Gene-targeted cancer therapies are primarily hampered by the extreme genetic heterogeneity observed across the patient population. ?One gene, one function, one disease? model can not reconcile with the complexity that different mutations of the same gene often lead to different phenotypes. In the recent past, genome and exome sequencing projects have identified thousands of genetic mutations in patients stricken by a large number of cancer types. However, the explosion of genomic information has left many fundamental questions regarding genotype-phenotype relationships in cancer unresolved. One critical challenge is to distinguish causal disease mutations from non-pathogenic polymorphisms. Even when causal mutations are identified, the functional consequence of such mutations is often elusive. The extent to which molecular interactome network perturbations are involved in cancer progression and how distinct interaction perturbation patterns can distinguish cancer mutations are largely unknown. This application describes a novel integrative approach to investigate genetic mutation-specific functional effects on molecular interaction rewiring, and a combination of experimental and computational approaches to unravel important functional network alterations in melanoma. In particular, triple wild-type melanoma (TWTM) is a common subtype characterized by a lack of mutations in driver genes BRAF, RAS, and NF1, and is a highly aggressive subtype with poor prognosis and no targeted therapy. To address this challenge, this application will (1) identify and functionally characterize novel driver mutations for TWTM, (2) determine how genetic mutations induce molecular interactome perturbations for TWTM progression, (3) determine molecular targets that suppress cancer mutations to reprogram oncogenic signaling. Together, this integrative approach is innovative because it will have provided insights in prioritizing cancer-causing variants, and uncovering patient mutation-specific disease mechanisms at a base-pair resolution, a critical step towards personalized precision medicine. Furthermore, the proposed research is significant because it will have determined distinct interaction perturbations underlying genetic heterogeneity, providing a fundamental link between genotype and phenotype in melanoma. In addition to its scientific proposal, this application proposes a comprehensive training program for preparing an independent investigator in the fields of cancer functional genomics, who develops cutting-edge experimental and computational methods to understand the function of genetic mutations and protein interaction perturbations in cancer.
Initial promise of oncogene-directed cancer therapies is often thwarted by the extreme genetic heterogeneity across diverse patient population. The proposed research is to functionally stratify cancer genomic mutations using a combination of novel computational methods and cutting-edge experimental strategies. The results from this application will provide valuable insights into how distinct mutations elicit different molecular interaction perturbations, and will reveal the underlying mechanisms responsible for cancer heterogeneity, guiding personalized medicine for melanoma cancer diagnosis and therapy.
| Li, Yongsheng; McGrail, Daniel J; Xu, Juan et al. (2018) Gene Regulatory Network Perturbation by Genetic and Epigenetic Variation. Trends Biochem Sci 43:576-592 |
| Li, Yongsheng; McGrail, Daniel J; Latysheva, Natasha et al. (2018) Pathway perturbations in signaling networks: Linking genotype to phenotype. Semin Cell Dev Biol : |
