Analysis of shared variants between cancer biospecimens Journal Article
| Authors: | Foote, M. B.; White, J. R.; Chatila, W. K.; Argilés, G.; Lu, S.; Rousseau, B.; Artz, O.; Johannet, P.; Walch, H.; Patel, M.; Lamendola- Essel, M. F.; Casadevall, D.; Abdelfattah, S.; Patel, S.; Yaeger, R.; Cercek, A.; Montagut, C.; Berger, M.; Schultz, N.; Diaz, L. A. Jr |
| Article Title: | Analysis of shared variants between cancer biospecimens |
| 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% (cancertype 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. © 2024 American Association for Cancer Research. |
| Keywords: | controlled study; human tissue; treatment response; aged; gene mutation; human cell; major clinical study; genetics; mutation; solid tumor; pancreas cancer; glioma; genetic analysis; sensitivity analysis; neoplasm; neoplasms; tumor associated leukocyte; melanoma; ovary cancer; breast cancer; prevalence; cohort analysis; genetic variability; genetic variation; lung cancer; tumor biopsy; pathology; algorithms; uvomorulin; tumor marker; electronic medical record; lung metastasis; algorithm; colon cancer; mismatch repair; tumor cell; thyroid cancer; k ras protein; tumor gene; multiple cancer; b raf kinase; predictive value; dna directed dna polymerase epsilon; high throughput sequencing; high-throughput nucleotide sequencing; humans; human; female; article; whole exome sequencing; biomarkers, tumor; malignant neoplasm; biobank; multiple tumor |
| Journal Title: | Clinical Cancer Research |
| Volume: | 31 |
| Issue: | 2 |
| ISSN: | 1078-0432 |
| Publisher: | American Association for Cancer Research |
| Date Published: | 2025-01-15 |
| Start Page: | 376 |
| End Page: | 386 |
| Language: | English |
| DOI: | 10.1158/1078-0432.Ccr-24-1583 |
| PUBMED: | 39561276 |
| PROVIDER: | scopus |
| PMCID: | PMC11747808 |
| DOI/URL: | |
| Notes: | The MSK Cancer Center Support Grant (P30 CA008748) is acknowledge in the PDF -- Corresponding authors is MSK author: Luis A. Diaz Jr -- Source: Scopus |
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