Journal of Translational MedicineBioinformaticsPeer-reviewed journal article
Three Conserved Immune Dysfunction and Exclusion Subtypes in Bladder and Pan-cancers: Prognostic and Immunotherapeutic Significance
Kun Chan ZhengiD, Youlong HaiiD, Hongqi CheniD, Yukun ZhangiD, Xiaoyong HuiD, Kai NiiD
Abstract
Molecular subtyping is expected to enable bladder cancer (BC) precise treatment. However, its clinical application remains defective and controversial. Given the significance of tumor immune dysfunction and exclusion (TIDE) in tumor immune escape and immunotherapy, we aimed to develop a novel TIDE-based subtyping method to facilitate personalized management. Transcriptome data of BC was used to evaluate the heterogeneity and the status of TIDE patterns. We identified 69 TIDE biomarker genes and classified BC samples into three subtypes. Subtype I showed the lowest TIDE status and malignancy with the best prognosis and highest sensitivity to immune checkpoint blockade (ICB) treatment, which was enriched of metabolic related signaling pathways. Subtype III represented the highest TIDE status and malignancy with the poorest prognosis and resistance to ICB treatment, resulting from its inhibitory immune microenvironment and T cell terminal exhaustion. Subtype II was in a transitional state with intermediate TIDE level, malignancy, and prognosis. We further confirmed the existence and characteristics of our novel TIDE subtypes using real-world BC samples. This subtyping method was proved to be more efficient than known methods in identifying non-responders to immunotherapy. We also found that combining our TIDE subtypes with known biomarkers can improve the sensitivity and specificity in predicting ICB response. Moreover, besides guiding ICB treatment, this classification approach can assist in selecting the frontline or recommended drugs. Finally, the TIDE subtypes are conserved across pan-tumors. In conclusion, our novel TIDE-based strategy is a powerful clinical tool for BC and pan-cancer patients, and potentially guiding personalized immunotherapy.
- organism: human
- assay: bulk RNA-seq
- research focus: clustering
- research focus: differential expression
- research focus: protein structure prediction
- research focus: drug response / drug discovery
- approach: statistical model
- Citations
- 34
- FWCI
- 5.62
- Field percentile
- top 3%
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