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Updated: Sep 23, 2025

Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
TIRSF: a web server for screening gene signatures to predict Tumor immunotherapy response
Li Chen1, Tianjian Chen1, Ya Zhang1
1School of Life Sciences, Institute of Precision Medicine, the First Affiliated Hospital, Sun Yat-sen University, Guangzhou 510060, China.
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/.
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