Stem cell identification via RNA sequencing in breast cancer.

Abstract

Breast cancer is a complex, heterogeneous disease with distinct cancer subtypes. When the breast organ develops, it has a large pool of mammary stem cells. These cells have the potential to give rise to the various cell types that constitute the breast, as such, they are at risk for acquiring mutations, which can lead to transformed stem cells, thereby promoting the process of tumorigenesis. Among the breast cancer cells, increasing evidence points to the presence of a rare, small and heterogeneous subpopulation of cancerous cells termed as breast cancer stem cells (BCSCs), which have unlimited renewal capacity and are responsible for repopulating and giving rise to the heterogeneous, overly aggressive tumors. The recent technology of gene expression profiling like RNA-seq has helped some studies try to figure a way of identifying BCSCs, but there is still much work to be done. In this work we will use Machine Learning approach together with RNA-seq techonology in order to try to solve this task.