A meta-analysis of gene expression-basedbiomarkers predicting response to paclitaxel therapy inbreast cancer

Background: Breast cancer (BC) is the most common type ofcancer in women and a major cause of cancer-related death.Paclitaxel (PTX) is a crucial component of the frontline chemotherapyregimens in patients. The development of PTX resistancefrequently impedes therapeutic management and hasa negative impact on patient outcomes. Comprehending themolecular mechanism of PTX resistance is vital to developresistance-fighting strategies. The investigations have indicateddifferentially expressed genes (DEG) and pathways in BC celllines treated with PTX compared to controls in independentstudies. We conduct a meta-analysis to merge the findings ofthese studies, deciphering the absolute effect of PTX treatmenton cancer cells.Materials and Methods: Five published microarray datasetswere included in this meta-analysis. Box-plot and PCA analyseswere used to evaluate intergroup variabilities. Five differentdatasets have been normalized and modified using batch effect removal. The GEOquery tool in Bioconductor ۳.۲ with R version۳.۲.۲ was used to analyze microarray datasets, and twowayHierarchical Clustering was employed to evaluate geneexpression data.Results: CDC۴۲, DYNC۱H۱, PIK۳R۱, ITGB۳BP, MAPK۱۳,and PXN were important differentially expressed genes in BCcell lines, according to a meta-analysis of various GEO datasets.Through functional enrichments of the PPI network, biologicalprocess, molecular function, and pathway analysis revealedtheir significant involvement of the potential genes inpurine ribonucleoside triphosphate binding, cytokine receptoractivity, the WNT pathway, the MAPK cascade, the intracellularmembrane-bounded organelle in addition to the nucleus,and signal transduction and pathway in cancer.Conclusion: Our findings concluded that PTX may significantlycontribute to chemo-resistance in BC by inducing itscommon potential targets genes that hold promise for the noveltherapeutic targets.