CCSG Pilot: Selection of Personalized Cancer Therapies by Evaluating Intra-tumoral Heterogeneity and Phylogentic Analysis

Grants and Contracts Details


Cancer usually arises from accumulation of somatically acquired genetic and epigenetic alterations. The accumulation of those somatic alterations has been shown to be an evolutionary process with diversification and selection of alterations that confer a survival advantage. As a result of this process, tumors are composed of mixtures of many subclones, and tumors often have dozens of mutations. Intra-tumor heterogeneity (ITH) is a major cause of drug resistance and treatment failure. In recent years, genomic sequencing has been more and more widely used in the clinic to identify genomic alterations in a patient and provide evidence for targeted therapies. The Markey Cancer Center has formed a molecular tumor board (MTB) consisting of a multidisciplinary team of scientists and clinicians to review patients’ genomic alterations, identify actionable mutations, and suggest personalized treatment strategies. However, almost all tumors are heterogenous and have multiple actionable mutations and a major difficulty is determining which mutation is most important to target. This proposal aims to address this problem by studying ITH. We hypothesize that characterizing the ITH can help clinicians better understand the evolution process of the tumor and optimize the treatment plan. To evaluate this hypothesis, we will characterize ITH and assess the clinical impact of phylogenetic analysis based on MTB patients’ data, evaluate multi-region tumor heterogeneity of ovarian cancer by integrating multi-omics data, and use phylogenetic analysis to prioritize targeted therapies for ovarian cancer patients and assess the effectiveness based on PDX models. Our study will demonstrate the value of phylogenetic analysis to selection of individualized therapies. This will be the first example of a prospective preclinical validation of a bioinformatics strategy. In addition, our study will delineate the power of using multi-omics data to enhance phylogenetic tree construction and explore the multi-region tumor heterogeneity. If successful, the ITH analysis will lead to a clinical trial evaluating the use of a bioinformatics resource to select the most efficacious precision medicine treatment.
Effective start/end date7/9/184/8/20


  • National Cancer Institute


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