| Literature DB >> 35813478 |
Zheng Zhou1, Yujia Zheng1, Shaobo Mo2, Shuofeng Li3, Xinlei Zheng4, Ran Wei3, Tao Fan1, Tianli Chen3, Chu Xiao1, Chunxiang Li1, Jie He1.
Abstract
Our study aims at developing an interferon-stimulated genes (ISGs) signature that could predict overall survival (OS) in cancer patients, which enrolled a total of 5643 pan-cancer patients. Linear models for microarray data method analysis were conducted to identify the differentially expressed prognostic genes in the global ISGs family. Time-dependent receiver operating characteristic (ROC) and Kaplan-Meier survival analysis were used to test the efficiency of a multi-gene signature in predicting the prognosis of pan-cancer patients. The prognostic performance and potential biological function of gene signature were verified by quantitative real-time PCR in a pan-cancer independent cohort. Three ISGs genes were finally identified to build a classifier, a specific risk score formula, with which patients were classified into the low- or high-risk groups. Time-dependent ROC analyses proved prognostic accuracy. Then, its prognostic value was validated in seven external validation series. A nomogram was constructed to guide the individualized treatment of patients with lung adenocarcinoma. Biological pathway and tumor immune infiltration analysis showed that the signature might cause poor prognosis by blocking NK cell activation. Finally, the signature in our centers was confirmed by real-time quantitative PCR. A robust ISGs-related feature was discovered to effectively classify pan-cancer patients into subgroups with different OS. © The author(s).Entities:
Keywords: Interferon-stimulated Genes; Natural Killer Cells; Pan-cancer Study; Tumor Biomarkers
Mesh:
Substances:
Year: 2022 PMID: 35813478 PMCID: PMC9254476 DOI: 10.7150/ijbs.71385
Source DB: PubMed Journal: Int J Biol Sci ISSN: 1449-2288 Impact factor: 10.750