Prognosis model of colorectal cancer patients based on , , and mutations.

BACKGROUND

Colorectal cancer (CRC) is one of the most common cancers. The aim of our study was to explore its related mutations, identify novel mutation markers, and construct predictive models for postoperative CRC patients, so as to provide evidence for the diagnosis, treatment, and prognosis of CRC.

METHODS

A total 50 CRC patients were collected, and the mutations in tissue samples were detected through next-generation sequencing (NGS). Meanwhile, 246 CRC cases with complete mutation data were downloaded from The Cancer Genome Atlas (TCGA) database. Afterwards, the co-mutations in both clinical and TCGA cohorts were identified, and the high-frequency mutation genes were selected. Subsequently, functional enrichment analysis was performed, and overall survival (OS) and progression-free survival (PFS) predictive models were constructed.

RESULTS

In all, 18 out of 238 co-mutation genes mutated in at least 20% of the samples and were selected out as common high-frequency mutation genes. They were significantly enriched in 460 Gene Ontology (GO) terms and 87 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways (P<0.05), which were closely related to the occurrence and development of CRC. Among the 18 genes, , histone lysine methyltransferase 2C (), and cAMP-response element binding protein-BP () were respectively associated with tumor position, stage, and PFS (P<0.05), and could be considered as potential biomarkers of CRC. Finally, OS and PFS predictive models were constructed and verified using the 50 clinical cases, with both models demonstrating high fitting degrees useful for predicting the OS and PFS of CRC patients.

CONCLUSIONS

, , and were found to be prospective biomarkers for the diagnosis and prognosis of CRC. The prognosis prediction models had high sensitivity and could be used to predict the OS and PFS of CRC patients.