Dataset Information

A Novel Clinical Six-Flavoprotein-Gene Signature Predicts Prognosis in Esophageal Squamous Cell Carcinoma.

ABSTRACT: Flavoproteins and their interacting proteins play important roles in mitochondrial electron transport, fatty acid degradation, and redox regulation. However, their clinical significance and function in esophageal squamous cell carcinoma (ESCC) are little known. Here, using survival analysis and machine learning, we mined 179 patient expression profiles with ESCC in GSE53625 from the Gene Expression Omnibus (GEO) database and constructed a signature consisting of two flavoprotein genes (GPD2 and PYROXD2) and four flavoprotein interacting protein genes (CTTN, GGH, SRC, and SYNJ2BP). Kaplan-Meier analysis revealed the signature was significantly associated with the survival of ESCC patients (mean survival time: 26.77 months in the high-risk group vs. 54.97 months in the low-risk group, P < 0.001, n?=?179), and time-dependent ROC analysis demonstrated that the six-gene signature had good predictive ability for six-year survival for ESCC (AUC?=?0.86, 95% CI: 0.81-0.90). We then validated its prediction performance in an independent set by RT-PCR (mean survival: 15.73 months in the high-risk group vs. 21.1 months in the low-risk group, P=0.032, n?=?121). Furthermore, RNAi-mediated knockdown of genes in the flavoprotein signature led to decreased proliferation and migration of ESCC cells. Taken together, CTTN, GGH, GPD2, PYROXD2, SRC, and SYNJ2BP have an important clinical significance for prognosis of ESCC patients, suggesting they are efficient prognostic markers and potential targets for ESCC therapy.

SUBMITTER: Peng L

PROVIDER: S-EPMC6878914 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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A Novel Clinical Six-Flavoprotein-Gene Signature Predicts Prognosis in Esophageal Squamous Cell Carcinoma.

Peng Liu L Guo Jin-Cheng JC Long Lin L Pan Feng F Zhao Jian-Mei JM Xu Li-Yan LY Li En-Min EM

BioMed research international 20191030

Flavoproteins and their interacting proteins play important roles in mitochondrial electron transport, fatty acid degradation, and redox regulation. However, their clinical significance and function in esophageal squamous cell carcinoma (ESCC) are little known. Here, using survival analysis and machine learning, we mined 179 patient expression profiles with ESCC in GSE53625 from the Gene Expression Omnibus (GEO) database and constructed a signature consisting of two flavoprotein genes (GPD2 and ...[more]

PMID: 31815134

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Project description:BackgroundEsophageal squamous cell carcinoma (ESCC) is correlated with worse clinical prognosis and lacks available targeted therapy. Thus, identification of reliable biomarkers is required for the diagnosis and treatment of ESCC.MethodsWe downloaded the GSE53625 dataset as a training dataset to screen differentially expressed RNAs (DERs) with the criterion of false discovery rate (FDR) < 0.05 and |log2fold change (FC)| > 1. A support vector machine classifier was used to find the optimal feature gene set that could conclusively distinguish different samples. An eight-lncRNA signature was identified by random survival forest algorithm and multivariate Cox regression analysis. The RNA sequencing data from The Cancer Genome Atlas (TCGA) database were used for external validation. The predictive value of the signature was assessed using Kaplan-Meier test, time-dependent receiver operating characteristic (ROC) curves, and dynamic area under the curve (AUC). Furthermore, a nomogram to predict patients' 3-year and 5-year prognosis was constructed. CCK-8 assay, flow cytometry, and transwell assay were conducted in ESCC cells.ResultsA total of 1136 DERs, including 689 downregulated mRNAs, 318 upregulated mRNAs, 74 downregulated lncRNAs and 55 upregulated lncRNAs, were obtained in the GES53625 dataset. From the training dataset, we identified an eight-lncRNA signature, (ADAMTS9-AS1, DLX6-AS1, LINC00470, LINC00520, LINC01497, LINC01749, MAMDC2-AS1, and SSTR5-AS1). A nomogram based on the eight-lncRNA signature, age, and pathologic stage was developed and showed good accuracy for predicting 3-year and 5-year survival probability of patients with ESCC. Functionally, knockdown of LINC00470 significantly suppressed cell proliferation, G1/S transition, and migration in two ESCC cell lines (EC9706 and TE-9). Moreover, knockdown of LINC00470 downregulated the protein levels of PCNA, CDK4, and N-cadherin, while upregulating E-cadherin protein level in EC9706 and TE-9 cells.ConclusionOur eight-lncRNA signature and nomogram can provide theoretical guidance for further research on the molecular mechanism of ESCC and the screening of molecular markers.

Project description:BackgroundIt has been reported that tumor immune microenvironment performs a vital role in tumor progress. However, acting mechanism of immune cell related genes (IRGs) in esophageal squamous cell carcinoma (ESCC) is uncertain.MethodsTCGA-ESCC, GSE23400, GSE26886, GSE75241, and GSE196756 datasets were gained via public databases. First, differentially expressed genes (DEGs) between ESCC and control samples from GSE23400, GSE26886, and GSE75241 were screened out by differential expression analysis, and overlapping DEGs were identified. Single-cell transcriptome data of GSE196756 were applied to explore immune cells that might be involved in regulation of ESCC. Then, weighted gene co-expression network analysis was applied to screen IRGs. Next, differentially expressed IRGs (DE-IRGs) were identified by overlapping IRGs and DEGs, and were incorporated into univariate Cox, least absolute shrinkage and selection operator, and multivariate Cox to acquire prognosis-related genes, and ESCC samples were grouped into high-/low-risk groups on the basis of median risk score. Finally, the role of prognosis model in immunotherapy was analyzed.ResultsTotally 248 DEGs were yielded by overlapping 3,915 DEGs in GSE26886, 459 DEGs in GSE23400, and 1,641 DEGs in GSE75241. Single-cell analysis found that B cells, dendritic cells, monocytes, neutrophils, natural killer cells, and T cells were involved in ESCC development. Besides, MEred, MEblack, MEpink, MEblue and MEbrown modules were considered as key modules because of their highest correlations with immune cell subtypes. A total of 154 DE-IRGs were yielded by taking intersection of DEGs and genes in key modules. Moreover, CTSC, ALOX12, and RMND5B were identified as prognosis-related genes in ESCC. Obviously, Exclusion and TIDE scores were notably lower in high-risk group than in the other one, indicating that high-risk group was more responsive to immunotherapy.ConclusionsThrough bioinformatic analysis, we identified a prognosis model consisting of IRGs (CTSC, ALOX12, and RMND5B) in ESCC, providing new ideas for studies related to treatment and prognosis of ESCC.

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.

Dataset Information

A Novel Clinical Six-Flavoprotein-Gene Signature Predicts Prognosis in Esophageal Squamous Cell Carcinoma.

Publications

A Novel Clinical Six-Flavoprotein-Gene Signature Predicts Prognosis in Esophageal Squamous Cell Carcinoma.

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