Suppr超能文献

基于 TNF 家族的signature 用于预测结直肠癌患者预后、肿瘤免疫特征和免疫治疗反应的开发和验证。

Development and Validation of a TNF Family-Based Signature for Predicting Prognosis, Tumor Immune Characteristics, and Immunotherapy Response in Colorectal Cancer Patients.

机构信息

Department of Integrated Traditional Chinese & Western Medicine, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China.

Department of Nephrology, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China.

出版信息

J Immunol Res. 2021 Sep 9;2021:6439975. doi: 10.1155/2021/6439975. eCollection 2021.

Abstract

In this study, a comprehensive analysis of TNF family members in colorectal cancer (CRC) was conducted and a TNF family-based signature (TFS) was generated to predict prognosis and immunotherapy response. Using the expression data of 516 CRC patients from The Cancer Genome Atlas (TCGA) database, TNF family members were screened to construct a TFS by using the univariate Cox proportional hazards regression and the least absolute shrinkage and selection operator- (LASSO-) Cox proportional hazards regression method. The TFS was then validated in a meta-Gene Expression Omnibus (GEO) cohort ( = 1162) from the GEO database. Additionally, the tumor immune characteristics and predicted responses to immune checkpoint blockade in TFS-based risk subgroups were analyzed. Eight genes (TNFRSF11A, TNFRSF10C, TNFRSF10B, TNFSF11, TNFRSF25, TNFRSF19, LTBR, and NGFR) were used to construct the TFS. Compared to the high-risk patients, the low-risk patients had better overall survival, which was verified by the GEO data. In addition, a high TFS risk score was associated with high infiltration of regulatory T cells (Tregs), nonactivated macrophages (M0), natural killer cells, immune escape phenotypes, poor immunotherapy response, and tumorigenic and metastasis-related pathways. Conversely, a low TFS risk score was related to high infiltration of resting CD4 memory T cells and resting dendritic cells, few immune escape phenotypes, and high sensitivity to immunotherapy. Thus, the eight gene-based TFS is a promising index to predict the prognosis, immune characteristics, and immunotherapy response in CRC, and our results also provide new understanding of the role of the TNF family members in the prognosis and treatment of CRC.

摘要

在这项研究中,对结直肠癌(CRC)中的 TNF 家族成员进行了全面分析,并生成了基于 TNF 家族的特征(TFS),以预测预后和免疫治疗反应。使用来自癌症基因组图谱(TCGA)数据库的 516 名 CRC 患者的表达数据,通过单变量 Cox 比例风险回归和最小绝对收缩和选择算子-(LASSO-)Cox 比例风险回归方法筛选 TNF 家族成员,构建 TFS。然后,在来自 GEO 数据库的 GEO 荟萃基因表达数据集(=1162)中验证 TFS。此外,分析了 TFS 风险亚组中的肿瘤免疫特征和预测对免疫检查点阻断的反应。使用 8 个基因(TNFRSF11A、TNFRSF10C、TNFRSF10B、TNFSF11、TNFRSF25、TNFRSF19、LTBR 和 NGFR)构建 TFS。与高危患者相比,低危患者的总体生存率更好,这一结果得到了 GEO 数据的验证。此外,高 TFS 风险评分与调节性 T 细胞(Tregs)、非激活巨噬细胞(M0)、自然杀伤细胞的高浸润、免疫逃逸表型、免疫治疗反应差以及肿瘤发生和转移相关途径有关。相反,低 TFS 风险评分与静息 CD4 记忆 T 细胞和静息树突状细胞的高浸润、免疫逃逸表型少以及对免疫治疗的高敏感性有关。因此,基于 8 个基因的 TFS 是预测 CRC 预后、免疫特征和免疫治疗反应的有前途的指标,我们的结果还为 TNF 家族成员在 CRC 预后和治疗中的作用提供了新的认识。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/91f8/8448595/1719546b9cfd/JIR2021-6439975.001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验