Integrative analysis identified THBS1 as a key prognostic biomarker with therapeutic vulnerability in patients with laryngeal cancer

Introduction

Laryngeal cancer, originating from the mucosal epithelium within the larynx, is a prevalent form of head and neck malignancies globally (1-4). The worldwide incidence rate of laryngeal cancer is declining, but it remains a significant health challenge (5,6). In the United States, an estimated 12,380 new cases of laryngeal cancer were diagnosed in 2023, with approximately 4,000 deaths attributed to the disease (7). For cases diagnosed and treated before the cancer has spread outside the larynx, the 5-year survival rate is around 80%; however, the 5-year survival rate is significantly reduced in laryngeal cancer patients with advanced tumor stage at initial presentation, rapid tumoral growth, lack of robust screening programs, and locoregional relapse following treatment (8).

Despite advancements in comprehensive therapy strategies, survival outcomes for advanced laryngeal cancer remain poor, with a 5-year survival rate of approximately 60%, which drops significantly, especially in metastatic cases (5,8). Surgical interventions can be effective but often lead to functional consequences such as voice loss and airway compromise (9). Radiotherapy and chemotherapy are essential for managing advanced cases but are associated with adverse effects like mucositis, xerostomia, and systemic toxicities, and the treatment resistance also results in attenuated efficacy (10-12). Immune checkpoint inhibitors have shown promise in improving prognosis for patients with laryngeal cancer, but the heterogeneous response rates are unresolved issues (13,14). Thus, identifying the prognostic biomarkers and potential therapeutic modalities for laryngeal cancer patients is of utmost importance.

This study was designed to explore the biological alterations and prognostic biomarkers for laryngeal cancer using gene expression profile and clinic-pathological data from The Cancer Genome Atlas (TCGA) database. The prognostic value and association with tumor microenvironment of potential targets were validated in independent datasets. Several in vitro experiments were utilized to evaluate its biological function in laryngeal cancer cells. Our research provides a new prognostic target with therapeutic promises for laryngeal cancer. We present this article in accordance with the MDAR reporting checklist (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-779/rc).

Methods

Dataset collection and analysis

Gene expression profiles of laryngeal tumors (N=116) and normal larynx tissues (N=12) from the TCGA database (N=128) were obtained from the University of California, Santa Cruz (UCSC) Xena platform (https://xenabrowser.net/). Two validation datasets, GSE27020 (N=109) and GSE65858 (N=48), containing expression profiles of laryngeal cancer tissues, were downloaded and annotated from the Gene Expression Omnibus (GEO) database (15-17). All gene expression profiles underwent background corrections, log₂ transformation, and data normalization before further analysis. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

Differentially expressed genes (DEGs) analysis

DEGs between laryngeal tumors and normal larynx tissues in the TCGA database were determined by the ‘limma’ R package. Genes with an absolute log fold change [|log₂fold change (FC)|] greater than 1 and an adjusted P value less than 0.05 were classified as significant DEGs. Differential mRNA expression was illustrated using a volcano plot, providing a comprehensive overview of the significance and fold change of each gene. The up-regulated DEGs were then selected for functional enrichment analysis using FunRich algorithm (18), revealing the altered biological processes and molecular pathways.

Selection of prognostic biomarkers

To refine the selection of genes that contribute most significantly to the prognosis of laryngeal cancer patients, two machine-learning approaches were employed. The least absolute shrinkage and selection operator (LASSO) regression analysis is particularly effective for feature selection in high-dimensional datasets by imposing a penalty on the absolute size of the regression coefficients, thereby shrinking some coefficients to zero. Random forest algorithm is applied to rank the importance of prognostic genes (100 times of iterations) using ‘randomForestSRC’ and ‘randomSurvivalForest’R package. These approaches ensure reducing redundancy of inter-related genes and retaining the independent genes with the most substantial prognostic impact.

Gene sets and gene set variation analysis (GSVA)

GSVA is a powerful tool for assessing pathway activity in complex genomic datasets, enabling the identification of biologically relevant patterns and associations (19). In the current research, hallmark gene sets were obtained from the Molecular Signatures Database (MSigDB) (20). Then, GSVA was performed to derive the enrichment scores of specific biological processes in each sample using the ‘GSVA’ R package. Pearson correlation analysis was conducted to evaluate the correlation between identified prognostic genes and hallmark processes.

Estimation of immune infiltrating

Immune cell infiltration of laryngeal tumors was analyzed using curated marker gene sets from Bindea’s research (21). The GSVA algorithm was utilized to deconvolve the relative proportions of 24 human immune cell types within the tumor microenvironment. Pearson correlation analysis was conducted to evaluate the correlation between identified prognostic genes and infiltrated immune cells. This method provides a robust statistical framework to assess the relationships between gene expression and immune cell infiltration.

Cell culture and transfection

The human laryngeal cancer cell lines [TU686 and HN-10, purchased from ATCC (Gaithersburg, USA)] were maintained in RPMI-640 medium supplemented with 10% fetal bovine serum (FBS), penicillin-streptomycin, and incubated at 37 ℃ with 5% CO₂. The lentivirus transfection system with Lipofectamine 3000 was applied to generated laryngeal cancer cell lines with stably altered expression of THBS1 (overexpression or knockdown), following the manufacturer’s protocol to achieve efficient gene delivery and expression.

Colony formation assay

The colony formation assay, a standard method for evaluating the proliferative potential and survival of cells under specific conditions, was employed to assess the impact of gene alteration or specific inhibitors on the colony-forming capacity of laryngeal cancer cells. A total of 2×10³ cells were seeded into each well of six-well plates, ensuring sufficient space for colony formation while allowing for clear differentiation between individual colonies. Cells with altered gene expression or treated with a specific inhibitor were incubated at 37 ℃ for 8–10 days until colonies became visible. Then the colonies were fixed using paraformaldehyde for 30 minutes and stained with a crystal violet solution (5%) for 30 minutes at room temperature, which were washed by phosphate buffered saline (PBS) for further quantification. Colonies were counted under an inverted microscope (Leica, Germany) and compared between different experimental groups.

Immunofluorescence

To assess the proliferative capacity of tumor cells following gene editing or drug treatment, cellular proliferation assays were performed using the Cell-Light EdU DNA Cell Proliferation Kit (RiboBio, Guangzhou, China; Cat#C10310-1) according to the manufacturer’s instructions. This assay is based on the incorporation of 5-ethynyl-2'-deoxyuridine (EdU) into newly synthesized DNA during the S phase of the cell cycle, allowing for the detection of proliferating cells. After cell incubation, EdU incorporation, cell fixation, and Apollo staining, the labeled tumor cells were then washed twice with 0.5% TritonX-100 to remove any unbound dye and re-washed with PBS. The excitation/emission wavelengths for the fluorescent dye were 550/565 nm, allowing for the detection and quantification of EdU-positive cells in the fluorescence microscope.

To evaluate the intracellular lipid content in cultured tumor cells, the Nile Red kit (Cat#B8209, APExBIO, Houston, USA) was employed. Nile Red is a fluorescent stain specifically designed for detecting intracellular lipid droplets. The assay was conducted following the manufacturer’s protocols. The lipid content was visualized by observing yellow-gold fluorescence under a fluorescence microscope, with an excitation wavelength ranging from 450 to 500 nm. This method allows for the precise detection and quantification of lipid droplets within cells, providing insights into lipid accumulation and metabolic activity.

Transwell assays

To assess the migratory capacity of cells, a Transwell migration assay was performed. A total of [4–6]×10⁴ cells in 200 µg of FBS-free medium was added to the top chamber of the Transwell insert. The attractant, which promotes cell migration, was a medium containing 20% FBS and was placed in the bottom chamber. The cells were then incubated for 24 hours at 37 ℃ to allow migration to occur. After incubation, non-migrated cells remaining in the top chamber were carefully removed using cotton swabs. The migrated cells were fixed and stained using a solution of 20% methanol and 0.1% crystal violet. The stained cells were visualized using an inverted microscope. For quantification, five random fields were selected, and the number of migrated cells in these fields was counted. As for tumor invasion assay, the upper chamber was pre-coated with 60 µL Matrigel (diluted by PBS at 1:5), and the chamber was then placed in 37 ℃ incubator for 2 hours for gelling. The following procedures were the same as tumor migration assay in a seeding density of [6–8]×10⁴ cells/200 µL.

Statistical analysis

Differences between the groups were assessed using an independent Student t-test if not otherwise stated. Data were expressed as mean ± standard deviation. Laboratory experiments were performed at least three times with biological replicates. The Kaplan-Meier method was employed to analyze survival differences between two groups, and the log-rank test was used to determine whether there was a statistically significant difference in survival using ’survminer’ R package. To evaluate the prognostic potential of the identified target genes, receiver operating characteristic (ROC) curves were constructed utilizing the ‘pROC’ R package. The correlations between the target genes and components of the tumor microenvironment (TME) were analyzed using Pearson correlation analysis. A P value or adjusted P value of less than 0.05 was considered statistically significant. All statistical analyses were performed with R (version 4.0.4) and GraphPad Prism (version 9.2.1).

Results

Identification and functional characterization of DEGs in laryngeal cancer

The transcriptomic data and clinical characteristics of laryngeal cancer samples from the TCGA database were retrieved, including 116 laryngeal tumors and 12 normal laryngeal tissues. To identify the DEGs between laryngeal cancer and normal laryngeal tissues, we employed the ‘limma’ algorithm. Through this analysis, we identified a total of 3,560 DEGs (including 1,864 up-regulated genes and 1,696 down-regulated genes) that met the criteria of an adjusted P value less than 0.05 and a |log₂FC| greater than 1. The results of this analysis are visually represented in a volcano plot, which illustrates the upregulated and downregulated DEGs in laryngeal tumors compared to normal laryngeal tissues (Figure 1A). The detailed list of these DEGs is provided in available online: https://cdn.amegroups.cn/static/public/tcr-2025-779-1.xlsx, for further reference.

Figure 1 Identification and functional characterization of DEGs in laryngeal cancer. (A) A volcano plot of the DEGs between laryngeal tumors and normal laryngeal tissues in the TCGA dataset. Each dot represents a gene, where the genes were denoted as red, green, or gray color if they were significantly up-regulated, significantly down-regulated, or not significantly dysregulated, respectively. (B) KEGG and GO-BP functional enrichment analysis of up-regulated DEGs between laryngeal tumors and normal laryngeal tissues. DEG, differentially expressed gene; GO-BP, Gene Ontology-Biological Process; KEGG, Kyoto Encyclopedia of Genes and Genomes; TCGA, The Cancer Genome Atlas.

Following the identification of DEGs, we proceeded with a comprehensive functional analysis to elucidate the biological roles and pathways associated with these genes. Specifically, we performed Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology-Biological Process (GO-BP) functional enrichment analyses on the 1864 up-regulated DEGs using ‘FunRich’ algorithm. The results of these analyses are detailed in available online: https://cdn.amegroups.cn/static/public/tcr-2025-779-2.xlsx. The top 5 enriched KEGG pathways and GO-BP are depicted in Figure 1B. Notably, the most significant pathways identified include the epithelial-to-mesenchymal transition (EMT), integrin signaling, and lipid metabolism. These pathways are critical in regulating cell survival, proliferation, and response to environmental stimuli (22-24), suggesting their potential roles in the molecular mechanisms underlying the progression of laryngeal cancer, which were validated in the corresponding GO-BP analysis. These outcomes suggested that these DEGs were closely associated with those biological processes indicating aggressive phenotype of cancer.

Identification and validation of hub prognostic genes

To reduce the redundancy in the inter-correlated genes and identify the most relevant prognostic genes, LASSO-Cox regression analysis was employed (Figure 2A,2B). This method is particularly effective for handling high-dimensional data and selecting a subset of genes that significantly contribute to the prediction of survival outcomes. Through this analysis, 24 genes were selected (Table 1). Apart from LASSO-Cox regression analysis, we utilized another machine learning method to identify hub prognostic genes using random forest algorithm. Genes with a relative importance >0.4 were defined as hub prognostic genes, and a total of 17 genes were finally identified (Table 1). Figure 2C illustrates the relationship between the error rate and the number of classification trees in the random forest model. Figure 2D displays the order of the out-of-bag importance for the top genes, where the out-of-bag importance is a measure of how much each gene contributes to the accuracy of the random forest model.

Figure 2 Identification of the hub prognostic genes using machine learning algorithms. (A) LASSO-Cox 10-fold cross-validation for the tuning parameter lambda (λ) selection. Mark a dotted line at the optimal λ value. (B) LASSO-Cox coefficients of identified 24 prognostic genes. (C) Random forest error rate for the data as a function of the classification tree. (D) Random forest out-of-bag importance values for the identified 17 prognostic genes. LASSO, least absolute shrinkage and selection operator.

We next performed an intersection between the two prognostic gene-sets, retaining four genes as the most important prognostic genes for further analysis: FRMD5, CLDN23, PLIN5, and THBS1. In the internal validation, as shown in Figure 3A, the four genes are all significantly associated with the prognosis of laryngeal cancer patients in the TCGA database (Figure 3B). They also showed satisfactory capacity in predicting 1-, 3-, and 5-year survival status of laryngeal cancer patients (Figure 3C).

Figure 3 Internal validation of the prognostic values of the identified prognostic genes in the TCGA dataset. (A) A Venn diagram depicts the common prognostic genes identified by LASSO and random forest algorithms. (B) Kaplan-Meier curves of OS, DSS, and DFI in patients with laryngeal cancer grouped by the indicated gene expression. (C) ROC curves showing the predictive values of indicated genes in predicting 1-, 3-, and 5-year OS. AUC, area under the curve; DFI, disease-free interval; DSS, disease-specific survival; LASSO, least absolute shrinkage and selection operator; OS, overall survival; ROC, receiver operating characteristic; TCGA, The Cancer Genome Atlas.

Then we conducted external validation of the prognostic genes in independent datasets. The two validation datasets containing expression profiles of laryngeal cancer tissues are GSE27020 (N=109) and GSE65858 (N=48), the public datasets with the most laryngeal cases. The three genes, FRMD5, CLDN23, and PLIN5, were found not significantly associated with prognosis of laryngeal cancer patients, while THBS1 exhibited significant prognostic effects in both external validation datasets (Figure 4A,4B). The area under the curve (AUC) revealed a greater prognostic value of THBS1 in GSE65858 dataset (overall survival status prediction of 1-year: AUC =0.647; 3-year: AUC =0.757; 5-year: AUC =0.699) (Figure 4C). Thus, THBS1 was identified as the hub prognostic gene in laryngeal cancer, and we chose it for further exploration.

Figure 4 External validation of the prognostic values of the identified prognostic genes in the independent GEO datasets. (A) Kaplan-Meier curves of prognosis in patients with laryngeal cancer grouped by the indicated gene expression in GSE65858 dataset. (B) Kaplan-Meier curves of prognosis in patients with laryngeal cancer grouped by the indicated gene expression in GSE27020 dataset. (C) ROC curves showing the predictive values of indicated genes in predicting 1-, 3-, and 5-year survival in GSE65858 dataset. AUC, area under the curve; DSS, disease-free survival; GEO, Gene Expression Omnibus; OS, overall survival; PFS, progression-free disease; ROC, receiver operating characteristic.

THBS1 expression is correlated with oncogenic hallmark processes and immunosuppressive tumor microenvironment in laryngeal cancer

The GSVA algorithm was utilized to quantify the hallmark biological process scores and immune infiltration for laryngeal cancer from the TCGA database. The Pearson correlation analysis (Figure 5A,5B) revealed that the THBS1 expression was significantly associated with EMT process (r=0.60, P=9.93E−13) and fatty acid metabolism (r=0.58, P=9.69E−12). These results indicated that the greater level of THBS1 was linked to the oncogenic EMT transition and lipid metabolic reprogramming.

Figure 5 Correlations between THBS1 expression and hallmark processes and immune infiltration in laryngeal cancer. (A) Pearson correlation analyses illustrating the associations between THBS1 expression and hallmark gene sets based on TCGA database data. (B) Scatter plots demonstrating the correlations between THBS1 expression and selected hallmark gene sets. (C) Pearson correlation analyses illustrating the associations between THBS1 expression and infiltrated immune cells based on TCGA database data. (D) Scatter plots demonstrating the correlations between THBS1 expression and selected immune cells. abs, absolute; TCGA, The Cancer Genome Atlas.

To elucidate the role of the prognostic hub gene THBS1 in immune infiltration, we evaluated its correlation with various immune cell types based on the TCGA database (Figure 5C,5D). The expression level of THBS1 was found to be positively correlated with the proportion of neutrophils (r=0.42, P=2.34E−6), macrophages (r=0.41, P=5.23E−6), and regulatory T cells (Tregs) (r=0.36, P=9.10E−5). These positive correlations with immune-suppressive cells suggest that higher expression of THBS1 is associated with an immunosuppressive status of the tumor microenvironment in laryngeal cancer. Figure 5C further illustrated the correlation of THBS1 with other immune cell types, providing a broader view of their impact on the overall immune landscape.

THBS1 promotes the proliferation, migration, and invasion of laryngeal cancer cell

To investigate the functional role of THBS1 in laryngeal cancer, we applied the lentivirus transfection system to generate laryngeal cancer cell lines with stably altered expression of THBS1 (overexpression of THBS1 in TU686, and knockdown of THBS1 in HN-10). The colony-forming assays (Figure 6A) and EdU staining (Figure 6B) showed that overexpression of THBS1 promoted the proliferation of laryngeal cancer cells, and knockdown of THBS1 reduced their proliferation. Transwell assays were conducted to evaluate the impact of THBS1 on laryngeal cancer cells, revealing that THBS1 enhanced the migrative (Figure 6C) and invasive (Figure 6D) capacities of laryngeal cancer cells. In summary, THBS1 promotes the proliferation, migration, and invasion of laryngeal cancer cells in vitro, suggesting that THBS1 is a significant gene in promoting the progression of laryngeal cancer.

Figure 6 THBS1 promotes the proliferation, migration, and invasion of laryngeal cancer cell. Colony-forming assays (A, stained by crystal violet dye), EdU proliferation assays (B, stained by EdU), Transwell migration assays (C, stained by crystal violet), and Transwell invasion assays (D, stained by crystal violet) were performed to evaluate the impact of altered THBS1 expression on the progression of laryngeal cancer. Scale bars, 100 µm (B), 50 µm (C,D). EdU, 5-ethynyl-2'-deoxyuridine; DAPI, 4',6-diamidino-2-phenylindole; NC, negative control; shNC, shRNA negative control.

THBS1 is a promising therapeutic target in inhibiting the progression of laryngeal cancer

The above results demonstrate that THBS1 is a crucial risk factor in promoting the progression of laryngeal cancer. Previous research has reported the inhibitory effects of Clopidogrel on the molecular function of THBS1 (25,26), thus we performed in vitro experiments to investigate the therapeutic potential of Clopidogrel on laryngeal cancer. As shown in Figure 7A,7B, colony-forming assays and EdU staining showed that Clopidogrel significantly inhibited the proliferation of laryngeal cancer cells in a dose-dependent manner. Transwell assays revealed that Clopidogrel evidently attenuated the migration (Figure 7C) and invasion (Figure 7D) of laryngeal cancer cells in a dose-dependent manner. Since THBS1 is associated with fatty acid metabolism (27,28), we also enquired whether inhibiting THBS1 alters the lipid metabolism in laryngeal cancer using Nile Red lipid staining. The results showed that inhibiting THBS1 using Clopidogrel significantly reduced intracellular lipid accumulation in laryngeal cancer cells (Figure 7E). These findings demonstrated the therapeutic promise of Clopidogrel in inhibiting the progression of laryngeal cancer, awaiting clinical validation in further clinical research.

Figure 7 Targeting THBS1 inhibits the progression of laryngeal cancer. Different doses of Clopidogrel were applied to evaluate the impact of targeting THBS1 on the progression of laryngeal cancer, including colony-forming ability (A, stained by crystal violet), EdU proliferation assays (B, stained by EdU), Transwell migration capacity (C, stained by crystal violet), Transwell invasion capacity (D, stained by crystal violet), and intracellular lipid accumulation (E, stained by NileRed). Scale bars, 100 µm (B,E), 50 µm (C,D). EdU, 5-ethynyl-2'-deoxyuridine; DAPI, 4',6-diamidino-2-phenylindole.

Discussion

Laryngeal cancer, primarily originating from the mucosal epithelium within the larynx, is a significant form of head and neck malignancies with a global presence (1,2,6). The prognosis for laryngeal cancer is heavily dependent on the stage at diagnosis; while the 5-year survival rate is around 80% for localized cases, it significantly decreases for advanced-stage tumors due to rapid growth, lack of robust screening programs, and locoregional relapse following treatment (1,5). This underscores the urgent need for reliable prognostic biomarkers that can identify patients at increased risk.

This study represents a comprehensive analysis of hub prognostic genes among patients with laryngeal cancer based on three large-scale cohorts containing transcriptomics and clinic-pathological data. Our analysis initially identified four significant prognostic genes using two machine learning algorithms, among which THBS1 was validated as the hub risk gene in internal and external independent datasets. Additionally, we explored the immune infiltration associated with THBS1 expression, offering insights into the underlying immune suppression microenvironment. Finally, we performed comprehensive in vitro experiments to validate the oncogenic role and therapeutic promise of THBS1 in inhibiting the progression of laryngeal cancer. THBS1 was identified as a key gene associated with worse prognosis and immunosuppressive tumor microenvironment with therapeutic vulnerability in laryngeal cancer.

In our research, we initially employed LASSO Cox regression analysis and random forest algorithm in TCGA dataset to identify four genes (FRMD5, CLDN23, PLIN5, and THBS1) that are correlated with patient survival, which have the potential to serve as biomarkers for prognostication. Subsequently, we performed external validation of the prognostic values of these genes in independent datasets from Greece (GSE27020, N=109) (15,16) and Germany (GSE65858, N=48) (17), exhibiting the correlation between THBS1 and worse prognosis in patients with laryngeal cancer. These findings demonstrate the prognostic value of THBS1 in laryngeal cancer, awaiting further validation in large cohort studies, which is in accord with previous reports showing the prognostic role of THBS1 in other solid cancers (29,30).

Our analysis of biological processes between laryngeal tumors and normal laryngeal tissues revealed altered immune system processes in laryngeal tumors, indicating the potential participation of the immune system in the development of laryngeal cancer. Thus, we next utilized GSVA deconvolution method to assess the infiltration of 24 types of immune cells in laryngeal cancer. Notably, laryngeal tumors with higher expression of THBS1 exhibited increased infiltration of immunosuppressive immune cells, particularly neutrophils, macrophages, and Tregs (31,32). Neutrophils are the most abundant leukocytes in the immune system and play an important role in the TME. They can suppress T cell activation through the secretion of arginase-1, reactive oxygen species (ROS), and nitric oxide (NO). Additionally, neutrophils release neutrophil extracellular traps (NETs) containing histones, neutrophil elastase, and matrix metalloproteinases (MMPs), which promote tumor cell proliferation and metastasis. Macrophages in the TME are predominantly tumor-associated macrophages (TAMs), in which the M2 macrophages are particularly immunosuppressive, remodeling the extracellular matrix, promoting angiogenesis, and recruiting Tregs and myeloid-derived suppressor cells (MDSCs) through secreting cytokines such as IL-10 and TGF-β, which inhibit antitumor immune responses. Tregs are a subset of T cells that play a critical role in maintaining immune tolerance and suppressing antitumor immune responses. They express high levels of inhibitory molecules such as CTLA-4 and PD-1, which dampen the activity of effector T cells, and they also secrete immunosuppressive cytokines like IL-10 and TGF-β, further suppressing the antitumor immune response. The role of THBS1 in promoting immune cell infiltration and immunosuppression in laryngeal cancer highlights the complexity of the TME and the need for personalized therapeutic strategies. THBS1 is a promising target to reverse immunosuppression, guiding effective and targeted immunotherapeutic approaches.

THBS1 is a multifunctional matricellular protein that plays a significant role in various aspects of tumor biology, involving cell differentiation, proliferation, migration, and apoptosis. THBS1 is well-known for its anti-angiogenic properties, which can inhibit tumor growth by restricting the formation of new blood vessels, particularly in the early stages of cancer (33). However, in advanced-stage cancer, THBS1 has been shown to promote tumor invasion and metastasis by inducing the expression of MMPs to degrade the ECM and facilitate cancer cell migration (34). THBS1 is also associated with increased infiltration of immunosuppressive cells in the TME, contributing to a less effective antitumor immune response (30,35). In our study, we performed comprehensive in vitro experiments and demonstrated the oncogenic effects of THBS1 in laryngeal cancer. In addition, Clopidogrel, a commonly used drug in clinical practice, has been reported to inhibit the molecular function of THBS1 (25,26). Thus, we treated laryngeal cancer cells with Clopidogrel and validated its therapeutic potential in inhibiting the progression of laryngeal cancer. This work is the first to testify to the prognostic value, oncogenic role, and therapeutic vulnerability of THBS1 in laryngeal cancer, providing guidance for the comprehensive therapy strategies of patients with laryngeal cancer.

Our study, while yielding significant insights, is subject to several limitations that should be addressed in future research. Firstly, the identification of prognostic THBS1 was based on retrospective data, which inherently lacks the rigor of prospective studies. Further large-scale, well-designed prospective studies are essential to enhance the robustness and generalizability of our findings. Secondly, our reliance on laryngeal cancer cell lines for in vitro experiments may not fully capture the heterogeneity of laryngeal cancer. Future studies should consider in vivo models, such as subcutaneous tumor inoculation models and patient-derived xenografts (PDX) models, to better reflect the diverse genetic and phenotypic profiles of laryngeal cancer. Lastly, while our bioinformatics analysis using multiple independent public datasets provided valuable insights, the results may have been influenced by noise inherent in such datasets. Future research should focus on minimizing these influences through advanced data cleaning techniques and rigorous statistical methods. Despite these limitations, our study provides a foundational understanding of the prognostic value, oncogenic role, and therapeutic vulnerability of THBS1 in laryngeal cancer. Addressing these limitations through collaborative efforts, larger cohort studies, and multi-center validations will be crucial in enhancing the translational impact of our findings and advancing the field of laryngeal cancer research.

In summary, our research underscores the potential of THBS1 as a valuable target for clinical decision-making in laryngeal cancer. THBS1 demonstrates high accuracy and effectiveness in predicting patient survival outcomes in multiple independent datasets. Moreover, our exploration of the THBS1-related immune landscape reveals a positive correlation between immunosuppressive cell infiltration, suggesting that targeting THBS1 may be promising in reversing immunosuppression and developing personalized immunotherapies. In addition, we validated the therapeutic potential of Clopidogrel, a commonly used drug in clinical practice, in inhibiting the progression of laryngeal cancer, awaiting further validation in prospective clinical studies.

Conclusions

Our study supports THBS1 as a potential prognostic predictor with therapeutic vulnerability for patients with laryngeal cancer. Future studies will focus on validating the utility of THBS1 in laryngeal cancer, aiming to affirm its clinical relevance and applicability in routine practice.

Acknowledgments

We would like to thank the specimen donors and research groups for the TCGA, GSE27020, and GSE65858 cohorts.

Footnote

Reporting Checklist: The authors have completed the MDAR reporting checklist. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-779/rc

Data Sharing Statement: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-779/dss

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-779/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-779/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments.

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

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