritized variants were interpreted according to the American College of Medical Genetics and Genomics (ACMG) criteria [ 12 ]. Results The developed pipeline enables precise identification of causal variants in patients with various types of cancer Using complete exome data from cancer patients, we developed a pipeline ( Fig 1 ) to identify germline variants in accordance with the Broad Institute´s best practices ( GATK ), and we confirmed the results using a pipeline validation cohort comprising samples previously characterized by a pipeline used in clinical diagnostic practice. This validation set identified the causal P/LP variants for various hereditary cancers in 25 patients, including breast cancer, tuberous sclerosis, juvenile myelomonocytic leukemia, colorectal cancer, ovarian cancer, multiple osteochondromas, schwannomatosis, neurofibromatosis, familial adenomatous polyposis, and Li-Fraumeni syndrome. It revealed a spectrum of P/LP variants in the BRCA1, BRCA2, TSC2, MLH1, TP53, PALB2, KRAS, STK11, PMS2, EXT1, BAP1, NF1, and NF2 genes. Download: PNG larger image TIFF original image Fig 1. Bioinformatics pipeline for the identification of germline variants in cancer susceptibility genes. https://doi.org/10.1371/journal.pone.0356762.g001 Based on validation cohort results (n = 25 patients), summarized in S3 Table , we identified 25 causal variants associated with cancer in patients, of which 23 (92%) are classified as pathogenic and 2 (8%) are likely pathogenic. Truncating events that result in loss of function, dominated—frameshift 11/25 (44%) and nonsense 7/25 (28%)—followed by missense 5/25 (20%) and canonical splice site 2/25 (8%). Most pathogenic variants were found in genes involved in the homologous recombination DNA repair pathway (HDR): ( BRCA1/BRCA2/PALB2 (13/25: 52%), followed by genes involved in the mismatch repair pathway ( MLH1/PMS2 , 3/25: 12%). and pathogenic variants were less frequently identified in other cancer predisposition syndromes, such as Li-Fraumeni syndrome, Peutz-Jeghers syndrome, tuberous sclerosis, and neurofibromatosis ( TP53, STK11, TSC2, NF1/NF2, BAP1, EXT1, KRAS ) among others. This pattern—characterized by the inactivation of tumor suppressors and the prevalence of truncating variants in BRCA1/BRCA2/PALB2 —is consistent with population studies indicating that protein-truncating variants in these genes significantly increase cancer risk and form the core of susceptibility to hereditary breast and ovarian cancer [ 18 ]. Overall, the results of the pipeline developed for germline variant identification show an exact match in detecting P/LP variants previously identified by a clinical diagnostic bioinformatics platform. These findings have significant clinical implications, including genetic counselling and monitoring family members for early follow-up and intervention for carriers of the identified P/LP variants. The whole-exome approach enables the detection of germline variants in cancer-susceptibility genes in TNBC patients After achieving 100% concordance in the pipeline validation cohort, we sequenced the whole exome of TNBC patients (TNBC discovery cohort) and processed the data through the pipeline. We analyzed all germline variants in a panel of 813 cancer genes ( pancancer panel ) ( Fig 2 and S4 Table ). A total of 13,781 variants were identified in these patients within the panel, including 10,694 single-nucleotide variants (SNVs) and 3,087 insertions/deletions (InDels) ( S5 Table ). Among these variants, 11,072 are benign or probably benign, 2,702 are variants of uncertain clinical significance, and 7 are P/LP variants, with only 3 explaining the hereditary cancer phenotype in patients with TNBC. We reviewed all variants in the pancancer panel and established the functional consequences for all patients ( Fig 3 ). Download: PNG larger image TIFF original image Fig 2. Genomic distribution of variants found in the pancancer panel. (A) Among all variants, 48.25% are in intronic regions, 21.74% in exons, and 17.63% in intronic regulatory regions. Variants in splicing regions make up 4.13% and variants in the 3′ and 5′ UTRs account for 4.12% and 2.08%, respectively, potentially affecting RNA maturation and translation. An additional 1.16% and 0.35% are located in upstream and downstream regulatory regions; other variants are mapped to these regions (0.29% and 0.13%). Canonical splice sites contain the fewest variants (acceptor, 0.10%; donor, 0.01%). Overall, most germline variants are found in non-coding regions. The high number of variants annotated as benign or likely benign (11,072/13,781) within pancancer genes indicates they are polymorphisms without direct roles in tumor development. (B) Counts and types of alterations in pancancer genes. SNV, single-nucleotide variant; indel, insertion/deletion. https://doi.org/10.1371/journal.pone.0356762.g002 Download: PNG larger image TIFF original image Fig 3. Analysis of variant distribution based on their functional effects in cancer genes identified in TNBC patients. The analysis shows that most variants are synonymous (1,413), followed by missense (1,348), and promoter region variants (1,051). Variants in promoter-flanking regions (815) and CTCF-binding sites (392) may influence epigenetic and transcriptional regulatory mechanisms. Additionally, variants were found in enhancers (182), open chromatin regions (126), and TF binding sites (71), suggesting a potential effect on chromatin accessibility. Non-frameshift variants (148), frameshift variants (67), and stop-gain mutations (13) can alter the length or integrity of the protein reading frame. In contrast, start-loss (6) or start-gain variants involve the loss or gain of the translation start codon. The remaining variants are mostly located in deep intronic regions, making their functional effects unclear. These findings emphasize the importance of studying both coding variants and those in genome regulatory regions. https://doi.org/10.1371/journal.pone.0356762.g003 We identified
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