Construction and Validation of Novel Ferroptosis-related Risk Score Signature and Prognostic Prediction Nomogram for Patients with Colorectal Cancer

Abstract

Background: Colorectal cancer (CRC) has a high morbidity and mortality. Ferroptosis is a phenomenon in which metabolism and cell death are closely related. The role of ferroptosis-related genes in the progression of CRC is still not clear. Therefore, we screened and validated the ferroptosis-related genes which could determine the prevalence, risk and prognosis of patients with CRC. Methods: We firstly screened differentially expressed ferroptosis-related genes by The Cancer Genome Atlas (TCGA) database. Then, these genes were used to construct a risk-score model using the least absolute shrinkage and selection operator (LASSO) regression algorithm. The function and prognosis of the ferroptosis-related genes were confirmed using multi-omics analysis. The gene expression results were validated using publicly available databases and qPCR. We also used publicly available data and ferroptosis-related genes to construct a prognostic prediction nomogram. Results: A total of 24 differential expressed genes associated with ferroptosis were screened in this study. A three-gene risk score model was then established based on these 24 genes and GPX3, CDKN2A and SLC7A11 were selected. The significant prognostic value of this novel three-gene signature was also assessed. Furthermore, we conducted RT-qPCR analysis on cell lines and tissues, and validated the high expression of CDKN2A, GPX3 and low expression of SLC7A11 in CRC cells. The observed mRNA expression of GPX3, CDKN2A and SLC7A11 was consistent with the predicted outcomes. Besides, eight variables including selected ferroptosis related genes were included to establish the prognostic prediction nomogram for patients with CRC. The calibration plots showed favorable consistency between the prediction of the nomogram and actual observations. Also, the time-dependent AUC (>0.7) indicated satisfactory discriminative ability of the nomogram. Conclusions: The present study constructed and validated a novel ferroptosis-related three-gene risk score signature and a prognostic prediction nomogram for patients with CRC. Also, we screened and validated the ferroptosis-related genes GPX3, CDKN2A, and SLC7A11 which could serve as novel biomarkers for patients with CRC.

Keywords: Colorectal Cancer; Ferroptosis; Nomogram; Prognosis; Risk model.

Figure 1

Identification and functional enrichment analysis of dysregulated ferroptosis-related genes in CRC. A: Schematic overview of the whole study. B-C: Differential gene volcano, heatmap of CRC based on TGCA data. D: Venn diagram representing intersections of CRC DEGs and ferroptosis-related genes. E: Heatmap of the expression levels of 24 ferroptosis-related DEGs based on TCGA data. F: Map of ranking of differences of 24 ferroptosis-related DEGs. G-I: Enriched Gene Ontology terms and KEGG pathways of 24 ferroptosis-related DEGs. J: Enriched Gene Ontology terms and KEGG pathways of 24 ferroptosis-related DEGs according to the Metascape. K: The correlation network of 24 ferroptosis-related DEGs according to the STRING database. L: The correlations heatmap of 24 ferroptosis-related DEGs.

Figure 2

LASSO regression and risk score calculation. A: Coefficient value of 24 ferroptosis-related DEGs. B: Partial likelihood deviance of 24 ferroptosis-related DEGs. C: Risk score and survival time distributions, and heatmaps of gene-expression levels of the ferroptosis-related signature based on the TCGA data. D: Kaplan-Meier analysis suggests the survival outcome in the high-risk and low-risk groups in the TCGA cohort. E: ROC curves and AUC values of the risk score model for predicting the 1-, 3-, and 5-year OS times in the TCGA cohort.

Figure 3

The validation of CDKN2A, GPX3 and SLC7A11 mRNA expression in patients with CRC. A-C: The validation of CDKN2A, GPX3 and SLC7A11 mRNA expression in several CRC and normal cell lines. D-E: The validation of CDKN2A, GPX3 and SLC7A11 mRNA expression in CRC and normal tissues. (Statistical significances were calculated using independent sample t-test. *P<0.05, **P<0.01, ***P<0.001, ****P<0.0001).

Figure 4

Associations between clinicopathologic features, tumor immunity and three selected ferroptosis-related genes in the TCGA-COAD dataset. A: ROC and AUC of CDKN2A, GPX3 and SLC7A11 to diagnose death for patients with CRC in the TCGA-COAD database. B-D: The relationships between GPX3, CDKN2A and SLC7A11 expression and infiltrating immune cells in the TCGA-COAD database. E-G: The relationships between GPX3, CDKN2A and SLC7A11 expression and CRC immune checkpoint genes of TCGA-COAD database.

Figure 5

Single cell localization of three selected ferroptosis-related genes and spatial transcriptome validation. A-B: Seventeen clusters were identified by t-SNE and uniform manifold approximation and projection (UMAP). C-D: Feature plots and spatial feature plots were utilized to illustrate the distribution expression of CDKN2A and SLC7A11. E: Seven major cell clusters were identified via UMAP. F: Dot plot of cells proportion in the respective cluster expressing selected marker genes (dot size), and average expression (color scale). G-I: UMAP plot of GPX3, SLC7A11 and CDKN2A expression across all cell clusters. J: Pseudo-time trajectory and modules of genes whose expression varied with pseudo-time. K: Pseudo-time analysis was used to plot the early-stage trajectories of CRC.

Figure 6

Prognostic nomogram for the 1-, 3-, and 5-year survival times of patients with CRC. A: Independent risk factors screened by multivariate Cox regression in the TCGA cohort were integrated into the nomogram model. B-D: Calibration curves of the nomogram for predicting 1-, 3-, and 5-year OS in the TCGA cohort. E-G: ROC curves and AUC values of the nomogram for predicting 1-, 3-, and 5-year OS.