Literature DB >> 33455113

Prognostic potential of miR-21-3p in gastric cancer.

Xiaofen Sun1, Kanru Zhang, Duoqiao Li.   

Abstract

PURPOSE: This study aimed to clarify the role of microRNA (miR)-21-3p in regulating progression and prognosis in gastric cancer (GC).
METHODS: One hundred patients with primary GC were included in this study. Their primary GC tissues and paracancer normal mucosa were collected for detecting miR-21-3p levels. Receiver operating characteristic (ROC) curves were depicted for analyzing the predictive ability of miR-21-3p in GC. Subgroup analyses were conducted based on tumor size, lymph node metastasis status and TNM staging in GC patients. All GC patients were followed up for 5 years, and survival analysis was conducted using Kaplan-Meier method with log-rank test. Univariate and multivariate Cox regression analyses were performed for exploring potential prognostic factors for GC.
RESULTS: MiR-21-3p was highly expressed in GC tissues. Subgroup analyses were conducted based on tumor size, lymph node metastasis status and tumor staging. Subgroup analyses showed higher level of miR-21-3p in GC tissues collected from patients with large tumor size, lymph node metastasis or advanced TNM staging. ROC curves confirmed the diagnostic potential of miR-21-3p in GC. In addition, Kaplan-Meier and log-rank test revealed lower progression-free survival (PFS) and overall survival (OS) in GC patients overexpressing miR-21-3p. Tumor size, lymph node metastasis, TNM staging and miR-21-3p level were independent risk factors for the prognosis of GC.
CONCLUSIONS: MiR-21-3p is upregulated in GC samples, which is closely related to GC progression. MiR-21-3p can be used to predict the prognosis of GC.

Entities:  

Year:  2020        PMID: 33455113

Source DB:  PubMed          Journal:  J BUON        ISSN: 1107-0625            Impact factor:   2.533


  4 in total

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4.  Establishing a three-miRNA signature as a prognostic model for colorectal cancer through bioinformatics analysis.

Authors:  Yiming Wang; Lumi Huang; Nan Shan; Huiwen Ma; Songmei Lu; Xingyue Chen; Hao Long
Journal:  Aging (Albany NY)       Date:  2021-08-13       Impact factor: 5.682

  4 in total

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