Cytokine production was evaluated in supernatants of cultured tumor cells that were obtained by biopsy of the breast invasive ductal carcinoma (IDC) and breast fibroadenoma (FA) and grown in vitro. In the IDC supernatants, the concentrations of pro-inflammatory (pro-oncogenic) cytokines IL-17, IL-18, and IFNγ and of IL-1 receptor antagonist were significantly higher than in the FA cell supernatants. The concentrations of anti-inflammatory cytokine IL-10 and MCP-1 protein in supernatants of IDC cells were significantly lower than those determined in FA supernatants.

This study was aimed at analyzing the relations of metastasis to regional lymph nodes (RLNs) with histopathological indicators of invasive breast carcinoma of no special type (IC-NST) and its cytokine profile. Enzyme-linked immunosorbent assays were performed to determine concentrations of IL-2, IL-6, IL-8, IL-10, IL-17, IL-18, IL-1β, IL-1Ra, TNF-α, IFN-γ, G-CSF, GM-CSF, VEGF-A, and MCP-1 in the culture supernatant of IC-NST samples from 48 female patients. Histopathological indicators (degree of tumor cell differentiation, mitoses, and others) and ER, PR, Her2/neu, Ki-67, and CD34 expression levels were determined. By means of three types of neural network models, it was shown that for different parameters of the output layer, different groups of parameters are involved that have predictive value regarding metastasis to RLNs. As a result of multi-dimensional cluster analysis, three clusters were formed with different cytokines profiles of IC-NST. Different correlations between indicators of cytokine production by IC-NST and its histopathological parameters were revealed in groups with different cytokine profiles. It was shown that at simultaneous evaluation of the production of even two cytokines, the importance of which relationship with metastasis was revealed by neural network modeling, can increase the probability of determining the presence of metastasis in the RLNs.