Tracking Cancer Evolution through the Disease Course.

癌症 计算生物学 精密医学
作者
Christopher Bailey,James R M Black,James L. Reading,Kevin Litchfield,Samra Turajlic,Nicholas McGranahan,Mariam Jamal-Hanjani,Charles Swanton
出处
期刊:Cancer Discovery [American Association for Cancer Research]
卷期号:11 (4): 916-932 被引量:13
标识
DOI:10.1158/2159-8290.cd-20-1559
摘要

During cancer evolution, constituent tumor cells compete under dynamic selection pressures. Phenotypic variation can be observed as intratumor heterogeneity, which is propagated by genome instability leading to mutations, somatic copy-number alterations, and epigenomic changes. TRACERx was set up in 2014 to observe the relationship between intratumor heterogeneity and patient outcome. By integrating multiregion sequencing of primary tumors with longitudinal sampling of a prospectively recruited patient cohort, cancer evolution can be tracked from early- to late-stage disease and through therapy. Here we review some of the key features of the studies and look to the future of the field. SIGNIFICANCE: Cancers evolve and adapt to environmental challenges such as immune surveillance and treatment pressures. The TRACERx studies track cancer evolution in a clinical setting, through primary disease to recurrence. Through multiregion and longitudinal sampling, evolutionary processes have been detailed in the tumor and the immune microenvironment in non-small cell lung cancer and clear-cell renal cell carcinoma. TRACERx has revealed the potential therapeutic utility of targeting clonal neoantigens and ctDNA detection in the adjuvant setting as a minimal residual disease detection tool primed for translation into clinical trials.
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