Immune response profile of primary tumour, sentinel and non-sentinel axillary lymph nodes related to metastasis in breast cancer: an immunohistochemical point of view

2019 ◽  
Vol 152 (3) ◽  
pp. 177-193 ◽  
Author(s):  
Albert Gibert-Ramos ◽  
Carlos López ◽  
Ramon Bosch ◽  
Laia Fontoura ◽  
Gloria Bueno ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Immune Response ◽  
Lymph Nodes ◽  
Primary Tumour ◽  
Point Of View ◽  
Axillary Lymph Nodes ◽  
Axillary Lymph ◽  
Response Profile

MicroRNAs involved in immune response as prognostic markers in early and metastatic breast cancer.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e15528-e15528
Author(s):  
Chara Papadaki ◽  
Konstantina Thomopoulou ◽  
George Koronakis ◽  
Alexia A Monastirioti ◽  
Maria A. Papadaki ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Immune Response ◽  
Lymph Nodes ◽  
Immune Escape ◽  
Metastatic Breast ◽  
Axillary Lymph Nodes ◽  
Axillary Lymph ◽  
Circulating Mirnas ◽  
Early Relapse ◽  
Expression Levels

e15528 Background: MicroRNAs (miRNAs) are involved in the regulation of immune response and have an important role in immune escape. We analyzed the expression levels of plasma miR-10b, miR-126, miR-19α, miR-20α and miR-155, which regulate tumor-immune interactions and investigated their prognostic implications in patients with early (eBC) and metastatic (mBC) breast cancer. Methods: Blood samples were obtained before treatment from 140 and 64 patients with eBC and mBC, respectively. Plasma miRNA expression levels were assessed by qRT-PCR and expression was classified as high or low according to the median values. Results: A panel of four miRNAs (miR-19a, miR-20a, miR-126 and miR-155) could discriminate eBC from mBC (AUC 0.802, p < 0.001). In early disease, miR-10b (p = 0.022) and miR-155 (p = 0.005) expression was lower in relapsed (n = 46) compared to non-relapsed (n = 94) patients; miR-155 expression along with lymph node infiltration and tumor grade had increased ability to predict relapse (AUC = 0.775; p = 0.003). In addition, miR-10b (p = 0.015), miR-19a (p = 0.003), miR-20a (p = 0.012), miR-126 (p = 0.001) and miR-155 (p < 0.001) expression levels were lower in patients with early relapse (relapse at ≤2 years). MiR-155 and miR-19a had the highest performance in discriminating early relapse (AUC 0.855; p < 0.001 and AUC = 0.729; p = 0.003, respectively), whereas, combined mir-155 and miR-19a expression further increased the accuracy of prediction (AUC = 0.867; p < 0.001). In eBC, the number of infiltrated lymph nodes and low miR-10b independently predicted for shorter DFS (p = 0.001 and p = 0.03, respectively) and axillary lymph nodes for shorter OS (p = 0.003). In the triple negative subgroup, low miR-155 strongly predicted for shorter DFS (p = 0.037). In mBC, recurrent disease and low miR-10b expression independently predicted for shorter PFS (p = 0.001 and p = 0.017, respectively), whereas performance status of 2 independently predicted for shorter OS (p = 0.03). Conclusions: Deregulated expression of circulating miRNAs involved in tumor-immune interactions can discriminate disease status in BC and independently predicts for patients’ outcome in early and mBC. Our results further support the notion that circulating miRNAs represent a useful prognostic tool in patients with BC.

scholarly journals Intra-mammary lymph nodes, an overlooked breast cancer prognostic tool?

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Tarek Hashem ◽  
Ahmed Abdelmoez ◽  
Ahmed Mohamed Rozeka ◽  
Hazem Abdelazeem
Keyword(s):  
Breast Cancer ◽  
Lymph Nodes ◽  
Ductal Carcinoma ◽  
Percutaneous Biopsy ◽  
Preoperative Imaging ◽  
Axillary Lymph Nodes ◽  
Axillary Lymph ◽  
Pathological Features ◽  
Breast Cancer Patients ◽  
Surgical Data

Abstract Background Due to the high variability of incidence and prevalence of intra-mammary lymph nodes (IMLNs), they might be overlooked during clinical and radiological examinations. Properly characterizing pathological IMLNs and detecting the factors that might influence their prevalence in different stages of breast cancer might aid in proper therapeutic decision-making and could be of possible prognostic value. Methods Medical records were reviewed for all breast cancer patients treated at the National Cancer Institute of Cairo University between 2013 and 2019. Radiological, pathological, and surgical data were studied. Results Intra-mammary lymph nodes were described in the final pathology reports of 100 patients. Five cases had benign breast lesion. Three cases had phyllodes tumors and two cases had ductal carcinoma in situ (DCIS). All ten cases were excluded. The remaining 90 cases all had invasive breast cancer and were divided into two groups: one group for patients with malignant IMLNs (48) and another for patients with benign IMLNs (42). Pathological features of the malignant IMLN group included larger mean tumor size in pathology (4.7 cm), larger mean size of the IMLN in pathology (1.7 cm), higher incidence of lympho-vascular invasion (65.9%), and higher rate of extracapsular extension in axillary lymph nodes (57.4%). In addition, the pathological N stage was significantly higher in the malignant IMLN group. Conclusion Clinicians frequently overlook intra-mammary lymph nodes. More effort should be performed to detect them during preoperative imaging and during pathological processing of specimens. A suspicious IMLN should undergo a percutaneous biopsy. Malignant IMLNs are associated with advanced pathological features and should be removed during surgery.

scholarly journals Dedicated Axillary MRI-Based Radiomics Analysis for the Prediction of Axillary Lymph Node Metastasis in Breast Cancer

Cancers ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 757
Author(s):  
Sanaz Samiei ◽  
Renée W. Y. Granzier ◽  
Abdalla Ibrahim ◽  
Sergey Primakov ◽  
Marc B. I. Lobbes ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Lymph Node ◽  
Lymph Node Metastasis ◽  
Lymph Nodes ◽  
Axillary Lymph Node ◽  
Axillary Lymph Node Metastasis ◽  
Axillary Lymph Nodes ◽  
Axillary Lymph ◽  
Mr Images ◽  
Node Metastasis

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.

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