Multi gene mutation signatures in colorectal cancer patients: predict for the diagnosis, pathological classification, staging and prognosis

Abstract

Background: Identifying gene mutation signatures will enable a better understanding for the occurrence and development of colorectal cancer (CRC), and provide some potential biomarkers for clinical practice. Currently, however, there is still few effective biomarkers for early diagnosis and prognostic judgment in CRC patients. The purpose was to identify novel mutation signatures for the diagnosis and prognosis of CRC. Methods: Clinical information of 531 CRC patients and their sequencing data were downloaded from TCGA database (training group), and 53 clinical patients were collected and sequenced with targeted next generation sequencing (NGS) technology (validation group). The relationship between the mutation genes and the diagnosis, pathological type, stage and prognosis of CRC were compared to construct signatures for CRC, and then analyzed their relationship with RNA expression, immunocyte infiltration and tumor microenvironment (TME). Results: Mutations of TP53, APC, KRAS, BRAF and ATM covered 97.55% of TCGA population and 83.02% validation patients. Moreover, 57.14% validation samples and 22.06% TCGA samples indicated that patients with mucinous adenocarcinoma tended to have BRAF mutation, but no TP53 mutation. Mutations of TP53, PIK3CA, FAT4, FMN2 and TRRAP had a remarkable difference between I-II and III-IV stage patients (P < 0.0001). Besides, the combination of PIK3CA, LRP1B, FAT4 and ROS1 formed signatures for the prognosis and survival of CRC patients. The mutations of TP53, APC, KRAS, BRAF, ATM, PIK3CA, FAT4, FMN2, TRRAP, LRP1B, and ROS1 formed the signatures for predicting diagnosis and prognosis of CRC. Among them, mutation of TP53, APC, KRAS, BRAF, ATM, PIK3CA, FAT4 and TRRAP significantly reduced their RNA expression level. Stromal score, immune score and ESTIMATE score were lower in patients with TP53, APC, KRAS, PIK3CA mutation compared non-mutation patients. All the 11 gene mutations affected the distributions of immune cells. Conclusion: This study constructed gene mutation signatures for the diagnosis, treatment and prognosis in CRC, and proved that their mutations affected RNA expression levels, TME and immunocyte infiltration. Our results put forward further insights into the genotype of CRC.