Pathology of primary tumors and axillary lymph nodes in British and Japanese women with breast cancer

1983 ◽  
Vol 3 (2) ◽  
pp. 165-169 ◽  
Author(s):  
G. H. Friedell ◽  
E. A. Soto ◽  
S. Kumaoka ◽  
T. Hirota ◽  
J. L. Hayward ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Lymph Nodes ◽  
Japanese Women ◽  
Axillary Lymph Nodes ◽  
Axillary Lymph ◽  
Primary Tumors

Quantitative DNA Fingerprinting May Distinguish New Primary Breast Cancer From Disease Recurrence

2004 ◽  
Vol 22 (10) ◽  
pp. 1830-1838 ◽  
Author(s):  
Benjamin L. Schlechter ◽  
Qiong Yang ◽  
Pamela S. Larson ◽  
Arina Golubeva ◽  
Rita A. Blanchard ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Lymph Nodes ◽  
Dna Fingerprinting ◽  
Clinical Diagnosis ◽  
Breast Tumor ◽  
Primary Breast Cancer ◽  
Axillary Lymph Nodes ◽  
Second Primary ◽  
Axillary Lymph ◽  
Primary Tumors

Purpose Approximately 10% of women with breast cancer develop a second breast tumor, either a new primary or a recurrence. Differentiating between these entities using standard clinical and pathologic criteria remains challenging. Ambiguous cases arise, and misclassifications may occur. We investigated whether quantitative DNA fingerprinting, based on allele imbalance (AI) or loss of heterozygosity (LOH), could evaluate clonality and distinguish second primary breast cancer from recurrence. Methods We developed a scoring system based on the AI/LOH fingerprints of 20 independent breast tumors and generated a decision rule to classify any breast tumor pair as related or unrelated. We validated this approach on eight related tumors (cancers and synchronous positive lymph nodes). Finally, we analyzed paired tumors from 13 women (bilateral cancers, primary tumors and contralateral positive axillary lymph nodes, or two ipsilateral tumors). Each pair's genetic classification was compared with their clinical diagnosis and outcome. Results Each independent cancer had a unique fingerprint. Every tumor pair's relationship was quantifiable. Six of eight related tumor pairs were genetically classified correctly, two were indeterminate, and none were misclassified. Among the 13 women with two cancers, four of five clinically indeterminate pairs could be classified genetically. In three of 13 women, the pair's classification contradicted the clinical diagnosis. These women had bilateral cancers genetically classified as related and disease progression. This challenges the paradigm that bilateral cancers represent independent tumors. Overall, women with tumors genetically classified as related had poorer outcomes. Conclusion Quantitative AI/LOH fingerprinting is a potentially valuable tool to improve diagnosis and optimize treatment for the growing number of second breast malignancies.

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.

scholarly journals Systemic immune reaction in axillary lymph nodes adds to tumor-infiltrating lymphocytes in triple-negative breast cancer prognostication

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Fangfang Liu ◽  
Thomas Hardiman ◽  
Kailiang Wu ◽  
Jelmar Quist ◽  
Patrycja Gazinska ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Immune Responses ◽  
Lymph Nodes ◽  
Triple Negative ◽  
Tumor Infiltrating Lymphocytes ◽  
Axillary Lymph Nodes ◽  
Axillary Lymph ◽  
Her2 Positive ◽  
Local Immunity ◽  
Infiltrating Lymphocytes

AbstractThe level of stromal tumor-infiltrating lymphocytes (sTILs) in triple-negative (TNBC) and HER2-positive breast cancers convey prognostic information. The importance of systemic immunity to local immunity is unknown in breast cancer. We previously demonstrated that histological alterations in axillary lymph nodes (LNs) carry clinical relevance. Here, we capture local immune responses by scoring TILs at the primary tumor and systemic immune responses by recording the formation of secondary follicles, also known as germinal centers, in 2,857 cancer-free and involved axillary LNs on haematoxylin and eosin (H&E) stained sections from a retrospective cohort of 161 LN-positive triple-negative and HER2-positive breast cancer patients. Our data demonstrate that the number of germinal center formations across all cancer-free LNs, similar to high levels of TILs, is associated with a good prognosis in low TILs TNBC. This highlights the importance of assessing both primary and LN immune responses for prognostication and for future breast cancer research.

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