Screening and analysis of ferroptosis-related genes impacting the prognosis of colorectal adenocarcinoma patients based on bioinformatics / 肿瘤研究与临床

ABSTRACT

Objective:To screen and analyze ferroptosis-related genes (FRG) impacting the prognosis of colorectal adenocarcinoma patients based on bioinformatics.Methods:RNA sequencing data including the clinical information of 545 colorectal adenocarcinoma patients and 602 data sets were downloaded from the Cancer Genome Atlas (TCGA) database. FRG gene sets were downloaded from FerrDb database. FRG expression dataset could be obtained after taking the intersection between FRG gene sets and TCGA database gene sets. Differentially expressed FRG and prognosis-related genes between colorectal adenocarcinoma tissues and the adjacent tissues were screened by using R software, and finally FRG influencing the prognosis of colorectal adenocarcinoma were obtained. According to protein-protein interaction networks, the interaction and the expression association of proteins were analyzed. LASSO regression analysis was used to build a risk model for patients' 5-year overall survival rate. The risk value was calculated for 509 colorectal adenocarcinoma samples in the TCGA database, and then the median risk value was taken as the cut-off value. All patients were divided into the high-risk group (≥ median risk value) and the low-risk group (< median risk value), and the survival curves of the two groups were drawn. The receiver operating characteristic (ROC) curve was drawn for predicting the 5-year overall survival rate of colorectal adenocarcinoma patients in a time-dependent way in TCGA database according to the risk value of FRG prognosis model. Cox proportional risk model was used to make univariate and multivariate survival analysis in order to screen factors affecting the prognosis. The pathway enrichment analysis of prognosis-related FRG of colorectal adenocarcinoma was performed based on gene ontology (GO) database and Kyoto Encyclopedia of Genes and Genomes (KEGG) database.Results:The clinical information of 545 patients and 602 datasets were extracted from the database. A total of differential expressed 199 FRG in colorectal adenocarcinoma and 28 prognosis-related FRG were identified. After taking the intersection, 21 FRG affecting the prognosis of colorectal adenocarcinoma patients were identified. DUOX2, NOX4, NOX1, DDIT3, JDP2, ATP6V1G2, ULK1, ATG3 were probably associated with WIPI1; expressions of NOX4, NOX5, PLIN4 were positively correlated with ATP6V1G2, while the expression of ULK1 was negatively correlated with MAPK1, MYB, FANCD2, ATG3 and ATP5MC3. LASSO regression analysis showed that 15 FRG were finally screened out (ATP5MC3, NOX4, NOX5, ALOX12B, ATG3, WIPI1, MAPK1, MYB, AKR1C1, DDIT3, JDP2, ATP6V1G2, DRD4, SLC2A3, PLIN4), and the risk model was constructed by calculating the risk value, and the risk value = NOX4×0.139-ATP5M3×0.108+NOX5×1.486+ALOX12B×0.475-ATG3×0.030-WIPI1×0.170-MAPK1×0.271-MYB×0.063+AKR1C1×0.021+DDIT3×0.186+JDP2×0.292+ATP6V1G2×0.777+DRD4×0.294+SLC2A3×0.059+PLIN4×0.113. The overall survival of patients in the high-risk group was worse than that in the low-risk group ( P < 0.001). The 5-year overall survival rate was 48.2% in the high-risk group and 76.8% in the low-risk group. Multivariate survival showed that the age and risk value were independent affecting factors of the prognosis. ROC curves revealed that the risk model constructed by using prognosis-related FRG could well predict the 5-year overall survival rate of patients (the area under the curve was 0.728). The differential expressed genes of both groups may be associated with genetic pathways such as extracellular matrix composition, extracellular structure composition and focal adhesion. Conclusions:The prognostic risk model constructed by the screened FRG can better evaluate the prognosis of colorectal adenocarcinoma patients. These FRG are expected to become new candidate biomarkers related to the prognosis of colorectal adenocarcinoma.