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Molecular subtype of breast cancer is associated with sentinel lymph node status. We sought to establish a mathematical prediction model that included breast cancer molecular subtype for risk of positive non-sentinel lymph nodes in breast cancer patients with sentinel lymph node metastasis and further validate the model in a separate validation cohort. We reviewed the clinicopathologic data of breast cancer patients with sentinel lymph node metastasis who underwent axillary lymph node dissection between June 16, 2014 and November 16, 2017 at our hospital. Sentinel lymph node biopsy was performed and patients with pathologically proven sentinel lymph node metastasis underwent axillary lymph node dissection. Independent risks for non-sentinel lymph node metastasis were assessed in a training cohort by multivariate analysis and incorporated into a mathematical prediction model. The model was further validated in a separate validation cohort, and a nomogram was developed and evaluated for diagnostic performance in predicting the risk of non-sentinel lymph node metastasis. Moreover, we assessed the performance of five different models in predicting non-sentinel lymph node metastasis in training cohort. Totally, 495 cases were eligible for the study, including 291 patients in the training cohort and 204 in the validation cohort. Non-sentinel lymph node metastasis was observed in 33.3% (97/291) patients in the training cohort. The AUC of MSKCC, Tenon, MDA, Ljubljana, and Louisville models in training cohort were 0.7613, 0.7142, 0.7076, 0.7483, and 0.671, respectively. Multivariate regression analysis indicated that tumor size (OR = 1.439; 95% CI 1.025–2.021; P = 0.036), sentinel lymph node macro-metastasis versus micro-metastasis (OR = 5.063; 95% CI 1.111–23.074; P = 0.036), the number of positive sentinel lymph nodes (OR = 2.583, 95% CI 1.714–3.892; P

// Zheng-Jun Yang 1, 2, 3, * , Yue Yu 1, 2, 3, * , Xin-Wei Hou 1, 2, 3 , Jiang-Rui Chi 1, 2, 3 , Jie Ge 1, 2, 3 , Xin Wang 1, 2, 3 , Xu-Chen Cao 1, 2, 3 1 The First Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin 300060, China 2 Key Laboratory of Cancer Prevention and Therapy, Tianjin 300060, China 3 Key Laboratory of Breast Cancer Prevention and Therapy, Tianjin Medical University, Ministry of Education, Tianjin 300060, China * These authors contributed equally to this work Correspondence to: Xu-Chen Cao, email: caoxuchen@tmu.edu.cn Keywords: breast cancer, nodal metastases, prognosis, molecular subtype Received: April 08, 2016 Accepted: December 05, 2016 Published: December 15, 2016 ABSTRACT Nodal metastases and breast cancer subtypes (BCS) are both well-recognized prognostic indicators. However, the association between nodal metastases and BCS, and the prognostic value of nodal metastases in different BCS are still remains unclear. Our aim was to investigate the association between nodal metastases and BCS, and the prognostic value of nodal metastases in the different BCS. We found that the breast cancer subtype was closely associated with the pN stage. pN stage and breast cancer subtype were significantly associated with disease-free survival. The subgroup analysis showed that the patients in higher pN stage had a poor outcome than patients in lower pN stage in each breast cancer subtype. Furthermore, when the analysis was stratified by breast cancer subtype, we found that even in the same pN stage (pN0-pN2), there was significant survival difference among patients in different BCS, and Luminal A breast cancer patients had the best survival outcome. However, there were no significant survival difference between Luminal A patients and other breast cancer subtype when patients in pN3 stage. Thus, our study suggested that both lymph node status and molecular subtype played important roles in the outcome of breast cancer patients and they cannot replace each other.

pN stage and breast cancer subtypes (BCS) are both well-recognized prognostic indicators. Our previous work has highlighted that patients even with the same pN stage exhibited a significant survival difference in different BCS. Given this achievement, we hypothesized that a statistical interaction might exist between pN stage and BCS. The aim of this retrospective cohort study was to compare the prognostic value of the combined pN stage and BCS (pNnew stage) with either pN stage or BCS alone, and to determine if this combined new stage could serve as an alternative discriminator of outcome. We combined pN stage and BCS to create a new variable named pNnew stage and then divided it into four groups: pN0new, pN1new, pN2new, and pN3new. Survival analysis was performed with the use of the Kaplan–Meier method and the log-rank test was used for univariate analysis. For multivariate analysis, cox proportional hazard models were applied, allowing for the estimation of disease-free survival (DFS). To assess discriminatory accuracy of the models, we compared the area under the receiver-operating characteristic curve (AUROC), the Akaike information criterion (AIC), and the Bayesian information criterion (BIC) values. Then, we used this pNnew stage to generate a TNnewM staging system according to the 7th AJCC staging system. A statistical interaction between pN stage and BCS was found. In multivariate survival analysis, the pNnew stage has been confirmed as an independent prognostic variable of 5-year DFS. The pNnew stage, with a smaller AIC or BIC value and larger AUROC, was a more powerful predictor of DFS than either pN stage or BCS alone. Results were validated in a separate cohort of patients. The TNnewM stage proposed in our present study was found comparable to the new 8th AJCC edition which includes anatomic T, N, and M plus tumor grade and the status of the biomarkers Her-2, ER, and PR with respect to prognostic value for breast cancer patients. The pNnew stage (combined pN stage and BCS) appears to be a more powerful predictor and discriminator for the outcome of breast cancer, as compared to pN stage or BCS alone, and the TNnewM stage may serve as a simple, easy-to-use alternative to the 8th AJCC edition staging manual.

Background Our purpose was to present a new method of endoscopic sentinel lymph node biopsy (ESLNB) and endoscopic axillary lymphadenectomy (EALND) without liposuction for treating early-stage breast cancer, and compare results with traditional open dissection. Methods The medical records of patients with early-stage breast cancer who underwent EALND/ESLNB without liposuction or traditional open dissection between March 2015 and September 2016 were retrospectively reviewed. Outcomes between the 2 groups were compared. Results A total 65 patients with a mean age of 41.2 ± 9.3 years (range, 23–60 years) were included. Thirty-three patients underwent traditional open lymph node dissection and 32 patients underwent endoscopic treatment. The 2 groups were similar with respect to age, body mass index (BMI), menopausal status, tumor location, and tumor disease stage (all, p > 0.05). The mean operating time was significantly higher in the endoscopic group (91.2 vs. 75.2 min, p = 0.022), while the mean blood loss was significantly lower (28.7 vs. 37.0 ml, p = 0.034). The mean number of SLNs harvested in the open (2.4 ± 1.6) and the endoscopic (2.3 ± 1.4) groups were not different (p = 0.829), with a sentinel lymph node retrieval rate of 80%. The mean number of axillary lymph nodes harvested in the open (13.8 ± 3.3) and the endoscopic (13.3 ± 3.1) groups were not different (p = 0.457). Scars were minimal in the endoscopic group. Conclusion ESLNB and EALND without liposuction for early-stage breast cancer is feasible, has a low complication rate, a lymph node harvest rate similar to that of open dissection, and has good cosmetic results. Future studies, however, are required to evaluate oncological outcomes.

Delta-aminolevulinate dehydratase (ALAD) catalyzes the second step in the biosynthesis of heme and is also an endogenous inhibitor of the 26S proteasome. The role of ALAD in breast cancer progression is still unclear. In this study, we found that the expression of ALAD was downregulated in breast cancer tissues compared with adjacent normal breast tissues. Enhanced ALAD expression was associated with a favorable outcome in patients with breast cancer. Overexpression of ALAD suppresses breast cancer cell proliferation and invasion and inhibits the epithelial-mesenchymal transition phenotype. Furthermore, we found that ALAD regulates transforming growth factor-β-mediated breast cancer progression. This finding suggests that ALAD might be a potential biomarker for breast cancer that suppresses breast cancer progression by regulating transforming growth factor-β-mediated epithelial-mesenchymal transition.