Identification of as a Prognostic Biomarker in Colorectal Cancer by an Integrated Bioinformatic Analysis.

The dysregulation of transcriptional factors (TFs) leads to malignant growth and the development of colorectal cancer (CRC). Herein, we sought to identify the transcription factors relevant to the prognosis of colorectal cancer patients. We found 526 differentially expressed TFs using the TCGA database of colorectal cancer patients ( = 544) for the differential analysis of TFs ( = 1,665) with 210 upregulated genes as well as 316 downregulated genes. Subsequently, GO analysis and KEGG pathway analysis were performed for these differential genes for investigating their pathways and function. At the same time, we established a genetic risk scoring model for predicting the overall survival (OS) by using the mRNA expression levels of these differentially regulated TFs, and defined the CRC into low and high-risk categories which showed significant survival differences. The genetic risk scoring model included four high-risk genes (, , , and ) and two low-risk genes ( and ), and validated the OS in two GEO databases ( = 0.0023 for the GSE17536, = 0.0193 for the GSE29623). To analyze the genetic and epigenetic changes of these six risk-related TFs, a unified bioinformatics analysis was conducted. Among them, is progressive in CRC and its high expression is linked with a poor diagnosis as well. Knockdown of inhibits the proliferative capacity of CRC cells. Moreover, the positive association between and cyclins (CDK2, CCNE2, CDK6, CHEK1) was also identified. Therefore, as a novel biomarker, may be a promising candidate in the diagnosis and prognostic evaluation of colorectal cancer.