Medicine Science (Mar 2023)
Comparison of lymph node metastasis rates in breast cancer molecular subtypes; A retrospective clinical study
Abstract
Breast cancer is the most common cancer in women. Axillary lymph node metastasis in breast cancer is the most important determinant of long-term prognosis, but isn't an independent risk factor for overall survival. Invasive breast cancer is divided into molecular subtypes according to the presence of estrogen, progesterone and Her2 receptors: these subtypes can guide systemic therapy. Our aim in the study is to compare the axillary lymph node metastasis rates statistically in breast cancer subtypes. Patients treated for breast cancer were retrospectively evaluated in Group1(LuminalA-likeERand/orPR+,Her2 -), Group2 (LuminalB-likeER and/or PR+,Her2-), Group3 (Her2+,ER and/or PR+), Group4 (Her2+,ER and/or PR-) and Group5 (Her2-,ER and PR-) analyzed for tumor type, pathological stage, lymph node metastasis.208 patients were included in the study, and the mean age of the patients was 57.3±12.8. Although the age distribution of the groups was similar, no significant difference was found between the groups in terms of menopausal status. While the lymph node distribution was highly proliferative in Group 2. Demonstrating metastasis organotropisms in the effect of molecular subtypes of breast cancer is necessary to understand tumor mechanisms. ER and PR positive tumors usually metastasize to bones, while Her2+ or triple-negative breast cancers usually tend to metastasize to the visceral system, including the central nervous system. As with distant metastasis habits, lymph node metastasis rates of molecular subtypes of breast cancer can also vary. Being aware of these metastasis possibilities is also helpful in understanding the clinical behavior of the disease. It is important to know the molecular subtypes and susceptibility of lymphatic metastases as well as trying to avoid unnecessary complications of axillary dissection using the sentinel lymph node sampling technique. [Med-Science 2023; 12(1.000): 52-7]
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