MET gene alterations predict poor survival following chemotherapy in patients with advanced cancer

Abstract

Background: To aid in oncology drug development, we investigated MET proto-oncogene receptor tyrosine kinase gene aberrations in 2,239 oncology patients who underwent next-generation sequencing (NGS) in clinical practice. Materials and methods: From November 2019 to January 2021, 2,239 patientswith advanced solid tumors who visited oncology clinics underwent NGS. The NGS panel included >500 comprehensive NGS tests using archival tissue specimens. Programmed death-ligand 1(PD-L1) 22C3 assay results and clinical records regarding initial chemotherapy were available for 1,137 (50.8%) and 1,761 (78.7%) patients, respectively for overall survival (OS) analysis. Results: The 2,239 patients represented 37 types of cancer. The NGS panel included >500 genes, microsatellite instability status, tumor mutational burden, and fusions. The most common cancer types were colorectal (N = 702), gastric (N = 481), and sarcoma (N = 180). MET aberrations were detected in 212 patients. All MET-amplified tumors had microsatellite stable status, and 8 had a high tumor mutational burden. Of 46 patients with MET-amplified cancers, 8 had MET-positive protein expression by immunohistochemistry (2+ and 3+). MET fusion was detected in 10 patients. Partner genes of MET fusion included ST7, TFEC, LRRD1, CFTR, CAV1, PCM1, HLA-DRB1, and CAPZA2. In survival analysis, patients with amplification of MET gene fusion had shorter OS and progression-free survival (PFS) than those without. Thus, MET aberration was determined to be a factor of response to chemotherapy. Conclusion: Approximately 2.1% and 0.4% of patients with advanced solid tumors demonstrated MET gene amplification and fusion, respectively, and displayed a worse response to chemotherapy and significantly shorter OS and PFS than those without MET gene amplification or fusion.

Keywords: MET; MET alterations; cancer; chemotherapy; next-generation sequencing; oncogene; overall survival analysis.

FIGURE 1

Classification of tumor types in patients enrolled in the study. (A) Distribution of tumor types in 2,239 patients. The most common type was colorectal cancer (31.4%), followed by gastric cancer (21.5%), and sarcoma (8.0%). (B) Diagram showing proportion of MET aberrations in the cohort, including amplification, fusion, and SNVs. CRC, Colorectal cancer; GC, Gastric cancer; CCC, cholangiocellular carcinoma; PACA, pancreatic cancer; NSCLC, non-small cell lung cancer; BLCA, bladder cancer; GBC, gallbladder cancer; HCC, hepatocellular carcinoma; BRCA, breast cancer; MUO, metastasis of unknown origin; NET, neuroendocrine tumor; AOV, ampulla of vater; HNC, head and neck cancer; GIST, gastrointestinal stromal tumor.

FIGURE 2

Genomic landscape of cancer patients with MET copy number variations. (A) Bar graph showing the incidence of MET amplification by tumor type. (B) The distribution of MET-amplified patients according to copy number. (C) The landscape of patients’ genomic profiles. Top panel, copy number of each patient; middle panel, clinical information including age, PD-L1 expression (IHC), MSI, sex, TMB, and cancer type; bottom panel, oncoprint showing SNV type of genes listed at the left. Left panel, the alterations rate of each gene in total samples (N = 46) with biological function annotation. IHC, immunohistochemistry; MSI, microsatellite instability; TMB, tumor mutational burden; SNV, single nucleotide variant.

FIGURE 3

Clinicopathological landscape of patients with MET fusions. (A) Diagram showing the distribution of patients and tumor types with MET fusion. (B) Chord diagram exhibiting flows or connections between the MET gene and other partner genes. (C) Landscape of the patient’s genomic profile. Upper panel, clinical information regarding MET expression (IHC), age, PD-L1, MSI, sex, TMB, and tumor type; lower panel, SNV profile of genes indicated at the left panel; right panel, mutation rate of each gene and biological functional annotation. IHC, immunohistochemistry; MSI, microsatellite instability; TMB, tumor mutational burden; SNV, single nucleotide variant.

FIGURE 4

MET-gene-associated SNV profiles. (A) Tumor types and proportions of patients with SNV in the MET gene. (B) The percentage of SNV samples for each cancer (SNV in MET gene). (C) Structure of MET protein and identified MET-gene-associated SNV in the group. (D) The signature of nucleotide changes showing the ratio of transition to transversion. (E) Bar graph showing the SNV type ratio by tumor types. SNV, single nucleotide variant. UK, unknown.

FIGURE 5

Correlation between MET gene alterations and response to first-line chemotherapy. (A) Cancer genomic landscape refers to the distribution pattern of MET gene alterations across the genome in tumor types. (B) Alluvial diagram showing the distribution of MET aberration in tumor types and the best response to first-line chemotherapy. Kaplan-Meier curves showing (C) overall survival (OS) and (D) progression-free survival (PFS) with (amplification of fusion) or without MET gene alterations.