Risk assessment has high prognostic value in patients with colorectal cancer (CRC), and the use of proper models is an effective approach frequently used to evaluate cancer progression for further treatment plans. Alterations in metabolism are confirmed to be a significant feature of tumor cells and have been an intense focus in disease research. Here, we mined the genes that were differentially expressed in CRC tissues compared to paired normal samples from a public database and then constructed a novel assessment system for the prognosis of patients based on the value of a risk score considering the expression status of metabolism-related genes after screening. The score successfully stratified patients by risk and was externally verified in our study. Moreover, we built a nomogram combining the score and clinical parameters to predict patient survival using a visual method. The results suggested that the risk score was well fit and could provide assistance for the individual treatment of CRC patients in the clinic.
Keywords: bioinformatics; colorectal cancer; metabolic-related gene; prediction model; risk score.
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