c-MET expression and immune landscape in locally advanced patients with non-small cell lung cancer undergoing radiochemotherapy and consolidative immunotherapy

Introduction

Non-small cell lung cancer (NSCLC) constitutes a significant proportion of all lung cancer cases (1), with traditional management strategies typically focusing on chemotherapy, often in conjunction with radiotherapy. Radiotherapy is a central component of lung cancer treatment, offering significant benefits to patients (2,3). The advent of immunotherapy has introduced a paradigm shift, greatly altering the treatment patterns and prognoses of patients with NSCLC (4), providing a more sustainable and systematic therapeutic approach. The combination of radiotherapy and immunotherapy has shown promise, with the tumor immune microenvironment (TIME) being recognized as a crucial factor in predicting and improving treatment efficacy (5). The composition and dynamics of the TIME can influence patients’ responses to therapy, rendering it a key biomarker for treatment planning and outcome assessment.

The role of the mesenchymal-epithelial transition factor (MET) gene in the TIME of NSCLC has emerged as a research area garnering increasing interest. Cellular MET (c-MET) is a receptor tyrosine kinase that is often abnormally regulated, including overexpression or mutation, in various cancers, including NSCLC, and these abnormalities are significantly associated with poor prognosis (6). Numerous studies have revealed a correlation between c-MET expression levels and TIME, suggesting that c-MET may play a role in modulating the immunological characteristics of tumors (7-9). The interaction between c-MET and the TIME could potentially influence the tumor’s responsiveness to immune checkpoint inhibitors (ICIs) and other immunotherapeutic agents. Therefore, a deeper understanding of the complex interplay between c-MET and TIME is crucial for the development of targeted therapeutic strategies that can not only disrupt c-MET-mediated oncogenic signaling pathways but also enhance the immune system’s ability to combat NSCLC more effectively.

This study aimed to investigate the interaction between c-MET protein expression and the TIME in patients with NSCLC who have received sequential immunotherapy after radiochemotherapy and assess the impact of this interaction on clinical treatment outcomes. Through this study, we aimed to elucidate the role of c-MET in tumor immune evasion and response to immunotherapy, providing potential biomarkers for precision medicine in NSCLC. This may not only deepen our understanding of the complex interactions within the tumor microenvironment but may also lead to the development of more personalized and effective treatment strategies for patients with NSCLC. Furthermore, the findings of this study are expected to provide a scientific basis for the design of future clinical trials and the formulation of treatment guidelines. We present this article in accordance with the REMARK reporting checklist (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-1036/rc).

Methods

Patients

A total of 44,712 individuals diagnosed with NSCLC were screened in this study, which was conducted at Shanghai Pulmonary Hospital between September 2019 and January 2022 (Figure S1). Ultimately, 60 cases were included after the screening process. The key inclusion criteria included a diagnosis of locally advanced or metastatic NSCLC that was unsuitable for surgical therapy, completion of sequential immunotherapy following radiochemotherapy, measurable disease, readable pathology slides, and adequate organ function. The primary exclusion criteria for this study were immunodeficiency diagnosis, concurrent administration of systemic corticosteroid treatment or immunosuppressive therapy with immunotherapy, presence of active autoimmune diseases necessitating systemic treatment, multiple tumor occurrences, and incomplete data on tumor response evaluation or survival tracking. The patient selection process is detailed in Figure S1.

Ethical approval and consent to participate

The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of Shanghai Pulmonary Hospital (approval No. L23-407). Informed consent was obtained from all patients.

Data collection

The general clinical data of the patients were collected, mainly age, gender, history of alcohol consumption, smoking history, tumor location, tumour, node, metastasis (TNM) staging, histological type, underlying lung disease status, history of previous treatments, and the type and combination of immunotherapy. The TNM staging was uniformly adjusted according to the eighth edition of the TNM staging guidelines endorsed by the Union for International Cancer Control (UICC) and the American Joint Committee on Cancer (AJCC) staging system.

Assay methods

Information on immunohistochemical molecular markers read by pathologists, including the staining intensity and percentage of positive cells for lymphocyte-activation gene 3 (LAG3), cluster of differentiation 8 (CD8), cluster of differentiation 68 (CD68), c-MET, forkhead box protein P3 (FOXP3), and T-cell immunoreceptor with Ig and ITIM domains (TIGIT) (Figure 1), was also collected. The reading process included applying a four-tier scoring system to assess the intensity of cellular staining, where no staining (negative) was assigned a score of 0, pale yellow (indicating weak positivity) a score of 1, brownish yellow (positive) a score of 2, and brown (strongly positive) a score of 3. Concurrently, the proportion of positively stained cells was graded on a similar four-tier scale, in which ≤25% positivity was given a score of 1, 26–50% a score of 2, 51–75% a score of 3, and >75% a score of 4, with the final score being the product of the two scores to yield a composite scoring result. To ensure methodological rigor, all immunohistochemistry (IHC) slides were independently evaluated by two experienced pathologists who were blinded to patients’ clinical characteristics and outcomes. Both staining intensity and percentage scores were recorded separately, and discrepancies were resolved by joint review to reach consensus. Inter-observer reproducibility was assessed, showing over 90% concordance in scoring. The cut-off threshold for molecular markers was defined by the cohort median (or another pre-specified percentile). This median (or percentile)-based approach is commonly used in immunohistochemical biomarker studies and helps to stratify “high” vs. “low” groups in the absence of externally validated thresholds.

Figure 1 Representative images of immunohistochemistry for advanced-stage NSCLC. Identification of various molecular marker information in patient pathological sections through immunohistochemical staining, including CD8 (A), CD68 (B), c-MET (C), FOXP3 (D), LAG3 (E), and TIGIT (F). c-MET, cellular mesenchymal-epithelial transition factor; CD68, cluster of differentiation 68; CD8, cluster of differentiation 8; FOXP3, forkhead box protein P3; LAG3, lymphocyte-activation gene 3; NSCLC, non-small cell lung cancer; TIGIT, T-cell immunoreceptor with Ig and ITIM domains.

To further evaluate the relationship between c-MET expression and immune infiltration, publicly available NSCLC transcriptomic datasets were analyzed. Correlations between MET gene expression and the abundance of immune cell populations were estimated using established computational methods. Results are presented in Figure S2.

In addition to the main cohort, for a subset of 33 patients with available paired tissue specimens (before and after radiochemotherapy and sequential immunotherapy), we assessed changes in c-MET expression. Paired t-test was used to examine shifts in expression intensity and percentage. Violin plots were generated to visualize the distributional changes (Figure S3).

Study design

This study was retrospective in nature and involved no stratification or matching. After screening (Figure S1), a total of 60 patients were ultimately included in the study. All enrolled patients were followed up until November 2023, with a median follow-up time of 30 months.

According to the Response Evaluation Criteria in Solid Tumors version 1.1 (10), the clinical treatment response following anti-programmed death 1/programmed cell death ligand 1 (anti-PD-1/PD-L1) therapy was categorized as stable disease (SD), progressive disease (PD), partial response (PR), or complete response (CR). Overall survival (OS) was considered to be the interval between the initiation of immunotherapy and either death or the final follow-up session. Progression-free survival (PFS) was recoded as time from the onset of immunotherapy to the initial detection of PD or death. The objective response rate (ORR) was defined as the percentage of patients achieving CR or PR, while the disease control rate (DCR) was defined as the percentage of patients achieving CR, PR, or SD.

Statistical analysis

All immunohistochemical molecular markers (the intensity and percentage of c-MET, LAG3, CD8, CD68, FOXP3, and TIGIT) were analyzed as categorical variables. Comparisons of categorical variables were conducted via the Chi-squared test. Survival curves were calculated with the Kaplan-Meier method. Multivariate analysis was conducted using the Cox proportional hazards model. All data were analyzed through SPSS 25.0 statistical software (IBM Corp., Armonk, NY, USA). A P value of less than 0.05 was considered statistically significant.

Results

Patients

A total of 60 patients with locally advanced NSCLC were enrolled in the retrospective analysis. The median age was 66 years (range, 41–80 years), with 70.0% of patients having tumors located in the upper lobe, 91.7% being free from underlying pulmonary diseases, and 90.0% receiving chemotherapy in combination with immunotherapy (Table 1).

Efficacy outcomes

Overall, the ORR and DCR of patients after receiving sequential immunotherapy with radiotherapy and chemotherapy were 48.3% and 83.3%, respectively. None of the patients (0/60) achieved CR, 48.3% (29/60) had PR, 35.0% (21/60) had SD, and 13.3% (8/60) experienced PD.

There were no statistically significant differences in ORR and DCR between the high-c-MET and low-c-MET expression groups or between the groups with increased and decreased CD68 infiltration.

Correlation analysis

Correlation analysis revealed a positive association between the intensity of c-MET and the percentage of CD68 infiltration in patients with NSCLC prior to treatment (r =0.69; P=0.01) (Figure 2), which is consistent with our analysis of The Cancer Genome Atlas (TCGA) database (Figure S2). In the subgroup analysis of the coexpression status of c-MET and CD68, we found that the group with positivity for either marker had the longest OS, followed by the group with positivity for both markers, while the group negative for both markers had the shortest OS (43.0 vs. 26.0 vs. 7.0 months, respectively; P=0.002) (Figure 3); PFS demonstrated a similar pattern, although the differences were not statistically significant (32.0 vs. 14.0 vs. 7.0 months, respectively; P=0.059) (Figure 3).

Figure 2 Correlation between c-MET expression and other molecular markers in the immunological microenvironment. The correlation heatmap between c-MET expression and the immune microenvironment markers in locally advanced NSCLC with curative radiochemotherapy followed by sequential immunotherapy. c-MET, cellular mesenchymal-epithelial transition factor; CD68, cluster of differentiation 68; CD8, cluster of differentiation 8; FOXP3, forkhead box protein P3; LAG3, lymphocyte-activation gene 3; NSCLC, non-small cell lung cancer; PD-L1, programmed cell death ligand 1; TIGIT, T-cell immunoreceptor with Ig and ITIM domains.

Figure 3 Kaplan-Meier curves of OS and the PFS. OS (A) and PFS (B) curves for patients with copositive, single-positive, or double-negative c-MET and CD68 expression. PFS (C) curves for patients with c-MET high expression and low expression. OS (D) curves for patients with high CD68 infiltration and low CD68 infiltration. OS (E) and PFS (F) curves for patients with PD-L1-positive and negative expression. c-MET, cellular mesenchymal-epithelial transition factor; CD68, cluster of differentiation 68; OS, overall survival; PD-L1, programmed cell death ligand 1; PFS, progression-free survival.

Furthermore, the intensity of c-MET expression before treatment in patients with NSCLC was positively correlated with PD-L1 expression (r =0.29; P=0.01), as was the c-MET multiplication score (r =0.22; P=0.01) (Figure 2). Additionally, the percentage of c-MET was positively correlated with the intensity of FOXP3 expression (r =0.70; P=0.04) (Figure 2).

Longitudinal changes of c-MET expression pre- and post-treatment

In a subset of 33 patients with paired pre- and post-chemoradiotherapy and sequential immunotherapy specimens, we examined changes in c-MET expression (intensity and percentage). Violin plots (Figure S3A for intensity; Figure S3B for percentage) show a general upward shift in c-MET expression after treatment. Statistical analysis by paired t-test revealed that the increase in both intensity (P=0.005) and percentage (P=0.001) was statistically significant. This exploratory result suggests that c-MET expression may evolve following chemoradiotherapy and sequential immunotherapy.

Survival outcomes

For the entire cohort, the median PFS and OS were 24.0 and 34.0 months, respectively. Kaplan-Meier survival analysis revealed that, as compared to low c-MET expression, high c-MET expression was significantly associated with a shorter PFS (12.0 vs. 32.0 months; P=0.03) (Figure 3). Similarly, low or absent CD68 infiltration was significantly associated with a shorter OS as compared to high CD68 infiltration (16.0 vs. 35.0 months; P=0.03) (Figure 3). Patients with low LAG3 expression, as compared to those with high LAG3 expression, demonstrated a modestly shorter OS (32.0 vs. 35.0 months; P=0.47) and PFS (20.0 vs. 32.0 months; P=0.32). Patients with reduced CD8 expression experienced a marginally poorer PFS as compared to those with high CD8 expression (20.0 vs. 32.0 months; P=0.74). Patients with high CD8 expression had a slightly shorter OS than did patients with low CD8 expression (32.0 vs. 35.0 months; P=0.31). Individuals with positive FOXP3 expression, as compared to those with negative FOXP3 expression, exhibited a slightly shorter OS (34.0 vs. 43.0 months; P=0.86) and PFS (13.0 vs. 32.0 months; P=0.09). Meanwhile, patients with negative TIGIT expression demonstrated a marginally inferior PFS as compared to those with positive TIGIT expression (24.0 vs. 35.0 months; P=0.22), and those with positive TIGIT expression had a slightly shorter OS compared to those patients with negative TIGIT expression (35.0 vs. 37.0 months; P=0.36). Finally, patients with negative PD-L1 expression, as compared to those with positive expression, had a slightly shorter OS (32.0 vs. 34.0 months; P=0.81) and PFS (26.0 vs. 32.0 months, P=0.75) (Figure 3).

Multivariate Cox regression analysis further revealed that age [hazard ratio (HR) =0.221; 95% confidence interval (CI): 0.090–0.542; P=0.001], c-MET expression (HR =3.894; 95% CI: 1.596–9.501; P=0.003), and CD68 percentage (HR =0.392; 95% CI: 0.166–0.928; P=0.03) were independent prognostic factors for PFS. Additionally, age (HR =0.277; 95% CI: 0.097–0.788; P=0.02) and CD68 percentage (HR =0.246; 95% CI: 0.085–0.710; P=0.01) were determined to be prognostic indicators for OS (Table 2).

Discussion

In recent years, the therapeutic landscape of NSCLC has evolved rapidly with the advent of novel systemic approaches, including next-generation ICIs, antibody-drug conjugates (ADCs), and targeted therapies directed against actionable oncogenic drivers. Several recent studies have emphasized the integration of immunotherapy with radiotherapy and chemotherapy as part of multimodal regimens to improve survival outcomes in locally advanced disease, and explored the role of some biomarkers in guiding personalized treatment strategies in different oncological contexts (11-15). These advances highlight the importance of understanding molecular determinants such as c-MET expression and macrophage infiltration in shaping treatment response and resistance mechanisms.

In the prognostic assessment of sequential immunotherapy following radiochemotherapy for NSCLC, the evaluation of biomarkers such as c-MET, LAG3, CD8, CD68, FOXP3, and TIGIT may provide novel insights. The expression profiles of these biomarkers can more comprehensively map the composition and functional status of immune cells within the TIME, providing crucial information for understanding the intercellular interactions within the TIME (16-19). Notably, CD68 is a specific marker for tumor-associated macrophages (TAMs), and CD68⁺ macrophages are the primary immune cells expressing PD-L1 in the TIME (20). In previous studies, there have been some explorations on the relationship between CD68 expression and prognosis (21-23). Therefore, the analysis of CD68 in TIME can provide a basis for assessing the extent of immune cell infiltration within tumors. However, despite the predictive value demonstrated by these biomarkers in previous studies, a deeper understanding of their clinical application and biological significance, given the heterogeneity of tumors and the complexity of treatment responses, requires further translational research and clinical validation.

Our study indicates that the protein expression level of c-MET is significantly correlated with the PFS of patients with NSCLC. High levels of c-MET expression were significantly associated with a shorter PFS as compared to low levels of c-MET expression (32.0 vs. 12.0 months; P=0.03), which partially aligns with a previous study (24). It was demonstrated that regardless of the patient’s stage or histology, patients with positivity for MET on fluorescence in situ hybridization (FISH) tend to exhibit reduced PFS than do MET-negative patients (data not shown) (24). Additionally, the study also reported that the median OS of FISH-confirmed MET positivity in patients with NSCLC was often worse than that of MET-negative patients, although the difference was not significant (69.0 vs. 87.0 months; P=0.42); however, in patients with squamous carcinoma, this difference was significant (median OS of 49.0 vs. 81.0 months; P=0.03) (24). In our study, no statistical difference in OS was found between the high- and low–c-MET expression groups, which may be due to the insufficient sample size.

Furthermore, we found that low or absent CD68 infiltration was significantly associated with shorter OS as compared to high CD68 infiltration levels (35.0 vs. 16.0 months; P=0.03). This corroborates previous research indicating that high PD-L1 expression in macrophages predicts prolonged OS, and elevated PD-L1 in macrophages is significantly associated with high CD68 levels in tumors (25).

Additionally, correlation analysis further revealed a significant positive correlation between the percentage of c-MET expression and CD68 levels (r =0.69; P=0.01), a finding that may suggest a potential link between the c-MET signaling pathway and macrophage infiltration. Macrophages exhibit significant plasticity and play an important role in the progression of NSCLC. They can differentiate into M1 and M2 phenotypes in diverse tissue settings. M1 macrophages display anti-tumor capabilities by enhancing adaptive immunity and inflammatory responses. Conversely, M2 macrophages foster tumor growth by dampening the tumor microenvironment’s immune functions and accelerating angiogenesis, tissue repair, and remodeling (26). In the immunological microenvironment of NSCLC, the activation of the hepatocyte growth factor (HGF)/c-MET signaling pathway downstream of the PI3K pathway can lead to a dependent induction of arginase 1 (Arg-1) expression. This affects the recruitment and activation of TAMs and transforms tumor-inhibitory M1 macrophages into tumor-promoting M2 macrophages (27), thereby influencing the immunosuppressive state of the TIME. A study has indicated that patients with altered MET in tumors exhibit a significant increase in the number of tumor-infiltrating lymphocytes (TILs) (28), which may also be related to changes in the levels of CD68-positive TAMs, supporting the complex role of c-MET signaling in regulating the TIME. Our subgroup analysis further corroborated these findings, showing that the positivity for both c-MET and CD68 was significantly associated with prolonged OS, and a similar association was found for PFS. These results suggest that c-MET-CD68 copositivity may be a more valuable prognostic marker in locally advanced NSCLC than PD-L1. Based on these findings, our future research will examine the interplay between c-MET and CD68 and their mechanisms of action in NSCLC. From our perspective, the integration of molecular and immune biomarkers such as c-MET and CD68 may help identify subgroups of NSCLC patients who derive greater benefit from immunoradiotherapy. In clinical practice, biomarker-driven patient stratification could optimize treatment selection and guide the rational incorporation of targeted agents. Our findings therefore support a precision-oncology approach to locally advanced NSCLC, bridging laboratory research and real-world treatment optimization. Recent progress in the development of MET inhibitors, such as capmatinib and tepotinib, has highlighted the clinical feasibility of targeting the MET pathway in NSCLC. A recent review (29) summarized the current landscape of MET-targeted agents and emphasized the need for biomarker-guided strategies to optimize such combinational approaches. Considering the potential differential response to treatment in c-MET-CD68 copositive patients, we plan to actively determine the application value of ADCs in combination with immunotherapy in this patient population. This combined treatment strategy is expected to further improve patient survival rates and provide an additional therapeutic option for clinical practice.

Despite these biomarkers demonstrating potential utility, our study has several limitations. First, the retrospective and single-center design may limit the generalizability of our findings. Second, the relatively small sample size may have reduced the statistical power to detect subtle associations, particularly for OS. However, our study focuses on generating hypotheses rather than confirming causality, and a relatively small sample size still holds some significance. Third, the use of different immunotherapy regimens and combinations could introduce potential confounding effects. In addition, functional validation of the c-MET-CD68 interaction was not performed and warrants further experimental and prospective clinical studies. And, in our study, the cut-off threshold for the markers was defined by the cohort median (or another pre-specified percentile). This median (or percentile)-based approach is commonly used in immunohistochemical biomarker studies and helps to stratify “high” vs. “low” groups in the absence of externally validated thresholds (30). Some prior studies in NSCLC and other tumors similarly use median or percentile-based cut-offs for TAM markers (31). We acknowledge that cut-off values may vary across cohorts and propose that future studies adopt receiver operating characteristic (ROC)-based or maximally selected rank statistics to optimize prognostic thresholds.

Moreover, one key limitation is that all baseline specimens were collected prior to chemoradiotherapy, and thus may not fully capture the tumor microenvironment status at the point of ICI administration. Post-treatment remodeling of immune infiltration or macrophage polarization could alter CD68 expression or phenotype. However, in a subset of 33 patients with paired samples, we observed an overall upward trend in c-MET expression (both intensity and percentage) following chemoradiotherapy and sequential immunotherapy (see Results, Figure S3). While this does not definitively prove that c-MET (or CD68) at ICI initiation mirrors this change, it provides preliminary evidence that expression levels may shift post-treatment. We caution that this analysis is exploratory, with a modest sample size, and should not be overinterpreted. And we acknowledge the possibility of confounding by prognosis: patients with inherently favorable biology (baseline molecular marker levels) might preferentially survive longer, thus creating an apparent association.

Therefore, future studies should employ prospective, randomized controlled trial designs with serial sampling during treatment to validate the prognostic predictive ability of these biomarkers and to clarify their mechanisms of action in different treatment strategies. Moreover, given the high heterogeneity of NSCLC, in-depth research on these biomarkers is necessary to support the development of personalized treatment strategies.

Conclusions

Our findings indicate that molecular markers of the TIME, c-MET, and CD68⁺ have prognostic value for the survival of patients with NSCLC undergoing radiotherapy and immunotherapy. High levels of c-MET expression were significantly correlated with shorter PFS, while low or absent CD68 infiltration was significantly associated with shorter OS. Additionally, c-MET expression was significantly correlated with the level of CD68 infiltration. Further clinical and translational research is warranted to validate these findings and elucidate the underlying mechanisms.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the REMARK reporting checklist. Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-1036/rc

Data Sharing Statement: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-1036/dss

Peer Review File: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-1036/prf

Funding: This research was supported by Zhejiang Provincial Natural Science Foundation of China (grant Nos. LTGY23H160011 and LTGY24H010003), Shanghai Municipal Science and Technology Innovation Action Plan (grant No. 2023Y11908700), Shanghai Pulmonary Hospital Clinical Research Fund (No. FKLY20006), and Shanghai Natural Science Foundation (grant No. 25ZR1402449).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-1036/coif). All authors report that this research was supported by Zhejiang Provincial Natural Science Foundation of China (grant Nos. LTGY23H160011 and LTGY24H010003), Shanghai Municipal Science and Technology Innovation Action Plan (grant No. 2023Y11908700), Shanghai Pulmonary Hospital Clinical Research Fund (No. FKLY20006), and Shanghai Natural Science Foundation (grant No. 25ZR1402449). The authors have no other conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of Shanghai Pulmonary Hospital (approval No. L23-407). Informed consent was obtained from all patients.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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