ArticleFEBS open bio2019
A six-microRNA signature to predict outcomes of patients with gastric cancer.
Article in FEBS open bio, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- Systematic Review of Prognostic Gene Signature in Gastric Cancer Patients.Frontiers in bioengineering and biotechnology · 2020Pooled it
- The role of microRNAs in gastritis, intestinal metaplasia, and gastric cancer: a narrative review.Translational cancer research · 2025Review
- MicroRNA dynamics in irisin-mediated signaling pathways within adipose tissue.Journal of biosciences · 2024Article
- The Value of Serum miR-139-3p Expression Level in Predicting Postoperative Survival of Colon Cancer Patients.International journal of general medicine · 2022Article
- Knockdown of CENPK inhibits cell growth and facilitates apoptosis via PTEN-PI3K-AKT signalling pathway in gastric cancer.Journal of cellular and molecular medicine · 2021Article
- Limb-bud and heart as a novel biomarker for gastric intestinal type adenocarcinoma.Oncology letters · 2020Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gastric cancer (GC) is a common gastrointestinal tumor with poor prognosis. However, conventional prognostic factors cannot accurately predict the outcomes of GC patients. Therefore, there remains a need to identify novel predictive markers to improve prognosis. In this study, we obtained microRNA expression profiles of 385 GC patients from The Cancer Genome Atlas. We performed Cox regression analysis to identify overall survival-related microRNA and then constructed a microRNA signature-based prognostic model. The accuracy of the model was evaluated and validated through Kaplan-Meier survival analysis and time-dependent receiver operating characteristic (ROC) curve analysis. The independent prognostic value of the model was assessed by multivariate Cox regression analysis. Enrichment analysis was performed to explore potential functions of the prognostic microRNA. Finally, a prognostic model based on a six-microRNA (miRNA-100, miRNA-374a, miRNA-509-3, miRNA-668, miRNA-549, and miRNA-653) signature was developed. Further analysis in the training, test, and complete The Cancer Genome Atlas set showed the model can distinguish between high-risk and low-risk patients and predict 3-year and 5-year survival. The six-microRNA signature was also an independent prognostic marker, and enrichment analysis suggested that the microRNA may be involved in cell cycle and mitosis. These results demonstrated that the model based on the six-microRNA signature can be used to accurately predict the prognosis of GC patients.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.