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Identifying survival of pan-cancer patients under immunotherapy using genomic mutation signature with large sample cohorts

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Abstract

Although immune checkpoint inhibitors have led to durable clinical response in multiple cancers, only a small proportion of patients respond to this treatment. Therefore, we aim to develop a predictive model that utilizes gene mutation profiles to accurately identify the survival of pan-cancer patients with immunotherapy. Here, we develop and evaluate three different nomograms using two cohorts containing 1,594 cancer patients whose mutation profiles are obtained by MSK-IMPACT sequencing and 230 cancer patients receiving whole-exome sequencing, respectively. Using eighteen genes (SETD2, BRAF, NCOA3, LATS1, IL7R, CREBBP, TET1, EPHA7, KDM5C, MET, KMT2D, RET, PAK7, CSF1R, JAK2, FAT1, ASXL1 and SPEN), the first nomogram stratifies patients from both cohorts into High-Risk and Low-Risk groups. Pan-cancer patients in the High-Risk group exhibit significantly shorter overall survival and progression-free survival than patients in the Low-Risk group in both cohorts. Meanwhile, the first nomogram also accurately identifies the survival of patients with melanoma or lung cancer undergoing immunotherapy, or pan-cancer patients treated with anti-PD-1/PD-L1 inhibitor or anti-CTLA-4 inhibitor. The model proposed is not a prognostic model for the survival of pan-cancer patients without immunotherapy, but a simple, effective and robust predictive model for pan-cancer patients’ survival under immunotherapy, and could provide valuable assistance for clinical practice.

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Data Availability

The datasets of patients treated with ICIs used in our study are downloaded from the Memorial Sloan Kettering Cancer Center (MSKCC) dataset and the Dana-Farber Cancer Institute. The information of MSK non-ICIs patients is also downloaded from the MSKCC dataset. The TCGA dataset is downloaded from the UCSC XENA database. The data used and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Funding

This study was supported by National Natural Science Foundation of China (project number 81973149, 82304250 and 81773551).

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  1. Liuchao Zhang and Yuanyuan Wang have been contributed equally to this work.

Authors and Affiliations

  1. Department of Epidemiology and Biostatistics, Public Health College, Harbin Medical University, Harbin, Hei Longjiang province, 150081, China

    Liuchao Zhang, Liuying Wang, Meng Wang, Shuang Li, Jia He, Jianxin Ji, Kang Li & Lei Cao

  2. Department of Nutrition and Food Hygiene, Public Health College, Harbin Medical University, Harbin, 150081, China

    Yuanyuan Wang

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  1. Liuchao Zhang
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Contributions

Study design: Z-LC, LK, CL. Data collection: Z-LC, W-YY. Data analysis and interpretation: Z-LC, W-YY. Writing of the manuscript: Z-LC, W-YY. Revision of the manuscript: CL, W-LY, WM, LS, HJ, J-JX. All authors read and approved the final manuscript.

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Correspondence to Kang Li or Lei Cao.

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Zhang, L., Wang, Y., Wang, L. et al. Identifying survival of pan-cancer patients under immunotherapy using genomic mutation signature with large sample cohorts. J Mol Med 102, 69–79 (2024). https://doi.org/10.1007/s00109-023-02398-1

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  • DOI: https://doi.org/10.1007/s00109-023-02398-1

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