MAFF inhibits angiogenesis in non-small cell lung cancer by suppressing YAP1 nuclear translocation

Transcriptome analysis

Bioinformatic analyses were performed using R software (version 4.3.0). To evaluate the pan-cancer expression profile of MAFF, we utilized the TIMER 2.0 web server. For LUAD, paired RNA-seq data and corresponding clinical information were obtained from The Cancer Genome Atlas (TCGA) database. After removing samples with missing or incomplete clinical annotations, a total of 58 paired tumor and adjacent normal tissues were retained for subsequent analysis. Gene Set Enrichment Analysis (GSEA) was carried out with the clusterProfiler R package to identify signaling pathways significantly associated with MAFF expression levels. Additionally, single-sample GSEA (ssGSEA), implemented through the GSVA package, was employed to estimate the relative abundance of tumor-infiltrating immune cell subsets in each sample.

Single-cell RNA sequencing data analysis

The GSE198099 dataset was acquired from the Gene Expression Omnibus (GEO) database, which included two LUAD samples and two adjacent non-tumor tissue samples. Single-cell RNA sequencing (scRNA-seq) data were processed using the Seurat package to ensure reproducibility. Stringent quality control criteria were applied as follows: (1) Gene expression cutoff: only cells expressing at least 200 genes were retained; (2) UMI Threshold: cells with more than 500 UMI counts were included; (3) Mitochondrial gene content: cells with mitochondrial gene expression exceeding 10% were excluded; (4) Hemoglobin gene expression: cells exhibiting hemoglobin gene expression above 0.1% were removed. After preprocessing, the datasets were integrated and normalized using Harmony to correct for batch effects. Principal component analysis (PCA) was employed for dimensionality reduction and identification of highly variable genes. Subsequently, Uniform Manifold Approximation and Projection (UMAP) was applied for non-linear dimensionality reduction to visualize cell clusters. Finally, gene set variation analysis (GSVA) was performed within TCGA cohort to assess prognostic associations, providing further clinical insights.

IHC

A total of 56 paracancerous normal tissue specimens and 77 LUAD samples were collected from Baise People’s Hospital. The inclusion criteria were as follows: (1) histopathologically confirmed diagnosis of LUAD; (2) no previous history of chemotherapy, radiotherapy, or targeted therapy; (3) absence of severe comorbidities or other synchronous malignancies; (4) completion of standard adjuvant therapy following surgical resection; and (5) availability of comprehensive clinicopathological records. The cohort consisted of 31 male and 46 female patients, with ages ranging from 40 to 77 years (44 patients <60 years and 33 patients ≥60 years). Based on pathological staging, the cases were distributed as follows: 50 stage I, 14 stage II, 9 stage III, and 4 stage IV. Lymph node metastasis was identified in 16 cases, and distant metastasis was present in six cases.

Written informed consent was obtained from all participants using institutionally approved consent documents. The study protocol was reviewed and approved by the Ethics Committee of Baise People’s Hospital (Approval No. KY2023111726) in accordance with the principles of the Declaration of Helsinki.

Formalin-fixed paraffin-embedded (FFPE) sections from the collected specimens were subjected to IHC staining using specific antibodies against MAFF (12771-1-AP, Proteintech, Rosemont, IL, USA; dilution 1:200) and YAP1 (A19134, Abclonal, Woburn, MA, SA; dilution 1:200). Protein expression levels were assessed using the Immunoreactive Score (IRS) system, which incorporates both staining intensity and the proportion of positive cells. Staining intensity was graded as follows: 0 (none), 1 (light yellow), 2 (brownish yellow), and 3 (tan). The percentage of positive cells was scored as: 0 (0–5%), 1 (6–25%), 2 (26–50%), 3 (51–75%), and 4 (>75%). The final IRS was calculated by multiplying the intensity and positivity scores, with a composite score of <3 considered indicative of negative expression.

Cell culture, lentiviral vector

This study utilized the following cell lines: immortalized human normal bronchial epithelial cells (BEAS-2B), immortalized human umbilical vein endothelial cells (HUVECs), human embryonic kidney 293T cells, and NSCLC cell lines (A549 and H1299). All cell lines were purchased from Wuhan Pricella Biotechnology Co., Ltd. (Wuhan, China). Cells were cultured in Dulbecco’s Modified Eagle Medium (DMEM) supplemented with 10% fetal bovine serum (FBS) under standard conditions (37 °C, 5% CO₂). For stable overexpression of MAFF, a lentiviral vector (pReceiver-Lv201) carrying the MAFF sequence was obtained from iGene Biotechnology Co., Ltd. (Columbia, MS, USA).

In vitro functional studies

Cell viability was measured using the Cell Counting Kit-8 (CCK-8) assay according to the manufacturer’s instructions. For the colony formation assay, stably transfected cells were cultured for 7 days to allow colony formation. The resulting colonies were then fixed with methanol and stained with 0.1% crystal violet for visualization and quantification. To evaluate cell migration, a wound healing assay was performed: stably transfected cells were seeded in six-well plates and grown to 90% confluence. A uniform scratch was introduced into the monolayer using a sterile pipette tip. After 24 h of incubation, wound closure was assessed following fixation and staining with 0.1% crystal violet. Cell invasion was examined using Transwell invasion chambers coated with Matrigel. For the angiogenesis assay, HUVECs were seeded onto Matrigel-coated 96-well plates and tube formation was observed and imaged after an appropriate incubation period. All experiments were performed in triplicate and repeated independently three times.

In vivo tumorigenicity assay

Eight female BALB/c nude mice (aged 4–5 weeks, weighing 15–17 g) were obtained from Beijing Vitong Lihua Animal Co., Ltd. All animals were housed under specific pathogen-free (SPF) conditions at Youjiang Nationality Medical University. Mice were kept in individually ventilated cages with controlled temperature (18–25 °C), humidity (50–70%), and a 12-h/12-h light/dark cycle. Each cage contained four mice, provided with sterilized corn-cob bedding (changed twice weekly), autoclaved standard rodent diet, and sterile water ad libitum. Environmental enrichment was supplied in the form of paper tube shelters. To minimize cage-related confounding effects, animals from different experimental groups were systematically distributed across the housing rack. The study protocol was approved by the Institutional Animal Ethics Committee of Youjiang Nationality Medical University (Approval No. 2024122001).

A total of 2 × 10⁶ transfected A549 cells suspended in 100 μL phosphate-buffered saline (PBS) were subcutaneously injected into the axillary region of anesthetized mice. The mice were randomly assigned to control or experimental groups using a computer-generated randomization sequence, with four mice per group. Tumor growth was monitored over 18 days, and tumor diameters were measured every 48 h using a caliper. All measurements were performed by investigators blinded to group assignments. Strict humane endpoints were applied throughout the study: animals exhibiting moribund status (e.g., inability to access food or water), severe mobility impairment, a tumor diameter exceeding 20 mm, or ulceration affecting >15% of the tumor surface area were euthanized immediately. All remaining mice were euthanized at the experimental endpoint (18 days post-injection).

Euthanasia was performed by placing mice in an induction chamber and administering 5% isoflurane mixed with oxygen (flow rate: 1 L/min) until respiratory arrest occurred. Cervical dislocation was then promptly carried out to ensure death. Absence of pupil reflex and cardiac activity was confirmed prior to the excision of xenograft tumors for subsequent analysis.

Statistical analysis

Bioinformatic analyses were conducted using the R programming language (version 4.3.0). Statistical analyses for cellular and animal experiments were performed with GraphPad Prism® (version 9.5.0). For continuous variables following a normal distribution (assessed using the Shapiro–Wilk test) with homogeneity of variance (evaluated by Levene’s test), comparisons between two groups were made using the unpaired Student’s t-test. For data that did not meet normality assumptions, the non-parametric Wilcoxon rank-sum test was applied. Categorical variables were analyzed using the following tests: the Chi-square test was used when all expected frequencies were greater than 5 and the total sample size was ≥40; Yates’ correction for continuity was applied when any expected frequency was between 1 and 5 and the sample size was ≥40; and Fisher’s exact test was employed when any expected frequency was less than 1 or the total sample size was less than 40. Additional details regarding statistical methods are provided in the Supplemental Materials.

Differential expression analysis of MAFF in cancer

We systematically evaluated the expression pattern of MAFF across multiple cancer types using the TIMER2.0 database. The results revealed significant differential expression of MAFF in various cancers (Fig. 1A). Compared with normal tissues, MAFF was consistently downregulated in numerous malignancies, including bladder cancer, breast cancer, cervical cancer, head and neck squamous cell carcinoma, kidney chromophobe carcinoma, kidney renal pelvis carcinoma, hepatocellular carcinoma, LUAD, LUSC, prostate cancer, and uterine corpus endometrial carcinoma, with all differences reaching statistical significance. These findings suggest that MAFF may function as a tumor suppressor in the development and progression of these cancers. To further validate these observations, we obtained paired transcriptomic data from TCGA for LUAD and evaluated MAFF expression using the Wilcoxon signed-rank test. The results confirmed that MAFF expression was significantly lower in LUAD tissues compared to adjacent normal samples (Fig. 1B), which was consistent with the TIMER2.0 findings.

Furthermore, we examined MAFF expression at the protein level using WB analysis in different cell types. The results showed that MAFF expression was significantly reduced in NSCLC cell lines (A549 and H1299) compared to immortalized human normal BEAS-2B cells (Figs. 1C and 1D), supporting a potential tumor-suppressive role of MAFF in NSCLC.

In summary, MAFF is significantly downregulated across a wide spectrum of cancers, as consistently demonstrated by both bioinformatic analyses and experimental validation. These results imply that MAFF may act as a tumor suppressor in various malignancies, underscoring the need for further functional studies to elucidate its mechanistic roles in cancer biology.

GSEA enrichment analysis and immune infiltration analysis

To elucidate the potential signaling pathways associated with MAFF in LUAD, we performed GSEA. The results revealed significant enrichment of MAFF-related genes in the VEGFA signaling pathway and the Hippo signaling pathway (Figs. 2A, 2B), suggesting a functional involvement of MAFF in these processes within NSCLC. The crosstalk between these pathways may offer important mechanistic insights into the biological roles of MAFF.

Additionally, we employed ssGSEA to examine the correlation between MAFF expression and immune cell infiltration. Our analysis showed a significant positive association between MAFF expression and the abundance of several immune cell types, including natural killer (NK) cells, neutrophils, CD8+ T cells, and eosinophils (Fig. 2C). These findings suggest that MAFF may promote the infiltration of immune cells into the tumor microenvironment, potentially enhancing antitumor immunity. This immunomodulatory function could contribute to remodeling the tumor microenvironment and may inform future combination strategies incorporating immunotherapy.

Single-cell RNA sequencing and functional analysis

Through single-cell RNA sequencing analysis, we successfully identified major cell types within the tumor microenvironment, including epithelial cells, endothelial cells, T cells, NK cells, B cells, mast cells, fibroblasts, and myeloid cells (Fig. 3A). Further subclustering of epithelial cells revealed transcriptionally distinct subpopulations (Fig. 3B). Violin plots illustrated the relative expression levels of MAFF across these subpopulations (Fig. 3C). Based on expression patterns, we categorized the cells into two groups: low MAFF expression (populations 0, 1, 2, 3, and 8) and high MAFF expression (populations 4, 5, 6, and 7) (Fig. 3D). Notably, tumor tissues exhibited a significant reduction in the proportion of MAFF-high cell populations compared to normal tissues (Fig. 3E), implicating MAFF as a potential modulator of tumor progression.

To further explore the functional significance of MAFF-negative cell populations, we performed GSVA using transcriptomic data from the TCGA cohort. The results indicated that higher GSVA scores for MAFF-negative populations were strongly correlated with worse patient prognosis (Fig. 3F). These findings suggest that MAFF may act as a tumor suppressor in the tumor microenvironment, and its loss could activate oncogenic signaling pathways, thereby facilitating tumor growth and progression. Together, these results underscore the multifaceted role of MAFF in cancer biology and support further investigation into its therapeutic potential.

The relationship between MAFF expression in NSCLC tissues and clinical pathological characteristics

IHC staining was performed on pathological sections from 56 paracancerous normal tissues and 77 NSCLC samples obtained from Baise People’s Hospital. The results demonstrated that MAFF expression was significantly downregulated in NSCLC tissues compared to adjacent normal tissues (Figs. 4A, 4B). To evaluate the clinical relevance of MAFF expression, we conducted a detailed correlation analysis between MAFF levels and clinicopathological parameters in this cohort (Table 1). The analysis indicated that MAFF expression was not significantly associated with patient age, gender, pathological stage, lymph node metastasis, or distant metastasis. However, a statistically significant correlation was observed between reduced MAFF expression and advanced clinical T-stage, as well as higher microvessel density MVD. These findings suggest that decreased MAFF expression is closely linked to enhanced tumor angiogenesis, implicating a potential role for MAFF in regulating the tumor microenvironment and modulating angiogenic processes during NSCLC progression.

MAFF inhibits NSCLC cell behavior in vitro

To investigate the biological function of MAFF in NSCLC cells, we established stable MAFF-overexpressing cell lines in A549 and H1299 cells through lentiviral infection followed by selection with puromycin. Fluorescence microscopy confirmed successful infection and the presence of a stably expressing cell population (Figs. 5A, 5D). WB analysis further verified that MAFF expression was significantly upregulated in transfected cells compared to control groups (Figs. 5B, 5C, 5E, 5F).

Functional assays were performed to assess the effects of MAFF overexpression. CCK-8 assays, conducted with three independent biological replicates each including at least three technical repeats, showed that MAFF significantly inhibited the proliferation of both A549 and H1299 cells (Figs. 6A, 6B). Similarly, plate colony formation assays demonstrated a marked suppression of clonogenic ability upon MAFF overexpression (Figs. 6C–6E). Transwell invasion assays revealed that MAFF significantly reduced invasive capacity (Figs. 6F–6H), and wound healing assays indicated impaired cell migration in MAFF-expressing cells (Figs. 6I–6K). All functional experiments were independently repeated three times, with each replicate comprising a minimum of three technical replicates for statistical analysis.

MAFF inhibits HUVEC angiogenesis in vitro

When A549 and H1299 stable cell lines reached 70–80% confluence, the complete culture medium was aspirated, and the cells were gently washed with phosphate-buffered saline PBS. Serum-free basal medium was then added, and the cells were incubated for 24 h to prepare conditioned medium for the angiogenesis assay. Subsequently, human umbilical vein endothelial cells (HUVECs) at 70–80% confluence were trypsinized, resuspended in the conditioned medium, and seeded at a density of 3 × 10⁴ cells per well into 96-well plates pre-coated with Matrigel. After 8 h of incubation under standard culture conditions, tube formation was assessed and photographed for quantitative analysis. The experiment was repeated three times independently with at least three technical replicates per condition.

The results demonstrated that overexpression of MAFF significantly inhibited the tube-forming ability of HUVECs (Figs. 7A, 7B). Furthermore, WB analysis confirmed that MAFF downregulated the expression of key angiogenic factors, including VEGFA and CTGF (Figs. 7D–7H).

MAFF inhibits YAP1 expression and its nuclear translocation

WB analysis was performed to examine the expression levels of YAP1 and its downstream angiogenesis-related factors, while IF was used to evaluate YAP1 nuclear translocation. All experiments were independently repeated three times, with each replicate including at least three technical repeats. WB results demonstrated that MAFF overexpression significantly downregulated YAP1 expression (Figs. 8A–8C). Consistent with this, IF analysis revealed a marked reduction in YAP1 nuclear translocation upon MAFF treatment (Figs. 8D–8F).

Inhibition of tumor cell growth by MAFF in vivo

To evaluate the antitumor effects of MAFF in vivo, a xenograft tumor model was established using A549 control cells and MAFF-overexpressing cells. A total of 2 × 10⁶ cells suspended in 100 μl of PBS were subcutaneously injected into the axilla of female Balb/c nude mice (n = 4 per group). Tumor volume was measured every two days using a caliper, and growth curves were generated accordingly. All mice were euthanized 18 days after inoculation, and the tumors were excised and weighed (Figs. 9A–9C). The results demonstrated that MAFF overexpression significantly inhibited tumor growth in vivo.

Tumor tissues were collected for subsequent protein analysis. WBting was performed to examine the expression of YAP1 and its downstream factors (Fig. 9E). The results indicated that MAFF downregulated the protein levels of YAP1, CTGF, and VEGFA (Fig. 9F). Additionally, paraffin-embedded tumor sections were subjected to immunohistochemical staining to evaluate MVD. The findings revealed that MAFF significantly reduced MVD compared with the control group (Figs. 9G, 9H). All experiments involving tissue analysis were repeated independently three times to ensure reproducibility.

Supplementary bioinformatics analysis

To further investigate the association between MAFF and the core effector of the Hippo pathway, YAP1, at the transcriptome level, we analyzed the relationship between MAFF expression and the mRNA levels of YAP1 and its canonical target genes CTGF (CCN2), CYR61 (CCN1), AMOTL2 and ANKRD1 in the TCGA-LUAD cohort. The results showed no statistically significant differences in the mRNA expression levels of YAP1 itself or these target genes between the MAFF-high and MAFF-low expression groups (Fig. 10). This finding suggests that MAFF’s regulation of the YAP pathway may not occur at the transcriptional level.

Additionally, we specifically examined MAFF expression in endothelial cells. Subclustering of endothelial cells revealed distinct populations (Fig. 11A). When categorized based on MAFF expression levels (Fig. 11B), we observed a decreasing trend in the proportion of the MAFF-low endothelial subpopulation within tumor tissues compared to normal tissues (Fig. 11C). This intriguing finding in the tumor vasculature compartment presents a contrast to the tumor-suppressive role of MAFF we identified in epithelial cells.