Zhuang Zhicheng, Cai Huajun, Lin Hexin, Guan Bingjie, Wu Yong, Zhang Yiyi, Liu Xing, Zhuang Jinfu, Guan Guoxian
Department of Colorectal Surgery, The First Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, China.
Department of Radiation Oncology, Fujian Medical University Union Hospital, Fuzhou, Fujian, China.
J Oncol. 2021 Nov 18;2021:5818512. doi: 10.1155/2021/5818512. eCollection 2021.
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.
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.
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.
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.
近年来，细胞焦亡已被确认为一种炎症性程序性细胞死亡。然而，细胞焦亡在结肠癌（CC）中的预后作用仍不清楚。
将来自TCGA数据库的数据集TCGA-COAD作为训练队列。将来自GEO数据库的GSE17538作为验证队列。确定正常组织和肿瘤组织之间的差异表达基因（DEG）。根据细胞焦亡相关DEG的表达特征将患者分为两个亚组。采用LASSO回归分析构建最佳预后特征，并通过Kaplan-Meier、ROC、PCA和t-SNE分析验证其可靠性。并基于多变量Cox分析建立了列线图。在GO和KEGG中进行富集分析以研究潜在机制。此外，我们探讨了高风险组和低风险组之间浸润免疫细胞丰度和免疫微环境的差异。并且我们还预测了常见免疫检查点与风险评分的关联。最后，我们通过免疫组织化学在蛋白质水平验证了细胞焦亡相关枢纽基因的表达。
在TCGA队列中总共鉴定出23个细胞焦亡相关DEG。基于DEG将患者分为两个分子簇（MC）。Kaplan-Meier生存分析表明，MC1患者的总生存期（OS）明显比MC2患者差。MC中13个与总生存期（OS）相关的DEG用于构建预后特征。高风险组患者的OS比低风险组患者差。结合临床特征，发现风险评分是CC患者的独立预后因素。上述结果在外部数据集GSE17538中得到验证。建立了列线图并显示出优异的性能。基因本体论（GO）和京都基因与基因组百科全书（KEGG）分析表明，高风险组和低风险组之间不同的预后表现可能与局部炎症介导的免疫反应有关。进一步分析表明，高风险组比低风险组具有更强的免疫细胞浸润和更低的肿瘤纯度。通过风险评分与免疫检查点表达之间的相关性，预测含T细胞免疫球蛋白和粘蛋白结构域蛋白3（TIM-3）是高风险组的潜在治疗靶点。
13基因特征与CC患者的OS、免疫细胞、肿瘤纯度和免疫检查点相关，可为免疫治疗、预测预后提供依据，并帮助临床医生做出个体化治疗决策。
