Sorting nexin 9 expression and prognostic implications in lung adenocarcinoma: integrative bioinformatic and in vitro validation

Abstract

Background

Sorting nexin 9 (SNX9) is involved in intracellular vesicle transport and signal transduction, and its abnormal expression is related to the occurrence and development of a variety of cancers. In lung adenocarcinoma (LUAD), the role and molecular mechanism of SNX9 remain unclear. This study combined bioinformatics analysis and in vitro validation to explore its expression characteristics in LUAD, its specific effects on tumor development, and its potential molecular mechanism and prognostic value.

Methods

In this study, the expression data and clinical information of SNX9 in LUAD were obtained from Tumor Immune Estimation Resource (TIMER) 2.0, The Cancer Genome Atlas (TCGA) and Human Protein Atlas (HPA) databases, and the relationship between SNX9 expression and prognosis was analyzed using TCGA database patient information and Kaplan-Meier plotter, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were used to reveal the mechanism of SNX9. Gene set enrichment analysis (GSEA) enrichment analysis highlighted the pathways and biological processes rich in gene sets in SNX9 high-expression samples, thereby providing insights into associated enrichment pathways. The effects of SNX9 on the proliferation, migration and invasion of LUAD cells were detected by Western blot and in vitro experiments.

Results

The results of this study showed that the expression level of SNX9 in LUAD tissues was significantly higher than that in normal lung epithelial cells, and its high expression was closely related to the increase in tumor grade and poor prognosis of patients. Functional enrichment analysis showed that SNX9-related genes were concentrated in epithelial-mesenchymal transition (EMT), extracellular matrix (ECM) and cell adhesion processes in LUAD, suggesting that the increased expression of SNX9 is positively correlated with the enhanced invasion ability of LUAD cells. In vitro experiments also showed that knockdown of endogenous SNX9 significantly inhibited the proliferation, migration and invasion of A549 and H1299 cells.

Conclusions

This study shows that SNX9 is overexpressed in LUAD and is associated with poor prognosis. We speculate that SNX9 is expected to be a prognostic marker and a potential therapeutic target for LUAD, providing a new direction and theoretical basis for related research and clinical application.

Highlight box.

Key findings

• Sorting nexin 9 (SNX9) is highly expressed in lung adenocarcinoma (LUAD) and is associated with a poor prognosis of LUAD.

• SNX9 affects the proliferation, metastasis and invasion of LUAD cells.

What is known and what is new?

• SNX9 plays an important role in the occurrence and development of various tumor diseases and is closely related to disease progression.

• SNX9 may be a potential target for the treatment of LUAD.

What is the implication, and what should change now?

• SNX9 can be used as a potential biomarker for the diagnosis and prognosis of LUAD.

• More experiments are needed to clarify the specific signaling pathways and molecular mechanisms of SNX9 affecting the development and progression of LUAD.

Introduction

Globally, lung cancer ranks as the primary cause of cancer-related mortality. In 2022, approximately 2.48 million new cases emerged, while 1.8 million fatalities were attributed to this disease (1). Non-small cell lung cancer (NSCLC) constitutes over 85% of all lung cancer cases lung adenocarcinoma (LUAD) represents the primary pathological subtype of NSCLC, making up roughly 45–55% (2,3). Patient prognosis in LUAD shows significant variation due to molecular heterogeneity and treatment resistance (4). While certain targeted therapies, including programmed death 1/programmed cell death ligand 1 (PD-1/PD-L1) inhibitors and epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI), have extended median survival times to over three years for some individuals, the overall 5-year survival remains below twenty percent. This highlights the constraints of current treatment options and prognostic assessment frameworks (5-7). The application of biomarkers in the treatment of breast, gastric, and colorectal cancer has helped to achieve partial success and greatly improved the prognosis of patients (8-10). Therefore, it is equally important to identify new biomarkers in LUAD, which will help to accurately predict patient prognosis and guide clinical treatment, thereby improving diagnostic and therapeutic effects (11,12).

Sorting nexin 9 (SNX9) belongs to the connexin family involved in sorting. The protein it encodes comprises an N-terminal Src homolog region and a Phox homolog (PX) region that binds to phosphoinositol (13). The PX domain enables specific lipid binding, including phosphatidylinositol-4,5-bisphosphate, and contributes to processes like clathrin-mediated or independent endocytosis, macropinocytosis, and F-actin formation. Interactions with proteins such as dynein, adaptor protein 2, and tyrosine kinase non-receptor 2 occur via the Src homology 3 (SH3) domain, while complexes form with membrane components including T cell receptor and lymphocyte function-associated antigen-1 (LFA-1), for roles in immune synapse assembly and signaling transduction (14,15). It plays a role in clathrin-independent endocytosis, cellular migration and invasion, mitotic progression, and cytokinesis completion (16). Previous studies have shown that SNX9 promotes metastasis in breast cancer by differentially modulating RhoGTPase activity to enhance cell invasion, and in colorectal cancer by governing the cell-surface abundance of integrin β1 in vascular endothelial cells, thereby driving angiogenesis and correlating with poor prognosis (17,18). Consistently, pan-cancer analysis from Tumor Immune Estimation Resource (TIMER) 2.0 revealed markedly elevated SNX9 expression in cholangiocarcinoma, esophageal, LUAD, lung squamous cell carcinoma and gastric cancer (P<0.001, Figure 1A), underscoring its potential role across diverse tumor types. However, the precise mechanism by which SNX9 contributes to LUAD progression remains unclear.

Figure 1.

The expression of SNX9 in LUAD. (A) Expression levels of SNX9 in pan-cancer and LUAD analyses from the TIMER 2.0 database. (B) The protein levels of SNX9 in normal lung tissue in HPA database (https://www.proteinatlas.org/ENSG00000130340-SNX9/tissue/lung#img) and the protein levels of SNX9 in LUAD tissue in HPA by ICH staining (https://www.proteinatlas.org/ENSG00000130340-SNX9/cancer/lung+cancer#img); scale bar: 100 μm; and quantitative analysis of both sets of images was performed [(A) red box]. (C) SNX9 mRNA expression in 539 LUAD tissues versus 59 normal lung tissues from the TCGA database (Wilcoxon rank-sum test). (D) SNX9 mRNA expression in 58 paired LUAD tissues and their matched adjacent normal tissues from the TCGA database (paired Wilcoxon signed-rank test). (E,F) The expression level of SNX9 in LUAD cell line and human normal lung epithelial cells BEAS-2B and the statistical graph of western blot gray value. Data are from three independent biological replicates. *, P<0.05; **, P<0.01; ***, P<0.001. AOD, average optical density; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; HPA, Human Protein Atlas; IHC, immunohistochemistry; LUAD, lung adenocarcinoma; SNX9, sorting nexin 9; TCGA, The Cancer Genome Atlas; TIMER, Tumor Immune Estimation Resource; TPM, transcripts per million.

The aim of this study was to investigate the relationship between SNX9 and the prognosis of LUAD by systematic bioinformatics analysis. Meanwhile, the signaling pathways involved in LUAD development were identified by enrichment analysis. Using The Cancer Genome Atlas (TCGA) database information and in vitro experiments, the biological function of SNX9 in LUAD was determined. Overall, these findings highlight the critical role of SNX9 in the development, progression, and prognosis of LUAD and suggest its potential as a biomarker and therapeutic target for predicting patient survival outcomes. We present this article in accordance with the MDAR and TRIPOD reporting checklists (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1083/rc).

Methods

Data acquisition

From the TCGA database (portal.gdc.cancer.gov), transcriptomic data for 539 LUAD samples and 59 normal lung tissue samples were acquired. A study was conducted on the relationship between SNX9 expression and LUAD clinical characteristics (19). The TIMER2.0 database serves as a tool for analyzing SNX9 gene expression across various cancers. This resource provides comprehensive data accessible at http://timer.cistrome.org/ for conducting detailed pan-cancer studies (20). The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Human Protein Atlas (HPA) database

The HPA (https://www.proteinatlas.org/) serves as an extensive database associated with TCGA cancers (21). This study used immunohistochemistry (IHC) images from the HPA database to compare SNX9 protein expression levels between normal lung tissue (alveolar cells) and lung cancer tissue (tumor cells) (antibody HPA031410).

Clinical expression profiles and survival prognosis analysis

All original RNA sequencing (RNA-seq) count data and corresponding clinical information were downloaded from the Genomic Data Commons (GDC) Data Portal (https://portal.gdc.cancer.gov). We used the TCGA-LUAD project dataset to examine SNX9 differential expression across various tumour-node-metastasis (TNM) stages, clinicopathological stages, age categories, and gender groups Kaplan-Meier analysis assessed the relationship between SNX9 expression and overall survival (OS) as well as progression-free survival (PFS) in LUAD patients to confirm SNX9 prognostic significance in this cancer type a visual predictive model was constructed, and nomogram was applied to measure the accuracy of SNX9 expression in forecasting patient survival outcomes.

Functional enrichment analysis

We performed functional enrichment analysis using TCGA-LUAD data, and the specific genes used for enrichment analysis can be viewed in the attachment. The ClusterProfiler software package conducted Gene Ontology (GO) enrichment analysis on SNX9 core genes, including biological process, cell component, molecular function (MF), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis (22-24). We carried out gene set enrichment analysis (GSEA) to identify relevant signaling pathways. Visualization of these outcomes was conducted with the “ggplot2” tool, ensuring clear graphical representation (25).

Cell culture and small interfering RNA (siRNA) transfection

The National BioMedical Cell Resource Center in Shanghai, China, provided human lung cancer cell lines, including A549, H441, H1299, and H1975, as well as normal human bronchial epithelial cells BEAS-2B. The cells were grown in Gibco DMEM and Gibco 1640 media (Thermo Fisher Scientific, Waltham, MA, USA), with additions of 10% fetal bovine serum and 100 IU/mL penicillin-streptomycin, maintained at 37 ℃ and 5% CO₂ under normal conditions. Medium changes and cell passaging occurred routinely. Following digestion, LUAD cells in the logarithmic growth phase underwent resuspension, counting, and plating. The siRNA sequences targeting SNX9, namely siSNX9#1 with sequence 5'-GCUAACACCUACUAACACUAATT-UUAGUGUUAGUAGGUGUUAGCTT-3' and siSNX9#2 with sequence 5'-CCCUUAACAAAUUUCCUGGAUTT-AUCCAGGAAAUUUGUUAAGGGTT-3', were obtained from GENE CREATE located in Wuhan, China. By the second day, transfection of siRNAs into cells at a confluency of 70–80% was conducted using Lipofectamine^® 6000 reagent provided by Beyotime in Shanghai, China (catalog No. #C0526FT).

Cell counting kit-8 (CCK-8) assay

Plating LUAD cells in 96-well plates occurred at a density of 5,000 cells per well, followed by incubation at 37 °C in a 5% CO₂ environment for 24 hours. Transfection of siRNA-NC, siRNA-siSNX9#1, and siRNA-siSNX9#2 into LUAD cells took place individually. At 24-, 48-, and 72-hour post-transfection, each well received 10 µL of CCK-8 reagent (Beyotime, catalog No. #C0038, Shanghai, China), with optical density assessed at 450 nm. Experimental procedures included a minimum of three replicates.

Cell scratch assay

Transfected LUAD cells were cultured in six-well plates until confluent. A sterile 100 µL pipette tip was used to create a straight scratch across the monolayer, generating a cell-free gap. Images were captured at 0 and 24 h. For each field, five non-overlapping microscope fields along the scratch were randomly chosen and photographed. Each condition was tested in three independent wells.

Transwell assay

Matrigel precoated the Transwell chambers. Serum-free medium resuspended transfected LUAD cells at a concentration of 1×10⁵ cells/mL. The upper chamber received 200 µL of cell suspension, while 600 µL of medium with 10% serum was placed in the lower chamber. The Transwell chambers were taken out after 48 h, then fixed in 4% paraformaldehyde for 15 min and stained using crystal violet for 5 min. Subsequently, these were observed via light microscopy and images captured.

Western blot

Adherent cells were harvested, and total protein was extracted using SEVEN’s RIPA lysis buffer (SW 104-02, Beijing, China). Protein concentration was measured with the Thermo Scientific BCA Protein Quantification Kit (catalog No.23235 Waltham, MA, USA) as per the manufacturer’s protocol. Equal amounts of protein were separated via vertical electrophoresis on 6–10% Sodium Dodecyl Sulfate-Polyacrylamide Gel electrophoresis (SDS-PAGE) and transferred to polyvinylidene fluoride (PVDF) membranes through wet transfer. The membranes were blocked with 5% skim milk powder solution at room temperature for 1 hour, followed by three washes with Tris-Buffered Saline-Tween (TBST) buffer. For primary antibody incubation, the membranes were incubated overnight at 4 °C in blocking solution containing specific primary antibodies. After TBST washing, the membranes were incubated with matching fluorescent secondary antibodies for 1 hour at room temperature in the dark. Chemiluminescent signals were detected using the Odyssey dual-color infrared laser imaging system after final TBST washing. The primary antibodies used were SNX9 (Abcam, ab181856, Cambridge, UK), E-Cadherin (Cell Signaling Technology, CST 3195, Danvers, MA, USA), N-Cadherin (CST 13116), vimentin (CST 5741), PCNA (Proteintech 10205-2-AP, Wuhan, China), Cyclin D1 (Proteintech 60186-1-Ig), MMP-2 (Proteintech 10373-2-AP), MMP-9 (Proteintech 10375-2-AP), and GAPDH (CST 2118T).

Statistical analysis

GraphPad Prism 9.0 and R (version 4.4.1) served for data processing and statistical evaluation. TCGA database information underwent handling via R packages. Assessment of the relationship between SNX9 and LUAD clinical characteristics utilized logistic regression modeling. The Kaplan-Meier method, along with the log-rank test, was applied for survival analysis. Prognostic significance of SNX9 was assessed through Cox regression. Forest plots and nomograms were generated by ggforest and survival R packages to illustrate the prognostic model, while its accuracy and consistency were examined. Analysis of protein blot images was carried out using ImageJ software. The thresholds for statistical significance were set at *, P<0.05; **, P<0.01; ***, P<0.001; with ns indicating no significance when P>0.05.

Results

Database analysis reveals SNX9 levels in LUAD

Analysis via the TIMER database revealed elevated SNX9 expression in cholangiocarcinoma, esophageal cancer, LUAD, lung squamous cell carcinoma, and gastric cancer compared to normal tissue (P<0.001, Figure 1A). Data from the HPA database revealed significant upregulation of SNX9 protein in LUAD tissues relative to normal lung tissues through IHC analysis (Figure 1B). As shown in Figure 1C, SNX9 messenger RNA (mRNA) levels were significantly higher in 539 LUAD samples compared with 59 normal lung tissues (P<0.001, Wilcoxon rank-sum test). In the paired cohort of 58 LUAD and matched adjacent normal tissues, SNX9 expression was also markedly elevated in tumors (P<0.001, paired Wilcoxon signed-rank test, Figure 1D). Western blot analysis performed on human LUAD cell lines, including A549, H441, H1299, and H1975, revealed significantly elevated SNX9 protein levels in LUAD cells relative to control lung epithelial cells (BEAS-2B), with statistical significance (P<0.001, Figure 1E,1F).

Association of SNX9 expression with clinical characteristics of LUAD in the TCGA database

Using the TCGA database, we evaluated the association between SNX9 expression and clinicopathologic characteristics. Significant differences were observed for T stage (P<0.05) and N stage (P<0.01) (Figure 2A,2B). No associations were found with age (P>0.05; Figure 2C). Pathological stage again showed significant variation (P<0.05; Figure 2D). Likewise, sex and M stage were not significantly associated with SNX9 expression (both P>0.05; Figure 2E,2F). We further carried out univariate and multivariate Cox regression analyses incorporating TNM stage, age, and sex; detailed results are shown in Figure S1A,S1B.

Figure 2.

The relationship between SNX9 expression and clinical features was analyzed using the TCGA-LUAD data. SNX9 expression variation in distinct T stages (A), N stages (B), M stages (C), pathologic stages (D), ages (E), and gender (F). *, P<0.05; **, P<0.01; and ns, P>0.05. LUAD, lung adenocarcinoma; M, metastasis; N, node; ns, no significance; SNX9, sorting nexin 9; T, tumor; TCGA, The Cancer Genome Atlas.

Association of SNX9 expression with LUAD prognosis

Analysis of the Kaplan-Meier curves for OS and PFS indicates that elevated SNX9 expression correlates with reduced OS and PFS, as shown in Figure 3A,3B with P<0.05. A prognostic nomogram was developed using SNX9 expression, gender, age, pathological stage, and TNM risk factors (Figure 3C). This nomogram showed accurate discrimination and consistency in predicting 1-, 3-, and 5-year survival rates for LUAD through calibration curves (Figure 3D).

Figure 3.

Survival prognosis in patients with SNX9. Kaplan-Meier method was used to analyze the effect of SNX9 expression on the OS (A) and PFS (B) of LUAD in TCGA database. (C) The nomogram with sex, age, SNX9 expression, pathological stage, T stage, and N stage as parameters was used to predict the OS of LUAD patients. (D) Nomogram calibration curve based on SNX9 in TCGA database. *, P<0.05; **, P<0.01. LUAD, lung adenocarcinoma; MNA, metastasis not applicable; N, node; OS, overall survival; PFS, progression-free survival; SNX9, sorting nexin 9; T, tumor; TCGA, The Cancer Genome Atlas.

Functional enrichment of SNX9-related genes in LUAD

The role of SNX9 in LUAD was investigated by conducting enrichment analyses on its co-expressed genes through GO-biological process (BP), KEGG, and GSEA. Biological processes like cell growth, differentiation, and extracellular matrix (ECM) component composition were revealed via BP, cellular component (CC) and MF analysis (Figure 4A,4B). Pathways such as the cytoskeleton in muscle cells, ECM-receptor interaction, and PI3K-AKT signaling show connections with SNX9 co-expressed genes through KEGG enrichment analysis (Figure 4C). GSEA enrichment analysis revealed associations between the genes and cancer invasiveness, prognosis, treatment response, and the epithelial-mesenchymal transition (EMT) process as shown in Figure 4D.

Figure 4.

Functional enrichment analysis. (A) Circular plot for GO enrichment analysis. (B) Bar plot for GO enrichment analysis. (C) Signaling pathways enriched displayed by KEGG analysis. (D) GSEA analysis presents signaling pathways enriched. BP, biological process; CC, cellular component; ECM, extracellular matrix; GO, Gene Ontology; GSEA, gene set enrichment analysis; KEGG, Kyoto Encyclopedia of Genes and Genomes; MF, molecular function.

SNX9 knockdown inhibited the proliferation, migration and invasion of LUAD cells

SNX9 expression was confirmed in LUAD cell lines at both transcriptomic and proteomic levels. The protein of SNX9 in A549 and H1299 showed markedly higher levels compared with normal lung epithelial BEAS-2B (Figure 1E). siRNA vectors were used to silence SNX9 in LUAD cell lines. Protein levels of SNX9 decreased markedly compared to negative controls in A549 and H1299 cells, as shown in Figure 5A. Follow-up analyses, such as CCK-8 and colony formation, showed marked suppression of cell proliferation after SNX9 knockdown relative to controls (Figure 5B,5C). Transwell invasion assay showed that a significant reduction in the invasive ability of A549 and H1299 cells was observed after SNX9 knockdown (Figure 5D). Protein levels of cyclin D1 and PCNA were markedly reduced by SNX9 silencing, as further verified through western blotting analysis (Figure 5E). Migration capabilities were evaluated via scratch assays. Significant decreases in the migratory capacities of A549 and H1299 cells were observed after SNX9 knockdown (Figure 6A,6B). We also explored the impact of siRNA on multiple metastasis-associated proteins and mesenchymal markers within LUAD cells. Reduced levels were observed for MMP2, MMP9, N-cadherin, and vimentin, while E-cadherin expression was increased, as shown in Figure 6C,6D.

Figure 5.

Knockdown of SNX9 inhibited the growth and metastasis of A549 and H1299 cells. (A) Western blot and densitometric quantification (n=3) showing SNX9 knockdown efficiency versus negative control (NC). (B) CCK-8 proliferation curves of A549 and H1299 cells transfected with NC, siSNX9#1 or siSNX9#2 for 0, 24, 48, and 72 h. (C) Representative images and quantification of colony-formation assays, by crystal violet staining method. (D) Transwell invasion images and statistical analysis, by crystal violet staining method. (E) Western blot and densitometry for cyclin D1 and PCNA after SNX9 knockdown. Data are from three independent biological replicates. *, P<0.05; ***, P<0.001. CCK8, cell counting kit-8; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; NC, non-transduced controls; PCNA, proliferating cell nuclear antigen; SNX9, sorting nexin 9; SNX9, sorting nexin 9.

Figure 6.

SNX9 knockdown affected the biological functions of A549 and H1299 cell lines. (A,B) Representative images of wound healing experiments in A549 and H1299 cell lines after SNX9 gene knockdown and statistical analysis of wound healing experiments. (C) Western blot was used to detect the effect of SNX9 knockdown on the expression of MMP-9 and MMP-2 and the expression of EMT-related protein levels in A549 cells. (D) Western blot was used to detect the effect of SNX9 knockdown on the expression of MMP-9 and MMP-2 and the expression of EMT-related protein levels in H1299 cells. Data are from three independent biological replicates. ***, P<0.001. EMT, epithelial-mesenchymal transition; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; NC, non-transduced controls; SNX9, sorting nexin 9.

Discussion

Lung cancer, the leading global cause of cancer-related deaths, is marked by high mortality and low survival rates (26). Its early symptoms, often hidden and non-specific, are easily confused with other respiratory diseases. This leads to most patients being diagnosed at advanced stages, missing the optimal treatment window. In regions without early screening, the delay from symptom onset to diagnosis exacerbates the condition (27,28). Early screening is crucial for improving prognoses. Evidence shows early detection can notably cut lung cancer mortality, with the US National Lung Screening Trial (NLST) indicating that low-dose computed tomography (LDCT) screening for high-risk groups can reduce mortality by about 20% (29). Yet, LDCT has drawbacks. It demands professional equipment and personnel, limiting its use in resource-poor areas. Also, false-positive results can burden patients (30). To enable early, non-invasive, and precise detection, there is a need for a cost-effective and widely applicable solution. One of the most promising approaches is to find the most potent set of biomarkers (31).

SNX9 serves as a sorting junction protein associated with numerous physiological roles. This protein participates in immune regulation processes, modulates endocytosis, and influences cell proliferation and migration (32). Moreover, SNX9 plays a crucial role in metabolic complications related to inflammation regulation (33,34). Current research on SNX9 primarily explores its role in cancer, highlighting its involvement in facilitating tumor growth and spread as well as contributing to multidrug resistance development. In this study, the expression level of SNX9 in LUAD was significantly higher than that in normal lung tissues by checking the transcriptome information of TCGA database, and the high protein level of SNX9 in LUAD was also confirmed by immunohistochemical results. The observation aligned with the cross-cancer expression profile analysis from TCGA database, indicating SNX9’s potential involvement in tumorigenesis mechanisms. Subsequently, we performed western blot in LUAD cell lines (A549, H441, H1299, H1975) and normal bronchial epithelial cells (BEAS-2B), and found that SNX9 expression was significantly higher in LUAD cells than in normal bronchial epithelial cells. This highlights its tumor-specific expression increase. Data imply SNX9 overexpression in LUAD contributes to cancer initiation and progression. Through analysis of clinical data in the TCGA database, a significant correlation was observed between SNX9 expression and the T stage as well as the N stage in LUAD patients. Significant associations also emerged regarding SNX9 expression across different pathological stages. No notable connection existed between SNX9 expression and the M stage, patient age, or gender. Meanwhile, high expression of SNX9 was significantly associated with poor OS and PFS in LUAD patients, as indicated by Kaplan-Meier analysis. A nomogram combining SNX9 expression with clinicopathological factors was developed, and its accuracy in predicting 1-, 3-, and 5-year survival rates was verified by calibration curves, thus providing a new method for personalized prognostic evaluation of LUAD (35). The findings indicate that SNX9 exhibits overexpression in LUAD and its level might serve as a possible biomarker for assessing patient prognosis. Then, GO and KEGG enrichment analysis revealed that SNX9-related genes were mainly involved in ECM remodeling, cell adhesion and EMT. GO analysis showed that the genes regulated by SNX9 were closely related to fibronectin binding and integrin signaling pathways, all of which were confirmed to be involved in tumor invasion and metastasis (36,37). Additionally, KEGG pathway analysis demonstrates that SNX9 correlates with the PI3K-Akt signaling pathway, TGF-β signaling pathway, and ECM-receptor interaction, suggesting its potential role in advancing LUAD through activation of downstream signals for proliferation and survival (38-40). GSEA indicated that gene sets associated with tumor invasion, including epithelial-mesenchymal transition markers and angiogenesis genes, were highly enriched in samples with elevated SNX9 expression. Such findings imply that SNX9 could facilitate LUAD proliferation, migration, and invasion through modulating ECM reconstruction, cellular adhesion, and EMT procedures (41). Finally, to verify the biological role of SNX9 in LUAD, siRNA was used to downregulate its expression in A549 and H1299 cells. CCK-8 and colony formation assays showed that SNX9 inhibition inhibited cell proliferation. As a nuclear protein, PCNA plays a key role in DNA replication and repair. Its elevated presence is associated with the proliferative activity of a variety of cancers, and it is used as a marker in pathological diagnosis to evaluate the degree of malignancy and prognosis of tumors (42). The CCND1 gene encodes cyclin D1, which belongs to the D-type cyclin family. Abnormal expression of this protein may result in loss of cell cycle control and promote cancer development (43). The reduction in cyclin D1 and PCNA protein levels following SNX9 knockdown was further confirmed through western blot analysis. Migration and invasion capabilities of LUAD cells were substantially suppressed upon SNX9 knockdown as demonstrated by scratch and Transwell assays. As critical factors, MMP-2 and MMP-9 contribute to tumor invasion, angiogenesis, and immune escape via ECM degradation, growth factor activation, and inflammatory microenvironment modulation (44,45). The regulation of its activity involves multiple levels such as gene expression, post-translational modification and tissue inhibitors of metalloproteinases (TIMPs). EMT represents a dynamic transformation of cell phenotype where epithelial cells gain mesenchymal cell features including motility and invasiveness by reducing polarity, cell-cell adhesion and migration capacity (46). This procedure is crucial for embryonic growth, tissue regeneration, and disease conditions like cancer spread and excessive scar tissue formation (47). Western blot analysis showed that knockdown of SNX9 reduced the expression of MMP-2, MMP-9, N-cadherin and vimentin, while enhancing the expression of E-cadherin. The results showed that the effect of SNX9 knockdown on MMP-2 and MMP-9 reduced the ability of tumor cells to degrade ECM and inhibited tumor cell migration, invasion, and EMT. Given the constraints of a single database and limited sample size, we collected clinical LUAD adjacent tissues and LUAD tissues to validate differential SNX9 expression by IHC (Figure S2A,S2B). Moreover, because lineage-specific co-staining is not provided by the HPA, we cannot exclude the possibility that some signal arises from stromal components. Whether SNX9 exhibits similar expression patterns and prognostic value in lung squamous cell carcinoma or mesothelioma remains unclear, and systematic cross-histology studies are warranted to clarify its pan-lung-cancer role. Additionally, stratifying SNX9 expression by PD-L1 status may provide insights into the immune microenvironment; however, such analyses were beyond the focused scope of the present study and are planned as part of our ongoing work. Furthermore, while our study focused on the role of SNX9 in tumor cells, future research should also consider evaluating the potential off-target effects and therapeutic window in normal lung epithelial cells to fully understand the therapeutic potential of SNX9 inhibition.

Conclusions

This research demonstrates that SNX9 exhibits substantial overexpression in LUAD, with its elevated level linked to unfavorable outcomes. It establishes that SNX9 drives tumor development through ECM remodeling and EMT regulation, highlighting its potential as a prognostic indicator and treatment focus. This insight offers novel strategies for precise LUAD management. Ongoing investigations should delve into the molecular basis and clinical significance of SNX9 to enhance LUAD patient outcomes.

Supplementary

The article’s supplementary files as

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.

Data Sharing Statement

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DOI: 10.21037/tcr-2025-1083