Proteomics reveals the regulation of ALG1 expression by lentivirus‑mediated THBS1 overexpression and its mechanism in meibomian gland carcinoma

Introduction

Meibomian gland carcinoma (MGC) is a malignant tumor arising from the meibomian glands of the eyelid, characterized by pronounced local invasiveness and a high propensity for metastasis to regional lymph nodes and distant organs (1,2). The overall incidence of SGC is ~2 cases per 100,000 person-years. The mortality rate of this disease has decreased from 50% to 2–10% (3,4). The early clinical manifestations of MGC are often subtle and non-specific, frequently leading to misdiagnosis or confusion with benign inflammatory conditions such as meibomian gland cysts. This diagnostic challenge often results in delayed treatment, thereby increasing the likelihood of tumor invasion and metastasis (5,6). Despite surgical resection being the current mainstay of treatment, the postoperative recurrence rate remains high, reaching up to 40% (5). To date, the molecular mechanisms underlying the pathogenesis and progression of MGC remain largely unclear, both domestically and internationally.

Our previous study successfully established and characterized cell models of MGC and normal meibomian gland cells through primary culture of freshly excised surgical tissue, followed by differential gene expression analysis (7). Using microRNA (miRNA or miR) microarray technology, miR-3907 was identified as notably upregulated in MGC tissues compared with in adjacent non-tumorous tissues. Bioinformatic analyses, along with dual-luciferase reporter assays, confirmed that thrombospondin 1 (THBS1) is a direct target of miR-3907. Functional experiments further demonstrated that miR-3907 promotes the proliferation and migration of MGC cells by downregulating THBS1 expression (8). THBS1, a well-established tumor suppressor, is notably downregulated in MGC, where it normally functions to inhibit tumor growth and metastasis. As an extracellular matrix protein, THBS1 serves a critical role in tumor progression and dissemination across multiple cancer types (9,10). For instance, its expression has been associated with clinical parameters such as tumor-node-metastasis staging and lymph node metastasis in laryngeal squamous cell carcinoma, and it has been reported to influence the trans-epithelial migration of breast cancer cells (11,12). Building upon the identification of the miR-3907-THBS1 regulatory axis, the present study aimed to further elucidate the role of chitobiosyldiphosphodolichol β-mannosyltransferase 1 (ALG1), a downstream effector protein. Due to the inherent limitations in delivering miR-3907 and the challenges posed by THBS1 as a large extracellular matrix protein for clinical drug administration (13), targeting ALG1 may offer a more practical therapeutic approach. ALG1, being amenable to inhibition by small-molecule compounds (14), represents a feasible downstream target for rapid clinical translation. Moreover, a comprehensive investigation of the entire ‘miRNA-target gene-effector protein’ pathway not only enhances mechanistic specificity but also facilitates the development of tiered therapeutic strategies. Proteomics, as a cutting-edge tool for systematically profiling protein expression and function in biological systems, provides powerful means to elucidate disease pathogenesis and progression, and to uncover novel therapeutic targets (15,16). Our research group performed a preliminary proteomic analysis of MGC after overexpressing THBS1 and identified certain differentially expressed proteins. However, in-depth functional validation of these proteins has not been performed (17).

The present study aimed to comprehensively assess the downstream regulatory mechanisms of THBS1 in MGC. Utilizing 4D label-free quantitative proteomics, differentially expressed proteins (DEPs) were identified between THBS1-overexpressing and control groups. Among these, ALG1 exhibited the most significant fold change and was selected as the primary focus of the present research. Furthermore, the functional role and molecular mechanisms of ALG1 within the miR-3907/THBS1/ALG1 regulatory axis were evaluated, with particular emphasis on its influence on MGC cell behavior and epithelial-mesenchymal transition (EMT). The findings of the present study provide new insights into the post-transcriptional regulatory network of MGC and offer promising avenues for the development of novel diagnostic biomarkers and targeted therapeutic strategies. The experimental workflow of the present study is presented in Fig. 1.

Figure 1. Study flowchart. Screening of differential target proteins in the downstream of THBS1 by proteomics, followed by the functional validation of ALG1 in meibomian gland carcinoma. THBS1, thrombospondin 1; ALG1, chitobiosyldiphosphodolichol β-mannosyltransferase 1; nc, negative control; oe, overexpression; miRNA/miR, microRNA.

Materials and methods

Materials

The following materials were used in the present study: RPMI-1640 medium (Gibco; Thermo Fisher Scientific, Inc.), phosphate-buffered saline (PBS; Gibco; Thermo Fisher Scientific, Inc.), trypsin (Gibco; Thermo Fisher Scientific, Inc.), dimethyl sulfoxide (Beijing Solarbio Science & Technology Co., Ltd.), Cell Counting Kit-8 (CCK-8) assay kit (Beijing Solarbio Science & Technology Co., Ltd.), RNA extraction kit (EZBioscience), first-strand cDNA synthesis kit (EZBioscience), quantitative real-time PCR kit (EZBioscience), total protein extraction kit (Beijing Solarbio Science & Technology Co., Ltd.), BCA protein concentration assay kit (Beijing Solarbio Science & Technology Co., Ltd.), apoptosis detection kit (Nanjing KeyGen Biotech Co., Ltd.).

Primary cell culture

In our previous research, fresh MGC tissues and adjacent paracancerous tissues were obtained from patients undergoing Mohs micrographic surgery (8). The primary cells used in the present study were derived from these tissue samples. Informed consent in writing from patients for all samples was obtained prior to the aforementioned published study. Moreover, the primary MGC cells were previously isolated, identified and characterized using Oil Red O staining and immunofluorescence, leading to the successful establishment of three primary MGC cell lines (7). Cells in the logarithmic growth phase between passages 4 and 10 were selected for all experiments. They were cultured in complete medium supplemented with 10% fetal bovine serum (FBS; Gibco; Thermo Fisher Scientific, Inc.) and 1% penicillin-streptomycin (HyClone; Cytiva), and maintained at 37°C in a humidified incubator with 5% CO2 (Thermo Fisher Scientific, Inc.). The culture medium was replaced every 2–3 days. Once cell confluence reached ~90%, the cells were harvested and used for subsequent assays. The study protocol was approved by the Ethics Committee of Tianjin Medical University Eye Hospital [Tianjin, China; approval no. 2020KY(L)-20].

Cell transfection and lentiviral overexpression

For small interfering (si)RNA-mediated gene knockdown experiments, siRNAs targeting ALG1 and negative control siRNAs were synthesized by OBiO Technology (Shanghai) Co., Ltd. The ALG1-specific siRNA sequences included a sense strand (5′-GAUCCUGCGGGCAAGCUAATT-3′) and an antisense strand (5′-UUAGCUUGCCCGCAGGAUCTT-3′), and the negative control siRNA sequences included a sense strand (5′-UUCUCCGAACGUGUCACGUTT-3′) and an antisense strand (5′-ACGUGACACGUUCGGAGAATT-3′). The siRNA was used at a final concentration of 50 nM for cell transfection. When preparing the transfection reagent, 50 µl Opti-MEM (BasalMedia) was used to dilute the siRNA, which was gently pipetted up and down to mix. Separately, 1.0 µl Lipofectamine™ 3000 (Invitrogen; Thermo Fisher Scientific, Inc.) was diluted with 50 µl Opti-MEM, gently pipetted to mix and incubated at room temperature for 5 min. The diluted transfection reagent and siRNA solution were then combined and incubated at room temperature for 20 min. After siRNA transfection, mRNA levels were detected 24–48 h later, whilst protein levels were analyzed after 48–96 h.

Lentiviral overexpression was performed using a second-generation packaging system [OBiO Technology (Shanghai) Co., Ltd.] consisting of pSLenti-SFH-EGFP-P2A-Puro-CMV-THBS1-3×FLAG-WPRE (THBS1OE) or pcSLenti-EF1-EGFP-P2A-Puro-CMV-ALG1-3×FLAG-WPRE (ALG1OE) as transfer plasmids, with corresponding empty vectors serving as negative controls. The mass of lentiviral vector plasmid was 2 µg, and the ratio of vector plasmid: packaging plasmid: envelope plasmid was 2:1.5:0.5. The packaging plasmid mixture (backbone: Shuttle=1:1; total=32 µg) was transfected into 293T cells (American Type Culture Collection) using Trans-fect Lentiviral Packaging Transfection Reagent [OBiO Technology (Shanghai) Co., Ltd.] following the manufacturer's protocol. Briefly, cells were seeded in a 100-mm dish to achieve a confluency of 70–80% at the time of transfection. Plasmids and reagents were separately diluted in 500 µl Opti-MEM, incubated at room temperature for 5 min, combined and further incubated at room temperature for 20 min to form complexes. After the medium was replaced with 10 ml Opti-MEM, the complexes were added to the cells. A total of 6–8 h post-transfection, the medium was replaced with fresh complete medium. Viral supernatants were harvested at 48 and 72 h post-transfection, pooled, centrifuged at 2,000 × g for 10 min at room temperature to remove debris, filtered through 0.22-µm membranes, and ultracentrifuged at 100,000 × g for 2 h at 4°C. The pellets were resuspended in pre-cooled DPBS, incubated overnight at 4°C, filtered again, aliquoted and stored at −80°C. For transduction, MGC cells were seeded in a 24-well plate to reach 30–40% confluency and infected with lentivirus at a multiplicity of infection of 40 (determined by pre-experiment) in the presence of 5 µg/ml polybrene. A total of 8–12 h post-infection, the medium was replaced and the cells were cultured at 37°C with 5% CO2. Transduced cells were selected using 5 µg/ml puromycin for 7–10 days, with medium changes every 24–48 h. In the maintenance phase, cells were cultured in medium containing 1 µg/ml puromycin.

Protein extraction

A total of 300 µl 8M urea was added to each primary cell sample for protein lysis, and a protease inhibitor cocktail was added at a concentration of 10% (v/v) of the total lysis volume. The lysates were centrifuged at 14,100 × g for 20 min at 4°C and the supernatants were carefully collected. Protein concentrations were determined using the Bradford assay. The remaining lysates were stored at −80°C for subsequent analyses.

Liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis

Protein digestion was performed using a commercial micro-protease digestion kit. Briefly, 20 µl protein lysate was mixed with MMB magnetic beads in an eight-tube strip and incubated at 37°C for 30 min. Subsequently, 45 µl binding buffer was added, followed by a 15-min incubation at room temperature. After discarding the supernatant, the beads were washed three times with wash buffer. Proteins were then resuspended in 20 µl digestion solution and incubated at 37°C for 5 h. The reaction was terminated by adding 5 µl quenching buffer, and the resulting peptides were freeze-dried. For LC-MS/MS analysis, two mobile phases were prepared: Mobile phases A (100% water with 0.1% formic acid) and B (80% acetonitrile with 0.1% formic acid). The freeze-dried peptide samples were reconstituted in 10 µl mobile phase A and centrifuged at 14,000 × g for 20 min at 4°C. The supernatant was then subjected to LC-MS/MS analysis. Chromatographic separation was performed under the conditions specified in Table I. Mass spectrometry analysis was performed on a timsTOF_HT instrument (Bruker Corporation) equipped with a Captive Spray ion source, operating in data-dependent acquisition mode. The ionization was conducted in positive ion mode. The nitrogen gas temperature was 200°C, the nebulizer pressure at 17.4 psi, and the nitrogen flow rate at 10 l/min. The mass scan range was set to m/z 100–1,700. The resolution for MS1 spectra was set to 60,000 at m/z 1,222. Within the TIMS tunnel, the ion accumulation time was 100 msec, and the ion mobility range was 0.6–1.6 cm2/V. A total cycle time of 1.1 sec was used, incorporating 10 parallel accumulation-serial fragmentation scans. Raw mass spectrometry data were acquired for further analysis.

Table I. Elution conditions for liquid chromatography, with a separation flow rate of 500 nl/min, and the separation gradients.

Table I.

Elution conditions for liquid chromatography, with a separation flow rate of 500 nl/min, and the separation gradients.

Time, min	Proportion of mobile phase B, %
00:00	3.5
17:00	32.0
18:00	95.0
20:00	95.0
21:00	1.0
22:00	1.0

Protein identification and quantification

All RAW files generated from mass spectrometry were analyzed using the Proteome Discoverer software suite (version 2.4; Thermo Fisher Scientific, Inc.). MS/MS spectra were searched against the Homo sapiens UniProt Swiss-Prot proteome database (uniprot.org/)(20,407 target sequences; downloaded on March 7, 2023). Furthermore, the Sequest HT search engine(used in Proteome Discoverer software) was employed with the following parameters: Fully tryptic enzyme specificity, allowing up to two missed cleavages, and a minimum peptide length of six amino acids. Carbamidomethylation of cysteine residues (+57.02146 Da) was set as a fixed modification, whilst oxidation of methionine residues (+15.99492 Da) was considered a variable modification. The precursor mass tolerance was set to 15 ppm, and the fragment mass tolerance was 0.02 Da for MS/MS spectra acquired in the Orbitrap. Peptide spectral matches and peptides were filtered using the Percolator algorithm (percolator.ms/) to achieve a false discovery rate (FDR) <1%. Following spectral assignment, peptides were assembled into proteins and further filtered based on the combined probability scores of constituent peptides, maintaining a final protein-level FDR of 1%. By default, the top-ranked or ‘master’ protein was defined as the one with the highest number of unique peptides and the lowest percent peptide coverage value (namely, the longest matching protein). Only unique and razor (parsimonious) peptides were considered for quantification.

Functional analysis of proteins and DEPs

Gene Ontology (GO) enrichment analysis was performed using the InterProScan 5 tool (ebi.ac.uk/interpro), based on annotations from the non-redundant protein database. Pathway analysis was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database (genome.jp/kegg/) to identify functionally relevant signaling pathways. Protein-protein interaction networks were predicted using the STRING database (https://string-db.org/), which integrates both known and predicted interactions based on orthologous relationships across species (18). GO and KEGG enrichment analyses were performed using a dedicated enrichment pipeline to further interpret the biological significance of DEPs.

Global analysis, differential protein screening and functional annotation

Differential expression analysis was performed using the Significance A algorithm within the MaxQuant software suite (version 2.6.4.0, available at http://www.biochem.mpg.de/6304115/maxquant). A paired-sample t-test was employed to compare protein expression levels between the experimental and control groups. Proteins exhibiting an absolute log2 fold change (FC) of >1.5 and a P-value of <0.05 were considered significantly differentially expressed. Among these, ALG1 was identified as the protein with the highest fold change based on the proteomics sequencing data. To further assess the functional and biological relevance of the DEPs, bioinformatic analyses were performed using the GO and the KEGG pathway databases, enabling a systematic understanding of the molecular functions, biological processes and pathways in which the DEPs are involved.

RNA extraction and quantitation

RNA was extracted from the collected primary cells using a commercial RNA extraction kit(Cat.No.:B0004DP, EZBioscience), followed by reverse transcription into cDNA using a specific reverse transcription kit(Cat.No.:A0010CGQ,EZBioscience), according to the manufacturer's protocol. Reverse transcription-quantitative PCR (RT-qPCR) was performed using the 2× Color SYBR Green qPCR Master Mix(Cat.No.:A0012-R1,EZBioscience). The amplification protocol consisted of an initial denaturation step at 95°C for 5 min, followed by 40 cycles of denaturation at 95°C for 10 sec, and annealing/extension at 60°C for 30 sec. Relative gene expression levels were calculated using the 2−ΔΔCq method (19), with GAPDH employed as the internal control for normalization. Primer sequences used in the present study are listed in Table II.

Table II. Primer sequences.

Table II.

Primer sequences.

	Sequence (5′-3′)
Gene	Forward	Reverse
ALG1	CCCCGAGTTTTCCAGTACGG	CAGCAATGCTAGGCAGACCT
THBS1	AGACTCCGCATCGCAAAGG	TCACCACGTTGTTGTCAAGGG
BAX	CCCGAGAGGTCTTTTTCCGAG	CCAGCCCATGATGGTTCTGAT
BCL-2	GGTGGGGTCATGTGTGTGG	CGGTTCAGGTACTCAGTCATCC
E-CADHERIN	TGGACCGAGAGAGTTTCCCT	CAAAATCCAAGCCCGTGGTG
N-CADHERIN	TCAGGCGTCTGTAGAGGCTT	ATGCACATCCTTCGATAAGACTG
VIMENTIN	AATGACCGCTTCGCCAACT	ATCTTATTCTGCTGCTCCAGGAA
GAPDH	GATGCTGGCGCTGAGTACG	GCTAAGCAGTTGGTGGTGC

[i] ALG1, chitobiosyldiphosphodolichol β-mannosyltransferase 1; THBS1, thrombospondin 1.

Western blot

Cell lysates were prepared by resuspending cells in a lysis buffer (cat. no. #BC3710,Solarbio) and incubating them on ice for 30 min. The lysates were then centrifuged at 12,000 × g for 30 min at 4°C, and the supernatants were collected for protein concentration determination using a BCA assay. A total of 25 µg/lane protein was separated using 10% SDS-PAGE and transferred onto PVDF membranes. To block nonspecific binding, membranes were blocked with 5% bovine serum albumin (Beijing Zhongshan Jinqiao Biotechnology Co., Ltd.) at room temperature for 2 h. The membranes were then incubated overnight at 4°C with primary antibodies against THBS1 (1:1,000, Affinity, DF6848), β-actin (1:8,000, Affinity, AF7018), ALG1 (1:1,000, Proteintech, 12872-1-AP), GAPDH (1:1,000, Affinity, cat. no. AF7021), Bax (1:1,000, Affinity, AF0120), and BCL-2 (1:1,000, Affinity, AF6139). After three washes with TBST (Beijing Solarbio Science & Technology Co., Ltd.) containing 0.1% Tween-20, membranes were incubated with goat anti-rabbit IgG(H+L)-HRP(1:7,000, Affinity, S0001) for 2 h at room temperature. Following an additional three washes, protein bands were visualized using an ECL detection kit(CAT:SQ201,EpiZyme), and images were captured using a chemiluminescence imaging system(Catalog number: Tanon 4600, Shanghai Tianneng Technology Co., Ltd.). Semi-quantification of protein expression was performed using ImageJ software (Version 1.8.0, National Institutes of Health) by measuring the band intensities. The relative expression level of each target protein was calculated as the ratio of its band intensity to that of the internal loading control.

Bioinformatics analysis

To assess the expression patterns of the target gene ALG1 across several tumor types, data were retrieved from the publicly available Tumor Immune Estimation Resource, version 2 (TIMER2.0) database (http://timer.cistrome.org/) using the ‘Gene DE’ module. Additionally, expression levels of ALG1 in tumor compared with in adjacent normal tissues were analyzed based on datasets from The Cancer Genome Atlas (TCGA; portal.gdc.cancer.gov/1) to evaluate its differential expression profile.

Protein-protein docking

The three-dimensional structures of THBS1 and ALG1 proteins were retrieved from the UniProt database (www.uniprot.org), the Protein Data Bank (rcsb.org/), and the AlphaFold Protein Structure Database (alphafold.ebi.ac.uk/). Rigid protein-protein docking was performed using GRAMM-X software (http://vakser.bioinformatics.ku.edu/resources/gramm/grammx) to predict the potential interaction interface between THBS1 and ALG1. The resulting docking models were analyzed and visualized using PyMOL software (version 2.4, http://pymol.org/) to further interpret the nature of the molecular interactions.

Immunofluorescence co-localization

Cells were cultured on sterilized glass coverslips until reaching ~80% confluency. Following three washes with PBS for 5 min each, cells were fixed with pre-chilled methanol at −20°C for 5 min. After fixation, non-specific binding sites were blocked using 5% BSA for 30 min at room temperature, followed by PBS washing. Primary antibodies against THBS1 (cat. no. AB1823, Abcam) and ALG1 (cat. no. 12872-1-AP, Proteintech) (1:100) were co-incubated with the cells overnight at 4°C. After washing with PBS, cells were incubated with the following fluorescently labeled secondary antibodies for 1 h at room temperature: Goat anti-rabbit DyLight 488 (A23220, Abbkine) and goat anti-mouse DyLight 594 (A23410, Abbkine). Nuclei were stained with DAPI for 5 min at room temperature, followed by further PBS washes. Coverslips were then mounted using the antifade mounting medium, and samples were observed using a confocal fluorescence microscope (LSM 800; Carl Zeiss AG).

Co-immunoprecipitation (Co-Ip)

A total of ~50 µl each MGC cell protein lysate, prepared using NP-40 lysis buffer (N8032,Solarbio), was reserved as an input control. The remaining sample was adjusted to a total volume of 300 µl, containing ~900 µg protein. To each sample, 30 µl 50% Protein A agarose beads were added, followed by incubation on ice for 45 min to pre-clear the lysates. Samples were then centrifuged at 700 × g for 5 min at 4°C, and the supernatants were collected whilst the pellets were discarded. For immunoprecipitation, 200 µl pre-cleared supernatant (~600 µg protein) was incubated with 7 µl of the primary antibody against THBS1 (cat. no. AB263905, Abcam) or ALG1 (12872-1-AP, Proteintech), whilst 100 µl (equivalent to ~300 µg protein) was incubated with 3.5 µl control IgG. Both mixtures were rotated overnight at 4°C. The following day, 30 µl of 50% agarose beads were added to the antibody sample, and 10 µl beads were added to the IgG control. Samples were then incubated for an additional 4 h at 4°C under constant rotation. After centrifugation under the aforementioned conditions, the supernatants were collected as negative controls. The beads were washed five times with 0.5 ml ice-cold PBS, and the first wash supernatant was retained for analysis. Subsequently, the beads were resuspended in 30 µl of 1X SDS loading buffer and boiled at 95°C for 5 min. The resulting immunoprecipitates were analyzed using western blotting as aforementioned to assess protein-protein interactions.

CCK-8 assay

Cell viability was assessed using the CCK-8 assay. Cells were seeded into 96-well plates at a density of 5×103 cells per well. Cell proliferation was evaluated at 0, 24, 48 and 72 h. At each time point, 10 µl CCK-8 reagent was added to each well. Plates were then incubated for 2 h at 37°C, and the absorbance was measured at 450 nm using a microplate reader (Tecan Group, Ltd.).

Wound-healing assay

When cells reached ~90% confluence, a linear scratch was made across the cell monolayer using a sterile 100 µl pipette tip. Detached cells were removed by washing with PBS, and the medium was replaced with a complete medium containing 1% FBS. Images of the wound area were captured at 0 and 24 h using an inverted microscope (Olympus Corporation). The cell migration rate was calculated using the following formula: Cell migration rate (%)=[(Width at 0 h-width at 24 h)/width at 0 h]-x100.

Transwell assay

Cell migration and invasion were evaluated using Transwell chambers. Migration assays were performed without Matrigel (cat. no. CLS3422, Corning, Inc.), whilst invasion assays used chambers pre-coated with Matrigel (CLS354480; Corning, Inc.). Cells were harvested, counted and resuspended in a serum-free medium at a density of 1×106 cells/ml. A total of 200 µl cell suspension was added to the upper chamber, whilst 500 µl complete medium containing 20% FBS (ExCell Bio) was added to the lower chamber as a chemoattractant. After 48 h of incubation at 37°C, the contents of both chambers were removed. Non-migratory or non-invasive cells on the upper surface of the membrane were carefully wiped off with a cotton swab. The chambers were washed with PBS, and cells on the lower membrane surface were fixed with 4% paraformaldehyde at room temperature for 20 min. Following air-drying, the membranes were stained with 0.1% crystal violet at room temperature for 20 min. After washing twice with PBS, stained cells were visualized and counted under an inverted microscope.

Apoptosis assay

Apoptosis was assessed using flow cytometry with Annexin V-FITC/APC and Propidium Iodide (PI)/7-AAD staining. Briefly, 5×105 cells were harvested following digestion with EDTA-free trypsin and resuspended in 500 µl binding buffer. The cell suspension was gently pipetted to ensure a single-cell distribution. Subsequently, 5 µl Annexin V-FITC (or APC) and 5 µl PI (or 7-AAD) were added to the suspension. Samples were incubated in the dark at room temperature for 5–10 min and analyzed within 1 h using a flow cytometer (BD FACSCelesta™; BD Biosciences) and FlowJo 10.6.2 software (FlowJo, LLC). The apoptosis rate was calculated by summing the proportions of early apoptotic cells (Q3 quadrant) and late apoptotic cells (Q2 quadrant).

Statistical analysis

All data are presented as the mean ± standard deviation of three independent experiments. All statistical analyses were performed using GraphPad Prism software (version 10.1.2; Dotmatics). For comparisons between two groups, independent sample t-tests were employed. Two-way analysis of variance (ANOVA) was applied for comparisons among multiple groups, as appropriate. When ANOVA results were significant, Tukey's HSD post hoc test was used to identify pairwise differences. P<0.05 was considered to indicate a statistically significant difference

Results

Proteomic analysis after THBS1 overexpression

Fluorescence microscopy demonstrated successful lentiviral infection of MGC cells, with strong fluorescence signals observed in both negative control overexpression (NCoe) and THBS1 overexpression (THBS1oe) groups at 72 h post-infection (Fig. 2A). Quantitative analysis further assessed the overexpression, demonstrating significantly elevated mRNA and protein levels of THBS1 in the THBS1oe group compared with in the NCoe group (Fig. 2B; P<0.05). Subsequent proteomic analysis identified a total of 35,894 peptides and 4,949 proteins. Quality control procedures, including hierarchical clustering of DEPs, confirmed high data reproducibility. The clustering dendrogram displayed in the heatmap (Fig. 2C) revealed consistent expression profiles among biological replicates. A volcano plot visually represented 685 DEPs between the THBS1oe and NCoe groups, of which 369 were upregulated and 316 were downregulated (Fig. 2D). Based on the criteria |log2(FC)|>1.5 and P<0.05, ALG1 was identified as the most significantly altered protein. GO enrichment analysis was performed across three domains: Biological process (BP), cellular component (CC) and molecular function (MF). In the BP category, DEPs were significantly enriched in processes such as translation, cytoplasmic translation, mRNA splicing via the spliceosome, intracellular protein transport and protein folding. In the CC category, DEPs were predominantly localized to the cytosol, mitochondria, endoplasmic reticulum and cellular membranes. For MF, enrichment was observed in RNA binding, identical protein binding, ATP binding and cadherin binding (Fig. 2E). KEGG pathway analysis revealed that DEPs were enriched in several disease-related pathways, including Ribosome, Amyotrophic Lateral Sclerosis, Spliceosome and Parkinson's disease (Fig. 2F). Additionally, DEPs were involved in core signaling pathways associated with cell cycle regulation, DNA replication and transcriptional dysregulation in cancer. These results indicate that THBS1 overexpression exerts widespread effects on the cellular proteome, providing new insights into its downstream molecular mechanisms.

Figure 2. Proteomic analysis following THBS1 overexpression. (A) Fluorescent imaging (×40; scale bar, 200 µm) of NCoe and THBS1oe groups after lentiviral-mediated THBS1 overexpression. (B) Evaluation of THBS1 overexpression using reverse transcription-quantitative PCR and western blot analysis. (C) Hierarchical clustering heatmap of differentially expressed proteins. (D) Volcano plot of DEPs: Green dots indicate downregulated proteins, and red dots indicate upregulated proteins. (E) GO and (F) KEGG pathway enrichment analysis of DEPs. **P<0.01. THBS1, thrombospondin 1; NC, negative control; oe, overexpression; DEP, differentially expressed protein; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; FC, fold change.

Interaction between THBS1 and ALG1

Proteomic analysis identified ALG1 as the most significantly altered protein following THBS1 overexpression. Quantitative expression analysis revealed that both mRNA and protein levels of ALG1 were significantly reduced in the THBS1oe group compared with in the NCoe group, consistent with the proteomic sequencing data (Fig. 3A). To further assess the potential interaction between THBS1 and ALG1, a protein-protein docking analysis was performed. The docking model demonstrated that THBS1 (depicted in pink) forms a stable complex with ALG1 (depicted in yellow), with hydrogen bonds formed between amino acid residues ASN-991 of THBS1 and MET-58 of ALG1 (indicated by yellow dashed lines), and a calculated binding energy of −4.9 kcal/mol (Fig. 3B). These findings suggest a strong and stable interaction between the two proteins with high binding affinity. To visualize their subcellular distribution, immunofluorescence co-localization experiments were performed. THBS1 (red fluorescence) and ALG1 (green fluorescence) were demonstrated to co-localize predominantly in the cytoplasm, whereas DAPI staining (blue fluorescence) clearly delineated the nuclear region (Fig. 3C). Finally, Co-IP assays revealed the direct physical interaction between THBS1 and ALG1. This interaction was demonstrated to be specific and unaffected by the presence of other proteins, further supporting the docking results (Fig. 3D).

Figure 3. Validation of the interaction between THBS1 and ALG1. (A) Validation of ALG1 downregulation following THBS1 overexpression via reverse transcription-quantitative PCR and western blot analyses. (B) Protein docking model of THBS1 and ALG1 showing their interface residues (THBS1, pink; ALG1, yellow; and hydrogen bonds, yellow dashed lines). (C) Immunofluorescence co-localization analysis of THBS1 and ALG1 (magnification, ×400; scale bar, 20 µm). (D) Immunoprecipitation analysis demonstrating the specific interaction between THBS1 and ALG1. ***P<0.001. ALG1, chitobiosyldiphosphodolichol β-mannosyltransferase 1; THBS1, thrombospondin 1; NC, negative control; oe, overexpression; CoIP, co-immunoprecipitation.

Expression profile of ALG1 and its effects on MGC cell proliferation, migration and invasion

Using bioinformatics analysis via the TIMER 2.0 platform, the expression pattern of ALG1 across several tumor types and their corresponding adjacent normal tissues were assessed in the TCGA database (Fig. 4A). ALG1 expression was significantly elevated in multiple malignancies, including bladder urothelial carcinoma, breast invasive carcinoma, cholangiocarcinoma, colon adenocarcinoma, esophageal carcinoma, glioblastoma multiforme, head and neck squamous cell carcinoma, kidney renal papillary cell carcinoma, liver hepatocellular carcinoma, lung adenocarcinoma, prostate adenocarcinoma, rectum adenocarcinoma, stomach adenocarcinoma and uterine corpus endometrial carcinoma, compared with in adjacent non-tumor tissues. These findings suggest that ALG1 is frequently overexpressed in diverse cancers, implying its potential oncogenic role and relevance in tumor progression, thus providing a rationale for further investigation into its functional significance in MGC cells. To experimentally evaluate ALG1 expression in MGC cells, RT-qPCR was performed to quantify ALG1 mRNA levels. The results indicated that ALG1 mRNA expression was significantly upregulated in MGC cells compared with in adjacent normal tissues (Fig. 4B). Fluorescence microscopy further demonstrated detectable ALG1-associated fluorescence signals across the NCsi, NCoe and ALG1 overexpression (ALG1oe) groups (Fig. 4C). Moreover, RT-qPCR and western blot analyses demonstrated successful knockdown of ALG1 in the ALG1si group and overexpression in the ALG1oe group, relative to their respective controls (Fig. 4D and E). Subsequently, the functional impact of ALG1 on MGC cell behavior was assessed. CCK-8 assays revealed that ALG1 knockdown significantly suppressed MGC cell proliferation, whereas ALG1 overexpression promoted cell proliferation compared with the NC group (Fig. 4F). In addition, scratch wound healing and Transwell invasion assays demonstrated that ALG1 knockdown significantly reduced the migration and invasion of MGC cells, whilst ALG1 overexpression significantly enhanced these phenotypes compared with the NC group (Fig. 4G and H).

Figure 4. Regulatory role of ALG1 in the Biological Behaviors of MGC Cells. (A) Differential expression analysis of ALG1 in tumors and adjacent normal tissues across several cancer types and subtypes using the Tumor Immune Estimation Resource 2.0. (B) Comparison of ALG1 mRNA expression levels in primary MG and MGC cells. (C) Fluorescence microscopy images (×40; scale bar, 200 µm) of MGC cells following ALG1 knockdown (ALG1si) and overexpression (ALG1oe) in NCsi, NCoe and ALG1oe groups. (D) Reverse transcription-quantitative PCR and (E) western blot analyses of successful knockdown and overexpression of ALG1 in MGC cells using siRNA and lentivirus, respectively. (F) Cell Counting Kit-8 assay evaluating the effects of ALG1 regulation on MGC cell proliferation. (G) Scratch wound-healing assay assessing the impact of ALG1 modulation on cell migration (×40; scale bar, 200 µm). (H) Transwell assay measuring the effects of ALG1 on MGC cell migration and invasion (×100; scale bar, 100 µm). *P<0.05; **P<0.01; ***P<0.001; ****P<0.0001. ALG1, chitobiosyldiphosphodolichol β-mannosyltransferase 1; MG, meibomian gland; MGC, MG carcinoma; si, small interfering; oe, overexpression; NC, negative control; TPM, transcripts per million; OD, optical density.

Regulatory effects of ALG1 on apoptosis and EMT

Flow cytometry analysis revealed that ALG1 knockdown (ALG1si group) significantly increased the apoptosis rate of MGC cells compared with that of the NC group (Fig. 5A). This finding was supported by the significant upregulation of the mRNA expression of the pro-apoptotic gene Bax and downregulated expression of the anti-apoptotic gene Bcl-2 in the ALG1si group compared with in the NCsi group (Fig. 5B). These findings suggest that ALG1 silencing induces apoptosis in MGC cells, which may contribute to the suppression of tumor growth and metastatic potential. Conversely, overexpression of ALG1 (ALG1oe group) produced the opposite effects (Fig. 5C and D). Meanwhile, the downregulation of Bax and upregulation of Bcl-2 following ALG1 overexpression were further demonstrated using western blot analysis (Fig. 5E and F).

Figure 5. Regulatory role of ALG1 in apoptosis and epithelial-mesenchymal transition of MGC Cells. (A) Flow cytometry analysis of cell apoptosis and quantification of the apoptosis rate following ALG1 knockdown. (B) RT-qPCR analysis of pro-apoptotic protein Bax and anti-apoptotic protein Bcl-2 expression levels after ALG1 knockdown. (C) Flow cytometry analysis of cell apoptosis and quantification of apoptosis rate after ALG1 overexpression. (D) RT-qPCR analysis of pro-apoptotic protein Bax and anti-apoptotic protein Bcl-2 expression levels after ALG1 overexpression. (E) Evaluation of the downregulation of Bax and the upregulation of Bcl-2 after ALG1 overexpression by western blot analysis. (F) Statistical analysis of the grayscale values of the downregulation of Bax and the upregulation of Bcl-2 after ALG1 overexpression. (G) RT-qPCR analysis of epithelial-mesenchymal transition-related genes (E-Cadherin, N-Cadherin, and Vimentin) after ALG1 knockdown. (H) RT-qPCR analysis of epithelial-mesenchymal transition-related genes (E-Cadherin, N-Cadherin, and Vimentin) after ALG1 overexpression. *P<0.05; **P<0.01; ***P<0.001; ****P<0.0001. RT-qPCR, reverse transcription-quantitative PCR; ALG1, chitobiosyldiphosphodolichol β-mannosyltransferase 1; NC, negative control; si, small interfering; oe, overexpression.

Moreover, EMT is a key biological process involved in tumor invasion and metastasis. EMT is characterized by the loss of epithelial markers, such as E-cadherin, and the gain of mesenchymal markers, including N-cadherin and vimentin, along with cytoskeletal remodeling and acquisition of mesenchymal phenotypes (20). To elucidate the role of ALG1 in EMT regulation, the expression levels of canonical EMT markers were assessed. In comparison with the NC group, knockdown of ALG1 was associated with a significant decrease in vimentin and N-cadherin expression, accompanied by a significant increase in E-cadherin expression. This indicates a reversal of the EMT process (Fig. 5G). Conversely, overexpression of ALG1 (ALG1oe group) produced the opposite effects, with significantly increased expression of mesenchymal markers and suppressed expression of E-cadherin compared with the NC group (Fig. 5H). Collectively, these results suggest that ALG1 promotes EMT, and its downregulation facilitates a mesenchymal-to-epithelial transition, thereby inhibiting the invasive and metastatic potential of MGC cells.

Discussion

Globally, MGC is the third most common malignant tumor of the eyelid. It predominantly affects elderly women and most frequently involves the upper eyelid (21,22). Early diagnosis and prompt surgical excision are essential to prevent recurrence; however, due to its nonspecific clinical presentation, MGC is frequently misdiagnosed or diagnosed at an advanced stage, often leading to regional lymph node involvement and distant metastasis, which severely compromise patient prognosis (23,24). Although radiotherapy and chemotherapy are commonly employed as adjunctive treatments for advanced MGC, their clinical efficacy remains unsatisfactory. Consequently, there is growing interest in molecular-targeted therapies as a promising alternative for managing this malignancy. Proteomic technologies offer a powerful approach to directly analyze global and dynamic changes in the proteome, enabling the discovery of novel diagnostic biomarkers and therapeutic targets (25,26). In this context, the identification of effective molecular markers capable of inhibiting MGC progression is urgently needed to improve therapeutic outcomes and patient survival.

Proteomics research in cancer primarily aims to identify and characterize key proteins involved in malignant transformation, discover biomarkers for early detection, predict prognosis, assess therapeutic efficacy, uncover novel drug targets, and ultimately advance the development of personalized medicine (27,28). Despite substantial progress in the field, proteomic investigations into the molecular mechanisms of MGC remain relatively limited. Previous studies have reported that miR-3907 is markedly upregulated in MGC and promotes cancer cell proliferation and migration by negatively regulating THBS1 expression (7). Building upon these findings, the present study employed 4D-label-free quantitative proteomics to systematically analyze downstream DEPs following THBS1 overexpression. GO enrichment analysis revealed that these DEPs were predominantly involved in critical biological processes such as translation, intracellular protein transport and protein folding. Furthermore, KEGG pathway analysis indicated significant enrichment in ribosome metabolism, as well as pathways associated with cell cycle regulation, DNA replication and transcriptional dysregulation in cancer. These results offer valuable insights into the functional landscape of THBS1-regulated proteins and provide a robust foundation for future research aimed at the identification of novel biomarkers and therapeutic targets. Follow-up validation experiments confirmed that THBS1 overexpression markedly downregulated the mRNA and protein expression levels of ALG1. Functional studies further demonstrated a direct interaction between THBS1 and ALG1 and revealed that ALG1 exerts a potential oncogenic role in MGC progression. Collectively, these findings deliver important theoretical evidence for elucidating the molecular mechanisms underlying MGC and contribute to the identification of promising therapeutic targets for improving clinical management of this malignancy.

ALG1, which encodes the enzyme responsible for catalyzing the first mannosylation step in the biosynthesis of lipid-linked oligosaccharides, serves a key role in glycometabolism. Notably, metabolic differences between normal and tumor cells are profound, with a well-documented shift from oxidative phosphorylation to aerobic glycolysis (the Warburg effect) recognized as a hallmark of cancer development (29). This metabolic reprogramming enhances tumor cell proliferation, invasion and chemoresistance, and is closely associated with the tumor microenvironment (TME) and immune evasion. Previous studies have revealed that ALG1 is markedly associated with immune cell infiltration, TME modulation and therapeutic responsiveness in gastric adenocarcinoma, highlighting its potential as a target in cancer treatment (30,31). Furthermore, ALG1 has been implicated in the early stages of N-glycosylation, a process intricately linked to the progression of hepatocellular carcinoma (31). In colorectal cancer, prognostic models based on glycolysis-related genes, including ALG1, have demonstrated positive associations with poor patient outcomes, EMT activation and immune modulation within the TME (32). However, the functional role and clinical significance of ALG1 in MGC have not yet been elucidated.

In the present study, through analysis of publicly available databases, the results demonstrated that ALG1 expression is elevated in multiple tumor types, underscoring its potential as a broadly applicable therapeutic target. It was further revealed that ALG1 is markedly upregulated in MGC cells, thereby expanding the spectrum of cancers characterized by high ALG1 expression. Moreover, through a combination of protein-protein docking, immunofluorescence co-localization, and Co-IP assays, the present study identified a direct physical interaction between THBS1 and ALG1, for the first time, to the best of our knowledge. Functional studies revealed that ALG1 knockdown significantly inhibited MGC cell proliferation, migration and invasion, whilst simultaneously promoting apoptosis. By contrast, ALG1 overexpression exerted the opposite effects. These findings suggest that ALG1 functions as a putative oncogene in MGC and raise the possibility that small-molecule inhibitors targeting ALG1 may serve as a novel therapeutic strategy, particularly in cancers with elevated ALG1 expression.

EMT is a fundamental biological process that facilitates cancer cell migration and invasion, and it is intimately associated with cellular stemness in both tissue homeostasis and cancer progression (33,34). This process is orchestrated by a set of core EMT-associated transcription factors, which suppress the expression of epithelial markers (such as E-cadherin) and simultaneously induce mesenchymal markers, including vimentin and N-cadherin (35). The present study demonstrated that ALG1 modulated EMT marker expression in MGC cells. Specifically, ALG1 knockdown resulted in increased E-cadherin expression, indicating enhanced epithelial characteristics and cell-cell adhesion. Conversely, overexpression of ALG1 suppressed E-cadherin expression, consistent with a shift toward a mesenchymal phenotype. In parallel, the expression levels of vimentin and N-cadherin were positively associated with ALG1 expression, further reinforcing the role of ALG1 in promoting EMT. These findings support the hypothesis that ALG1 contributes to MGC cell metastasis and invasiveness by regulating EMT-associated genes. However, the present study only explored the role of ALG1 in MGC cells via cell function experiments and detection of EMT-related markers. Subsequent research should focus on the signaling pathways closely associated with EMT in KEGG. By detecting the phosphorylation levels of key proteins and analyzing upstream-downstream regulatory relationships, further studies should aim to thoroughly dissect the regulatory mechanisms of these pathways and comprehensively uncover the exact molecular mechanisms by which ALG1 regulates EMT. Such insights will provide a foundation for precision medicine approaches and may lead to the development of personalized therapeutic strategies targeting EMT and metastatic progression. Moreover, to address the limitation of focusing solely on ALG1, future research should utilize proteomics data to study other proteins among the identified differentially expressed proteins. Bioinformatics and functional analyses should employ to explore their roles in cell phenotypes and analyze their expression in larger patient cohorts to uncover new mechanisms, biomarkers and therapeutic approaches.

In conclusion, the present study demonstrated that THBS1 overexpression suppresses MGC progression via the downregulation of ALG1, and revealed a direct molecular interaction between THBS1 and ALG1. Functionally, silencing ALG1 significantly inhibited MGC cell proliferation, migration and invasion, whilst promoting apoptosis. Mechanistically, these effects were associated to ALG1-mediated modulation of EMT, characterized by downregulation of E-cadherin and upregulation of mesenchymal markers such as N-cadherin and vimentin. Collectively, these findings highlight ALG1 as a critical oncogenic mediator in MGC and suggest its positioning within the miR-3907/THBS1/ALG1 regulatory axis. This axis represents a promising theranostic biomarker for the diagnosis, prognosis and treatment of MGC.

Acknowledgements

Not applicable.

Funding

The present work was supported by the Open Project of Tianjin Key Laboratory of Retinal Functions and Diseases (grant no. 2021tjswmm001), Tianjin Health Science and Technology Project (grant no. TJWJ2022MS012) and Tianjin Key Medical Discipline (Specialty) Construction Project (grant no. TJYXZDXK-037A).

Availability of data and materials

The mass spectrometry proteomics data generated in the present study may be found in the ProteomeXchange Consortium via the PRIDE (36) partner repository under accession number PXD059655 or at the following URL: http://www.ebi.ac.uk/pride.

Authors' contributions

WW, HTW, GJW, XL, LMZ, FT and TTL conceived and designed the study. WW, HTW, GJW, XL, LMZ, FT, and TTL acquired, analyzed and interpreted the data. WW drafted the manuscript. WW, HTW, GJW, XL, LMZ, FT and TTL revised the manuscript. WW, HTW and GJW performed the statistical analyses. LMZ and TTL obtained funding for the present study. WW and HW confirm the authenticity of all the raw data. All authors have read and approved the final manuscript.

Ethics approval and consent to participate

The present study was performed in accordance with the Declaration of Helsinki, and approved by the Ethics Committee of Tianjin Medical University Eye Hospital [approval no. 2020KY(L)-20]. Informed written consent was obtained from all subjects involved in the study.

Patient consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

References