An Analytical Approach that Combines Knowledge from Germline and Somatic Mutations Enhances Tumor Genomic Reanalyses in Precision Oncology. J Comput Biol 2025 Jan;32(1):89-103
Date
12/11/2024Pubmed ID
39659251Pubmed Central ID
PMC11839515DOI
10.1089/cmb.2023.0461Scopus ID
2-s2.0-85215145104 (requires institutional sign-in at Scopus site)Abstract
Background: Expanded analysis of tumor genomics data enables current and future patients to gain more benefits, such as improving diagnosis, prognosis, and therapeutics. Methods: Here, we report tumor genomic data from 1146 cases accompanied by simultaneous expert analysis from patients visiting our oncological clinic. We developed an analytical approach that leverages combined germline and cancer genetics knowledge to evaluate opportunities, challenges, and yield of potentially medically relevant data. Results: We identified 499 cases (44%) with variants of interest, defined as either potentially actionable or pathogenic in a germline setting, and that were reported in the original analysis as variants of uncertain significance (VUS). Of the 7405 total unique tumor variants reported, 462 (6.2%) were reported as VUS at the time of diagnosis, yet information from germline analyses identified them as (likely) pathogenic. Notably, we find that a sizable number of these variants (36%-79%) had been reported in heritable disorders and deposited in public databases before the year of tumor testing. Conclusions: This finding indicates the need to develop data systems to bridge current gaps in variant annotation and interpretation and to develop more complete digital representations of actionable pathways. We outline our process for achieving such methodologic integration. Sharing genomics data across medical specialties can enable more robust, equitable, and thorough use of patient's genomics data. This comprehensive analytical approach and the new knowledge derived from its results highlight its multi-specialty value in precision oncology settings.
Author List
DeVoe E, Reddi HV, Taylor BW, Stachowiak S, Geurts JL, George B, Shaker R, Urrutia R, Zimmermann MTAuthors
Bradley W. Taylor Chief Research Informatics Officer in the Clinical and Translational Science Institute department at Medical College of WisconsinRaul A. Urrutia MD Center Director, Professor in the Surgery department at Medical College of Wisconsin
Michael T. Zimmermann PhD Director, Associate Professor in the Data Science Institute department at Medical College of Wisconsin
MESH terms used to index this publication - Major topics in bold
Computational BiologyDatabases, Genetic
Female
Genomics
Germ-Line Mutation
Humans
Male
Medical Oncology
Mutation
Neoplasms
Precision Medicine
