ArticleHeliyon2019
Bioinformatic evidences and analysis of putative biomarkers in pancreatic ductal adenocarcinoma.
Article in Heliyon, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- GNA15 predicts poor outcomes as a novel biomarker related to M2 macrophage infiltration in ovarian cancer.Frontiers in immunology · 2025Article
- Histaminergic System and Inflammation-Related Genes in Normal Large Intestine andInternational journal of molecular sciences · 2023Article
- Identification and Interaction Analysis of Molecular Markers in Pancreatic Ductal Adenocarcinoma by Bioinformatics and Next-Generation Sequencing Data Analysis.Bioinformatics and biology insights · 2023Article
- Truncated isoforms of GPSM2 containing the GoLoco motif region promote CD4Lupus science & medicine · 2022Article
- Annexin-A1: The culprit or the solution?Immunology · 2022Review
- Differential expression profile of CXC-receptor-2 ligands as potential biomarkers in pancreatic ductal adenocarcinoma.American journal of cancer research · 2022Article
- Downregulation of GNA15 Inhibits Cell ProliferationFrontiers in oncology · 2021Article
- Article
- CXCL5 expression in tumor tissues is associated with poor prognosis in patients with pancreatic cancer.Oncology letters · 2020Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPancreatic ductal adenocarcinoma (PDAC) is one of the most lethal human cancers. Aberrant expression of genes plays important role in the procession of PDAC. The analysis of gene expression profile will contribute to the research of carcinoma mechanism.
objectiveThis present study is focused to investigate the differentially expressed genes (DEGs) from 3 PDAC microarray datasets, which would provide candidate genes for putative biomarkers to understand the mechanism of PDAC and potential targets of treatment.
methodBased on the overlap genes obtained from 3 GEO datasets, the hub genes were identified using STRING and Cytoscape plugin MCODE. The enrichment and function analysis were applied using DAVID. The protein-protein interaction network was performed using cBioPortal and UCSC Xena. The Oncomine was finally used to determine the candidate gene by analyzing their expression between pancreas sample and PDAC sample.
results25 hub genes were selected from a total of 1006 DEGs from 3 GEO datasets, consisting of 14 upregulated genes and 11 downregulated genes. The overall decline of hub gene expression enriched in G1 phase of cell cycle in other subtypes of pancreatic cancer. Oncomine database was ultimately performed to determine the 8 candidate genes, including CXCL5, CCL20, NMU, F2R, ANXA1, EDNRA, LPAR6, and GNA15.
conclusionsConclusively, 8 candidate genes would become the potential PDAC combined biomarkers for diagnosis and therapeutic strategies.
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