Analysis of microRNA expression profiles reveals a 5‑microRNA prognostic signature for predicting overall survival time in patients with gastric adenocarcinoma

Zhao, Ruihong; Zhao, Lei; Xu, Xu; Xu, Hong

doi:10.3892/or.2019.7048

Cited by 3 publications

(2 citation statements)

References 58 publications

(65 reference statements)

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“…An appropriate formula was developed to use this panel. However, the authors have shown that a history of relapse and age over 65 years are independent prognostic factors [146].…”

Section: Mir-585mentioning

confidence: 99%

MicroRNA in Gastric Cancer Development: Mechanisms and Biomarkers

et al. 2020

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Gastric cancer (GC) is one of the most common and difficult diseases to treat. The study of signaling pathway regulation by microRNA provides information on the mechanisms of GC development and is the basis for biomarker creation. In this study, a circuit of microRNA interactions with signaling pathways was constructed. The microRNAs, associated with metastasis and chemoresistance, are described. In most cases, microRNAs in GC regulate the Wnt/β-catenin, PI3K/AKT/mTOR, RAS/RAF/ERK/MAPK, NF-kB, TGF-β, and JAK/STAT pathways. Part of the microRNA acts on several target genes that function in different pathways. This often leads to an intensification of the induced processes. MicroRNAs have also been described that have the opposite effect on different pathways, causing different functional consequences. By acting on several target genes, or genes associated with several pathways, microRNAs can function in a signaling network. MicroRNAs associated with metastasis most often interact with the Wnt/β-catenin pathway. MicroRNAs affecting chemoresistance, in most cases, affect the regulators of apoptosis and are associated with the PI3K/AKT/mTOR pathway. The characteristics of microRNAs proposed as candidates for GC biomarkers were analyzed. The currently developed diagnostic and prognostic panels of microRNAs are also considered.

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“…An appropriate formula was developed to use this panel. However, the authors have shown that a history of relapse and age over 65 years are independent prognostic factors [146].…”

Section: Mir-585mentioning

confidence: 99%

MicroRNA in Gastric Cancer Development: Mechanisms and Biomarkers

et al. 2020

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“…Gene regulation is a complex network, and researchers began to use sequencing data to build a multi-gene model, combined with multiple gene detection to study tumors. For example, Zhao et al (2019) used univariate and multivariate Cox regression analysis to identify miRNA related to GC patients’ prognosis from the TCGA-STAD cohort. A predictive risk model based on a 5-miRNA signature was established.…”

Section: Introductionmentioning

confidence: 99%

Development and clinical validation of a 3-miRNA signature to predict prognosis of gastric cancer

Zhang

2021

PeerJ

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Aims Identification of miRNA signature to predict the prognosis of gastric cancer (GC) patients by integrating bioinformatics and experimental validation. Methods The miRNA expression profile and clinical data of GC were collected. The univariable and LASSO-Cox regression were used to construct the risk signature. The receiver operating characteristic (ROC) curve analysis confirmed the good performance of the prognostic model. Results A 3-miRNA prognostic signature was constructed, which included hsa-miR-126-3p, hsa-miR-143-5p, and hsa-miR-1275. A nomogram, including the prognostic signature to predict the overall survival, was established, and internal validation in the The Cancer Genome Atlas (TCGA) cohort was performed. We found that compared with the traditional pathological stage, the nomogram was the best at predicting the prognosis. Conclusions The predictive model and the nomogram will enable patients with GC to be more accurately managed in clinical practice.

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An integrated analysis of DNA promoter methylation, microRNA regulation, and gene expression in gastric adenocarcinoma

et al. 2021

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Background: Gastric adenocarcinoma (GAC), a common type of gastric cancer, poses a significant public health threat worldwide. This study aimed to determine the transcriptional regulatory mechanisms of GAC.Methods: HTSeq-FPKM raw data were obtained from The Cancer Genome Atlas Stomach Adenocarcinoma data collection. Subsequently, the limma package in R was used to identify differentially expressed genes (DEGs). Differentially methylated genes (DMGs), DEGs, and differentially expressed microRNAs (miRNAs) in normal, and tumor tissues of the same patients were screened and compared using R software tools. A functional enrichment analysis was performed using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) for various DEGs, DMGs, promoter methylation, and miRNAs. DEG-specific methylation and transcription factors were analyzed using ENCODE ChIP-seq.Results: DEGs were centrally modified by the histone trimethylation of lysine 27 on histone H3 (H3K27me3). Upstream transcription factors of DEGs were enriched in different ChIP-seq clusters, such as Forkhead Box M1, E2F Transcription Factor 4, and suppressor of zest 12. Integrated regulatory networks of DEGs, promoter methylation, and miRNAs were constructed. Two miRNAs (hsa-mir-1 and hsa-mir-133a) and four DEGs (A disintegrin and metalloproteinase domain 12, transcription factor AP-2 alpha, solute carrier family 5 member 7, and cadherin 19) separately played important roles in the integrated regulatory network. Therefore, these DEGs, DMGs, promoter methylation, and miRNAs may play an important role in GAC pathogenesis. Conclusions:In summary, the present study results provide insights into the oncogenesis and progression of GAC, thus accelerating the development of novel targeted GAC therapies.

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Analysis of microRNA expression profiles reveals a 5‑microRNA prognostic signature for predicting overall survival time in patients with gastric adenocarcinoma

Cited by 3 publications

References 58 publications

MicroRNA in Gastric Cancer Development: Mechanisms and Biomarkers

MicroRNA in Gastric Cancer Development: Mechanisms and Biomarkers

Development and clinical validation of a 3-miRNA signature to predict prognosis of gastric cancer

An integrated analysis of DNA promoter methylation, microRNA regulation, and gene expression in gastric adenocarcinoma

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