{ "abstract": "Transcription is regulated through the sequence-specific binding of transcription factors (TFs) to cis-regulatory regions (CRRs); DNA variants in CRRs can disrupt TF-DNA interactions and gene regulatory networks through a cascading effect. Despite a few cases of reported recurrent cis-regulatory variants (CRVs), another approach for detecting non-coding functional events relies on combining gene-CRR associations capturing the regulatory elements controlling gene transcription, and functional impact (FI) scores quantifying the deleterious effect of variants. While many methods exist for each, how much they agree and how strongly the choice of CRR-FI score combination impacts the prediction of cis-regulatory altered genes has not been systematically assessed. Here, we demonstrate that gene-CRR associations and FI scoring methods exhibit little consensus, highlighting the impact of the choice of a specific CRR-FI score combination in a given analysis. These observations point to the need for a systematic approach to evaluate several gene-CRR and FI scoring methods in a unified framework. To address this gap, we developed HiFIseek, a Snakemake pipeline of two enrichment detection methods exploring the enrichment of high FI variants in CRRs associated with a gene using all region-score combinations. We applied HiFIseek to detect genes exhibiting high functional impact CRVs in eight cancer cohorts and a set of breast cancer risk-associated single-nucleotide polymorphisms (SNPs). We demonstrate that cancer driver genes exhibit a higher frequency of FI CRVs compared to non-cancer genes. In the cancer cohorts, HiFIseek detected genes pointing to cancer-related pathways with enrichment for high FI CRVs despite a small degree of agreement across CRR-FI score combinations. In the SNP cohort, HiFIseek found again small consensus across CRR-score combinations, one of which returned 18 known cancer-related genes, including BRCA1, showing an enrichment of high-impact CRVs. Author summary: While most of our genome does not code for proteins, it contains DNA segments that control the activation of genes. When mutations occur in these segments, they can disrupt how genes are regulated and may contribute to diseases such as cancer. However, identifying which mutations in these segments are important is an ongoing challenge. In this study, we show that computational methods largely disagree when assessing the functional impact of a mutation and which gene will likely be impacted. To provide a broader perspective on the prediction of genes associated with cancer through mutations in regulatory DNA segments, we developed HiFIseek, a flexible computational pipeline that systematically tests every combination of methods to find genes whose regulatory segments are unusually enriched for high-impact mutations. Applying HiFIseek to cancer datasets and breast cancer risk variants, we recovered known cancer genes and highlighted candidates worth further investigation.", "abstract_shown": true, "affiliations": [ "Norwegian Center for Molecular Biosciences and Medicine (NCMBM), Nordic EMBL Partnership, University of Oslo, Oslo, Norway.", "Department of Medical Genetics, Oslo University Hospital, Oslo, Norway.", "Institute for Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway.", "Biostatistics Unit, The Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus.", "Princeton Precision Health, Princeton University, Princeton, New Jersey, United States of America.", "Flatiron Institute, Simons Foundation, New York, New York, United States of America.", "Bioinformatics in Life Science (BiLS) Initiative, Department of Informatics, University of Oslo, Oslo, Norway." ], "article_type": "Research Article", "arxiv": null, "author_total": 6, "authors": [ { "affs": [ 0 ], "name": "Rafael Riudavets Puig", "orcid": "0000-0002-2855-9952" }, { "affs": [ 1, 2, 3 ], "name": "Denise G O'Mahony", "orcid": "0000-0002-7212-0920" }, { "affs": [ 1, 2 ], "name": "Ina Skaara Brorson", "orcid": "0000-0001-6691-9413" }, { "affs": [ 4, 5 ], "name": "Ksenia Sokolova" }, { "affs": [ 1, 2 ], "name": "Vessela N Kristensen", "orcid": "0000-0001-5012-7438" }, { "affs": [ 0, 1, 6 ], "name": "Anthony Mathelier", "orcid": "0000-0001-5127-5459" } ], "bibtex": "https://research.draconitic.com/paper/e4ww8c3d6hbyh.bib", "cited_by": 0, "doi": "10.1371/journal.pcbi.1014842", "fulltext_url": "https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1014842", "id": "e4ww8c3d6hbyh", "issns": [ "1553-7358", "1553-734X" ], "landing_url": "https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1014842", "language": "eng", "licence": "CC-BY", "licence_label": "CC BY", "licence_source": "article", "licence_url": "https://creativecommons.org/licenses/by/4.0/", "metadata_licence": null, "native_subjects": [ [ "openalex", "1311|Genetic Associations and Epidemiology" ], [ "plos", "/Biology and life sciences/Computational biology/Genome analysis/Genome annotation" ], [ "plos", "/Biology and life sciences/Genetics/Genomics/Genome analysis/Genome annotation" ], [ "plos", "/Biology and life sciences/Genetics/Mutation" ], [ "plos", "/Biology and life sciences/Genetics/Single nucleotide polymorphisms" ], [ "plos", "/Medicine and health sciences/Epidemiology/Medical risk factors/Cancer risk factors/Genetic causes of cancer" ], [ "plos", "/Medicine and health sciences/Gastroenterology and hepatology/Liver diseases/Hepatocellular carcinoma" ], [ "plos", "/Medicine and health sciences/Oncology/Cancer risk factors/Genetic causes of cancer" ], [ "plos", "/Medicine and health sciences/Oncology/Cancers and neoplasms" ], [ "plos", "/Medicine and health sciences/Oncology/Cancers and neoplasms/Breast tumors/Breast cancer" ], [ "plos", "/Medicine and health sciences/Oncology/Cancers and neoplasms/Carcinoma/Hepatocellular carcinoma" ], [ "plos", "/Medicine and health sciences/Oncology/Cancers and neoplasms/Gastrointestinal tumors/Hepatocellular carcinoma" ], [ "plos", "/Medicine and health sciences/Oncology/Cancers and neoplasms/Lung and intrathoracic tumors" ] ], "openalex": "W7220844870", "pdf_url": "https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1014842&type=printable", "pmcid": "PMC13657309", "pmid": "42837436", "published": "2026-10-06", "publisher": "Public Library of Science", "ris": "https://research.draconitic.com/paper/e4ww8c3d6hbyh.ris", "sources": [ { "first_seen": "2026-10-30T12:17:36Z", "native_id": "10.1371/journal.pcbi.1014842", "source": "plos", "url": "https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1014842" }, { "first_seen": "2026-10-30T12:18:10Z", "native_id": "MED:42837436", "source": "europepmc", "url": "https://europepmc.org/article/MED/42837436" } ], "subjects": [ { "field": "biology", "origin": "plos:genomics", "subfield": "genetics-genomics" }, { "field": "medicine", "origin": "plos:oncology", "subfield": "oncology" } ], "title": "HiFIseek: Gene-specific enrichment of high-impact mutations in associated genomic regions", "title_text": "HiFIseek: Gene-specific enrichment of high-impact mutations in associated genomic regions", "type": "peer-reviewed", "updated_at": "2026-10-30T12:18:10Z", "url": "https://research.draconitic.com/paper/e4ww8c3d6hbyh", "venue": "PLOS Computational Biology", "versions": [] }