Tensor Decomposition of Largest Convolutional Eigenvalues Reveals Pathological Predictive Power of RhoB in Rectal Cancer Biopsy.

Abstract

RhoB protein belongs to the Rho GTPase family, which plays an important role in governing cell signaling and tissue morphology. RhoB expression is known to have implications in pathological processes of diseases. Investigation in the regulation and communication of this protein detected by immunohistochemical staining on the microscope is worth exploring to gain insightful information that may lead to identifying optimal disease treatment options. In particular, the role of RhoB in rectal cancer is not well-discovered. Here, we report that methods of deep learning-based image analysis and the decomposition of multiway arrays discover the predictive factor of RhoB in two cohorts of rectal cancer patients having survival rates of less and more than 5 years. The analysis results show distinctions between the tensor decomposition factors of the two cohorts.