ReviewCell journal2022
Determining The Role of MicroRNAs in Self-Renewal, Metastasis and Resistance to Drugs in Human Gastric Cancer Based on Data Mining Approaches: A Systematic Review.
Review in Cell journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.
- Tracing the history of clinical practice of liquid biopsy: a bibliometric analysis.Frontiers in immunology · 2025Pooled it
- MiR-21 Is a Novel Diagnostic and Prognostic Circulating Biomarker in Pleural Mesothelioma.Diagnostics (Basel, Switzerland) · 2026Article
- piR-37524 Overexpression in Colorectal Cancer: A Potential Diagnostic Bio-Marker and Therapeutic Target.Oncology research · 2026Article
- Prognostic Significance of DNAJB4 Expression in Gastric Cancer: Correlation with CD31, Caspase-3, and Tumor Progression.Diagnostics (Basel, Switzerland) · 2025Article
- Liquid biopsy in cancer current: status, challenges and future prospects.Signal transduction and targeted therapy · 2024Review
- MicroRNA-34a negatively regulates Netrin1 and mediates MEK/ERK pathway to regulate chemosensitivity of gastric cancer cells.Discover oncology · 2024Article
- Chemokine Ligand 2 Promotes Migration in Osteosarcoma by Regulating the miR-3659/MMP-3 Axis.Biomedicines · 2023Article
- Clinical application and detection techniques of liquid biopsy in gastric cancer.Molecular cancer · 2023Review
- The oncogenic potential of Rab-like protein 1A (RBEL1A) GTPase: The first review of RBEL1A research with future research directions and challenges.Journal of Cancer · 2023Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gastric cancer (GC) is one of the leading causes of cancer-related deaths worldwide. The major problems of patients with GC are the lack of proper response to the treatment, drug resistance and metastasis attributed to the presence of a subpopulation of cells inside the tumour that are called cancer stem cells (CSCs). In addition, deregulation of microRNAs (miRNAs) has been reported in different stages of GC. The aim of the present study is to determine and introduce miRNAs that contribute to regulation of stemness, metastasis and drug resistance in GC. A systematic review, we conducted data mining of available datasets and a review of previous studies to select miRNAs that target stemness, epithelial-mesenchymal transition (EMT) and drug resistance. All selected miRNAs were analysed by R software to find a common miRNA target for all three processes. Then, the target prediction of miRNAs and their related signalling pathways were obtained by using bioinformatics tools, ONCO.IO and KEGG databases, respectively. We identified seven miRNAs (miR-34a, miR-23a, miR-27a, miR-30a, miR-19b, miR-107, miR-100) from our searching approach. These miRNAs regulate pathways that contribute to stemness, EMT and drug resistance in GC. Four (miR- 34a, miR-23a, miR-30a, and miR-100) had significant interactions with each other and 52 target genes among them, from which
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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.