Background
Due to a lack of early diagnosis
Conclusions
Overall, the diagnostic model built based on four significant DMRs could accurately distinguish tumor and normal tissues. The five drug candidates might be repurposed as promising therapeutics for particular PDAC patients.
Methods
We used methylation, transcriptome and CNV profiles to build a diagnostic model for PDAC. The protein expression of three model-related genes were externally validated using PDAC samples. Then, potential therapeutic drugs for PDAC were identified by interaction information related to existing drugs and genes.
Results
Four significant differentially methylated regions (DMRs) were selected from 589 common DMRs to build a high-performance diagnostic model for PDAC. Then, four hub genes, PHF12, FXYD3, PRKCB and ZNF582, were obtained. The external validation results showed that PHF12, FXYD3 and PRKCB protein expression levels were all upregulated in tumor tissues compared with adjacent normal tissues (P<0.05). Promising candidate drugs with activity against PDAC were screened and repurposed through gene expression analysis of online datasets. The five drugs, including topotecan, PD-0325901, panobinostat, paclitaxel and 17-AAG, with the highest activity among 27 PDAC cell lines were filtered. Conclusions: Overall, the diagnostic model built based on four significant DMRs could accurately distinguish tumor and normal tissues. The five drug candidates might be repurposed as promising therapeutics for particular PDAC patients.