ArticleMedical science monitor : international medical journal of experimental and clinical research2020
An Integrated Microarray Analysis Reveals Significant Diagnostic and Prognostic Biomarkers in Pancreatic Cancer.
Article in Medical science monitor : international medical journal of experimental and clinical research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed, 17 citations in OpenAlex.
- Computational theranostics strategy for pancreatic ductal adenocarcinoma.Molecular diversity · 2026Article
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- Construction and validation of a diagnostic model for dermatomyositis based on the LASSO algorithm.Central-European journal of immunology · 2025Article
- AHNAK2 Promotes the Progression of Pancreatic Ductal Adenocarcinoma by Maintaining the Stability of c-MET.Cancer management and research · 2024Article
- Proteomics-Driven Biomarkers in Pancreatic Cancer.Proteomes · 2023Review
- NREP is a Diagnostic and Prognostic Biomarker, and Promotes Gastric Cancer Cell Proliferation and Angiogenesis.Biochemical genetics · 2023Article
- Review
- AHNAKs roles in physiology and malignant tumors.Frontiers in oncology · 2023Review
- Multi-omics analysis of LAMB3 as a potential immunological and biomarker in pan-cancer.Frontiers in molecular biosciences · 2023Article
- AHNAK2 is a biomarker and a potential therapeutic target of adenocarcinomas.Acta biochimica et biophysica Sinica · 2022Article
- The Obscure Potential of AHNAK2.Cancers · 2022Review
- Construction of a Redox-Related Prognostic Model with Predictive Value in Survival and Therapeutic Response for Patients with Lung Adenocarcinoma.Journal of healthcare engineering · 2022Article
- ITGA2, LAMB3, and LAMC2 may be the potential therapeutic targets in pancreatic ductal adenocarcinoma: an integrated bioinformatics analysis.Scientific reports · 2021Article
- Amino Acid Transporter SLC6A14 (ATBFrontiers in cell and developmental biology · 2020Review
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND Pancreatic cancer (PAC) is a lethal cancer and it is essential to develop accurate diagnostic and prognostic biomarkers for PAC. MATERIAL AND METHODS An integrated microarray analysis of PAC was conducted to identify differentially expressed genes (DEGs) between PAC and non-tumor controls. Expression of DEGs were further confirmed by The Cancer Genome Atlas and the Genotype-Tissue Expression. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis, and protein-protein integration network construction were performed to further research the biological functions of DEGs. Receiver-operating characteristic analysis and survival analysis were used to evaluate the diagnostic and prognostic value of DEGs for PAC. RESULTS Seventeen microarray datasets were downloaded from Gene Expression Omnibus to conduct the integrated microarray analysis. A total of 1136 DEGs (596 upregulated and 540 downregulated DEGs) in PAC tissues compared with non-tumor controls were identified. Pancreatic secretion (Kegg: 04972), insulin signaling pathway (Kegg: 04910), and several cancer-related pathways including pathways in cancer (Kegg: 05200), MAPK signaling pathway (Kegg: 04010), and pancreatic cancer (Kegg: 05212) were enriched for DEGs in PAC. Seven DEGs (AHNAK2, CDH3, IFI27, ITGA2, LAMB3, SLC6A14, and TMPRSS4) were found to have both great diagnostic and prognostic value for PAC. High expression of these 7 DEGs were significantly associated with poor prognosis of patients with PAC. CONCLUSIONS These 7 DEGs might be potential diagnostic and prognostic biomarkers for PAC and help uncovering the mechanism of PAC.
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