IMPACT: a web server for exploring immunotherapeutic predictive and cancer prognostic biomarkers

Liu, Y.; Zhang, Y.; Xie, W.; Zhao, J.; Dong, Y.; Xu, C.; Wang, Y.; Li, M.; Wang, G.; Zhu, X.; Wang, W.; Lin, K.; Lu, H.; Han, Y.; Li, L.; Duan, J.; Cai, S.; Wang, J.; Wang, Z.

doi:10.1101/2023.01.31.526401

bioRxiv · 10.1101/2023.01.31.526401

IMPACT: a web server for exploring immunotherapeutic predictive and cancer prognostic biomarkers

Liu, Y.·Zhang, Y.·Xie, W.·Zhao, J.·Dong, Y.·Xu, C.·Wang, Y.·Li, M.·Wang, G.·Zhu, X.·Wang, W.·Lin, K.·Lu, H.·Han, Y.·Li, L.·Duan, J.·Cai, S.·Wang, J.·Wang, Z.

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Abstract

Immune checkpoint inhibitors (ICIs) are a breakthrough in oncology treatment, and studies of screening predictive biomarkers of ICIs are emerging. We developed a web server named IMPACT (http://impact.brbiotech.com/) to thoroughly explore immunotherapeutic predictive or prognostic biomarkers. IMPACT contains a large dataset of 6,276 patients treated with ICIs and integrates 11 well-designed function modules, enabling an in-depth solution for biomarkers exploration. Compared with the existing tools, IMPACT was implemented with one exclusive module for interaction analysis and several optimized conventional functions for discovering novel biomarkers. Specifically, the interaction analysis of biomarker-treatment effect is essential to determine whether a biomarker is predictive and/or prognostic for ICIs. Moreover, several optimized functions allow complicated biomarker exploration, including customized selections of variant types in more detail, automatically screening meaningful co-mutations among multiple genes, and selecting cut-off values for gene expression biomarkers. In summary, IMPACT is a comprehensive analysis resource to facilitate biomarker research of ICIs.

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Liu, Y., Zhang, Y., Xie, W., Zhao, J., Dong, Y., Xu, C., Wang, Y., Li, M., Wang, G., Zhu, X., Wang, W., Lin, K., Lu, H., Han, Y., Li, L., Duan, J., Cai, S., Wang, J., Wang, Z.. 2023-02-03. IMPACT: a web server for exploring immunotherapeutic predictive and cancer prognostic biomarkers. https://doi.org/10.1101/2023.01.31.526401

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