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Identification and validation of an eight-lncRNA signature that predicts prognosis in patients with esophageal squamous cell carcinoma

BACKGROUND: Esophageal 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. METHODS: We downloaded the GSE53625 dataset as a training dataset t...

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Autores principales: Zhang, Jinfeng, Ling, Xiaodong, Fang, Chengyuan, Ma, Jianqun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9109328/
https://www.ncbi.nlm.nih.gov/pubmed/35578166
http://dx.doi.org/10.1186/s11658-022-00331-x
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author Zhang, Jinfeng
Ling, Xiaodong
Fang, Chengyuan
Ma, Jianqun
author_facet Zhang, Jinfeng
Ling, Xiaodong
Fang, Chengyuan
Ma, Jianqun
author_sort Zhang, Jinfeng
collection PubMed
description BACKGROUND: Esophageal 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. METHODS: We 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 |log(2)fold 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. RESULTS: A 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. CONCLUSION: Our eight-lncRNA signature and nomogram can provide theoretical guidance for further research on the molecular mechanism of ESCC and the screening of molecular markers. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s11658-022-00331-x.
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spelling pubmed-91093282022-05-17 Identification and validation of an eight-lncRNA signature that predicts prognosis in patients with esophageal squamous cell carcinoma Zhang, Jinfeng Ling, Xiaodong Fang, Chengyuan Ma, Jianqun Cell Mol Biol Lett Research BACKGROUND: Esophageal 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. METHODS: We 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 |log(2)fold 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. RESULTS: A 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. CONCLUSION: Our eight-lncRNA signature and nomogram can provide theoretical guidance for further research on the molecular mechanism of ESCC and the screening of molecular markers. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s11658-022-00331-x. BioMed Central 2022-05-16 /pmc/articles/PMC9109328/ /pubmed/35578166 http://dx.doi.org/10.1186/s11658-022-00331-x Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Research
Zhang, Jinfeng
Ling, Xiaodong
Fang, Chengyuan
Ma, Jianqun
Identification and validation of an eight-lncRNA signature that predicts prognosis in patients with esophageal squamous cell carcinoma
title Identification and validation of an eight-lncRNA signature that predicts prognosis in patients with esophageal squamous cell carcinoma
title_full Identification and validation of an eight-lncRNA signature that predicts prognosis in patients with esophageal squamous cell carcinoma
title_fullStr Identification and validation of an eight-lncRNA signature that predicts prognosis in patients with esophageal squamous cell carcinoma
title_full_unstemmed Identification and validation of an eight-lncRNA signature that predicts prognosis in patients with esophageal squamous cell carcinoma
title_short Identification and validation of an eight-lncRNA signature that predicts prognosis in patients with esophageal squamous cell carcinoma
title_sort identification and validation of an eight-lncrna signature that predicts prognosis in patients with esophageal squamous cell carcinoma
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9109328/
https://www.ncbi.nlm.nih.gov/pubmed/35578166
http://dx.doi.org/10.1186/s11658-022-00331-x
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