In this note, we describe a methodology based on the discretization of Bakry-Emery Ricci curvature for weighted graphs with an emphasis on studying cancer networks from The Cancer Genome Atlas (TCGA) . In particular, we utilize the Gamma-2 calculus of Bakry-Emery which suggest a discrete notion analogous to curvature in the general framework of a Markov semigroup. The condition is based on the Bochner inequality with dimension condition CD(K,N). This said, the empirical study focuses on illuminating differences between normal and cancer tissue derived from a variety of publicly available cancer samples in TGCA. The goal here is to continually build on an existing framework that shows curvature as a potential “cancer hallmark”.