Jiang Xiaoye, Jiang Zhongxiang, Xiang Lichun, Chen Xuenuo, Wu Jiao, Jiang Zheng
Departments of Gastroenterology, Chongqing Medical University First Affiliated Hospital, Chongqing, 400016, China.
Cancer Cell Int. 2021 Feb 8;21(1):95. doi: 10.1186/s12935-021-01782-6.
Increasing evidence has shown that cytolytic activity (CYT) is a new immunotherapy biomarker that characterises the antitumour immune activity of cytotoxic T cells and macrophages. In this study, we established a prognostic model associated with CYT.
A prognostic model based on CYT-related genes was developed. Furthermore, aberrant expression of genes of the model in colon cancer (CC) was identified by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC) assays. Next, the correlation between the model and T-cell infiltration in the CC microenvironment was analysed. The Tumour Immune Dysfunction and Exclusion (TIDE) algorithm and subclass mapping were used to predict clinical responses to immune checkpoint inhibitors.
In total, 280 of the 1418 genes were differentially expressed based on CYT. A prognostic model (including HOXC8 and MS4A2) was developed based on CYT-related genes. The model was validated using the testing set, the whole set and a Gene Expression Omnibus (GEO) cohort (GSE41258). Gene set enrichment analysis (GSEA) and other analyses showed that the levels of immune infiltration and antitumour immune activation in low-risk-score tumours were greater than those in high-risk-score tumours. CC patients with a low-risk-score showed more promise in the response to anti-immune checkpoint therapy.
Overall, our model may precisely predict the overall survival of CC and reflect the strength of antitumour immune activity in the CC microenvironment. Furthermore, the model may be a predictive factor for the response to immunotherapy.
越来越多的证据表明，细胞溶解活性（CYT）是一种新的免疫治疗生物标志物，可表征细胞毒性T细胞和巨噬细胞的抗肿瘤免疫活性。在本研究中，我们建立了一个与CYT相关的预后模型。
开发了一种基于CYT相关基因的预后模型。此外，通过逆转录定量聚合酶链反应（RT-qPCR）和免疫组织化学（IHC）分析确定该模型基因在结肠癌（CC）中的异常表达。接下来，分析该模型与CC微环境中T细胞浸润之间的相关性。使用肿瘤免疫功能障碍和排除（TIDE）算法及亚类映射来预测对免疫检查点抑制剂的临床反应。
基于CYT，1418个基因中共有280个基因差异表达。基于CYT相关基因开发了一个预后模型（包括HOXC8和MS4A2）。使用测试集、全集和基因表达综合数据库（GEO）队列（GSE41258）对该模型进行验证。基因集富集分析（GSEA）和其他分析表明，低风险评分肿瘤中的免疫浸润水平和抗肿瘤免疫激活水平高于高风险评分肿瘤。低风险评分的CC患者对抗免疫检查点治疗的反应更有前景。
总体而言，我们的模型可能准确预测CC的总生存期，并反映CC微环境中抗肿瘤免疫活性的强度。此外，该模型可能是免疫治疗反应的一个预测因素。
