Development and Validation of a Robust Pyroptosis-Related Signature for Predicting Prognosis and Immune Status in Patients with Colon Cancer

Abstract

Background. Pyroptosis has been confirmed as a type of inflammatory programmed cell death in recent years. However, the prognostic role of pyroptosis in colon cancer (CC) remains unclear. Methods. Dataset TCGA-COAD which came from the TCGA portal was taken as the training cohort. GSE17538 from the GEO database was treated as validation cohorts. Differential expression genes (DEGs) between normal and tumor tissues were confirmed. Patients were classified into two subgroups according to the expression characteristics of pyroptosis-related DEGs. The LASSO regression analysis was used to build the best prognostic signature, and its reliability was validated using Kaplan–Meier, ROC, PCA, and t-SNE analyses. And a nomogram based on the multivariate Cox analysis was developed. The enrichment analysis was performed in the GO and KEGG to investigate the potential mechanism. In addition, we explored the difference in the abundance of infiltrating immune cells and immune microenvironment between high- and low-risk groups. And we also predicted the association of common immune checkpoints with risk scores. Finally, we verified the expression of the pyroptosis-related hub gene at the protein level by immunohistochemistry. Results. A total of 23 pyroptosis-related DEGs were identified in the TCGA cohort. Patients were classified into two molecular clusters (MC) based on DEGs. Kaplan–Meier survival analysis indicated that patients with MC1 represented significantly poorer OS than patients with MC2. 13 overall survival- (OS-) related DEGs in MCs were used to construct the prognostic signature. Patients in the high-risk group exhibited poorer OS compared to those in the low-risk group. Combined with the clinical features, the risk score was found to be an independent prognostic factor of CC patients. The above results are verified in the external dataset GSE17538. A nomogram was established and showed excellent performance. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses indicated that the varied prognostic performance between high- and low-risk groups may be related to the immune response mediated by local inflammation. Further analysis showed that the high-risk group has stronger immune cell infiltration and lower tumor purity than the low-risk group. Through the correlation between risk score and immune checkpoint expression, T-cell immunoglobulin and mucin domain-containing protein 3 (TIM-3) was predicted as a potential therapeutic target for the high-risk group. Conclusion. The 13-gene signature was associated with OS, immune cells, tumor purity, and immune checkpoints in CC patients, and it could provide the basis for immunotherapy and predicting prognosis and help clinicians make decisions for individualized treatment.

Integrated Analysis of Necroptosis-Related Genes for Prognosis, Immune Microenvironment Infiltration, and Drug Sensitivity in Colon Cancer

“…NRS-score showed a significant positive correlation with ESTIMATES score and stromal score, but a negative correlation with tumor purity. In other words, tumors in the high NRS-score group were of lower purity and had a worse prognosis, consistent with the findings of several previous studies in colon cancer ( 67 , 68 ). We hypothesized that this might be due to the recruitment of more immune-suppressive cells in low-purity tumors than in high-purity tumors.…”

Establishment of pyroptosis-related genes prognostic model for forecasting status of immune and inflammation in patients with colorectal cancer

“…Pyroptosis can also inhibit the tumor as certain possible prognosis biomarkers for tumors [8] . In CRC, several PRGs based models were constructed to forecast prognosis [9][10][11][12] . However, a new model as well as a comprehensive study have still been required, and our investigation was carried on to attain this purpose.…”

“…In a former study by Wei Song et al [9] , a PRG_score for forecasting recurrence-free survival (RFS) was established. Different prognosis PRGs models were also developed by Jiawei Rao et al [10] , Zhicheng Zhuang et al [11] , and Chen Zheng et al [12] . However, in our investigation, we rstly set up a new pyroptosisassociated prognosis gene modeling for CRC, which gives more selections for prognosis forecast in CRC.…”

Ogt Demonstrated Conspicuous Clinical Significance in Cancers, from Pan-Cancer to Small-Cell Lung Cancer

“…ESTIMATE [ 32 – 35 ] is a tool used to measure scores of patients based on gene expression profiles, including a stromal score (for stromal cells), an immune score (for immune cells), and an estimated score (for tumor purity). Another algorithm, TIMER [ 36 – 39 ], can be used to detect immune cell infiltration levels.…”