A novel investigation into an E2F transcription factor‐related prognostic model with seven signatures for colon cancer patients

Abstract

Abstract The pathogenesis of colon cancer, a common gastrointestinal tumour, involves complicated factors, especially a series of cell cycle‐related genes. E2F transcription factors during the cell cycle play an essential role in the occurrence of colon cancer. It is meaningful to establish an efficient prognostic model of colon cancer targeting cellular E2F‐associated genes. This has not been reported previously. The authors first aimed to explore the links of E2F genes with the clinical outcomes of colon cancer patients by integrating data from the TCGA‐COAD (n = 521), GSE17536 (n = 177) and GSE39582 (n = 585) cohorts. The Cox regression and Lasso modelling approach to identify a novel colon cancer prognostic model involving several hub genes (CDKN2A, GSPT1, PNN, POLD3, PPP1R8, PTTG1 and RFC1) were utilised. Moreover, an E2F‐related nomogram that efficiently predicted the survival rates of colon cancer patients was created. Additionally, the authors first identified two E2F tumour clusters, which showed distinct prognostic features. Interestingly, the potential links of E2F‐based classification and ‘protein secretion’ issues of multiorgans and tumour infiltration of ‘T‐cell regulatory (Tregs)’ and ‘CD56dim natural killer cell’ were detected. The authors’ findings are of potential clinical significance for the prognosis assessment and mechanistic exploration of colon cancer.

Keywords

• bioinformatics
• cancer