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1.
Environ Toxicol ; 39(1): 9-22, 2024 Jan.
Article in English | MEDLINE | ID: mdl-37584547

ABSTRACT

BACKGROUND: Aberrant expression of MUC1 correlates with the progression of esophageal squamous cell carcinoma (ESCC), this study aimed to explore the effect of targeting MUC1 by Go-203 on malignant behavior of ESCC and the underlying mechanism. METHODS AND RESULTS: IHC was used to examine the expression of MUC1 and DNAJB6 in ESCC samples. qRT-PCR and western blotting were used to examine the expression of MUC1 and DNAJB6 in ESCC cell lines. CCK8, wound healing, and transwell assays were used to determine the effect of regulating MUC1/DNAJB6 on the proliferation, migration, and invasion of ESCC cells. The effect of overexpressing/targeting MUC1 on the activation of the AKT/HSF-1 pathway was determined by western blotting. A negative correlation was confirmed between the expression of DNAJB6 and MUC1 in ESCC tissue samples by IHC, and high expression of MUC1 and low expression of DNAJB6 correlated with lymph node metastasis in ESCC patients. Overexpressing MUC1 downregulated the expression of DNAJB6, promoted ESCC proliferation, invasion, migration and activated the AKT pathway, while targeting MUC1 suppressed proliferation, invasion, migration, and the AKT pathway and up-regulated DNAJB6 expression in vitro. Moreover, MUC1 increased the phosphorylation of HSF-1 via the AKT pathway, and inhibiting AKT-HSF-1 increased the expression of DNAJB6 in vitro. CONCLUSIONS: This study indicated that MUC1 could promote tumorigenesis and metastasis in ESCC by downregulating DNAJB6 expression through AKT-HSF-1 pathway.


Subject(s)
Esophageal Neoplasms , Esophageal Squamous Cell Carcinoma , Humans , Esophageal Squamous Cell Carcinoma/genetics , Esophageal Squamous Cell Carcinoma/metabolism , Esophageal Squamous Cell Carcinoma/pathology , Esophageal Neoplasms/metabolism , Lymphatic Metastasis , Proto-Oncogene Proteins c-akt/metabolism , Cell Line, Tumor , Cell Proliferation , Cell Movement , Gene Expression Regulation, Neoplastic , Nerve Tissue Proteins/metabolism , Molecular Chaperones/metabolism , HSP40 Heat-Shock Proteins/genetics , HSP40 Heat-Shock Proteins/metabolism , Mucin-1/metabolism
2.
Int J Gen Med ; 14: 9007-9022, 2021.
Article in English | MEDLINE | ID: mdl-34876838

ABSTRACT

BACKGROUND: Early-stage lung squamous cell carcinoma (LUSC) progression is accompanied by changes in immune microenvironments and the expression of immune-related genes (IRGs). Identifying innate IRGs associated with prognosis may improve treatment and reveal new immunotherapeutic targets. METHODS: Gene expression profiles and clinical data of early-stage LUSC patients were obtained from the Gene Expression Omnibus and The Cancer Genome Atlas databases and IRGs from the InnateDB database. Univariate and multivariate Cox regression and LASSO regression analyses were performed to identify an innate IRG signature model prognostic in patients with early-stage LUSC. The predictive ability of this model was assessed by time-dependent receiver operator characteristic curve analysis, with the independence of the model-determined risk score assessed by univariate and multivariate Cox regression analyses. Overall survival (OS) in early-stage LUSC patients was assessed using a nomogram and decision curve analysis (DCA). Functional and biological pathways were determined by gene set enrichment analysis, and differences in biological functions and immune microenvironments between the high- and low-risk groups were assessed by ESTIMATE and the CIBERSORT algorithm. RESULTS: A signature involving six IRGs (SREBF2, GP2, BMX, NR1H4, DDX41, and GOPC) was prognostic of OS. Samples were divided into high- and low-risk groups based on median risk scores. OS was significantly shorter in the high-risk than in the low-risk group in the training (P < 0.001), GEO validation (P = 0.00021) and TCGA validation (P = 0.034) cohorts. Multivariate Cox regression analysis showed that risk score was an independent risk factor for OS, with the combination of risk score and T stage being optimally predictive of clinical benefit. GSEA, ESTIMATE, and the CIBERSORT algorithm showed that immune cell infiltration was higher and immune-related pathways were more strongly expressed in the low-risk group. CONCLUSION: A signature that includes these six innate IRGs may predict prognosis in patients with early-stage LUSC.

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