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Abstract:
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Intratumor heterogeneity is characterized by the presence of genetically distinct subclones of tumor cells within a tumor. Such genetic diversity within a tumor is increasingly recognized as a driver of rapid disease progression, resistance to targeted therapies, and poor survival outcome. It also has important implications in defining "actionable" driver genes in the cancer genome. Inferring subclonal genetic alterations is often confounded by tumor purity, ploidy and local DNA copy number states. We present a statistical framework for inferring intratumor heterogeneity using whole-genome, whole-exome, and targeted capture sequencing data. We demonstrate its performance in large-scale cancer sequencing datasets.
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