Axillary Lymph Node Metastasis Research Articles

Predictive value of 18F-fluorodeoxyglucose uptake for axillary lymph node metastasis in operable breast cancer: impact of molecular subtypes.

To evaluate the predictive value of standardized uptake value (SUV) in both primary tumors and axillary lymph nodes (ALNs) using FDG PET/CT for lymph node metastasis in breast cancer patients, and to assess the influence of molecular subtypes on this predictive performance. This retrospective study included 287 patients with invasive ductal carcinoma (IDC) who underwent FDG PET/CT prior to surgery between September 2016 and December 2019. The maximum standardized uptake value (SUVmax)of primary tumors (SUV-B) and ALNs (SUV-LN) were analyzed. Molecular subtypes were classified as hormone receptor-positive, HER2-positive, and triple-negative breast cancer (TNBC). Receiver operating characteristic (ROC) curve analysis was performed to assess and compare the diagnostic performance of SUV-B and SUV-LN for predicting ALN metastasis. Among the 287 patients, 62 (21.6%) had confirmed ALN metastasis. The median SUV-LN was significantly higher in patients with metastasis compared to those without metastasis(1.5 vs. 0.9; P < 0.001). SUV-LN demonstrated good discriminative performance for ALN metastasis (AUC: 0.796), whereas SUV-B did not show significant predictive value (AUC: 0.536). The SUV_LN demonstrated significantly lower predictive performance for ALN metastasis in the hormone-positive group (AUC: 0.796) compared to the excellent discriminative performance in the HER2-positive (AUC: 0.923, P = 0.018) and TNBC (AUC: 0.940, P = 0.004) groups. Hormone receptor-positive tumors also exhibited lower FDG uptake in metastatic lymph nodes compared to HER2-positive and TNBC subtypes (P = 0.031). FDG PET/CT SUV-LN effectively predicts ALN metastasis in HER2-positive and TNBC subtypes. Hormone receptor-positive breast cancers show lower FDG uptake in metastatic ALNs, reducing diagnostic accuracy. This finding may aid in selecting the most appropriate diagnostic modality based on tumor characteristics in the era of personalized medicine.

Comparative Analysis of Nomogram and Machine Learning Models for Predicting Axillary Lymph Node Metastasis in Early-Stage Breast Cancer: A Study on Clinically and Ultrasound-Negative Axillary Cases Across Two Centers

ObjectiveEarly and accurate prediction of axillary lymph node metastasis (ALNM) is crucial in determining appropriate treatment strategies for patients with early-stage breast cancer. The aim of this study was to evaluate the efficacy of radiomic features extracted from ultrasound (US) images combined with machine learning (ML) methods in predicting ALNM to improve diagnostic accuracy and patient prognosis. MethodsIn this retrospective study, data of 282 early-stage breast cancer patients from two centers were analyzed. We considered clinicopathological characteristics, conventional US features, contrast-enhanced ultrasound (CEUS) characteristics, and radiomics features. Radiomics features were extracted from US images, and using least absolute shrinkage and selection operator (LASSO) regression, 12 key features were selected to compute a Radiomics score (Rad-score). A nomogram was developed based on these features, alongside five ML models: Logistic Regression (LR), Naive Bayes (NB), Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Extreme Gradient Boosting (XGBoost). Model performance was evaluated using metrics such as the area under the curve (AUC), accuracy (ACC), sensitivity (SEN), specificity (SPE), negative predictive value (NPV), and positive predictive value (PPV). ResultsBoth the nomogram and ML models, including the Rad-score combined with histologic type, significantly predicted ALNM. Among all models, the XGBoost model showed the best performance with an AUC of 0.810 and an accuracy of 84.1% in the external test set, surpassing the nomogram and other ML models. SHapley Additive exPlanations (SHAP) analysis further provided insights into the influence of individual radiomics features on ALNM prediction. ConclusionsWhile the nomogram provides a useful traditional statistical approach, integrating radiomics features with ML, particularly the XGBoost model enhanced by SHAP interpretability, offers superior predictive accuracy for ALNM in early-stage breast cancer patients.

Expression of the Hopeful Therapeutic Target CD15 in Women with Breast Cancer

Background: CD15 is emerging as a recent prognostic marker with potential as a future therapeutic target in human malignancies. Its biological role in human cancer involves facilitating tumor cell adhesion through interaction with E-, L-, and P-selectins. This interaction allows adhesion to endothelial cells, enhancing metastatic potential. Objective: to study CD15 expression and its relationship to some pathologic parameters to provide the first Iraqi data-driven analysis of this growing concept in women with breast cancer. Subjects and Methods: A retrospective study was carried out utilizing tissue samples obtained from 85 patients with invasive breast cancer. Materials included one formalin-fixed paraffin-embedded tissue block, one hematoxylin and eosin-stained histological section, and two immunohistochemical-stained ER and HER2/NEU sections for each patient. The samples were obtained through core needle biopsy under ultrasound guidance. Data review and immunohistochemical staining with CD15 were conducted, followed by statistical analysis using the chi-square test to explore correlations. Results: CD15 expression was observed in 55% of breast cancer samples. There was a highly significant statistical relationship between CD15 expression and the presence of axillary lymph node metastasis (proven by fine needle aspiration cytology). However, there was no significant statistical relationship between CD15 expression and the histological grade, ER receptor, HER2-NEU status, and tissue calcification. Conclusion: CD15 expression was detected in breast cancer cells, with a highly significant association observed between CD15 expression and axillary lymph node metastasis at presentation. CD15 could serve as a prognostic marker as association with axillary lymph nodes reflects negative impact on prognosis and at the same time a promising therapeutic target for patients with breast cancer as blockage of CD15 antigen’s function will result in reduction of the metastatic potential and it could be an immunotherapeutic target.

Post-biopsy to Surgery Interval Tends to Increase Axillary Nodal Metastasis, Especially in Early Breast Cancer Patients

Objective: Delays between diagnosis and breast cancer surgery may raise concerns about tumor progression. Tumors of the same size should exhibit same proportions of N staging. We aimed to evaluate the impact of time to surgery (TTS) on the proportion of metastatic axillary lymph nodes (N-Staging), controlled by tumor size. Materials and Methods: A cross-sectional study of primary breast cancer patients treated between October 2021 - December 2022 at the Division of Head Neck and Breast Surgery, Siriraj Hospital, Thailand examined the association between lymph node staging and TTS, stratified by primary tumor size. Patients with neoadjuvant therapy, DCIS, or underwent excisional biopsy were excluded. Results: Of 424 patients, mean age 60.95 years, had an average tumor size 17±13.38 mm, and 20.8% LNs metastasis. The mean TTS was 7 ± 3.11 weeks. The proportion of + LNs patients stratified by tumor size was 10.6% for T1, 34.56% for T2, and 43.75% for T3 lesions. There was no significant difference between TTS and the proportion ofN-staging for all T2 and T3 tumors. In contrast, a significant finding was observed among T1 tumors. Axillary nodal metastasis became more advanced as TTS increased (p-value = 0.022); and increased N2 and N3 nodal staging was noted in patients with delayed surgery. No significant additional differences were found concerning breast cancer subtype, pathological grading, or lympho-vascular/perineural invasion. Conclusion: Increasing TTS was significantly associated with more advanced N staging. This finding highlights the need for timely intervention in early breast cancer, particularly in T1 tumors.

Triple Negative Breast Cancer: Experience From A Tertiary Care Institute In Kannur

Aims &amp; Objectives The incidence of breast cancer in Kerala is on the rise, and it is now the commonest cancer affecting women in the state. The present study was designed to investigate the prevalence of triple negative breast cancer (TNBC) in our population and also to compare the various clinicopathological characteristics of TNBC with non-TNBC in these patients. Methods A cross sectional study was conducted among 221cases of female breast cancer who reported to the Department of General surgery, Government Medical College, Kannur from 1st October 2020 to 31st September 2022 Results The mean age at presentation was 52 years (range 26-82 years). The prevalence of triple negative breast cancer was 19.9% . Most of the subjects were belongs to the age group 40-60 years. Majority were with grade 2 and 3 disease. 50.7% were ER positive and 43% were PR positive. 43% were Her2-neu positive. Conclusion Triple negative breast cancer represented 19.9%, which is in concordance with the literature. TNBC are associated with large tumor size, high-grade tumors, and a higher rate of axillary lymph node metastasis

Computer-assisted diagnosis for axillary lymph node metastasis of early breast cancer based on transformer with dual-modal adaptive mid-term fusion using ultrasound elastography

Accurate preoperative qualitative assessment of axillary lymph node metastasis (ALNM) in early breast cancer patients is crucial for precise clinical staging and selection of axillary treatment strategies. Although previous studies have introduced artificial intelligence (AI) to enhance the assessment performance of ALNM, they all focus on the prediction performances of their AI models and neglect the clinical assistance to the radiologists, which brings some issues to the clinical practice. To this end, we propose a human-AI collaboration strategy for ALNM diagnosis of early breast cancer, in which a novel deep learning framework, termed DAMF-former, is designed to assist radiologists in evaluating ALNM. Specifically, the DAMF-former focuses on the axillary region rather than the primary tumor area in previous studies. To mimic the radiologists’ alternative integration of the UE images of the target axillary lymph nodes for comprehensive analysis, adaptive mid-term fusion is proposed to alternatively extract and adaptively fuse the high-level features from the dual-modal UE images (i.e., B-mode ultrasound and Shear Wave Elastography). To further improve the diagnostic outcome of the DAMF-former, an adaptive Youden index scheme is proposed to deal with the fully fused dual-modal UE image features at the end of the framework, which can balance the diagnostic performance in terms of sensitivity and specificity. The clinical experiment indicates that the designed DAMF-former can assist and improve the diagnostic abilities of less-experienced radiologists for ALNM. Especially, the junior radiologists can significantly improve the diagnostic outcome from 0.807 AUC [95% CI: 0.781, 0.830] to 0.883 AUC [95% CI: 0.861, 0.902] (P-value <0.0001). Moreover, there are great agreements among radiologists of different levels when assisted by the DAMF-former (Kappa value ranging from 0.805 to 0.895; P-value <0.0001), suggesting that less-experienced radiologists can potentially achieve a diagnostic level similar to that of experienced radiologists through human-AI collaboration. This study explores a potential solution to human-AI collaboration for ALNM diagnosis based on UE images.

Relationship between expression of p53 protein in breast cancer and axillary lymph node metastasis

ObjectiveTo explore the expression of p53 protein in cancer tissue of breast cancer, analyze the relationship between positive rate of expression of p53 protein and axillary lymph node status. Method137 breast cancer patients in general hospital of PLA from June 2023 to October 2023 were selected and divided into axillary lymph node metastasis group and non-axillary lymph node metastasis group according to routine pathological outcome after surgery. Detect the situation of expression of p53 protein in cancer tissue using immunohistochemical method. The rate of expression of p53 protein between axillary lymph node metastasis group and non-axillary lymph node metastasis group were compared by χ2 test. At the same time, the relationship between the expression of p53 protein in breast cancer tissue and the age, the longest tumor diameter and tumor TNM stage was analyzed. ResultThe rate of expression of p53 protein was 60.78%, 43.02% in the axillary lymph node metastasis group and non-axillary lymph node metastasis group respectively. The difference was statistically significant (χ2 ​= ​4.040, P ​= ​0.044＜0.05). The expression of p53 protein in breast cancer tissue was of no relationship with age (P ​= ​0.945＞0.05),the longest tumor diameter (P ​= ​0.200＞0.05) and tumor TNM stage (P ​= ​0.300 ​> ​0.05). ConclusionThere was a close relationship between expression of p53 protein in breast cancer tissue and axillary lymph node metastasis, and it can be regard as a predictive factor in the axillary lymph node status.

Enhancing detection of high-level axillary lymph node metastasis after neoadjuvant therapy in breast cancer patients with nodal involvement: a combined approach of axilla ultrasound and breast elastography.

To develop a combined approach using shear wave elastography (SWE) and conventional ultrasound (US) to determine the extent of positive axillary lymph nodes (LNs) following neoadjuvant therapy (NAT) in breast cancer patients with nodal involvement. This prospective, multicenter study was registered on the Chinese Clinical Trial Registry (ChiCTR2400085035). From October 2018 to February 2024, a total of 303 breast cancer patients with biopsy-proven positive LN were enrolled. The conventional US features of axillary LNs and SWE characteristics of breast lesions after NAT were analyzed. The diagnostic performances of axilla US, breast SWE, and their combination in detecting residual metastasis in axillary level III after NAT were assessed. Pathologically positive LN(s) in axilla level III were detected in 13.75% of cases following NAT. The kappa value for the axilla level with positive LN confirmed by surgical pathology and detected by US is 0.39 (p < 0.001). The AUC of conventional axilla US to determine the status of axilla level III LNs after NAT was 0.67, with a sensitivity of 51.52%, a specificity of 74.36%. The breast SWE displayed moderate performance for detecting residual metastasis in axilla level III following NAT, with an AUC of 0.79, sensitivity of 84.85%, and specificity of 74.36%. Compared to axilla US and breast SWE alone, the combination of axilla US with breast SWE achieved a stronger discriminatory ability (AUC, 0.86 vs 0.67 vs 0.79, p < 0.05, Delong's test) and precise calibration (X2 = 13.90, p = 0.085, HL test), with an improved sensitivity of 93.94% and a comparable specificity of 75.64%%. SWE outperformed conventional US in identifying the axilla levels with nodal metastasis following NAT in patients with initially diagnosed positive axilla. Furthermore, combining breast SWE with axilla US showed good diagnostic performance for detecting residual metastasis in axilla level III after NAT.

Construction of a risk prediction model for axillary lymph node metastasis in breast cancer based on gray-scale ultrasound and clinical pathological features.

This study aimed to develop a model to predict the risk of axillary lymph node (ALN) metastasis in breast cancer patients, using gray-scale ultrasound and clinical pathological features. A retrospective analysis of 212 breast cancer patients who met the inclusion criteria from January 2011 to December 2021 was carried out. Clinical and pathological characteristics, including age, tumor size, pathological type, molecular subtype, estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and proliferation cell nuclear antigen (Ki-67), were examined. Preoperative ultrasound examinations were performed, and ultrasound radiomics features of breast cancer lesions were extracted using Pyradiomics software. The data was divided into training (70%) and testing (30%) sets. A predictive model for axillary lymph node metastasis (ALNM) was established by combining clinical and ultrasound features. The diagnostic performance of the model was evaluated using receiver operating characteristic (ROC) curves and five-fold cross-validation. The rate of lymph node metastasis was 41.51%. Using LASSO algorithm, 17 features linked to ALN metastasis were extracted from a comprehensive databank of 8 clinical features and 1314 ultrasound radiomic attributes. Of these, four were clinical-pathological features (tumor size, tumor type, age, and expression levels of the Ki-67 protein), and 13 were radiomic features. And the following features exhibited both high weights and correlation coefficients: tumor size (R=0.29, weight=0.071), tumor type (R=-0.24, weight=-0.048), wavelet-LH_glcm_Imc1 (R=0.28, weight=0.029363), wavelet-LH_glszm_SZNUN (R=-0.20, weight=-0.028507), and squareroot_ firstorder_ Minimum (R= -0.25, weight= -0.059). The ROC area under the curve for the model in the training and testing sets was 0.882 (95% CI: 0.830-0.935) and 0.853 (95% CI: 0.762-0.945), respectively. The predictive model demonstrated a sensitivity of 87.5% on the training set and 79.2% on the test set, with corresponding specificities of 75.0% and 77.5%, accuracy of 80.4% and 78.1%, respectively. When evaluated using 5-fold cross-validation, the model achieved an average test set area under the curve (AUC) of 0.799 and a training set AUC of 0.852. The clinical-radiomic model has the potential to predict axillary lymph node metastasis in breast cancer.

Effects on lymph node size, staging and primary tumor histology on diagnostic accuracy of axillary lymph node aspirate of breast cancers.

Fine-needle aspiration cytology is preferred for axillary lymph node metastasis with low costs and minimal risks. To improve diagnostic performance by incorporating clinical-radiological-pathological parameters, a large cohort pre-operative aspirates in were reviewed for parameters affecting adequacy rate and accuracy. Axillary nodal aspirates from three institutions with histologic correlation were retrieved. Case notes were reviewed for parameters pertaining to the primary tumor, nodal status, histologic and cytologic diagnoses. Totally 1361 specimens were included. The risk of malignancy for C1-C5 categories were 53.39%, 27.45%, 70.97%, 83.33% and 88.00%, increasing to 75.86%, 94.59% and 99.28% for C3/C4/C5 categories excluding cases with neoadjuvant therapy. Node size (p < 0.001) and histologic grade (p = 0.003) of primary tumor positively correlated with specimen adequacy. Presence of in situ component trended towards inadequacy (p = 0.069). Lymph node size remained a strong predictor of concordant cytologic diagnosis (p < 0.001). A higher percentage of involved node (p = 0.006) and HER2 overexpressed breast cancers (p = 0.027) increased concordance. Cases with ≥ 4 (up to ≥ 10) positive nodes were more likely to be concordant (p = 0.009- < 0.001), with improvements of 8.27%-12.37%. For size, cut-offs of ≥ 5 and ≥ 10mm were significant (p = 0.006- < 0.001). It is critical that clinical-radiological-pathological findings be interpreted together with cytology. Aspirates from smaller nodes are more likely to be non-informative, irrespective of the total number of suspicious nodes, or a high-grade primary. In axillae with less than 4 suspicious nodes and/or a target node of less than 5-10mm, the diagnostic accuracy of aspiration cytology decreases and should be interpreted cautiously.

The correlation between multi-mode ultrasonographic features of breast cancer and axillary lymph node metastasis.

This study aimed to explore the correlation between multi-mode ultrasonographic features of breast cancer and axillary lymph node metastasis. A total of 196 patients with surgically confirmed breast cancer between September 2019 and December 2023 were included. Data on preoperative B-mode ultrasound (US), color Doppler, and shear wave elastography (SWE) features of breast cancer masses were collected and analyzed to determine their correlation with axillary lymph node metastasis. The area under the receiver operating characteristic curve (AUC) of B-mode US, color Doppler, SWE, and the multi-mode predictive model for evaluating axillary lymph node metastasis were compared. Among the 196 patients, 70 had positive axillary lymph nodes, while 126 had negative axillary lymph nodes. There was no significant difference in the color features between the negative and positive axillary lymph node groups. Multifocality/multicentricity, architectural distortion, microcalcifications, and the "stiff rim" sign in SWE were identified as independent risk factors to predict axillary lymph node metastasis according to binary logistic regression analysis. The AUC of the predictive model based on these independent risk factors was 0.803 (95% CI: 0.739-0.867), which was significantly higher than that of B-mode US or SWE alone. Multifocality/multicentricity, architectural distortion, microcalcifications, and the "stiff rim" sign in SWE were found to be valuable for predicting axillary lymph node metastasis in patients with breast cancer. The predictive model developed in this study, combining the multi-mode ultrasonographic features of breast cancer masses, could serve as a noninvasive and convenient method to predict axillary lymph node status. This approach could aid in clinical decision-making and individualized treatment to improve the prognosis of breast cancer patients.

Are background breast parenchymal features on preoperative breast MRI associated with disease-free survival in patients with invasive breast cancer?

To evaluate whether breast parenchymal features of the contralateral breast on preoperative MRI are associated with primary breast cancer characteristics and disease-free survival (DFS) in women with invasive breast cancer. Women with newly diagnosed invasive breast cancer who underwent preoperative breast MRI followed by surgery were retrospectively evaluated. Background parenchymal enhancement (BPE) on dynamic contrast-enhanced MRI and background diffusion signal (BDS) on diffusion-weighted MRI of the contralateral breast were qualitatively assessed using a four-category scale: minimal, mild, moderate, or marked. Primary breast cancer characteristics were compared based on the degree of BPE or BDS. Cox proportional hazards models were used to evaluate the association between MRI parenchymal features and DFS after adjusting for clinicopathologic features. A total of 515 women (mean age, 54years) were included. Of whom, 46 (8.9%) patients who developed disease recurrence at a median follow-up of 60months were observed. A high level (moderate/marked) of BPE or BDS was associated with younger age (≤ 45) and premenopausal status (all P < 0.05) compared to a low level (minimal/mild), but it was not associated with primary cancer characteristics such as tumor stage, grade, or subtype. Multivariable Cox proportional hazards analysis demonstrated that larger tumor size (> 2cm) (hazard ratio [HR], 3.877; P < . 001), triple-negative subtype (HR, 2.440; P = .013), and axillary node metastasis (HR, 1.823; P = .049) were associated with worse DFS. No associations were observed between background parenchymal features and disease outcomes. MRI parenchymal features, including BPE and BDS, of the contralateral breast showed no associations with primary breast cancer characteristics or DFS in women with invasive breast cancer.

Factors affecting lymphedema after neoadjuvant chemotherapy and axillary dissection in female breast cancer patients: a retrospective cohort study based on the Chinese population.

Breast cancer-related lymphedema (BCRL) is a common complication among breast cancer survivors. Most BCRL studies have focused on patients receiving adjuvant chemotherapy, with relatively little attention paid to BCRL in patients undergoing neoadjuvant chemotherapy (NAC). This study aimed to investigate the risk factors associated with BCRL in Chinese women undergoing NAC and axillary lymph node dissection (ALND). At our institution, this cohort study collected data from 336 women with breast cancer and documented axillary nodal metastasis at diagnosis, who received NAC and ALND surgery between 2015 and 2020. BCRL was assessed through both objective limb circumference measurements and subjective self-reported symptoms. Multivariate logistic regression was employed to identify risk factors for BCRL, considering clinical, demographic, and lifestyle-related characteristics. The cumulative incidence of BCRL within 2.5 years was 43.75%. Factors independently associated with BCRL included radiotherapy (versus no radiotherapy; hazard ratio (HR) = 1.611; P = 0.020), NAC duration of 105 days or shorter (versus 105-143 days; HR = 0.471; P = 0.020), removal of more than 15 lymph nodes (versus 15 or fewer lymph nodes; HR = 1.593; P = 0.036), drainage duration of 20-29 days (versus 10-19 days; HR = 1.568; P = 0.028), and sleeping biased toward the affected arm (versus sleeping biased toward the healthy arm; HR = 2.033; P = 0.019). This study identified several risk factors for BCRL in breast cancer patients following NAC and ALND. Patients presenting with one or more of these factors should be monitored closely for early detection and intervention. Further research is warranted to explore the impact of drainage duration and sleep position on the development of BCRL.

The Efficacy of MRI-Based ADC Measurements in Detecting Axillary Lymph Node Metastasis: Evaluation of a Prospective Study.

Objective: This study aimed to evaluate the efficacy of MRI-based Apparent Diffusion Coefficient (ADC) measurements in detecting axillary lymph node metastasis in breast cancer patients. By comparing preoperative MRI findings with intraoperative sentinel lymph node biopsy (SLNB) and postoperative pathological results, we sought to explore the potential of ADC values as a non-invasive alternative to axillary interventions. Methods: A total of 104 female patients diagnosed with breast cancer between 2019 and 2021 were included in this prospective study. ADC values of axillary lymph nodes, tumors, and muscle tissues were measured using a 3T MRI system. The correlation between these measurements and pathological outcomes was analyzed. Statistical analyses, including t-tests, ANOVA, and ROC curve analysis, were employed to assess the diagnostic performance of ADC values. Results: The results indicated that, while the mean ADC values of metastatic lymph nodes were lower than those of benign nodes, the sensitivity and specificity of MRI-based ADC measurements were inferior to the expected standards. The tumor ADC value and the tumor-to-lymph node ADC ratio were found to be more reliable indicators of metastasis than the lymph node ADC value alone. The diagnostic power of the tumor ADC value was significant, with a sensitivity of 75% and a specificity of 73%. Conclusions: MRI-based ADC measurements, particularly the tumor ADC value and the tumor-to-lymph node ADC ratio, show promise as potential non-invasive markers for axillary lymph node metastasis in breast cancer patients. However, the current results suggest that ADC measurements cannot yet replace SLNB in clinical practice.

Locoregional event or dyssynchronous distant metastasis: clinicopathological and molecular analysis of contralateral axillary lymph node metastasis in breast cancer patients.

Contralateral axillary lymph node metastasis (CAM) is a rare clinical condition in patients with breast cancer (BC). CAM can be either a locoregional event or a distant metastasis. Molecular application for clonal evolution in BC has not been reported in CAM cases. We studied six patients with CAM with clinical, pathological and/or molecular evidence of distant metastasis; those patients had poor outcomes. Two cases with molecular analysis of paired primary and CAM established clonal evolution of the CAM with its corresponding primary with additional molecular alteration, increased tumour mutation burden, and copy number variations (CNVs) in the CAMs. Four cases containing alterations from genes potentially modulate chromatin organization, supporting chromatin and subsequent transcriptional signature changes are essential in CAM. Molecular analysis is critical to establish the connection between CAM and its primary counterpart. Distant CAM shows clonal evolution compared with its corresponding primary with additional molecular alterations, increased mutation burden and/or copy number variations. CAM should be evaluated individually and handled in a personalized fashion. Evidence of a true metastatic CAM can be supported by distant metastasis to other organs, specific morphological features and/or clonal evolution.

Upstaging of Invasive Lobular Cancer With FES PET/CT.

A 78-year-old woman diagnosed with left breast invasive lobular carcinoma with left axillary nodal metastasis underwent 18 F-fluoroestradiol (FES) PET/CT imaging for further evaluation of indeterminate right axillary lymph nodes seen on staging 18 F-FDG PET/CT. 18 F-FES PET/CT revealed abnormal 18 F-FES-avid right axillary and bilateral cervical nodes, subsequently biopsy-proven metastases, upstaging the patient from stage II to IV and greatly changing patient management. This case demonstrates the value of 18 F-FES PET/CT in accurately staging metastatic invasive lobular carcinoma at diagnosis, an indication for which 18 F-FES PET/CT "may be appropriate" per current Society of Nuclear Medicine and Molecular Imaging guidelines.

Expression of histone methyltransferase WHSC1 in invasive breast cancer and its correlation with clinical and pathological data

BackgroundThe WHSC1 protein facilitates specific dimethylation of histone H3 at the K36 position, enhancing gene transcription and expression. Studies have confirmed its high expression in diverse malignant tumors. We aimed to identify novel molecular markers to assess the biological behavior of breast cancer cells. MethodsWe conducted a comprehensive analysis of mRNA expression in breast cancer and adjacent tissues based on TCGA data. We enrolled 141 breast cancer patients treated at the First Affiliated Hospital of Fujian Medical University between 2012 and 2016. Patient clinical information and pathological specimens were obtained. We utilized tissue microarray (TMA) technology. We employed the chi-square test for between-group comparisons, with p < 0.05 indicating statistical significance. Furthermore, we analyzed the associations between WHSC1 expression and clinical or pathological data. ResultsWHSC1 mRNA expression was significantly higher in breast cancer tissues than in adjacent tissues (p < 0.001). Moreover, high WHSC1 protein expression in breast cancer was associated with several important clinical parameters, such as pathological type (p = 0.007), high Ki67 expression(Ki67＞20 %) (p < 0.001), lymph node metastasis (p < 0.001), T stage (p = 0.011), N stage (p < 0.001), postoperative pathological stage (p < 0.001), premenopausal status (p = 0.004), and positive HER2 status (p < 0.001). Multivariate regression analysis showed that high WHSC1 expression, elevated Ki67 levels, and positive HER2 status were independent risk factors for axillary lymph node metastasis in breast cancer patients. ConclusionWHSC1 protein expression is upregulated in breast cancer patients and represents an independent risk factor influencing axillary lymph node metastasis, highlighting its potential significance as a strong candidate biomarker.

Comparison among Various Prognostic Pathologic Markers Revealed Significantly Poorer Prognosis in Non-basal-like than in Basal-like Triple Negative Breast Cancer

Objective: To find the incidence and prognosis of basal-like (TNB) and non-basal-like (TNN) in triple negative breast cancer. Methods: Triple negative breast cancer (TN) cases were retrospectively reviewed and biomarkers studied on tissue microarray for ER, PR, HER2, Ki67, basal cytokeratins (CK5/6, CK14, CK17), EGFR, CD117, p63, p53, vimentin, CK7, CK8/18, CK19, BCL2, p16, WT1, and cyclin D1. The patients were reclassified according to ER, PR, HER2, Ki67 index, basal CKs and EGFR results into: lumA, lumB, HER2+, TNB and TNN. Results: From 2007 to 2010, there were 193 female patients (120 TNB, 17 TNN, 42 lumB, and 14 HER2+). There were 184 (95.3%) invasive ductal carcinoma (IDC). All 17 TNN were IDC. High grade histology accounted for 71.5%. The median follow up time was 62.93 months. There were no significant differences in age, histologic grade, and tumor size between TNB and TNN while TNN had significant number of higher stage (p=0.028), axillary lymph node metastasis of more than 3 nodes (p=0.005) and lower disease free survival (DFS, p= 0.004) and overall survival (OS, p=0.001). TNN also had the poorest prognosis among the four subtypes.Tumor size and axillary nodal involvement were the independent predictors for DFS and OS. Absence of EGFR expression was an independent factor for lower DFS and OS in TN. Absence of CK8/18 expression was an independent factor for lower DFS in any combined group and OS in the combined TN and lumB group. Absence of p16 expression was an independent factor for lower DFS and OS of all cohort. Conclusion: TNN accounted for12.3% of TN and had poorer prognosis. Tumor size and axillary nodal involvement were the independent predictors for DFS and OS. Absence of EGFR, CK8/18 or p16 expression had influence on survival in TN or combined group.

Comparison of Sentinel Lymph Node Sampling with Positron Emission Tomography in the Evaluation of Axillary Lymph Node Involvement in Breast Cancer Patients

Objectives Axillary lymph node status is the most important prognostic factor in breast cancer patients.: This study was carried out to evaluate the diagnostic accuracy of FDG-PET/CT as a noninvasive technique and intraoperative frozen biopsy of sentinel lymphadenectomy (SLNB) in detecting axillary lymph node metastasis. Materials and Methods This study was carried out retrospectively on 44 patients diagnosed with breast cancer, who underwent preoperative FDGPET/ CT imaging and intraoperative SLNB, at the General Surgery Clinic of Istanbul Medeniyet University Göztepe Training and Research Hospital. The axilla was clinically negative in all patients. Preopative FDG-PET/CT imaging and intraoperative SLNB were performed. FDG-PET/CT results were compared with the histopathological results of SLNB and axillary lymph node dissection (ALND). Results According to the pathology results of axillary dissection, metastatic nodes were detected in 22 of 44 cases, and FDG-PET/ CT imaging gave false-negative results in 10. The number of false negative cases of SLNB was 3; Axillary involvement was detected as a result of pathology in one of them, while the others were evaluated as skip metastases. The sensitivity of SLNB and FDG-PET/CT imaging was measured as 86.3% and 54.5%. The specificity values were 95.4% and 100%. FDG-PET/CT imaging has low sensitivity; specificity and positive predictive value were at acceptable levels Conclusion: The sensitivity of FDG-PET/CT imaging is low in detecting axillary involvement, and SLNB is needed in those with negative axillary involvement in FDG-PET/ CT imaging. In our study, SLNB examination was superior to FDG-PET/CT imaging in detecting axillary nodal status. Bangladesh Journal of Medical Science Vol. 23 No. 04 October’24 Page : 1083-1094

Role of Ultrasonographic and Clinicopathological Characteristics in Assessing Stromal Tumor-Infiltrating Lymphocyte Density in Triple-Negative Breast Cancer

A high density of stromal tumor-infiltrating lymphocytes (sTILs) is positively correlated with the pathological complete response rate and favorable survival in patients with triple-negative breast cancer (TNBC). Heterogeneity in stromal lymphocyte distribution and limited tumor sampling may affect the accuracy of sTIL quantification in biopsy samples from patients receiving neoadjuvant therapy. Thus, identifying additional biomarkers to complement sTIL evaluation is essential. To identify biomarkers that could be used to complement sTILs evaluation. Retrospective cohort study. A total of 162 patients with invasive TNBC were enrolled in the study. The following data were gathered: sTIL density, Ki67, nuclear grades of cancer cells, lymphovascular invasion status, the American Joint Committee on Cancer stage, axillary lymph node metastasis status, and ultrasonographic parameters of the tumor (size, shape, orientation, margin, internal echo pattern, posterior feature, and vascularity). The relationship between sTIL density and ultrasonographic or clinicopathological characteristics was investigated using both continuous and categorical analyses. Posterior features of the primary tumors was associated with sTIL density (p = 0.038). Additionally, the Ki67 levels and nuclear grades were also associated with sTIL density (p < 0.001 and p = 0.024, respectively). When stratified according to a 20% cut-off of sTIL density, the posterior features of primary tumors, Ki67 levels, and nuclear grades significantly differed between the high and low sTIL density tumors. Tumors with high Ki67 levels were more likely to exhibit high sTIL density than low sTIL density [odds ratio (OR): 2.75, p = 0.021]. Furthermore, nuclear grade III tumors demonstrated significantly higher sTIL density than nuclear grade I-II tumors (OR: 2.49, p = 0.014). Additionally, tumors with posterior enhancement or no posterior features were more likely to exhibit high sTIL density than tumors with acoustic shadows (OR: 2.91, p = 0.028; OR: 2.74, p = 0.022, respectively). Low sTIL density is frequently observed in tumors exhibiting acoustic shadows on ultrasound. However, high sTIL density is more common in tumors with posterior enhancement or no posterior features. Furthermore, high Ki67 levels (> 40%) and high nuclear grades are positively correlated with high sTIL density. This study findings highlight the need for closer surveillance of these biomarkers to complement sTIL evaluation in TNBC.