Abstract

1050 Background: Axillary lymph node dissection (ALND) may not be necessary in women with breast cancer (BC) who have micrometastasis in a sentinel lymph node (SLN), owing to the low risk of non-SLN (NSLN) involvement. In our Institute we validated and adopted the molecular diagnostic tool OSNA based on the quantitative measurement of Cytokeratin 19 (CK19) mRNA.The aims of our work in a subgroup of women with micrometastatic SLN, were: 1) to correlate the copy numbers of CK19 mRNA with the risk of additional positive NSLNs; 2) to assess the relationships between the molecular subtype classification and the probability of a positive ALND; 3) to verify whether a combination of the new above mentioned parameters is able to identify a subgroup of patients with a micrometastatic SLN and a negligible risk of positive NSLNs in whom ALND may be avoided. Methods: The SLN lysates from 709 patients were analyzed by OSNA assay. We considered only patients with a micrometastatic SLN (copy numbers between 250 and 5000/μL) and the probability of having a positive ALND was calculated by the logistic regression model. This series of BC patients were divided into four main subtypes taking in account the BC classification as defined by a combination of estrogen, progesteron receptors and HER2 status. Results: OSNA positivity for micrometastasis was reported in 91/709 cases (12,8%).The number of patients with positive ALND was 20 (22%). The statistical analyses showed that the metastatic involvement of NSLNs is associated with SLNs with a high copy numbers (>2000) of CK19 mRNA together with HER2 subtype. Otherwise none of the luminal A patients with a positive SLN but presenting a copy number <1000, had a positive NSLNs. Conclusions: We showed that biologically-driven analyses may be able to build new models with higher performance in terms of breast cancer axillary status prediction after positive SLN biopsy for micrometastasis. The copy numbers of CK19 mRNA and the molecular subtypes are more advantageous than traditional parameters because they are not pathologist-dependent and therefore they are more reliable and reproducible.

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