Background:Pancreatic adenocarcinoma (PAAD) is one of the most prevalent cancers, and it has high death rates.
Only 10% of PAAD patients can survive until 5 years. Hence, the improvement of survival rate of the patients should be improved.Aim:The present study used a computational approach to identify novel biomarkers and potentially effective small drug-like
molecules in PAAD.Objective:The objective of this study was to identify the Differentially Expressed Genes (DEGs) and survival rate affecting
genes (SDEGs) to single out the specific gene responsible for pancreatic cancer and predict the efficacy of interactions with
hesperetin and emodin. Further, another objective was to validate the predicted efficacies using an MTT assay.Methods:The GEPIA2 database was used to analyze the TCGA-PAAD dataset and identify DEGs and SDEGs. Venn identified
the commonly scattered genes between the DEGs and SDEGs. Network Analyst v3.0, CytoScape v3.10.1, and cytoHubba
were used for PPI network construction and hub genes identification was described as target proteins. The PDB and PubChem
were utilized to obtain the PDB structure of the target proteins and 13 phytocompounds in SDF format. Molecular docking
studies were carried out and visualized by utilizing Autodock vina and Discovery Studio Visualizer v19.1.0.1828. The cytotoxicity
was measured in the MiaPaCa-2 cell line after being treated with hesperetin and emodin.Results:A total of 9219 Differentially Expressed Genes (DEGs) from the TCGA-PAAD dataset were identified. Among
them, 8740 and 479 genes were up and down-regulated with the statistical significance of P ≤ 0.05, respectively. Likely, 500
most survival rate affecting genes (SDEGs) in PAAD patients with a statistical significance of P ≤ 0.05 were identified. The
common 137 genes were identified between these obtained DEGs and SDEGs. The survival heat map was delineated for the
predicted 137 common genes. Ninety-six genes were identified as the most hazardous genes (highlighted in red). After that,
the network was constructed by using protein-protein interaction (PPI) for the most hazardous 96 genes. From the constructed
PPI network, the highly interacted top 10 genes were identified. The survival analysis was carried out to identify the most
hazardous genes and revealed that all the identified genes significantly reduced the survival rate of the patients affected by
PAAD. From that, high survival affecting 5 genes, such as CDK1, CENPE, NCAPG, KIF20A, and c-MET, were selected for
further analysis. The molecular docking studies were carried out for the identified top 5 genes, with the 13 phytocompounds reviewed
previously for anti-cancer activity. The molecular docking analysis revealed that the hesperetin (binding affinity (BA)
= -8.0 kcal/mol; Root mean square deviation (RMSD) = 2.012 Å) and emodin (BA = -8.6 kcal/mol; RMSD = 1.605 Å) interacted
well with the c-MET based on the number of hydrogen bonds and BA. Hence, the synergistic efficacy was validated in
the cell line MiaPaCa-2 with the hesperetin, emodin, and hesperetin: emodin in combination and obtained the IC50 values of
171.3 μM, 72.94 μM, and 92.36 μM respectively.Conclusion:The results stated that emodin significantly reduced the cell proliferation rate of the MiaPaCa-2 pancreatic cells,
and no synergistic effects were observed in this context with hesperetin. However, emodin improved the hesperetin efficacy in
pancreatic cells, indicating that structural modification through pharmacokinetics by coupling these two compounds may help
to identify novel compounds to treat pancreatic cancer in the future. However, further pancreatic cell lines, such as Panc-1, Bx-
PC-3, etc., and in vivo models that include CDX and PDX are needed to verify the combination effect of hespertin and emodin
on pancreatic cells.