Predictive and Prognostic Significance of mRNA Expression and DNA Copies Aberrations of ERCC1, RRM1, TOP1, TOP2A, TUBB3, TYMS, and GSTP1 Genes in Patients with Breast Cancer

Abstract

Increasingly, many researchers are focusing on the sensitivity in breast tumors (BC) to certain chemotherapy drugs and have personalized their research based on the assessment of this sensitivity. One such personalized approach is to assess the chemotherapy’s gene expression, as well as aberrations in the number of DNA copies—deletions and amplifications with the ability to have a significant effect on the gene’s activity. Thus, the aim of this work was to study the predictive and prognostic significance of the expression and chromosomal aberrations of eight chemosensitivity genes in breast cancer patients. Material and methods. The study involved 97 patients with luminal B breast cancer IIB–IIIB stages. DNA and RNA were isolated from samples of tumor tissue before and after treatment. Microarray analysis was performed for all samples on high-density microarrays (DNA chips) of Affymetrix (USA) CytoScanTM HD Array and Clariom™ S Assay, human. Detection of expression level of seven chemosensitivity genes—RRM1, ERCC1, TOP1, TOP2a, TUBB3, TYMS, and GSTP1—was performed using PCR real-time (RT-qPCR). Results. The expression of the RRM1 (AC scheme), TOP2α, TYMS, and TUBB3 genes in patients with an objective response to treatment (complete and partial regression) is higher than in patients with stabilization and progression (p < 0.05). According to our results, the presence of a high level of GSTP1 in a tumor biopsy is associated with the low efficiency of the NAC CP scheme (p = 0.05). The presence of RRM1 deletion is associated with complete and partial regression, as for the TOP1 and TUBB3 genes (p < 0.05). Higher rates of metastatic survival are associated with a high level of expression and amplification of the GSTP1 gene (log-rank test p = 0.02 and p = 0.05). Conclusion. Thus, a complex assessment of the chemotherapy’s gene expression is important not only for understanding the heterogeneity and molecular biology of breast cancer but also to obtain a more accurate disease prognosis.