WITHDRAWN: Identification of Cell Subgroups Related to Driver Mutations in Cancer
Maduranga Kasun Dassanayake, Student
Keywords: Cancer, Genetic Mutations, Epigenomic Data, Nonparametric Clustering
The Cancer Genome Atlas (TCGA) is a National Institutes of Health (NIH) effort to catalog genome-wide features of cancer genomes to enhance our understanding of the molecular basis of cancer. Cancer is thought to be primarily a genetic disease in the sense that genetic changes (i.e., mutations and other alterations in gene sequence) cause cells to proliferate out of control. One of the key problems is to identify “driver mutations,” (i.e., those gene mutations the cancer depends on) and consequently the genes that will need to be targeted for effective treatment. This study focuses on the analysis of epigenomic data (level 3) on myeloid leukemia and glioblastoma multiforme. Nonparametric clustering methods are used to identify cell subgroups that are common across patients and correspond to the same type of mutations.