Identification of potential core genes at single-cell level contributing to pathogenesis of pancreatic ductal adenocarcinoma through bioinformatics analysis

Cancer Biomark. 2022;34(1):1-12. doi: 10.3233/CBM-210271.

Abstract

Background: Pancreatic ductal adenocarcinoma (PDAC) prognosis has not improved over the last decades because of the lack of effective diagnostic and therapeutic methods in the early stage of the disease.

Methods: Several gene expression profiles were downloaded from the Expression Omnibus (GEO) database. We calculated the differentially expressed mRNAs (DEGs) and miRNAs (DEmiRs). Then, we constructed a miRNA-mRNA regulatory network by using the miRWalk database. For the DEGs regulated by DEmiRs, we introduced GEPIA to confirm these DEGs' expression and effect on overall survival. We used other GEO datasets and mRNA-miRNA target databases to validate these DEGs and their relationship with DEmiRs. All these potential core DEGs regulated by DEmiRs were also analyzed at the single-cell level to confirm their cell type source.

Results: CCNB2 and KCNN4, which were regulated by several micro RNAs, showed relatively high expression levels in PDAC patients and significant association with worse overall survival. Furthermore, we identified many DEGs at single-cell level and found that 10 oncogenes were significantly upregulated in type 2 ductal cell type, thereby further demonstrating that type 2 ductal cells might be major sources of malignant cells and are valuable therapeutic targets in PDAC.

Conclusions: Our data added some new insights into the molecular mechanism of PDAC and may be helpful for finding potential biomarkers for diagnosis. These discovery at single-cell level may also be useful for developing new therapeutic targets for PDAC patients.

Keywords: CCNB2; GEO; KCNN4; Pancreatic ductal adenocarcinoma; TCGA; miRNA-mRNA network; single-cell RNA-seq.

MeSH terms

  • Biomarkers, Tumor / genetics
  • Biomarkers, Tumor / metabolism
  • Carcinoma, Pancreatic Ductal* / pathology
  • Computational Biology / methods
  • Gene Expression Profiling / methods
  • Gene Expression Regulation, Neoplastic
  • Gene Regulatory Networks
  • Humans
  • MicroRNAs* / genetics
  • MicroRNAs* / metabolism
  • Pancreatic Neoplasms* / pathology
  • Protein Interaction Maps / genetics
  • RNA, Messenger / genetics

Substances

  • Biomarkers, Tumor
  • MicroRNAs
  • RNA, Messenger

Supplementary concepts

  • Pancreatic Carcinoma