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Inferring early genetic progression in cancers with unobtainable premalignant disease. | LitMetric

AI Article Synopsis

  • Researchers analyzed the progression of genetic events in tumors, finding that some cancers lack premalignant tissue, making genetic progression hard to determine.
  • They developed a method called PhylogicNDT to infer this progression from exome sequencing of primary tumors, successfully validating it in HPV-negative head and neck squamous cell carcinoma (HNSCC).
  • The study revealed previously unknown genetic progression in HPV-positive HNSCC, linked the timing of genetic changes to tumor characteristics, and highlighted the potential for improved early detection and treatment strategies.

Article Abstract

Analysis of premalignant tissue has identified the typical order of somatic events leading to invasive tumors in several cancer types. For other cancers, premalignant tissue is unobtainable, leaving genetic progression unknown. Here, we demonstrate how to infer progression from exome sequencing of primary tumors. Our computational method, PhylogicNDT, recapitulated the previous experimentally determined genetic progression of human papillomavirus-negative (HPV) head and neck squamous cell carcinoma (HNSCC). We then evaluated HPV HNSCC, which lacks premalignant tissue, and uncovered its previously unknown progression, identifying early drivers. We converted relative timing estimates of driver mutations and HPV integration to years before diagnosis based on a clock-like mutational signature. We associated the timing of transitions to aneuploidy with increased intratumor genetic heterogeneity and shorter overall survival. Our approach can establish previously unknown early genetic progression of cancers with unobtainable premalignant tissue, supporting development of experimental models and methods for early detection, interception and prognostication.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10132986PMC
http://dx.doi.org/10.1038/s43018-023-00533-yDOI Listing

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