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PathwayTMB: A pathway-based tumor mutational burden analysis method for predicting the clinical outcome of cancer immunotherapy.

ABSTRACT: Immunotherapy has become one of the most promising therapy methods for cancer, but only a small number of patients are responsive to it, indicating that more effective biomarkers are urgently needed. This study developed a pathway analysis method, named PathwayTMB, to identify genomic mutation pathways that serve as potential biomarkers for predicting the clinical outcome of immunotherapy. PathwayTMB first calculates the patient-specific pathway-based tumor mutational burden (PTMB) to reflect the cumulative extent of mutations for each pathway. It then screens mutated survival benefit-related pathways to construct an immune-related prognostic signature based on PTMB (IPSP). In a melanoma training set, IPSP-high patients presented a longer overall survival and a higher response rate than IPSP-low patients. Moreover, the IPSP showed a superior predictive effect compared with TMB. In addition, the prognostic and predictive value of the IPSP was consistently validated in two independent validation sets. Finally, in a multi-cancer dataset, PathwayTMB also exhibited good performance. Our results indicate that PathwayTMB could identify the mutation pathways for predicting immunotherapeutic survival, and their combination may serve as a potential predictive biomarker for immune checkpoint inhibitor therapy.

SUBMITTER: Li X

PROVIDER: S-EPMC10514137 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

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PathwayTMB: A pathway-based tumor mutational burden analysis method for predicting the clinical outcome of cancer immunotherapy.

Li Xiangmei X He Yalan Y Jiang Ying Y Pan Bingyue B Wu Jiashuo J Zhao Xilong X Huang Junling J Wang Qian Q Cheng Liang L Han Junwei J

Molecular therapy. Nucleic acids 20230907

Immunotherapy has become one of the most promising therapy methods for cancer, but only a small number of patients are responsive to it, indicating that more effective biomarkers are urgently needed. This study developed a pathway analysis method, named PathwayTMB, to identify genomic mutation pathways that serve as potential biomarkers for predicting the clinical outcome of immunotherapy. PathwayTMB first calculates the patient-specific pathway-based tumor mutational burden (PTMB) to reflect th ...[more]

PMID: 37744173

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Project description:BackgroundAbnormalities in the KEPA1-NRF2 pathway have a role in cancer progression, metastasis, and resistance to chemo- and radiotherapies. Persistent activation of NRF2 associates with poor prognosis across different cancer types. However, the beneficial therapeutic strategy to harness this pathway in cancer remains unclear. This study aimed to investigate the clinical outcome with immunotherapy in NFE2L2/KEAP1 mutant population.Materials and methodsWe investigated the correlation between NFE2L2/KEAP1 mutations and tumor mutational burden (TMB) and programmed death-ligand 1 (PD-L1) expression status to identify the therapeutic vulnerability. For this purpose, relevance analysis with TMB value was performed in 9,040 patients with cancer, and relevance analysis with PD-L1 expression was performed in 3,457 patients. The Memorial Sloan Kettering Cancer Center (MSKCC) database and real-world evidence were used to assess the immunotherapy response in NFE2L2/KEAP1 mutant subsets.ResultsNFE2L2/KEAP1 mutations occurred in various cancers, and the highest mutation incidences occurred in lung squamous cell carcinoma (LUSC) at 19.16% (NFE2L2) and 10.31% (KEAP1). We confirmed that higher TMB value and PD-L1 expression were associated with NFE2L2/KEAP1 mutations compared with wild-type, especially in non-small lung cancer. MSKCC database analysis showed the improved survival of patients with NFE2L2/KEAP1 mutant with immunotherapy compared with other treatments (median overall survival 22.52 VS 12.89, p = .0034). Real-world evidence further confirmed the efficacy of immunotherapy in the mutant population.ConclusionOur study revealed that patients with NFE2L2/KEAP1 mutant could achieve improved outcomes from immunotherapy than the other treatments. These findings may broaden the application of immune checkpoint blockade to patients harboring NFE2L2/KEAP1 mutations.Implications for practiceNFE2L2/KEAP1 alterations occur frequently in multiple cancer types and are associated with poor prognosis; however, the efficacious strategy to inhibit this pathway in cancer is poorly understood. This study was designed to analyze the mutational characteristics of NFE2L2/KEAP1 alterations in 9,243 Chinese patients. The highest mutation incidences occurred in lung squamous cell carcinoma at 19.16% (NFE2L2) and 10.31% (KEAP1). Relevance analysis showed the NFE2L2/KEAP1 mutant subsets were associated with higher tumor mutational burden value and programmed death-ligand 1 expression. Clinical data further confirmed NFE2L2/KEAP1 mutations correlate with improved outcome with immunotherapy. These findings suggest the clinical application of immunotherapy in the NFE2L2/KEAP1 mutant population.

Dataset Information

PathwayTMB: A pathway-based tumor mutational burden analysis method for predicting the clinical outcome of cancer immunotherapy.

Publications

PathwayTMB: A pathway-based tumor mutational burden analysis method for predicting the clinical outcome of cancer immunotherapy.

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