Axillary metastasis in clinically node-negative breast cancer

Investigating the role of tumour-to-skin proximity in predicting nodal metastasis in breast cancer

BACKGROUND

Understanding the factors influencing nodal status in breast cancer is vital for axillary staging, therapy, and patient survival. The nodal stage remains a crucial factor in prognostication indices. This study investigates the relationship between tumour-to-skin distance (in T1-T3 tumours where the skin is not clinically involved) and the risk of nodal metastasis.

METHODS

We retrospectively reviewed data from 100 patients who underwent neoadjuvant chemotherapy (NACT). Besides patient demographics and tumour variables, a radiologist retrospectively reviewed pre-operative MRI to measure tumour-to-skin distance. R core packages were used for univariate (χ2 and T-Wilcoxon tests) and bivariate logistic regression statistical analysis.

RESULTS

Of 95 analysable datasets, patients' median age was 51 years (IQR: 42-61), 97% were symptomatic (rest screen detected), and the median tumour size was 43 mm (IQR, 26-52). On multivariate analysis, increasing invasive tumour size (p = 0.02), ER positivity (p = 0.007) and shorter tumour-to-skin distance (p = 0.05) correlated with nodal metastasis.  HER2 was not included in multivariate analysis as there was no association with nodal status on univariate analysis. In node-positive tumours, as tumour size increased, the tumour-to-skin distance decreased (r = - 0.34, p = 0.026). In node-negative tumours, there was no correlation (r = + 0.18, p = 0.23).

CONCLUSION

This study shows that non-locally advanced cancers closer to the skin (and consequent proximity to subdermal lymphatics) are associated with a greater risk of nodal metastasis. Pre-operative identification of those more likely to be node positive may suggest the need for a second-look USS since a higher nodal stage may lead to a change in therapeutic strategies, such as upfront systemic therapy, node marking, and axillary clearance without the need to return to theatre following sentinel node biopsy.

Study on the Relationship Between Differentially Expressed Proteins in Breast Cancer and Lymph Node Metastasis

INTRODUCTION

Lymph node metastasis is a cause of poor prognosis in breast cancer. Mass spectrometry-based proteomics aims to map the protein landscapes of biological samples and profile tumors more comprehensively. Here, proteomics was employed to identify differentially expressed proteins (DEPs) that were associated with lymph node metastasis.

METHODS

Tandem mass tag (TMT) quantitative proteomic approaches were applied for extensive profiling of conditioned medium of MDA-MB-231 and MCF7 cell lines and serums of patients who did or did not have lymph node metastasis, and DEPs were analyzed by bioinformatics. Furthermore, potential secreted or membrane proteins MUC5AC, ITGB4, CTGF, EphA2, S100A4, PRDX2, and PRDX6 were selected for verification in 114 tissue microarray samples of breast cancer using the immunohistochemical method. The relevant data was analyzed and processed by independent sample t test, chi-square test, or Fisher's exact test using SPSS 22.0 software.

RESULTS

In the conditioned medium of MDA-MB-231 cell lines, 154 proteins were upregulated, while 136 were downregulated compared to those of MCF7. In the serum of patients with breast cancer and lymph node metastasis, 17 proteins were upregulated, and 5 proteins were downregulated compared to those without lymph node metastasis. Furthermore, according to tissue verification, CTGF, EphA2, S100A4, and PRDX2 were associated with breast cancer lymph node metastasis.

CONCLUSION

Our study provides a new perspective for the understanding of the role of DEPs (especially CTGF, EphA2, S100A4, and PRDX2) in the development and metastasis of breast cancer. They could become potential diagnostic and prognostic biomarkers and therapeutic targets.

Nomogram Based on Breast MRI and Clinicopathologic Features for Predicting Axillary Lymph Node Metastasis in Patients with Early-Stage Invasive Breast Cancer: A Retrospective Study

INTRODUCTION

To establish a nomogram for predicting axillary lymph node (ALN) involvement in patients with early-stage invasive breast cancer (BC) based on magnetic resonance imaging (MRI) features and clinicopathological characteristics.

MATERIALS AND METHODS

Patients with confirmed early-stage invasive BC between 03/2016 and 05/2017 were retrospectively reviewed at the National Cancer Center/Cancer Hospital. Risk factors for ALN metastasis (ALNM) were identified by univariable and multivariable logistic regression analysis. The independent risk factors were used to create a nomogram.

RESULTS

This study included 214 early-stage invasive BC patients, including 57 (26.6%) with positive ALNs. Tumor location (OR = 4.019, 95% CI: 1.304 -12.383, P = .015), tumor size (OR = 3.702, 95%CI: 1.517 -9.034, P = .004), multifocality (OR = 3.534, 95%CI: 1.249 -9.995, P = .017), MR-reported suspicious ALN (OR = 9.829, 95%CI: 4.132 -23.384, P <0.001), apparent diffusion coefficient (ADC) value (OR = 0.367, 95%CI: 0.158 -0.852, P = .020), and lymphovascular invasion (LVI) (OR = 3.530, 95%CI: 1.483 -8.400, P = .004) were identified as independent risk factors associated with ALNM. A nomogram was created for predicting the probability of ALNM by using these risk factors. The calibration curve of the nomogram showed that the nomogram predictions are consistent with the actual ALNM rate. The area under the curve was 0.88 (95% CI: 0.83 -0.93). The nomogram had a bootstrapped-concordance index of 0.88 and was well-calibrated.

CONCLUSION

The nomogram based on MRI and clinicopathologic features might be a useful tool for predicting ALNM in early-stage invasive BC and could help clinical decision-making.

Predictors of non-sentinel lymph node metastasis in clinical early stage (cT1-2N0) breast cancer patients with 1-2 metastatic sentinel lymph nodes

OBJECTIVE

The purpose of this study was to determine the risk factors that caused non-sentinel lymph nodes (nonSLNs) metastasis by considering the clinicopathological characteristics of patients who have 1-2 sentinel lymph node (SLN) metastasis in the clinical early stage (T1-2, N0) breast cancer.

METHODS

The demographic and clinicopathological characteristics of the patients were recorded retrospectively. Among these, age, size of the primary breast tumor, tumor localization and multifocality/multicentricity status, preoperative serum Neutrophil/Lymphocyte rate (NLR), c-erbB2/HER2-neu status, Estrogen Receptor (ER) and Progesterone Receptor (PR) status, primary tumor proliferation index (Ki-67), histopathological grade, molecular subtypes, histopathological subtypes, nipple/areola infiltration, Lymphatic Invasion (LI), Vascular Invasion (VI), Perineural Invasion (PNI), number of metastatic SLN m(SLN), mSLN diameter, SLN Extranodal Extension (ENE) status, and number of metastatic nonSLNs were recorded.

RESULTS

According to the univariate analysis, the HER2 positivity, Ki-67≥%20, mSLN diameter, LI, VI, PNI, ENE and molecular subtypes were found to be significant. However, the age, tumor localization, multifocality/multicentricity, T stage, ER and PR status, tumor size, histopathological grade and subtypes, nipple/areola infiltration and NLR were not found to be significant. In the multivariate analysis, significant independent predictors in nonSLN metastasis development were found to be HER2 positivity, PNI, mSLN diameter ≥10,5 mm and ENE.

CONCLUSION

The HER2 positivity, ENE, PNI and mSLN diameter ≥10,5 mm were found to be very strong predictors in nonSLN metastasis development. The findings of this study have the potential to be a guideline for surgeons and oncologists when determining their patients' treatment plan. These components are candidates for inclusion among the clinicopathological factors that may be used in the new nomograms due to their higher sensitivity and specificity.