TCGA data mining of mutation gene difference between age-related groups in breast cancer
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Breast cancer is one of the most common cancers with greater than 1,300,000 cases and 450,000 deaths each year worldwide. The primary risk factors are age, race, gender, genetics, etc. Considering the poorer prognosis in younger group, the hypothesis was raised if any recurrently mutated gene is associated with age difference in breast cancer incidence. The Cancer Genome Atlas (TCGA) project has generated next-generation sequencing data for over 1000 breast patients. However, the potential utility of this TCGA sequencing data set in predicting age-related gene mutation is largely unexplored. In this work, we analyzed the somatic mutation landscapes within each of the four subtypes of breast cancer. We have applied several different statistical methods to search genes whose mutation pattern is associated with the age of breast cancer patients. The results and limitations of this work are discussed.