RESEARCH ARTICLE
A 16 Epithelia-mesenchymal Transition Associated LncRNAs Signature to Optimize Prognosis Predication of Stomach Adenocarcinoma
Yanhua Yan1, #, Xinru He2, #, Yanfen Chen1, Yuancheng Huang1, Xiaotao Jiang1, Junhui Zheng1, Xu Chen3, *
Article Information
Identifiers and Pagination:
Year: 2023Volume: 10
E-location ID: e187422032212200
Publisher ID: e187422032212200
DOI: 10.2174/18742203-v9-e221222-2022-11
Article History:
Received Date: 31/3/2022Revision Received Date: 23/10/2022
Acceptance Date: 25/10/2022
Electronic publication date: 07/03/2023
Collection year: 2023

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Aim:
The study aimed to identify critical long non-coding RNAs (lncRNAs) and constructed a prognostic signature to optimize prognosis predication of patients with Stomach Adenocarcinoma (STAD).
Background:
STAD is a common malignant tumor with a high metastasis rate and low survival rate. LncRNAs participate in the regulation process of epithelial-mesenchymal transition (EMT) and the development of STAD.
Methods:
RNAseq data were obtained from TCGA-STAD, while 200 EMT-associated genes (EAGs) from the ‘HALLMARK_EPITHELIAL_MESENCHYMA-L _TRANSITION’ gene set. Differentially expressed EAGs and EMT-associated lncRNAs (EALs) were identified. Moreover, Lasso-Cox regression analysis was used to construct a signature of differentially expressed EALs, and univariate and multivariate analyses, Kaplan-Meier analysis, receiver operating characteristic curve (ROC) analysis, and nomogram were conducted to predict its prognostic value. An enrichment functional analysis was performed. Quantitative Real-Time PCR (qRT-PCR) was used to determine lncRNAs expressions in cell lines.
Results:
A total of 52 differentially expressed EAGs and 320 EALs were identified in this study. Meanwhile, 16 EALs were used to construct the signature, and further analysis indicated that it had a high prognostic value for STAD patients. Enrichment functional analysis revealed the signature was correlated to tumor immunity in STAD. Moreover, three novel EALs expressions were confirmed in cell lines.
Conclusion:
A novel survival signature was established to predict and evaluate the prognosis of STAD patients.