MUC15 acts as a tumor suppressor gene which correlates with prognosis and immune infiltration in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC), as a common malignant tumor of the digestive system, has been a challenge in improving and prolonging the postoperative survival of patients. This study aims to identify novel biomarkers that can guide the clinical diagnosis and treatment by using bioinformatics methods. The RNA-seq data and corresponding clinical data of ESCC were downloaded from the TCGA and GEO database. Weighted co-expression network analysis (WGCNA) was used to identify candidate biomarkers. The LASSO analysis was performed to classify the biomarkers. ROC curve and AUC were used to evaluate the sensitivity and specificity of biomarkers. CIBERSORT was applied to estimate the relative abundances of immune cell types through gene expression profiling. Univariate and multiple Cox regression were performed to screen out prognostic factors. MUC15, which abnormally expressed in different physiological processes and participates in inhibiting or promoting function in different types of tumors, was selected of candidate biomarker. Finally, we validated the expression of MUC15 in ESCC tissues and its inhibitory effect on cell function through <i>in vitro</i> and <i>in vivo</i> experiments. In conclusion, we identified MUC15 could serve as a tumor suppressor gene and may become a promising candidate for individualized clinical diagnosis and treatment of ESCC.

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Publication Details

Journal
International Journal of Medical Sciences
Published
2025-03-21
DOI
https://doi.org/10.7150/ijms.108926
Primary Topic
Glycosylation and Glycoproteins Research
Type
article
Field-Weighted Citation Impact
0.00

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article

MUC15 acts as a tumor suppressor gene which correlates with prognosis and immune infiltration in esophageal squamous cell carcinoma

Xiaoping Lin, Ying Chen, Hao Wu, Shifeng Xing et al.
International Journal of Medical Sciences
Glycosylation and Glycoproteins Research
article

MUC15 acts as a tumor suppressor gene which correlates with prognosis and immune infiltration in esophageal squamous cell carcinoma

Xiaoping Lin, Ying Chen, Hao Wu, Shifeng Xing, Xiang Fei, Lei Chen, Hailong Liu, Bin Sun, Aili Wang
article en

Abstract

Esophageal squamous cell carcinoma (ESCC), as a common malignant tumor of the digestive system, has been a challenge in improving and prolonging the postoperative survival of patients. This study aims to identify novel biomarkers that can guide the clinical diagnosis and treatment by using bioinformatics methods. The RNA-seq data and corresponding clinical data of ESCC were downloaded from the TCGA and GEO database. Weighted co-expression network analysis (WGCNA) was used to identify candidate biomarkers. The LASSO analysis was performed to classify the biomarkers. ROC curve and AUC were used to evaluate the sensitivity and specificity of biomarkers. CIBERSORT was applied to estimate the relative abundances of immune cell types through gene expression profiling. Univariate and multiple Cox regression were performed to screen out prognostic factors. MUC15, which abnormally expressed in different physiological processes and participates in inhibiting or promoting function in different types of tumors, was selected of candidate biomarker. Finally, we validated the expression of MUC15 in ESCC tissues and its inhibitory effect on cell function through <i>in vitro</i> and <i>in vivo</i> experiments. In conclusion, we identified MUC15 could serve as a tumor suppressor gene and may become a promising candidate for individualized clinical diagnosis and treatment of ESCC.

International Journal of Medical SciencesVol. 22(8)
Second Military Medical University (CN), Ruijin Hospital (CN), Shanghai University of Traditional Chinese Medicine (CN), Changhai Hospital (CN), Shanghai Pulmonary Hospital (CN), Shanghai Traditional Chinese Medicine Hospital (CN), Yangpu Hospital of Tongji University (CN)
Natural Science Foundation of Shanghai
Openalex Percentile: Top 94%
Glycosylation and Glycoproteins Research
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