Pan-cancer analysis of MET mutation and its association with the efficacy of immune checkpoint blockade

Abstract

The mesenchymal-epithelial transition factor (MET) proto-oncogene plays important roles during tumor development. Recently, evidence has revealed MET signaling may impact tumor immunogenicity and regulate the immune response. Here we conducted a comprehensive bioinformatic and clinical analysis to explore the characteristics of MET mutation and its association with the outcomes in pan-cancer immunotherapy. In 4149 patients with 12 tumor types treated with immune checkpoint inhibitors, MET mutation indicated favorable overall survival (hazard ratio = 0.61; 95% CI, 0.50-0.74; P < 0.001), progression-free survival (hazard ratio = 0.74; 95% CI, 0.60-0.92; P = 0.01), and objective response rate (40.3% vs. 28.1%; P = 0.003). Moreover, we developed a nomogram to estimate the 12-month and 24-month survival probabilities after the initiation of immunotherapy. Further multi-omics analysis on both intrinsic and extrinsic immune landscapes revealed that MET mutation enhanced tumor immunogenicity, enriched infiltration of immune cells, and improved immune responses. In summary, MET mutation improves cancer immunity and is an independent biomarker for favorable outcomes in pan-cancer immunotherapy. These results may influence clinical practices, guide treatment decision-making, and develop immunotherapy for personalized care.

Keywords: Biomarker; Cancer; Immune checkpoint inhibitor; Immunotherapy; Mesenchymal-epithelial transition factor; Tumor immunogenicity.

Figure 1

MET mutation as an independent biomarker for favorable outcomes in pan-cancer immunotherapy. (A) Kaplan–Meier survival analysis stratified by MET mutation status in 2539 cancer patients with 7 tumor types treated with ICIs in the discovery cohort. (B) The association between MET mutation and OS in 1610 patients with 10 tumor types in the validation cohort. (C–E) The comparison of OS (C), PFS (D), and ORR (E) between patients with MET mutation and patients with MET non-mutation in 4149 subjects with 12 tumors treated with ICIs. (F, G) Univariate (F) and multivariate (G) Cox analyses of the association between MET mutation and OS in 4149 patients with 12 tumors treated with ICIs. (H) The nomogram for predicting the 12- and 24-month survival. It can calculate overall survival from the date of immunotherapy start. To use, users should locate the “age” axis and draw a line up to the “point” axis to get a score associated with age and repeat for the other features to get their scores. Afterward, the users sum all scores, locate it on the “total point” axis, and draw a line to the “12-month survival” axis to get the 12-month OS probability. (I) Calibration plots for validation of the 12- and 24-month survival from the nomogram in the discovery cohort. The average predicted probability (X-axis) was plotted against the observed Kaplan-Meier estimate in the subgroup (Y-axis, 95% CIs of the estimates are presented as vertical lines). The continuous line is the reference line, indicating what an optimal nomogram would be. (J, K) Based on the optimal cutoff value (total points = 60) derived from the nomogram, a low score was associated with favorable OS in both the discovery cohort (J) and validation cohort (K). CI, confidence interval; CUP, cancer of unknown primary; CR, complete response; EC, esophagogastric cancer; HNC, head and neck carcinoma; HR, hazard ratio; ICI, immune checkpoint inhibitor; LC, lung cancer; ORR, objective response rate; OS, overall survival; PFS, progression-free survival; PD, progressive disease; PR, partial response; SD, stable disease.

Figure 2

The characteristics of MET mutation in 33 tumor types based on The Cancer Genome Atlas (TCGA) cohort. (A) The mutation frequencies of MET gene across 33 tumor types. (B) The subtypes and distributions of MET somatic mutations. X-axis, amino acid; Y-axis, numbers of MET mutations. Sema, Sema domain (59–498); PSI, plexin repeat (520–561); PSI, plexin repeat (520–561; 657–728; 742–815); Pkinase_Tyr, protein tyrosine kinase (1078–1336). Green, missense mutation; black, truncating mutation; orange, splice mutation; purple, fusion mutation; brown, Inframe mutation. (C, D) Comparison of PFS (C) and OS (D) between patients with MET mutation and patients with MET non-mutation in 10,953 subjects with 33 tumor types. PFS, progression-free survival; OS, overall survival.

Figure 3

The differences in tumor immune microenvironment between patients with MET-mutant and MET-non-mutant tumors. (A) Comparison of TMB, non-silent mutation rate, and silent mutation rate between MET-mutant and MET-non-mutant tumors. (B) mRNA expression levels of PD-1, PD-L1, and CTLA-4 in patients with MET-mutant and MET-non-mutant tumors. (C) The immune cell infiltration revealed by leukocyte fractions, lymphocyte fraction, and tumor-infiltrating lymphocyte fraction in MET-mutant and MET-non-mutant tumors. (D) The abundances of SNV neoantigens/Indel neoantigens and the diversity of TCR/BCR in MET-mutant and MET-non-mutant tumors. (E) Differences of 29 immune signatures estimated by ssGSEA between MET-mutant and MET-non-mutant tumors. (F) Comparison of 8 immune and 2 stromal cell populations between MET-mutant and MET-non-mutant tumors. (G) Expression differences of 16 MHC-related antigen-presenting molecules and 25 co-stimulators between MET-mutant and MET-non-mutant tumors. (H) Comparison of 48 chemokines and their receptors between MET-mutant and MET-non-mutant tumors. (I) Expression differences of 39 immune-stimulators between MET-mutant and MET-non-mutant tumors. BCR, B cell receptor; CTLA-4, cytotoxic T-lymphocyte-associated antigen 4; MHC, major histocompatibility complex; PD-1, programmed cell death protein 1; PD-L1, programmed cell death ligand 1; SNV, single nucleotide variants; TCR, T cell receptor; TIL, tumor-infiltrating lymphocyte; TMB, tumor mutation burden.

Figure 4

COSMIC reference signatures associated with MET mutation. (A) The illustrations of four identified SBS signatures related to MET mutation and their frequencies in MET-mutant and MET-non-mutant tumors. Bold black, SBS signature and its known etiologies. Green, frequency in MET-mutant cancer. Orange, frequency in MET-non-mutant cancer. (B) The associations between four identified mutation signatures with OS in cancer immunotherapy. HR, hazard ratio; OS, overall survival; SBS, single base substitution.

Figure S1

Univariate (A) and multivariate (B) Cox analyses of the association between MET mutation and progression-free survival in 4149 patients with 12 tumors treated with immune checkpoint inhibitors.