Unveiling Potential Therapeutic Targets for Breast Cancer Recurrence: Differentially Expressed Genes and Pathways in Post-Surgery Patients

Abstract

Various intrinsic and extrinsic factors, including genetic changes and environmental factors, have been reported to contribute to tumor recurrence. However, insufficient information about the significantly dysregulated genes and pathways responsible for cancer recurrence, even after surgical removal of tumors and chemotherapy. The aim of this research is to find out the fundamental genes linked with progression of cancer that may play a critical role in breast cancer recurrence. To achieve this, a microarray dataset of Affymetrix Human Genome U133 Plus 2.0 Array platform was used to identify downregulated and upregulated genes that associated with tumor recurrence in post-surgery patients. The study includes 20 specimen, 10 samples extracted at the time of diagnosis and 10 samples taken 30 minutes post-surgery and chemotherapy. Genes that stand out from the rest in their level of expression were further subjected to subsequent functional enrichment analysis and hub genes identification to pinpoint the key genes associated with recurrence. Results revealed that significantly overexpressed genes were found to be enriched in cancer progression-associated signaling pathways, for example, Wnt pathway and proteoglycans in cancer. Moreover, the identified key hub genes (COL1A1, IGF1, COL1A2, DCN, LUM, MMP2, JUN, CXCL12, THBS2, and LOX) majorly found to play a role in gene expression regulation, dysregulated immune system, epithelial-to-mesenchymal transition, and extracellular matrix remodeling thus promoting the development of cancer and increasing the chances of recurrence after surgery and chemotherapy. The findings have uncovered key therapeutic targets associated with tumor recurrence through potential ECM-related genes whose overexpression may significantly contribute to tumorigenesis in breast cancer survivors by epithelial-to-mesenchymal transition and targeting them may improve the chances of better survival breast cancer patients and increase the quality of life by reducing the chances of recurrence. However, the study is solely bioinformatics-based; therefore, future study will be experimental validations to bring forth these key genes as potential therapeutic targets.