TIRSF: a web server for screening gene signatures to predict Tumor immunotherapy response. Issue Volume 50:Issue W1(2022) (12th May 2022)

• Record Type: Journal Article
• Authors: Chen, Li; Chen, Tianjian; Zhang, Ya; Lin, Haichen; Wang, Ruihan; Wang, Yihang; Li, Hongyu; Zuo, Zhixiang; Ren, Jian; Xie, Yubin
• Is Part Of: Nucleic acids research. Volume 50:Issue W1(2022)
• Page Start: W761
• Page End: W767
• Publication Date: 2022-05-12
• Subjects: Nucleic acids -- Periodicals; Molecular biology -- Periodicals; 572.805
• DOI: 10.1093/nar/gkac374
• Languages: English
• ISSNs: 0305-1048

Abstract

Abstract: Immune checkpoint blockade (ICB) therapy has been successfully applied to clinically therapeutics in multiple cancers, but its efficacy varies greatly among different patients and cancer types. Therefore, the construction of gene signatures to identify patients who could benefit from ICB therapy is particularly important for precision cancer treatment. However, due to the lack of a user-friendly platform, the construction of such gene signatures is a great challenge for clinical investigators who have limited programming skills. In light of this challenge, we developed a web server called Tumor Immunotherapy Response Signature Finder(TIRSF) for the construction of gene signatures to predict ICB therapy response in cancer patients. TIRSF consists of three functional modules. The first module is the Signature Discovery module which provides signature construction and performance evaluation functionalities. The second is a module for response prediction based on the TIRSF signatures, which enables response prediction and prognostic analysis of immunotherapy samples. The last is a module for response prediction based on existing signatures. This module currently integrates 24 published signatures for ICB therapy response prediction. Together, all of above features can be freely accessed at http://tirsf.renlab.org/ . Graphical Abstract: