Unveiling the Potential Role of Hesperetin and Emodin as a Combination Therapy to Inhibit the Pancreatic Cancer Progression against the C-Met Gene.

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 cytoHubbawere used to construct protein-protein interactions (PPI) network and identifying hub genes which were described as target proteins. The Protein Data Bank (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 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 IC 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.