New models and online calculator for predicting non-sentinel lymph node status in sentinel lymph node positive breast cancer patients

<p>Abstract</p> <p>Background</p> <p>Current practice is to perform a completion axillary lymph node dissection (ALND) for breast cancer patients with tumor-involved sentinel lymph nodes (SLNs), although fewer than half will have non-sentinel node (NSLN) metastasis. Our goal was to develop new models to quantify the risk of NSLN metastasis in SLN-positive patients and to compare predictive capabilities to another widely used model.</p> <p>Methods</p> <p>We constructed three models to predict NSLN status: recursive partitioning with receiver operating characteristic curves (RP-ROC), boosted Classification and Regression Trees (CART), and multivariate logistic regression (MLR) informed by CART. Data were compiled from a multicenter Northern California and Oregon database of 784 patients who prospectively underwent SLN biopsy and completion ALND. We compared the predictive abilities of our best model and the Memorial Sloan-Kettering Breast Cancer Nomogram (Nomogram) in our dataset and an independent dataset from Northwestern University.</p> <p>Results</p> <p>285 patients had positive SLNs, of which 213 had known angiolymphatic invasion status and 171 had complete pathologic data including hormone receptor status. 264 (93%) patients had limited SLN disease (micrometastasis, 70%, or isolated tumor cells, 23%). 101 (35%) of all SLN-positive patients had tumor-involved NSLNs. Three variables (tumor size, angiolymphatic invasion, and SLN metastasis size) predicted risk in all our models. RP-ROC and boosted CART stratified patients into four risk levels. MLR informed by CART was most accurate. Using two composite predictors calculated from three variables, MLR informed by CART was more accurate than the Nomogram computed using eight predictors. In our dataset, area under ROC curve (AUC) was 0.83/0.85 for MLR (n = 213/n = 171) and 0.77 for Nomogram (n = 171). When applied to an independent dataset (n = 77), AUC was 0.74 for our model and 0.62 for Nomogram. The composite predictors in our model were the product of angiolymphatic invasion and size of SLN metastasis, and the product of tumor size and square of SLN metastasis size.</p> <p>Conclusion</p> <p>We present a new model developed from a community-based SLN database that uses only three rather than eight variables to achieve higher accuracy than the Nomogram for predicting NSLN status in two different datasets. </p

PRC2/EED-EZH2 Complex Is Up-Regulated in Breast Cancer Lymph Node Metastasis Compared to Primary Tumor and Correlates with Tumor Proliferation <em>In Situ</em>

<div><h3>Background</h3><p>Lymph node metastasis is a key event in the progression of breast cancer. Therefore it is important to understand the underlying mechanisms which facilitate regional lymph node metastatic progression.</p> <h3>Methodology/Principal Findings</h3><p>We performed gene expression profiling of purified tumor cells from human breast tumor and lymph node metastasis. By microarray network analysis, we found an increased expression of polycomb repression complex 2 (PRC2) core subunits <em>EED</em> and <em>EZH2</em> in lymph node metastatic tumor cells over primary tumor cells which were validated through real-time PCR. Additionally, immunohistochemical (IHC) staining and quantitative image analysis of whole tissue sections showed a significant increase of EZH2 expressing tumor cells in lymph nodes over paired primary breast tumors, which strongly correlated with tumor cell proliferation <em>in situ</em>. We further explored the mechanisms of PRC2 gene up-regulation in metastatic tumor cells and found up-regulation of <em>E2F</em> genes, <em>MYC</em> targets and down-regulation of tumor suppressor gene E-cadherin targets in lymph node metastasis through GSEA analyses. Using IHC, the expression of potential EZH2 target, E-cadherin was examined in paired primary/lymph node samples and was found to be significantly decreased in lymph node metastases over paired primary tumors.</p> <h3>Conclusions/Significance</h3><p>This study identified an over expression of the epigenetic silencing complex PRC2/EED-EZH2 in breast cancer lymph node metastasis as compared to primary tumor and its positive association with tumor cell proliferation <em>in situ</em>. Concurrently, PRC2 target protein E-cadherin was significant decreased in lymph node metastases, suggesting PRC2 promotes epithelial mesenchymal transition (EMT) in lymph node metastatic process through repression of E-cadherin. These results indicate that epigenetic regulation mediated by PRC2 proteins may provide additional advantage for the outgrowth of metastatic tumor cells in lymph nodes. This opens up epigenetic drug development possibilities for the treatment and prevention of lymph node metastasis in breast cancer.</p> </div

Validation of <i>EZH2</i> and <i>EED</i> mRNA expressions by real-time PCR.

<p>White bars indicate primary tumor and the adjacent black bars indicate their matched lymph node metastasis.</p

Immunohistochemical staining and quantitative image analysis of whole tissue sections of E-cadherin protein expression.

<p>Proportion of E-cadherin expressing tumor cells in paired lymph node and primary tumor sections are presented as adjacent bars. Percentages of E-cadherin+ tumor cells among the total number of tumor cells are indicated by Y axis.</p

Genes up-regulated in lymph node metastasis compared to primary tumor.

<p>Genes up-regulated in lymph node metastasis compared to primary tumor.</p