Identification of diagnostic markers of pancreatic ductal adenocarcinoma using transcriptomic tumour and blood sample data

• Published in: Clinical and translational discovery Vol. 3; no. 5
• Main Authors: Sionakidis, Aristeidis, Lalagkas, Panagiotis Nikolaos, Malousi, Andigoni, Vizirianakis, Ioannis S.
• Format: Journal Article
• Language: English
• Published: Birtinya John Wiley & Sons, Inc 01.10.2023; Wiley
• Subjects: Biomarkers; Biopsy; diagnosis; Gene expression; Medical research; microRNA; MicroRNAs; Pancreatic cancer; Pancreatitis; PDAC; pharmacogenomics; precision medicine; Proteins; Standard scores; Tumors
• ISSN: 2768-0622; 2768-0622
• DOI: 10.1002/ctd2.248

Background Pancreatic ductal adenocarcinoma (PDAC) is the most frequently diagnosed form of pancreatic cancer worldwide. PDAC is associated with a poor survival rate mainly due to the disease being usually diagnosed at late stages. Methods Publicly available gene expression data from 10 studies with tumour tissue (448 samples) and/or blood samples (128 samples) from PDAC patients were pooled together and analyzed for the identification of stage‐specific and global diagnostic markers using differential gene expression analysis. The list of statistically significant (padj<0.05${p_{adj}}\; < \;0.05$) differentially expressed genes were used to carry out enrichment analysis via active subnetworks and miRNA enrichment analysis. We then used the results from these analyses to identify the most significant genes and pathways and map these to marketed drugs’ pharmacological targets. The same process was replicated for studies with blood samples and results were compared to those from the tissue analysis. A set of consistently deregulated genes (pancreatic tumour signature, PTS) in both tissue and blood samples was derived and validated in external cohorts and The Cancer Genome Atlas (TCGA) data. Results Notable gene expression deregulation was found in all tumour stages with significant overlap. We identified 820 consistently deregulated genes (PTS) in tissue samples of all stages and blood samples. Active subnetwork analysis revealed enriched ribosome, proteasome, adherens junction and cell cycle pathways across all stages and blood samples. Our findings suggest that microRNA (miRNA) contribution to PDAC pathology plays a significant role and is probably mediated by distinct miRNAs across stages of PDAC. Stage‐specific enriched miRNAs with diagnostic potential included miR‐21, miR‐29, miR‐124 and miR‐30, for stages 1–4, respectively. By investigating the pharmacogenetic interactions of the identified targets with clinically approved drugs, we outline potential paths for personalized interventions. Importantly, the PTS showed a significant association with survival in TCGA data. Conclusion Thus, we present a compilation of protein‐coding markers and miRNAs that hold potential as a diagnostic tool for the early detection of PDAC, as well as for designing novel therapeutic strategies aimed at improving patient outcomes. In this study, we pool publicly available gene expression data from clinical samples (tissue biopsies and blood samples) and derive and validate a signature of consistently deregulated genes across pancreatic ductal adenocarcinoma (PDAC) samples. We identify molecular processes which are aberrated in PDAC and investigate microRNA involvement in pathology and progression. Finally, we harness documented pharmacogenomic interactions and results from our analysis to propose potential pharmacological interventions.