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A subset of nondescript axillary lymph node inclusions have the immunophenotype of endosalpingiosis.

ABSTRACT: We report 2 cases of bland, otherwise nondescript axillary lymph node inclusions that have the immunophenotype of endosalpingiosis in patients with concurrent invasive breast carcinomas. Neither inclusion demonstrated the classic morphology of endosalpingiosis with admixed ciliated and secretory cells. Rather, both cases were composed of nondescript cuboidal to columnar bland epithelial cells situated within the lymph node capsule. Whereas both inclusions labeled diffusely for estrogen receptor and lacked evidence of a myoepithelial component, both labeled diffusely for PAX8 and WT-1, which distinguished them from their corresponding concurrent primary mammary carcinomas. These findings suggest that a subset of otherwise nondescript axillary lymph node inclusions represent endosalpingiosis and highlight the utility of PAX8 and WT-1 immunohistochemistry in distinguishing these from metastatic well-differentiated ductal carcinoma.

SUBMITTER: Carney E

PROVIDER: S-EPMC4370106 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature

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A subset of nondescript axillary lymph node inclusions have the immunophenotype of endosalpingiosis.

Carney Erin E Cimino-Mathews Ashley A Argani Cynthia C Kronz Joseph J Vang Russell R Argani Pedram P

The American journal of surgical pathology 20141201 12

We report 2 cases of bland, otherwise nondescript axillary lymph node inclusions that have the immunophenotype of endosalpingiosis in patients with concurrent invasive breast carcinomas. Neither inclusion demonstrated the classic morphology of endosalpingiosis with admixed ciliated and secretory cells. Rather, both cases were composed of nondescript cuboidal to columnar bland epithelial cells situated within the lymph node capsule. Whereas both inclusions labeled diffusely for estrogen receptor ...[more]

PMID: 24921637

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Project description:PurposeSentinel lymph node biopsy (SLNB) alone following neoadjuvant chemotherapy (NAC) remains controversial in patients with breast cancer who are initially lymph node-positive. The present study aimed to evaluate the impact of SLNB and axillary lymph node dissection (ALND) on breast cancer recurrence and survival in patients who converted from lymph node-positive to pathological node-negative (ypN0) after NAC.MethodsThis single-center retrospective study included 223 patients who converted to axillary lymph node-negative status after NAC and underwent breast and axillary surgery between January 2006 and December 2015. This study compared the overall survival (OS), disease-free survival (DFS), ipsilateral axillary lymph node recurrence rates and incidence of postoperative complications, especially, arm lymphedema and shoulder stiffness between SLNB and ALND.ResultsThis study included 223 patients with axillary pathological complete response (pCR) after NAC and surgery. The SLNB and ALND groups included 94 and 129 patients, respectively. The median follow-up time was 57 (range, 6-155) in the SLNB group and 99 (range 2-159) months in the ALND group. The corresponding 5-year OS and DFS rates were 96.3% and 94.2% (p = 0.392), and 89.2% and 86.4% (p = 0.671), respectively. Four patients (4.3%) in the SLNB group and nine (7.0%) in the ALND group developed locoregional recurrences. Ipsilateral axillary lymph node recurrence and distant metastasis were observed in one (1.1%) and three (2.3%) patients, and in 10 (10.6%) and 11 (8.5%) patients, respectively. Patients in the ALND group were more likely than their SLNB counterparts to experience complications, such as shoulder stiffness (9 [7.0%] vs. 4 [4.3%] patients, p = 0.57). The rate of lymphedema in the ALND group was three times that in the SLNB group (35 [27.1%] vs. 8 [8.5%] patients, p < 0.001).ConclusionAs an alternative to ALND, SLNB has oncological safety in patients with axillary pathological complete response after NAC.

Project description:Radiomics features may contribute to increased diagnostic performance of MRI in the prediction of axillary lymph node metastasis. The objective of the study was to predict preoperative axillary lymph node metastasis in breast cancer using clinical models and radiomics models based on T2-weighted (T2W) dedicated axillary MRI features with node-by-node analysis. From August 2012 until October 2014, all women who had undergone dedicated axillary 3.0T T2W MRI, followed by axillary surgery, were retrospectively identified, and available clinical data were collected. All axillary lymph nodes were manually delineated on the T2W MR images, and quantitative radiomics features were extracted from the delineated regions. Data were partitioned patient-wise to train 100 models using different splits for the training and validation cohorts to account for multiple lymph nodes per patient and class imbalance. Features were selected in the training cohorts using recursive feature elimination with repeated 5-fold cross-validation, followed by the development of random forest models. The performance of the models was assessed using the area under the curve (AUC). A total of 75 women (median age, 61 years; interquartile range, 51-68 years) with 511 axillary lymph nodes were included. On final pathology, 36 (7%) of the lymph nodes had metastasis. A total of 105 original radiomics features were extracted from the T2W MR images. Each cohort split resulted in a different number of lymph nodes in the training cohorts and a different set of selected features. Performance of the 100 clinical and radiomics models showed a wide range of AUC values between 0.41-0.74 and 0.48-0.89 in the training cohorts, respectively, and between 0.30-0.98 and 0.37-0.99 in the validation cohorts, respectively. With these results, it was not possible to obtain a final prediction model. Clinical characteristics and dedicated axillary MRI-based radiomics with node-by-node analysis did not contribute to the prediction of axillary lymph node metastasis in breast cancer based on data where variations in acquisition and reconstruction parameters were not addressed.

Project description:Whether the expression status of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER-2) receptor and Ki-67 show concordance between the primary tumors and the synchronous axillary lymph node (ALN) metastases has been discussed in numerous studies. However, to date, the results of these studies remain controversial. Therefore, the present study aimed to investigate whether the expression of ER, PR, HER-2 and Ki-67 was in concordance between the primary tumors and synchronous ALN metastases in patients with operable breast cancer (BC). A total of 60 tissue samples were collected from patients with primary operable BC diagnosed with primary tumors and synchronous ALN metastases. The expression levels of the four biomarkers, ER, PR, HER-2 and Ki-67, were assessed in primary lesions and synchronous ALN metastases samples using immunohistochemistry. The cut-off values were set to 10% for ER and PR, while the labeling index of Ki-67 was set to 14%. The immunostaining intensity of ER and PR was scored as negative (?), 1+, 2+ and 3+. The criteria for HER-2 testing in BC were implemented according to the American Society of Clinical Oncology (ASCO) and the College of American Pathologists (CAP) guidelines. The concordance rates for ER, PR and HER-2 were 96.7 (58/60), 96.7 (58/60) and 90% (54/60), respectively. In addition, the kappa values of consistency in the primary lesions and the synchronous ALN metastases were 0.773 for ER, 0.654 for PR and 0.785 for HER-2. Furthermore, the P-values of ER, PR and Ki-67 numerical variables between the two groups were 0.393, 0.400 and 0.331, respectively, as demonstrated using a non-parametric Wilcoxon signed rank test. The findings of the present study demonstrated a high degree of concordance between the expression of ER, PR, HER-2 and Ki-67 in the primary tumors and that in the synchronous ALN metastases, suggesting that the BC primary tumor biomarkers may be used for the prognosis of synchronous ALN metastases in patients with operable BC.

Project description:PurposeTo develop a clinical-radiomics model based on radiomics features extracted from MRI and clinicopathologic factors for predicting the axillary pathologic complete response (apCR) in breast cancer (BC) patients with axillary lymph node (ALN) metastases.Materials and methodsThe MR images and clinicopathologic data of 248 eligible invasive BC patients at the Peking University First Hospital from January 2013 to December 2020 were included in this study. All patients received neoadjuvant chemotherapy (NAC), and the presence of ALN metastases was confirmed through cytology pre-NAC. The data from January 2013 to December 2018 were randomly divided into the training and validation sets in a ratio of 7:3, and the data from January 2019 to December 2020 served as the independent testing set. The following three types of prediction models were investigated in this study. 1) A clinical model: the model was built by independently predicting clinicopathologic factors through logistic regression. 2) Radiomics models: we used an automatic segmentation model based on deep learning to segment the axillary areas, visible ALNs, and breast tumors on post-NAC dynamic contrast-enhanced MRI. Radiomics features were then extracted from the region of interest (ROI). Radiomics models were built based on different ROIs or their combination. 3) A clinical-radiomics model: it was built by integrating radiomics signature and independent predictive clinical factors by logistic regression. All models were assessed using a receiver operating characteristic curve analysis and by calculating the area under the curve (AUC).ResultsThe clinical model yielded AUC values of 0.759, 0.787, and 0.771 in the training, validation, and testing sets, respectively. The radiomics model based on the combination of MRI features of breast tumors and visible ALNs yielded the best AUC values of 0.894, 0.811, and 0.806 in the training, validation, and testing sets, respectively. The clinical-radiomics model yielded AUC values of 0.924, 0.851, and 0.878 in the training, validation, and testing sets, respectively, for predicting apCR.ConclusionWe developed a clinical-radiomics model by integrating radiomics signature and clinical factors to predict apCR in BC patients with ALN metastases post-NAC. It may help the clinicians to screen out apCR patients to avoid lymph node dissection.

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A subset of nondescript axillary lymph node inclusions have the immunophenotype of endosalpingiosis.

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A subset of nondescript axillary lymph node inclusions have the immunophenotype of endosalpingiosis.

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