For this purpose, using the CRC-derived NAT and tumor paired transcriptome data generated by Samsung Medical Center (SMC) in Korea, we build two classes of elastic net-based machine-learning models, i.e., NAT-based models and tumor tissue-based model, to predict CRC prognosis, and examine which of the two types of models predict better the recurrence states of CRC patients, i.e., recurrent (shorten to be RC) and nonrecurrent (shorten to be nonRC) states. Here, BRD2 is linked to neoplasm.