Axillary lymph node changes in different molecular subtypes of breast cancer

Background. The prediction of molecular subtypes based on the ultrasound (US) indicators of metastatic axillary lymph nodes in patients with BC has received particular attention in recent years. Purpose. The study aimed to establish the relationship between breast cancer subtypes and morphological characteristics of axillary lymph nodes using US examination. Materials and Methods. In this study, 184 female BC patients, aged 24–75 (53.1±0.8), who were evaluated and treated at the Oncology Clinic of Azerbaijan Medical University of the Ministry of Health of Azerbaijan, had their axillary lymph nodes checked by ultrasound (US). The immunohistological examination of tumor tissue obtained by the tru-cut biopsy method was used to determine the molecular subtypes of the tumor in patients. The US method was used in the «LOGIQ C5-Premium» (2012) device to assess the size and shape of the axillary lymph nodes. Results. In our study, we noticed that determining the tumorʼs histological subtype has clinical significance in predicting metastases to the axillary lymph nodes. ER, PR, and HER2/neu+ receptor expression in BC histology can predict axillary lymph node metastases. TNBC is more aggressive, but it has fewer metastases to the axillary lymph nodes. The HER2+ subtype, on the other hand, has a higher rate of axillary lymph node metastasis. The axillary lymph nodes are more oval and unevenly thickened in the TNBC subtype, while the axillary lymph nodes are spherical and the normal structure of the cortex is disrupted in the HER2+ subtype. Metastasis is most common in the subclavian lymph nodes in the HER2+ subtype, while it is more common in the supraclavicular lymph nodes in the luminal B/HER2+ subtype. Conclusions. Our data indicate that metastatic ALN can be distinguished by their cortical structure before biopsy. US of the сortical structure simplifies the diagnosis of tumor metastasis, is easier to perform, is less expensive and can be used when predicting metastasis.