ZNF217 Gene Copy Number as a Marker of Response to Standard Therapy Drugs According to ERα Status in Breast Cancer

Abstract

Purpose The therapeutic decision for the management of breast cancer (BC) patients is based on the evaluation of prognostic factors alongside clinical and pathological parameters. Despite the use of standard biomarkers, response and resistance to therapy represent a challenge for clinicians. Among the new potential biomarkers for BC the ZNF217 gene have gained importance in recent years. However, while associations between ZNF217 gene copy number and clinicopathological characteristics have been established, its correlation with treatment response remains unclear. Patients and Methods This study aimed to evaluate the ZNF217 gene copy number and establish its associations with treatment response in estrogen receptor positive (ERα+) and ERα negative (ERα-) BC cell lines. In addition, a validation of the relationship between ZNF217 gene copy number and its prognostic value was performed using datasets of BC patients retrieved from the cBioPortal public database. Results Our data show that in ERα+ cells, ZNF217 gene copy number increase (amplification), while cell proliferation decreases in response to standard drug treatments. In contrast, both ZNF217 gene copy number (gain) and cell proliferation increases in response to standard drug treatments in ERα- cells. The results obtained align with findings from the cBioPortal database analysis, demonstrating that ERα+/HER2- low proliferation patients, exhibiting ZNF217 gene amplification or gain, have a significantly higher survival probability after treatment, compared to ERα-/HER2- and HER2+ patients. Conclusion Our results suggest that in ERα+ BC cells, ZNF217 gene amplification could be indicative of a favorable response, while in ERα- BC cells, ZNF217 gene gain could be postulated as a potential predictor of treatment resistance. A broader understanding of the role of ZNF217 gene in treatment response, together with prospective studies in BC patients, could contribute to confirming our data, as well as optimizing existing treatments and exploring novel approaches to improve overall cancer treatment outcomes.