A deep learning approach for improved detection of homologous recombination deficiency from shallow genomic profiles
A deep learning approach for improved detection of homologous recombination deficiency from shallow genomic profiles
Abstract Homologous Recombination Deficiency (HRD) is a predictive biomarker of poly-ADP ribose polymerase 1 inhibitors (PARPi) response. Most HRD detection methods are based on genome wide enumeration of scarring events and require deep genome sequence profiles (> 30x). The cost and workflow-specific biases introduced by these genome profiling methods currently limits clinical adoption of HRD testing. We introduce the Genomic Integrity Index (GII), a Convolutional Neuronal Network, that leverages features from low pass (1x) Whole Genome Sequencing data to distinguish HRD positive and negative samples. In a cohort of 230 ovarian and breast cancer, we found GII supports accurate stratification of samples yielding results that are highly concordant with state-of-the-art HRD detection methods (0.865<AUC<0.996) which require 50x deeper coverage. We conclude that the deep learning framework supporting GII allows accurate detection of HRD from shallow genome profiles, reducing biases and data generation costs making it uniquely suited for clinical applications.
Andre Gregoire、Coletta Tommaso、Bieler Jonathan、Chong Chloe、Saitta Alexandra、Janiszewski Adrian、Bonilla Ximena、Grimm Christoph、Xu Zhenyu、Wozelka-Oltjan Lisa、M¨1llauer Leonhard、Kempfer Rieke、Macheret Morgane、Smith Ewan、Postl Magdalena、Bonet Jaume、Willig Adrian、Marques Ana C.、Pozzorini Christian、Arrigo Nils、Santos-Silva Hugo
SOPHiA GENETICS SASOPHiA GENETICS SASOPHiA GENETICS SASOPHiA GENETICS SASOPHiA GENETICS SASOPHiA GENETICS SASOPHiA GENETICS SADivision of General Gynecology and Gynecologic Oncology, Gynecologic Cancer Unit, Comprehensive Cancer Center, Medical University of ViennaSOPHiA GENETICS SADepartment of Pathology, Medical University of ViennaDepartment of Pathology, Medical University of ViennaSOPHiA GENETICS SASOPHiA GENETICS SASOPHiA GENETICS SADivision of General Gynecology and Gynecologic Oncology, Gynecologic Cancer Unit, Comprehensive Cancer Center, Medical University of ViennaSOPHiA GENETICS SASOPHiA GENETICS SASOPHiA GENETICS SASOPHiA GENETICS SASOPHiA GENETICS SASOPHiA GENETICS SA
医学研究方法基础医学肿瘤学
Andre Gregoire,Coletta Tommaso,Bieler Jonathan,Chong Chloe,Saitta Alexandra,Janiszewski Adrian,Bonilla Ximena,Grimm Christoph,Xu Zhenyu,Wozelka-Oltjan Lisa,M¨1llauer Leonhard,Kempfer Rieke,Macheret Morgane,Smith Ewan,Postl Magdalena,Bonet Jaume,Willig Adrian,Marques Ana C.,Pozzorini Christian,Arrigo Nils,Santos-Silva Hugo.A deep learning approach for improved detection of homologous recombination deficiency from shallow genomic profiles[EB/OL].(2025-03-28)[2025-05-01].https://www.biorxiv.org/content/10.1101/2022.07.06.498851.点此复制
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