Data from Analysis of Shared Variants between Cancer Biospecimens
Year: 2025
Type: other
Abstract: Purpose: Mutational data from multiple solid and liquid biospecimens of a single patient are often integrated to track cancer evolution. However, there is no accepted framework to resolve if individual samples from the same individual share variants due to common identity versus coincidence. Experimental Design: Utilizing 8,000 patient tumors from The Cancer Genome Atlas across 33 cancer types, we estimated the background rates of co-occurrence of mutations between discrete pairs of samples across cancers and by cancer type. We developed a mutational profile similarity (MPS) score that uses a large background database to produce confidence estimates that two tumors share a unique, related molecular profile. The MPS algorithm was applied to randomly paired tumor profiles, including patients who underwent repeat solid tumor biopsies sequenced with Memorial Sloan Kettering-IMPACT (n = 53,113). We also evaluated the MPS in sample pairs from single patients with multiple cancers (n = 2,012), as well as patients with plasma and solid tumor variant profiles (n = 884 patients). Results: In unrelated tumors, nucleotide-specific variants are shared in 1.3% (cancer-type agnostic) and in 10% to 13% (cancer-type specific) of cases. The MPS method contextualized shared variants to specify whether patients had a single cancer versus multiple distinct cancers. When multiple tumors were compared from the same patient and an initial clinicopathologic diagnosis was discordant with molecular findings, the MPS anticipated future diagnosis changes in 28% of examined cases. Conclusions: The use of a novel shared variant framework can provide information to clarify the molecular relationship between compared biospecimens with minimal required input.
Authors: Michael B. Foote, James Robert White, Walid K. Chatila, Guillem Argilés, Steve Lu, Benoit Rousseau, Oliver Artz, Paul Johannet, Henry Walch, Mitesh Patel, Michelle F. Lamendola-Essel, David Casadevall, Somer Abdelfattah, Shrey Patel, Rona Yaeger, Andrea Cercek, Clara Montagut, Michael Berger, Nikolaus Schultz, Luis A. Diaz
Language: English
Subfield: Cancer Research
Domain: Life Sciences
Open Access status: gold
OpenAlex ID: W4406541817