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T Cell-to-Stroma Enrichment (TSE) score: a gene expression metric that predicts response to immune checkpoint inhibitors (ICI) in patients with urothelial cancer

Description

The TSE score is a transcriptomic metric that predicts response to ICIs. The study reported by Rijnders, Nakauma-Gonzalez, et al., entitled Gene-expression-based T-Cell-to-Stroma Enrichment (TSE) score predicts response to immune checkpoint inhibitors in urothelial cancer was published in Nature Communications.

We identified the abundance of T cells as a predictor of response, while the abundance of stromal cells/products is a predictor of non-response to ICI. Both predictors are affected by tumor purity, but when combined into the TSE score, the effect of purity disappears making the TSE score a robust biomarker even for immune cell-riched organs such as lymph nodes (Figure). Additionally, the TSE score can predict responders and non-responders because it combines the positive and negative predictive values of T and stromal cells into one single metric.

The TSE score is a robust biomarker that outperforms the tumor mutational burden (TMB). Patients with a positive TSE score live twice as long as other patients.

Calculate the TSE score

Please refer to the R package TSECalculatoR.

Scripts in this repository

The scripts in this repository were used to process the data provided by the Hartwig Medical Foundation (HMF) and to generate figures and results for the manuscript. Access to HMF data is controlled and must be requested under the request number DR-176. WGS data, RNA-seq data and corresponding clinical data are freely available for academic use from the HMF through standardized procedures. Request forms can be found at https://www.hartwigmedicalfoundation.nl.

Reference

Rijnders, M., Nakauma-González, J.A., Robbrecht, D.G.J. et al. Gene-expression-based T-Cell-to-Stroma Enrichment (TSE) score predicts response to immune checkpoint inhibitors in urothelial cancer. Nat Commun 15, 1349 (2024). https://doi.org/10.1038/s41467-024-45714-0

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Calculate the TSE score to predict response to ICIs

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