Intra-tumor heterogeneity presents itself through the evolution of subclones during cancer progression. While recent research suggests that this clonal diversity is a key factor in therapeutic failure, the determination of subclonal architecture of human tumors remains a challenge. To address the problem of accurately determining subclonal frequencies in tumors as well as their evolutionary history, we have developed a novel combinatorial method named CITUP (Clonality Inference in Tumors Using Phylogeny). An important feature of CITUP is its ability to exploit data from multiple time-point and/or regional samples from a single patient in order to improve estimates of mutational profiles and subclonal frequencies. Using extensive simulations and real datasets comprising tumor samples from two leukemia drug-response studies, we show that CITUP can infer the evolutionary trajectory of human tumors with high accuracy.
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Thesis advisor: Sahinalp, Suleyman Cenk
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