Успехи молекулярной онкологии (Oct 2024)

Mechanisms of drug resistance to neoadjuvant chemotherapy in breast cancer

  • K. A. Aliev,
  • E. Yu. Zyablitskaya,
  • T. P. Makalish,
  • L. E. Sorokina,
  • E. R. Asanova

DOI
https://doi.org/10.17650/2313-805X-2024-11-3-103-113
Journal volume & issue
Vol. 11, no. 3
pp. 103 – 113

Abstract

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Aim. Тo study the molecular genetic characteristics of the tumor microenvironment and the mechanisms of cell death in resistant locally advanced breast cancer.Materials and methods. The study included 48 patients with breast cancer T2–4N0–3M0–1 (mean age 55.6 ± 9.8 years), and 29 patients of comparable age with breast fibroadenoma. According to the design of the study, patients were divided into groups: Group 1 included women with breast cancer resistant to neoadjuvant chemotherapy (n = 23), Group 2 – with breast cancer and a complete response to neoadjuvant chemotherapy (n = 25), control Group – with fibroadenoma (n = 29). The expression of markers CD4+, CD8+, CD20+, CD68+, tumor necrosis factor α (TNF-α), vascular endothelial growth factor A (VEGF A), Ang-2, matrix metalloproteinase 12 (MMP-12), inducible nitric oxide synthase (iNOS), bcl-2, p53, CD95 was assessed using immunohistochemistry.Results. When phenotyping immune cells, the following differences were obtained: in the tumor tissue of patients in Group 1, a significant decrease in the number of cytotoxic CD8+ cells was noted compared to Group 2 (p = 0.001) and control (p = 0.032). In Group 2, a significant increase in the number of CD68+ cells was revealed in relation to Group 1 (p = 0.027). The cytokine profile of the tumor microenvironment in Group 1 is characterized by statistically significant overexpression of TNF-α compared to Group 2 (p >0.001) and the control Group (p = 0.01). With regard to apoptotic factors, noteworthy is the significant decrease in the expression of bcl-2 and p53 in Group 1 compared to Group 2 (p = 0.001 and p = 0.02 accordingly).Conclusion. The presented results can serve as the basis for the creation of diagnostic algorithms that have predictive value regarding the effectiveness of NCT, and also to help identify new targets to justify the use of combined breast cancer treatments in the early stage.

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