MiR-200a regulates PD-L1 and predicts response to immune checkpoint inhibitors in advanced non-small cell lung cancer

Introduction

Lung cancer is the leading cause of cancer-related deaths worldwide. Historically, lung cancer has been challenging to treat due to the lack of effective therapies. However, the development of immune checkpoint inhibitors (ICIs) has revolutionized the treatment of lung cancer, particularly in patients with advanced disease. ICI works by blocking the proteins that prevent the immune system from attacking cancer cells, such as programmed death-ligand 1 (PD-L1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) (1). Clinical trials have shown that ICI improves overall survival (OS) and progression-free survival (PFS) in patients with non-small cell lung cancer (NSCLC) (2,3). However, not all patients respond to ICI, and some may experience severe adverse effects (4). Therefore, there is an urgent need to develop novel approaches to enhance the efficacy of ICI therapy and identify reliable biomarkers that can better predict treatment response and adverse events.

Recent studies have suggested that microRNAs (miRNAs) may play a role in the response to ICI (5-7). miRNAs are small non-coding RNAs that regulate gene expression post-transcriptionally by binding to the 3'-untranslated region (3'-UTR) of target mRNAs, leading to their degradation or translational repression (5,8). These molecules influence immune checkpoint (IC) gene expression and serve as important regulators in both T-cells and tumor cells. Notably, miRNAs can affect immune checkpoint expression both directly and indirectly through various signaling pathways, including phosphatase and tensin homolog deleted from chromosome 10 (PTEN) and interferon regulatory factor 1 (IRF-1) (5,6).

The microRNA (miR)-200 family, consisting of miR-200a, miR-200b, miR-200c, miR141, and miR429, has emerged as a particularly important group of miRNAs in cancer biology. Expression levels of miR-200 family members are dysregulated in cancer tissues and altered in body fluids of cancer patients, correlating with clinical parameters such as survival rates (9). In NSCLC, it has been reported that miR-200 may contribute to chemotherapy resistance to docetaxel and gefitinib and is associated with higher grade and invasiveness (10-12). Importantly, these resistance mechanisms and invasive characteristics may be reversed through the reintroduction of miR-200, suggesting its potential as a therapeutic target.

Despite these advances in understanding miR-200’s role in cancer progression and drug resistance, its specific function in modulating PD-L1 expression and potential utility as a biomarker for ICI therapy in NSCLC remains poorly understood. In this study, we investigated the relationship between miR-200 family members and PD-L1 expression through analysis of public databases, in vitro experiments, and clinical samples, with particular focus on miR-200a and miR-200b. We also evaluated serum miR-200a levels as a potential predictive biomarker for ICI therapy in advanced NSCLC patients. We present this article in accordance with the MDAR reporting checklist (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-117/rc).

Methods

Integrated analysis of miRNA expression in CD274 stratified groups

Using the TCGAbiolinks package on R Studio, primary tumor samples of lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) from The Cancer Genome Atlas (TCGA) data portal. Data from the Clinical Proteomic Tumor Analysis Consortium (CPTAC3) projects were obtained as well. These data were already aligned with hg38. Variance stabilizing transformation (VST) normalization was performed on the obtained count data using the DSEq2 package, followed by differentially expressed gene (DEG) analysis to the extraction of the expression variation genes was performed.

For each patient, RNA and miRNA expression data were merged. The integrated dataset was then divided into three groups based on expression levels after VST normalization of CD274 (PD-L1). MiRNA expression was compared between the CD274 low and high groups, and between the tumor and normal tissues. The comparison was based on log₂fold change >|0.5| with a significance threshold of P<0.001. Finally, miRNAs were identified in all four groups: TCGA, CPTAC3, and in both tumor and normal tissues.

Cell lines and cultures

Human lung cancer cell lines H460 (large cell carcinoma, KRAS mutation positive), H520 (squamous cell carcinoma, FGFR1 mutation positive), and A549 (adenocarcinoma, RAS mutation positive) were obtained from the American Type Culture Collection, whereas H1975 (adenocarcinoma, EGFR mutation positive) and OKa-C-1 (squamous cell carcinoma) was obtained from the Japanese Cancer Research Resources Bank. All cell lines were cultured at 37 ℃ and 5% CO₂ in RPMI 1640 medium (Sigma-Aldrich, St. Louis, MO, USA) supplemented with 10% fetal bovine serum (Biowest, Maine-et-Loire, France) and 1% penicillin/streptomycin (Gibco, Waltham, MA, USA).

Flow cytometry

The cultured cells were harvested using 1.0 mM ethylenediaminetetraacetic acid (EDTA) and washed twice in ice-cold phosphate-buffered saline supplemented with 10% fetal bovine serum. The cells were incubated for 30 minutes at 4 ℃ with allophycocyanin (APC)-conjugated antibodies targeting human PD-L1 (1:20; APC anti-human CD274; Clone: 29E2A3; Cat: 329708; BioLegend, San Diego, CA, USA) or APC-conjugated isotype control antibodies (1:20; APC mouse IgG2b; κ Isotype; Clone: MPC-11; Cat: 400322; BioLegend). Flow cytometry was performed using a FACS Canto II system (BD, Franklin Lakes, NJ, USA), and data analysis was performed using the FlowJo software (v10; BD). The experiments were repeated more than twice independently. Data are presented as the mean ± standard error.

Western blotting

The cultured cells were lysed using a cell lysis buffer (1:10 dilution) supplemented with protease/phosphatase inhibitor cocktail (1:100). After homogenization, the total protein concentration was quantified using a Nanodrop 2000 system (Thermo Fisher Scientific, Waltham, MA, USA). After 10 µg of protein was heated at 95 ℃ for five minutes, the samples were separated using electrophoresis and 10% sodium dodecyl sulfate-polyacrylamide gel (BIORAD, Hercules, CA, USA) and subsequently transferred onto poly-vinylidene difluoride membranes (Invitrogen, Carlsbad, CA, USA). The membranes were blocked for one hour using 5% nonfat dry milk in Tris-buffered saline and Tween 20 (1:10) and then incubated for one hour at room temperature with primary antibodies targeting PD-L1 [1:2,000; PD-L1 (E1L3N) XP rabbit mAb; Cat: 13684; CST, Danvers, MA, USA] and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) [1:2,000; GAPDH (14C10) rabbit mAb; Cat: 2118; CST]. The membranes were washed and incubated for one hour at room temperature with horseradish peroxidase (HRP)-linked secondary antibodies (1:5,000; anti-rabbit IgG; HRP-linked antibody; Cat: 7074; CST), and the band intensities were quantified using a ChemiDoc Touch system (BIORAD). The experiment was replicated with two independent samples. Data are presented as the mean ± standard error.

Total RNA isolation and reverse-transcription

Total RNA from the cell lines was extracted using a RNeasy mini kit (QIAGEN, Hilden, Germany) according to the manufacturer’s instructions. Total RNA was also extracted from the serum using a miRNeasy serum/plasma advanced kit (QIAGEN). The purity and the concentration of the extracted total RNA were measured using the Nanodrop 2000 system (Thermo Fisher Scientific). For complementary DNA (cDNA) synthesis, Mir-X miRNA First Strand Synthesis Kit (Takara Bio, Mountain View, CA, USA) or TaqMan MicroRNA Reverse-Transcription Kit (Applied Biosystems, Foster City, CA, USA) and TaqMan MicroRNA Assays (Applied Biosystems).

Reverse transcription quantitative polymerase chain reaction (RT-qPCR)

RT-qPCR was performed using the CFX96 Real-Time PCR Detection System (BIORAD) with TB Green Advantage qPCR Premix (Takara Bio). The following PCReady primers (Eurofins Genomics, Tokyo, Japan) were used: miR-200a-3p (5'-TAACACTGTCTGGTAACGATGT-3'), miR-200a-5p (5'-CATCTTACCGGGACAGTGCTGGA-3'), and miR-200b-3p (5'-TAATACTGCCTGGTAATGATGA-3'). The reverse transcription samples from cell lines were analyzed according to the manufacturer’s protocol. Expression levels of miRNAs were normalized to U6 as an internal control, and relative expression was calculated using the 2^−ΔΔCq method, where ΔCq represents the difference between the target and reference Cq values (ΔCq = Cq_target − Cq_reference). The experiments were repeated more than twice independently. Data are presented as the mean ± standard error.

Droplet digital polymerase chain reaction (ddPCR)

The reverse transcription samples obtained from serum, ddPCR Supermix for Probes (no dUTP) (BIORAD), TaqMan MicroRNA Assays (Applied Biosystems; assay ID: 000502, 001011, 002251, and 002299) primers were used to perform ddPCR according to the manufacturer’s protocol. The miR-191-5p was used as endogenous control to correct for miR-200 family expression. The experiment was replicated with two independent samples. Data are presented as the mean ± standard error.

Interferon gamma (IFN-γ) stimulation

A549 and H460 cells (2×10⁵/well) were seeded in six-well plates. Cells were left untreated or IFN-γ (10 ng/mL) was added and cultured for 48 hours. Cells were collected, centrifuged, and analyzed by flow cytometry or RT-qPCR.

Mimic miR-200 family

The cell lines were seeded for 24 hours before transfection with mimic miR-200a-3p, miR-200a-5p, miR-200b-3p (GeneDesign, Osaka, Japan), and S-TuD as negative control (NC) (GeneDesign). Transfection was performed using Lipofectamine 2000 (final concentration: 10 nM; Invitrogen) according to the manufacturer’s protocol and analyzed after 48 hours. The sequences used were as follows: mimic miR-200a-3p (upstream primer, 5'-UAACACUGUCUGGUAACGAUGU-3'), mimic miR-200a-5p (upstream primer, 5'-CAUCUUACCGGACAGUGCUGGA-3'), mimic miR-200b-3p (upstream primer, 5'-UAAUACUGCCUGGUAAUGAUGA-3'), and S-TuD NC (upstream primer, 5'-GACGGCGCUAGGAUCAUCAACUAUCGCGAGUAUCGACGUCGAGGCCCAAGUAUUCUGGU-3').

Patients and samples

All clinical procedures in this study were approved by the Yokohama City University Ethics Committee (approval No. F220200003). This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. Patients with suspected primary lung cancer were prospectively recruited at the Yokohama City University Hospital and Yokohama City University Medical Center between November 2022 and September 2023. Samples were obtained from patients who provided informed consent for the research use of their serum. We selected cases that have been histologically diagnosed as NSCLC and evaluated the miRNA expression of the serum samples obtained before chemotherapy. The tumor proportion score (TPS) for PD-L1 expression was evaluated by a pathologist based on the immunohistochemical staining for PD-L1 (22C3 pharmDx; Dako, Carpinteria, CA, USA).

Statistical analysis

Statistical analyses were conducted utilizing JMP version 17.0 (SAS Institute Inc., Cary, NC, USA) and Python version 3.9.17. Intergroup differences were evaluated using the Student’s t-test, and for multiple comparisons, the Tukey-Kramer method was used. The Mann-Whitney U test was used for serum samples. Survival outcomes between the cohorts were assessed using Kaplan-Meier estimates and compared with the log-rank test. Cox proportional hazards regression models were employed to calculate hazard ratios (HRs) and 95% confidence intervals (CIs). Data are presented as the mean ± standard error of the mean, unless otherwise stated, and P values of <0.05 were considered statistically significant.

Results

Twelve miRNAs correlate with PD-L1 expression by clinical data analysis

To identify miRNAs associated with PD-L1 (CD274) expression in lung cancer, we performed an integrated analysis of RNA sequencing (RNA-seq) data from TCGA and CPTAC3. After rigorous data processing (see the “Methods” section), we first stratified samples into “low”, “intermediate”, and “high” groups based on their CD274 expression levels (Figure 1A). Comparing tumor vs. normal tissue, we found 579 differentially expressed miRNAs in the TCGA dataset and 644 in the CPTAC3 dataset (log₂fold change >|0.5|, P<0.001). When comparing PD-L1 high vs. low groups, 116 miRNAs were differentially expressed in the TCGA dataset, and 37 in the CPTAC3 dataset. Notably, 12 miRNAs exhibited differential expression in both datasets when comparing PD-L1 high and low groups, indicating a robust association with PD-L1 expression. Further investigation of these 12 miRNAs using a heatmap (Figure 1B) revealed two distinct clusters. One cluster, including miR-200a, miR-200b, miR-429, miR-196a2, miR-196a1, miR-615, miR-3664, and miR-410, displayed an inverse correlation with PD-L1 expression, being downregulated in the PD-L1 high group and upregulated in the PD-L1 low group. This observation aligns with a previous report of an inverse correlation between miR-200b in blood and PD-L1 expression in lung cancer tissues (13) and suggests a potential role for the miR-200 family in regulating or responding to PD-L1. The second cluster, including miR-4758, miR-155, miR-511, and miR-100, showed a positive correlation with PD-L1 expression.

Figure 1 Analysis of lung cancer RNA-seq data using public databases. (A) After VST normalization of TCGA-LUAD and LUSC lung cancer RNA-seq data, samples were divided into three groups according to their values: PD-L1 (CD274) high, medium, and low. (B) Heatmap visualization of the difference in miRNA expression in the two groups of PD-L1 high and low. LUAD, lung adenocarcinoma; LUSC, lung squamous cell carcinoma; miR, microRNA; miRNA, microRNA; PD-L1, programmed death-ligand 1; RNA-seq, RNA sequencing; TCGA, The Cancer Genome Atlas; VST, variance stabilizing transformation.

Relationship between PD-L1 expression and miR-200 family expression in lung cancer cell lines

Flow cytometry analysis showed low expression of PD-L1 in H520 cells and high expression of PD-L1 in A549, H460, H1975, and OKa-C-1 cells (Figure 2A,2B). Western blotting similarly confirmed low PD-L1 expression in H520 and high expression in H1975, the difference in PD-L1 expression between the two cell lines was significant (P=0.001) (Figure 2C). Among the 12 miRNAs identified in the public database analysis, 10 miRNAs were analyzed for expression except for miR-3664 and miR-4758, which were very low expressed (Figure 2D). MiR-200a-3p and miR-200b-3p expression levels were significantly higher in H520 (PD-L1 low-expressing cell line) than in H1975 (PD-L1 high-expressing cell line), consistent with the inverse correlation suggested by the public database analysis. Significant differences in expression levels were also observed for miR-155 and miR-511, but the public database analysis suggested a positive correlation with PD-L1, which was the opposite of the results. Based on these results, we focused on miR-200a and miR-200b among the 12 miRNAs for further investigation. miR-200a-3p expression in H520 cells was significantly higher than that in A549, H460, and H1975 cells, and similar results were obtained for miR-200b-3p (Figure 2E). MiR-200a and miR-200b expression was higher in PD-L1 low-expressing cell lines, and their expression was lower in PD-L1 high-expressing cell lines.

Figure 2 Expression of PD-L1 and miRNA in human lung cancer cell lines H520, A549, H460, H1975, and OKa-C-1. P values were determined using the Student’s t-test. Data are presented as the mean ± standard error. (A) PD-L1 expression in each cell line was assessed by flow cytometry (red: APC-PD-L1; blue: isotype control). (B) PD-L1 expression rate in each lung cancer cell line. (C) Comparison of PD-L1 expression between cells by Western blotting. (D) Expression levels of miRNAs identified by RNA-seq analysis were measured using RT-qPCR to examine differences in expression in PD-L1 low expression H520 and PD-L1 high expression H1975 (red: inverse correlation; blue: positive correlation). (E) Expression levels of miR-200a-3p, miR-200a-5p, and miR-200b-3p in each cell line were measured using RT-qPCR. APC, allophycocyanin; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; M, molecular weight marker; miR, microRNA; miRNA, microRNA; PD-L1, programmed death-ligand 1; RNA-seq, RNA sequencing; RT-qPCR, reverse transcription quantitative polymerase chain reaction.

MiR-200a and miR-200b expression after IFN-γ stimulation in lung cancer cell lines

PD-L1 expression has been shown to be induced by IFN-γ stimulation of lung cancer cell lines (14). PD-L1 expression in H520, A549, and H460 after IFN-γ stimulation was analyzed by flow cytometry showed an increase in PD-L1 expression as previously reported (Figure 3A). Western blotting similarly confirmed that PD-L1 expression was upregulated by IFN-γ in H520 cells (Figure 3B). In A549 and H460, PD-L1 expression was altered after the addition of IFN-γ, miR-200a-3p, miR-200a-5p, and miR-200b-3p expression was analyzed by RT-qPCR. However, no significant changes in expression were observed in any of them (Figure 3C). These results suggest that the regulation of PD-L1 expression in lung cancer cells by the miR-200 family may be through a pathway that is not mediated by IFN-γ, and there may be direct or indirect regulatory mechanisms through other pathways.

Figure 3 Expression of PD-L1 and miR-200 after IFN-γ stimulation. Data are presented as the mean ± standard error. (A) Flow cytometry was used to evaluate PD-L1 expression in H520, A549, and H460 cells after IFN-γ stimulation and control (red: APC-PD-L1; blue: isotype control). (B) PD-L1 expression in H520 after IFN-γ stimulation was evaluated by Western blotting. (C) MiR-200 expression in A549 and H460 cells after IFN-γ stimulation and control based on RT-qPCR assays. APC, allophycocyanin; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; IFN-γ, interferon gamma; M, molecular weight marker; miR, microRNA; PD-L1, programmed death-ligand 1; RT-qPCR, reverse transcription quantitative polymerase chain reaction.

PD-L1 expression changes by transfection of mimic miR-200a and miR-200b

To further investigate the functional impact of miR-200a and miR-200b on PD-L1 expression, we performed mimic transfection experiments in lung cancer cell lines. RT-qPCR after transfection of mimic miR-200a-3p, mimic miR-200a-5p, and mimic miR-200b-3p confirmed increased expression of each miRNA selective upregulation effect was observed with mimic for each miRNA (Figure 4A). Flow cytometric analysis revealed that miR-200 mimics significantly decreased PD-L1 expression in H1975 and OKa-C-1 cells, which express high baseline levels of PD-L1. However, no significant changes in PD-L1 expression were observed in A549 and H460 cells (Figure 4B). These results suggest the possibility of suppression of PD-L1 expression by the miR-200 family in cell lines with particularly high PD-L1 expression.

Figure 4 Expression of PD-L1 and miR-200 after transfection with mimic miR-200a or miR-200b. Data are presented as the mean ± standard error, and the P values were determined using the Tukey-Kramer method. (A) MiR-200a-3p, miR-200a-5p, and miR-200b-3p expression in H460 cells after transfection with mimic miR-200a-3p, miR-200a-5p, miR-200b-3p, or S-TuD NC as control based on RT-qPCR assays. (B) Flow cytometry was used to evaluate PD-L1 expression in A549, H460, H1975, and OKa-C-1 cells after transfection with mimic miR-200a-3p, miR-200a-5p, miR-200b-3p, or S-TuD NC. MiR, microRNA; NC, negative control; PD-L1, programmed death-ligand 1; RT-qPCR, reverse transcription quantitative polymerase chain reaction.

Serum miR-200a expression is elevated in advanced NSCLC patients with low PD-L1 expression

During the period described, we first selected patients who had undergone bronchoscopy for suspected lung cancer. Of these patients, 41 patients consented to this study, 25 of whom were excluded for reasons shown in Figure 5. As a result, 16 patients were included in the study. Using ddPCR, we confirmed that it is possible to analyze the expression of miR-200a-3p, miR-200a-5p, and miR-200b-3p in collected lung cancer patient serum. The expression levels of each in the serum of lung cancer patients were different in each sample, and in the results of seven of the 16 patients who were initially evaluated, it was found that miR-200a-3p and miR-200a-5p were predominantly expressed compared to miR-200b-3p expression (Figure 6A), so only miR-200a was analyzed for the remaining patients. In a study of 16 patients with untreated advanced NSCLC, the patient characteristics are shown in Table 1. The median (min–max) expression levels of miR-200a-3p and miR-200a-5p after correction for endogenous controls were 113.7 (1.2–3,115.7) and 114.3 (0.4–1,787.8) copies/µL, respectively. The logarithmic transformation results are shown in Figure 6B. MiR-200a-3p expression was significantly higher in the PD-L1 low expression group (P=0.042), and a similar trend was observed for miR-200a-5p, although not significantly different (P=0.11).

Figure 5 Flowchart of enrolled and excluded patients for serum sample review. PD-L1, programmed death-ligand 1.

Figure 6 MiR-200 expression in serum of patients with advanced NSCLC and analysis of clinical data. Data are presented as the mean ± standard error. The P values were determined using the Mann-Whitney U test. The PFS was compared with the log-rank test. (A) Expression of miR-200a and miR-200b in serum of patients with advanced NSCLC based on ddPCR. (B) Relationship between miR-200a expression in serum of lung cancer patients and PD-L1 TPS in lung cancer patient tissues. (C) Comparison of PFS in patients with advanced NSCLC treated with first-line chemotherapy including ICIs in the miR-200a low-expressing group vs. the miR-200a high-expressing group. CI, confidence interval; ddPCR, droplet digital polymerase chain reaction; ICI, immune checkpoint inhibitor; miR, microRNA; NA, not available; NSCLC, non-small cell lung cancer; PD-L1, programmed death-ligand 1; PFS, progression-free survival; TPS, tumor percentage score.

Low serum miR-200a expression is associated with better PFS in advanced NSCLC patients treated with ICIs to investigate the potential of serum miR-200a expression as a prognostic biomarker in advanced NSCLC patients receiving ICI-based therapy, we analyzed a subgroup of 10 patients from our cohort who had received first-line chemotherapy in combination with ICIs. The baseline characteristics of these patients are summarized in Table 2. Patients were stratified into two groups based on their serum miR-200a levels and then compared between these groups using Kaplan-Meier analysis (Figure 6C).

The median PFS was significantly longer in the miR-200a low group [200 days; 95% CI: 200–not available (NA)] compared to the miR-200a high group (129 days; 95% CI: 62–166) (log-rank test, P=0.008). These findings indicate that low serum miR-200a expression may serve as a promising biomarker to identify advanced NSCLC patients who are likely to derive greater benefit from first-line treatment with chemotherapy plus ICIs.

Discussion

In this study, we have elucidated the pivotal role of the miR-200 family in modulating the expression of PD-L1, a critical immune checkpoint protein, in the context of NSCLC. Our comprehensive analysis leveraged large-scale genomic datasets to unveil a significant inverse correlation between the expression of miR-200 family members and PD-L1 levels. This inverse relationship was consistently observed across multiple lung cancer cell lines and corroborated by serum analysis from NSCLC patients undergoing ICI therapy. Functionally, we demonstrated that the modulation of miR-200 family members, through mimic transfection, directly impacts PD-L1 expression, suggesting a potential regulatory mechanism by which these miRNAs could influence immune surveillance and response to immunotherapy. Furthermore, our clinical findings implicate the serum levels of miR-200a as a prognostic biomarker for ICI response. Although the relationship between the miR-200 family and PD-L1 has already been reported in several cancer types, including NSCLC, this study confirms the consistency of these findings with RNA-seq analysis and cell line experiments, and further evaluated prospectively with patient serum. This presents an opportunity to refine therapeutic strategies towards a more personalized approach in the treatment of lung cancer (15,16).

Our findings indicate that miR-200a and miR-200b are negatively correlated with PD-L1 expression (Figures 1,2), and overexpression of these miRNAs reduces the expression of PD-L1 in NSCLC (Figure 4B). This is consistent with our previous study that has identified a negative correlation between miR-200b and PD-L1 expression in NSCLC cell lines and clinical specimens from lung cancer patients (13). The miR-200 family, which includes miR-200a and miR-200b, has been shown to regulate PD-L1 expression (9,17). The 3'-UTR of PD-L1 contains two sites for possible binding to members of the miR-200 family (miR-200a, miR-200b, and miR-200c), suggesting that PD-L1 expression is directly regulated by the miR-200 family. This regulation likely occurs at a post-transcriptional level, as miRNAs are known to regulate gene expression post-transcriptionally.

However, miR-200 may also act indirectly on PD-L1 by modulating upstream regulators. One possible mechanism of regulation involves the zinc-finger E-box-binding homeobox 1 (ZEB1). Upregulation of ZEB1 in NSCLC has been shown to inhibit the expression of miR-200, resulting in increased PD-L1 levels (18). In this study, the changes in PD-L1 expression upon transfection of mimics vary from cell line to cell line, and the regulatory mechanism may depend on the subtype of the cell line. The two cell lines in which significant changes in PD-L1 expression were obtained in this study were found to have very high naive PD-L1 expression. One of them, H1975, is EGFR mutation positive and may have a distinctive PD-L1 expression regulatory mechanism.

Additionally, miR-200 could regulate other immune-related proteins besides PD-L1, as it has been shown to target interleukin 6 (IL6) and C-X-C chemokine ligand (CXCL) 1/2 chemokines (9). The miR-200 family may also be involved in a wide range of other biological processes, including cell proliferation, differentiation, and apoptosis (19). In this study, we examined the role of the miR-200 family in NSCLC in regulating tumor immunity through PD-L1 regulation. Dissecting the precise molecular interactions governing miR-200’s multi-pronged impact requires further mechanistic investigation across diverse lung cancer backgrounds.

The miR-200 family has emerged as a key regulator of tumor behavior and response to therapy, including immunotherapy, in various cancers. While our result demonstrated an inverse relationship between miR-200a expression levels and favorable ICI outcomes (Figure 6), the literature presents heterogeneous associations for other miR-200 family members. In a noteworthy study, Grenda et al. reported contrasting findings: high miR-200b expression correlated with improved ICI response in lung cancer patients (HR =0.42; 95% CI: 0.17–1.04; P=0.05), while low miR-429 expression was associated with better PFS (HR =0.13; 95% CI: 0.017–0.960; P=0.046). These divergent findings highlight the complex roles of miR-200 family members in modulating anti-tumor immunity and underscore the need for further investigation into their distinct mechanisms of action in the tumor microenvironment (20).

The performance of miR-200a as a prognostic tool contrast with that of PD-L1, where PD-L1 expression alone has shown limitations as a predictive biomarker due to its dynamic expression and the heterogeneity of tumor cells (21). Unlike PD-L1, whose expression can be influenced by various factors such as IFN-γ levels and may not fully reflect the immunological milieu, miR-200 levels appear to offer a more stable and consistent biomarker, as supported by our serum-based analysis. Furthermore, the quantification of miRNAs in circulating blood offers a non-invasive approach that can be advantageous over tissue biopsies, which are subject to sampling error and may not represent the entire tumor landscape (22). Emerging evidence shows circulating miRNAs can reflect cancer biology and associate with therapeutic efficacy across malignancies (23-25). MiRNAs mediate crosstalk between tumor and immune cells, making their quantification clinically valuable for immunotherapies (26). Indeed, specific signatures combining miR-200 with other miRNAs outperformed PD-L1 in predicting programmed cell death protein 1 (PD-1) inhibitor response in melanoma (27). A lung cancer study has reported that overexpression of miR-200b is associated with increased chemotherapy sensitivity (28). Our work extends these concepts to miR-200a and immune checkpoint blockade, warranting validation in larger NSCLC cohorts.

Manipulating miR-200 levels through miRNA mimics or other modalities represents a promising immunomodulatory treatment approach for lung cancer. As key regulators of tumor inflammation and immune surveillance, miR-200 restoration aims to recalibrate dysregulated networks back towards homeostasis (29). Reconstituting miR-200 could upregulate cytotoxic cytokine release from tumor-infiltrating lymphocytes while downregulating immunosuppressive signals from cancer cells, reinvigorating anti-tumor immunity (30). However, miR-200 delivery poses challenges requiring innovative solutions like conjugation to targeting antibodies or nanoparticles. Defining synergistic combinations with immunotherapies is also needed, as our experiments suggest that miR-200 could be involved in immune checkpoint regulation. Mimicking endogenous miRNA fluctuations to stimulate immune reactions against cancer opens new possibilities for RNA medicine alongside traditional modalities. Therefore, further research is needed to fully understand the role of miR-200 in lung cancer and its potential as a therapeutic target.

While this study reveals important connections between miR-200 and the regulation of anti-tumor immunity, there are certain limitations to consider. Our integrated bioinformatic analysis relied on publicly available datasets which can vary in sample size and clinical features. Additional patient cohorts would further validate the inverse miR-200/PD-L1 relationship. Similarly, testing more types of lung cancer cell lines could confirm trends observed herein. While our results suggest a regulatory effect of miR-200 on PD-L1, we have not been able to show evidence of its direct regulation in this study, which should be confirmed by 3'-UTR reporter assays and mutation analysis. Exploration of this detailed mechanism is an important future challenge. The small sample size of the clinical cohort is a major limitation of this study. Statistical power is low due to the insufficient sample. Although this study shows that miR-200a may predict longer PFS in the ICI-treated group, this limitation limits the interpretation of these results to exploratory findings. Further large-scale validation studies are needed to generalize these results. Moreover, the systemic delivery and tumor-specific uptake of miR-200 mimics poses an ongoing bioengineering challenge requiring innovation, and additional in vivo investigations with miR-200 mimics or inhibitors would expand their potential as therapeutic targets. While acknowledging these limitations, our data lays the foundation to elucidate miR-200’s role orchestrating anti-tumor immunity and motivates development of miR-200-based predictive biomarkers or immunotherapies for lung cancer.

Conclusions

Our study underscores the miR-200 family’s integral role in regulating PD-L1 and influencing the response to ICIs in NSCLC. We have demonstrated an inverse relationship between miR-200 expression and PD-L1 levels, indicating the potential of miR-200a and miR-200b as predictive biomarkers for immunotherapy outcomes. The correlation between lower miR-200a serum levels and improved patient prognosis particularly points to its clinical utility. While further validation is necessary, our research suggests that miR-200-based interventions could represent a new frontier in personalizing lung cancer treatment.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the MDAR reporting checklist. Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-117/rc

Data Sharing Statement: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-117/dss

Peer Review File: Available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-117/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-117/coif). The authors have no 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. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Yokohama City University Ethics Committee (approval No. F220200003) and informed consent was obtained from all individual participants.

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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