Clinicopathological correlation of PTPN3 expression in breast cancer and in silico drug screening against PTPN3 for therapeutics

Abstract

PTPN3 regulates cellular signaling and is dysregulated in cancer. There has been less research about the oncogenic impact of PTPN3 in breast cancer patients. This study analyzed PTPN3 mRNA levels and their prognostic significance in breast cancer using TCGA datasets. qRT-PCR was used to assess PTPN3 expression in formalin-fixed, paraffin-embedded Indian breast cancer patient samples (tumor-74, control-36). PTPN3 protein levels (ER-positive 15; ER-negative: 15; distant normal breast tissues: 20) were also immunohistochemically assessed using the H-score method. The biomarker potential was examined using a receiver operating characteristic (ROC) analysis. Docking and molecular dynamics (MD) simulations were used to find PTPN3 inhibitors (PDB ID: 2B49) from 892 FDA-approved natural chemicals in the ZINC database. PTPN3 mRNA and protein expression were significantly higher in breast cancers and associated with clinicopathological variables such as age, ER status, tumor stage, grade, Ki-67 index, menopause, and lymph node metastasis (p < 0.05). ROC analysis revealed an AUC of 0.7654, indicating PTPN3′s biomarker potential. Docking yielded three high-affinity inhibitors: Cyclocort (ZINC000003977777), Toposar (ZINC000003938684), and Tetracycline (ZINC000084441937), with binding energies of -9.3, -8.73, and -8.66 kcal/mol, respectively. MD simulations confirmed stable connections via hydrogen bonds and hydrophobic interactions under minimal constraints. In conclusion, PTPN3 overexpression supports its role as a prognostic biomarker, and Cyclocort, Toposar, and Tetracycline need further confirmation as potential PTPN3 inhibitors.