Dataset Information

A Novel Three-Gene Model Predicts Prognosis and Therapeutic Sensitivity in Esophageal Squamous Cell Carcinoma.

ABSTRACT: To precisely predict the clinical outcome and determine the optimal treatment options for patients with esophageal squamous cell carcinoma (ESCC) remains challenging. Prognostic models based on multiple molecular markers of tumors have been shown to have superiority over the use of single biomarkers. Our previous studies have identified the crucial role of ezrin in ESCC progression, which prompted us to hypothesize that ezrin-associated proteins contribute to the pathobiology of ESCC. Herein, we explored the clinical value of a molecular model constructed based on ezrin-associated proteins in ESCC patients. We revealed that the ezrin-associated proteins (MYC, PDIA3, and ITGA5B1) correlated with the overall survival (OS) and disease-free survival (DFS) of patients with ESCC. High expression of MYC was associated with advanced pTNM-stage (P=0.011), and PDIA3 and ITGA5B1 were correlated with both lymph node metastasis (PDIA3: P < 0.001; ITGA5B1: P=0.001) and pTNM-stage (PDIA3: P=0.001; ITGA5B1: P=0.009). Furthermore, we found that, compared with the current TNM staging system, the molecular model elicited from the expression of MYC, PDIA3, and ITGA5B1 shows higher accuracy in predicting OS (P < 0.001) or DFS (P < 0.001) in ESCC patients. Moreover, ROC and regression analysis demonstrated that this model was an independent predictor for OS and DFS, which could also help determine a subgroup of ESCC patients that may benefit from chemoradiotherapy. In conclusion, our study has identified a novel molecular prognosis model, which may serve as a complement for current clinical risk stratification approaches and provide potential therapeutic targets for ESCC treatment.

SUBMITTER: Zeng FM

PROVIDER: S-EPMC6899311 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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A Novel Three-Gene Model Predicts Prognosis and Therapeutic Sensitivity in Esophageal Squamous Cell Carcinoma.

Zeng Fa-Min FM He Jian-Zhong JZ Wang Shao-Hong SH Liu De-Kai DK Xu Xiu-E XE Wu Jian-Yi JY Li En-Min EM Xu Li-Yan LY

BioMed research international 20191125

To precisely predict the clinical outcome and determine the optimal treatment options for patients with esophageal squamous cell carcinoma (ESCC) remains challenging. Prognostic models based on multiple molecular markers of tumors have been shown to have superiority over the use of single biomarkers. Our previous studies have identified the crucial role of ezrin in ESCC progression, which prompted us to hypothesize that ezrin-associated proteins contribute to the pathobiology of ESCC. Herein, we ...[more]

PMID: 31886273

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Project description:BackgroundThe role of the PRDM5 in esophageal squamous cell carcinoma (ESCC) has not been revealed. This study investigated the relationship between PRDM5 expression and survival outcome in esophageal squamous cell carcinoma and explored the mechanism in tumor development.MethodsIn present study, expression of PRDM5 mRNA in esophageal squamous cell carcinoma patients was conducted using the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. The expression of PRDM5 was assessed by immunohistochemical staining. Kaplan-Meier curve and Cox regression analysis was performed to analyze the survival outcome and independent predictive factors. qRT-PCR and Methylation-specific PCR were performed to identify the mRNA level of PRDM5 and Methylation rate. Cibersort algorithm to analyze the relationship between PRDM5 expression and immune cell invasion. Western-blot was performed to confirm the expression of esophageal tumor tissues and adjacent tissues.ResultsThe TCGA database and GEO database show that PRDM5 mRNA level in esophageal squamous cell carcinoma adjacent tissues was higher than that of cancer tissues, and ESCC patients with high expression of PRDM5 mRNA had better overall survival. Tissue microarray showed that the protein level of PRDM5 in the adjacent tissues of patients with ESCC was higher than that in cancer tissues, and the expression level of PRDM5 was significantly correlated with the grade of clinicopathological characteristics (P < 0.001). Patients with high expression of PRDM5 displayed a better OS and DFS. Cox regression analysis showed that PRDM5 was an independent risk factor and prognostic factor for ESCC patients (HR: 2.626, 95%CI: 1.824-3.781; P < 0.001). The protein level of PRDM5 matched with the transcriptional level, whereas the DNA methylation affected the transcriptional level. Cibersort showed that T cells CD4 memory resting, mast cells resting, eosinophils, M2 macrophages and mast cells activated were significantly positively correlated with PRDM5 expression (P < 0.05), while regulatory T cells, monocytes and dendritic cells negatively correlated with PRDM5 expression (P < 0.05).ConclusionPRDM5 can be used as a biomarker to predict the survival of ESCC patients. Furthermore, PRDM5 expression in ESCC cells may affect WNT/β-catenin signaling pathways, thus further affect the ESCC cell proliferation, migration, and invasion capacity.

Project description:Esophageal squamous cell carcinoma (ESCC) is the most prevalent form of esophageal cancer in China and is closely associated with malignant biological characteristics and poor survival. Ferroptosis is a newly discovered iron-dependent mode of cell death that plays an important role in the biological behavior of ESCC cells. The clinical significance of ferroptosis-related long noncoding RNAs (FRLs) in ESCC remains unknown and warrants further research. The current study obtained RNA sequencing profiles and corresponding clinical data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and FRLs were obtained through coexpression analysis. Consensus clustering was employed to divide the subjects into clusters, and immune-associated pathways were identified by functional analysis. The current study observed significant differences in the enrichment scores of immune cells among different clusters. Patients from TCGA-ESCC database were designated as the training cohort. A ten-FRL prediction signature was established using the least absolute shrinkage and selection operator Cox regression model and validated using the GEO cohort and our own independent validation database. Real-time quantitative polymerase chain reaction was used to verify the expression of the ten FRLs, and the ssGSEA analysis was employed to evaluate their function. In addition, the IMvigor database was used to assess the predictive value of the signature in terms of immunotherapeutic responses. Multivariate Cox and stratification analyses revealed that the ten-FRL signature was an independent predictor of the overall survival (OS). Patients with ESCC in the high-risk group displayed worse survival, a characteristic tumor immune microenvironment, and low immunotherapeutic benefits compared to those in the low-risk group. Collectively, the risk model established in this study could serve as a promising predictor of prognosis and immunotherapeutic response in patients with ESCC.

Project description:BackgroundEsophageal squamous cell carcinoma (ESCC) is closely correlated with malignant biological characteristics and poor survival. Recently, chemokines have been reported to be involved in the progression of tumors, and they can also regulate the tumor microenvironment. However, it is unclear whether chemokine-related long noncoding RNAs (lncRNAs) affect the prognosis of ESCC.MethodsWe downloaded RNA-seq and clinical data from the Gene Expression Omnibus (GEO database. Chemokine-related lncRNAs were screened by differential analysis and Pearson correlation analysis. Then, prognosis-related lncRNAs were screened by using univariate COX regression, and risk models were constructed after the least absolute shrinkage and selection operator (LASSO) regression and multivariate COX regression. The predictive value of the signature was assessed using Kaplan-Meier test, time-dependent receiver operating characteristic (ROC) curves, decision curve analysis (DCA) and calibration curve. Moreover, a nomogram to predict patients' 1-year 3-year and 5-year prognosis was constructed. Gene set enrichment analyses (GSEA), Gene Ontology/Kyoto Encyclopedia of Genes and Genomes (GO/KEGG), evaluation of immune cell infiltration, and estimation of drug sensitivity were also conducted.ResultsIn this study, 677 chemokine-related lncRNAs were first obtained by differential analysis and Pearson correlation. Then, six chemokine-related lncRNAs were obtained by using univariate COX, LASSO and multivariate COX to construct a novel chemokine-related lncRNAs risk model. The signature manifested favorable predictive validity and accuracy both in the testing and training cohorts. The chemokine-related signature could classify ESCC patients into two risk groups well, which indicated that high-risk group exhibited poor prognostic outcome. In addition, this risk model played an important role in predicting signaling pathways, immune cell infiltration, stromal score, and drug sensitivity in ESCC patients.ConclusionsThese findings elucidated the critical role of novel prognostic chemokine-related lncRNAs in prognosis, immune landscape, and drug therapy, thus throwing light on prognostic evaluation and therapeutic targets for ESCC patients.

Dataset Information

A Novel Three-Gene Model Predicts Prognosis and Therapeutic Sensitivity in Esophageal Squamous Cell Carcinoma.

Publications

A Novel Three-Gene Model Predicts Prognosis and Therapeutic Sensitivity in Esophageal Squamous Cell Carcinoma.

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