SynthesisBioMed research international2022
Abnormally Expressed lncRNAs as Potential Biomarkers for Gastric Cancer Risk: A Diagnostic Meta-Bioinformatics Analysis.
Synthesis in BioMed research international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- Screening and validation of long non-coding RNAs associated with colorectal cancer based on random forest and LASSO regression algorithm.Discover oncology · 2025Article
- Decoding the regulatory landscape of lncRNAs as potential diagnostic and prognostic biomarkers for gastric and colorectal cancers.Clinical and experimental medicine · 2024Review
- Long Non-Coding RNAs (lncRNAs) as Regulators of the PI3K/AKT/mTOR Pathway in Gastric Carcinoma.International journal of molecular sciences · 2023Review
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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
Background and Aims: Abnormal expression of lncRNAs is relevant to the occurrence and development of gastric cancer (GC), but the significance remains inconclusive. We performed a diagnostic meta-bioinformatics analysis to elucidate the association between lncRNA expression and GC risk. Methods: Published datasets were selected from PubMed, Embase, CNKI, and Web of Science, up to 1st December 2021. The pooled sensitivity (SEN), specificity (SPE), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve (AUC) were calculated to evaluate the diagnostic value. RNA sequencing data were downloaded for validation. Results: 54 studies with 4671 patients and 4652 matched controls were included in the meta-analysis. The pooled SEN, SPE, PLR, NLR, DOR, and AUC were 0.71, 0.76, 2.9, 0.39, 8, and 0.79, respectively. Subgroup analyses showed that the DOR and AUC of intergenic lncRNAs, circulating lncRNAs, larger sample size (>200), and high-quality (NOS score ≥ 7) groups were superior to antisense lncRNAs, tissue lncRNAs, smaller sample size (≤200), and low-quality (NOS score < 7) groups, respectively. However, only circulating lncRNAs had significantly higher diagnostic utility than that tissue lncRNAs. Nine differentially expressed lncRNAs in the meta-analysis were verified in TCGA-STAD. PVT1 was the most effective single lncRNA, with AUC of 0.949, SEN of 0.808, and SPE of 0.969, while PVT1 and C5orf66-AS1 were the most effective combination, with AUC of 0.972, SEN of 0.941, and SPE of 0.937. Conclusion: Abnormally expressed lncRNAs, especially circulating lncRNAs, might be potential diagnostic biomarkers for GC risk. A novel combined model of lncRNAs might achieve better GC diagnosis performance.
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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.