While genomic analysis of tumor cells is a mainstay in cancer research, there is
growing interest in the characterization of the tumor microenvironment, comprised of
nearby healthy somatic cells, most notably fibroblasts and invading immune cells.
Studying the RNA expression profile of the tumor microenvironment provides a way to
analyze local response to tumor growth and ultimately to better characterize bodily
response to different stages or genetic subsets of cancer. The purpose of this research was
to develop a tool that efficiently separates tumor sequence data from human xenograft
mice (mice with genetically human tumors) into separate microenvironment and tumor
expression profiles. While this separation was previously done by physically excising
healthy tissue under a microscope using laser capture microdissection, performing this
separation in silico allows for rapid analysis of hundreds of samples. Further, using this
tool, we can re-examine tumor expression profiles after filtering out ‘contaminating’
microenvironment sequence, resulting in a more accurate RNA expression profile.Bachelor of Scienc
