ArticleMedicine2018
Identification of key microRNAs and their targets in exosomes of pancreatic cancer using bioinformatics analysis.
Article in Medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
11 citing papers in PubMed, 18 citations in OpenAlex.
- Exosomes in Cancer: Diagnostic and Therapeutic Applications.Clinical Medicine Insights. Oncology · 2024Review
- Engineering of Cell Derived-Nanovesicle as an Alternative to Exosome Therapy.Tissue engineering and regenerative medicine · 2024Review
- The importance of miRNA-630 in human diseases with an especial focus on cancers.Cancer cell international · 2022Review
- microRNA-21 Regulates Stemness in Pancreatic Ductal Adenocarcinoma Cells.International journal of molecular sciences · 2022Article
- Identification of a five-miRNA signature as a novel potential prognostic biomarker in patients with nasopharyngeal carcinoma.Hereditas · 2022Article
- MicroRNA‑524‑5p regulates the proliferation and invasion of HTR‑8/SVneo trophoblasts by targeting NUMB in the Notch signaling pathway.Molecular medicine reports · 2021Article
- Role of exosomes in pancreatic cancer.Oncology letters · 2021Review
- Review
- Exosomal biomarkers for cancer diagnosis and patient monitoring.Expert review of molecular diagnostics · 2020Review
- Differentiation ofGastroenterology and hepatology from bed to bench · 2020Article
- Identification of novel genes associated with a poor prognosis in pancreatic ductal adenocarcinoma via a bioinformatics analysis.Bioscience reports · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pancreatic cancer (PC) is one of the most lethal tumors, due to late diagnosis and limited surgical strategies. It has been reported that serum exosomal microRNAs (S-Exo-miRNAs) play a pivotal role as signaling molecules and serve as noninvasive diagnosis methods for PC. The combination of S-Exo-miRNAs with the corresponding target also plays an important role in the tumor microenvironment.Here we investigated S-Exo-miRNAs involved in PC. The gene expression profile was downloaded from the Gene Expression Omnibus (GEO) database. The analysis was carried out using GEO2R. The targets of differentially expressed serum exosomal miRNAs (DE-S-Exo-miRNAs) were predicted by 4 bioinformatic algorithms (miRanda, miRDB, miRWalk, and Targetscan). Further analysis with gene ontology (GO) and Kyoto Encyclopedia of Genomes pathway (KEGG) enrichment analyses were performed with Cytoscape software version 3.4.0. Subsequently, the interaction regulatory network of target genes was performed with the Search Tool for the Retrieval of Interacting Genes (STRING) database (http://www.string-db.org/) and visualized using Cytoscape software.We downloaded the gene expression profile GSE50632, which was based on an Agilent microarray GPL17660 platform containing 4 eligible samples. In total 467 DE-S-Exo-miRNAs were obtained, including 7 overexpressed miRNAs (1.50%), and 460 remaining underexpressed miRNAs (98.50%). The databases miRWalk, miRDB, miRanda, and TargetScan were used to predict their potential targets, which were subsequently submitted to Cytoscape software version 3.4.0 (www.cytoscape.org). Next the functional and pathway enrichment analysis were used for the KEGG pathway and GO categories analysis. The enrichment analysis identified the genes involved in such processes as developmental and negative regulation of multicellular organismal processes, regulation of anatomical structure morphogenesis, regulation of cell death, apoptotic processes and mitogen-activated protein kinase (MAPK) signaling pathway, transforming growth factor - beta (TGF -β) signaling pathway, cyclic adenosine monophosphate (cAMP) signaling pathway, and the phosphatidylinositol-3 kinases/Akt (PI3K-Akt) signaling pathway. Subsequently according to the protein-protein interaction (PPI) network, the top 10 genes were obtained. The enrichment analyses of the genes involved in a significant module revealed that these genes were related to the TGF-β signaling pathway. After reviewing the literature, we identified the apoptosis genes, and their corresponding miRNAs that have a relationship with apoptosis of the tumor.This analysis provides a comprehensive understanding of the roles of S-Exo-miRNAs and the related targets in the development of PC. Additionally, the present study provides promising candidate targets for early diagnosis and therapeutic intervention. However, these predictions require further experimental validation in future studies.
Indexed as
Identifiers
What OpenQuestion holds
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.