Developmental Deconvolution Suggests New Tumor Biology and a Tool for Predicting Cancer Origin

Defining the developmental origins of cancer can help uncover cellular mechanisms of cancer development and progression and identify effective treatments, but it has been challenging. In this issue of Cancer Discovery, Moiso and colleagues constructed a developmental map of 33 cancer types, based on which they deconvoluted tumors into developmental components and constructed a deep learning classifier capable of high-accuracy tumor type prediction.