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. 2025 Jul 14;32(7):403.
doi: 10.3390/curroncol32070403.

MET Exon 14 Skipping Mutations in Lung Cancer: Clinical-Pathological Characteristics and Immune Microenvironment

Qianqian Xue  1   2   3 , Yue Wang  1   2   3 , Qiang Zheng  1   2   3 , Ziling Huang  1   2   3 , Yicong Lin  1   2   3 , Yan Jin  1   2   3 , Yuan Li  1   2   3
Affiliations

MET Exon 14 Skipping Mutations in Lung Cancer: Clinical-Pathological Characteristics and Immune Microenvironment

Qianqian Xue et al. Curr Oncol. .

Abstract

MET exon 14 skipping mutations have emerged as significant driver alterations in non-small-cell lung cancer (NSCLC), contributing to tumor progression. This study examines the immune microenvironment in NSCLC patients with these mutations and its prognostic implications. We performed multiplex immunofluorescence (mIF) staining on formalin-fixed paraffin-embedded (FFPE) tissue samples from nine NSCLC patients, including four recurrent/metastatic and five non-recurrent/non-metastatic patients. Two panels assessed immune cell markers (CD8, CD4, CD20, CD68, and FoxP3) and immune checkpoints (PD-L1, LAG3, and TIM3). Immune cell infiltration and checkpoint expression were analyzed using HALOTM software (version 3.6.4134.464). Nearest neighbor analysis was conducted to assess the proximity of immune cells to tumor cells. Univariate Cox regression analysis assessed factors associated with disease-free survival (DFS). CD8+TIM3+ and CD8+LAG3+ cells were predominantly located in the tumor parenchyma of recurrent/metastatic patients but localized to the stroma in non-recurrent/non-metastatic patients. Non-recurrent/non-metastatic patients exhibited a higher density of tertiary lymphoid structures and closer proximity of CD20+ B cells, CD8+TIM3+, and CD8+LAG3+ cells to tumor cells compared to recurrent/metastatic patients, though the differences were not statistically significant. Cox regression analysis suggested a potential association between higher densities of CD8+TIM3+ cells and improved DFS (HR = 0.89), though these findings did not reach statistical significance. Our findings suggest that differences in immune microenvironmental factors, particularly those related to immune checkpoint expression (TIM3 and LAG3), may influence clinical outcomes in NSCLC patients with MET exon 14 skipping mutations. Further studies are needed to validate these observations and explore potential therapeutic implications.

Keywords: MET exon 14 skipping mutation; immune checkpoints; immune microenvironment; multiplex immunofluorescence; non-small-cell lung cancer.

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Conflict of interest statement

The authors have no relevant financial or non-financial interests to disclose.

Figures

Figure 1
Figure 1
Co-mutation frequencies among patients with MET exon 14 skipping mutations.
Figure 2
Figure 2
Multiplex immunofluorescence (mIF) staining results for a representative sample of Panel 1 (A) and Panel 2 (B). (C–E) Schematic of the analysis workflow. Region segmentation—red indicates tumor parenchyma, green indicates stroma (C); nuclear identification (D); and identification of positive cells in each channel (E). (F,G) Identification and quantification of various infiltrating immune cells in different regions for Panel 1 (F) and Panel 2 (G).
Figure 3
Figure 3
Percentage of each infiltrating immune cell type within entire field of view (A), within the tumor parenchyma (B), and within the tumor stroma (C). Panels (D–J) show the distribution of various immune cell types in both the tumor parenchyma and stroma. With R/M, with recurrent/metastatic patients; Without R/M, without recurrent/metastatic patients.
Figure 4
Figure 4
Differences in infiltrating immune cells between recurrent/metastatic and non-recurrent/non-metastatic patients in the whole-section view (A) and the tumor stroma (B). With R/M, with recurrent/metastatic patients; Without R/M, without recurrent/metastatic patients. ns.—p > 0.05.
Figure 5
Figure 5
(A,B) Schematic representation of tertiary lymphoid structures. The multiplex immunofluorescence staining image (A); the corresponding HALOTM software model (B). (C) Comparison of tertiary lymphoid structures between recurrent/metastatic and non-recurrent/non-metastatic patients. ns.—p > 0.05.
Figure 6
Figure 6
(A–C) Schematic representation of the nearest neighbor analysis for CD8+TIM3+ cells in Panel 2. The multiplex immunofluorescence staining image (A); the in situ map from HALOTM analysis (B); and the HALOTM model (C). (D) Comparison of the average minimum distances between various infiltrating immune cells and tumor cells in recurrent/metastatic versus non-recurrent/non-metastatic patients. With R/M, with recurrent/metastatic patients; Without R/M, without recurrent/metastatic patients.
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