Detection Of Metastatic Breast Cancer Research Articles

Deciphering Breast Origin in Malignant Effusions: The Diagnostic Utility of an MGP, GATA-3, and TRPS-1 Immunocytochemical Panel

Introduction: Defining the origin of metastatic cancer is crucial for establishing an optimal treatment strategy, especially when obtaining sufficient tissue from secondary malignancies is limited. While cytological examination is often used in this diagnostic setting, morphologic analysis alone often fails to differentiate metastases derived from the breast from other primaries. The hormone receptor, human epidermal growth factor receptor-2, gross cystic disease fluid protein 15, and mammaglobin immunohistochemistry are often used to diagnose metastatic breast cancer. However, their effectiveness decreases in estrogen receptor (ER)-negative breast cancers, including the triple-negative breast cancer (TNBC) subtype. Methods: We conducted a comprehensive evaluation of GATA-binding protein 3 (GATA-3), trichorhinophalangeal syndrome type 1 (TRPS-1), and Matrix Gla Protein (MGP) immunochemistry across 140 effusion cytology specimens with metastatic adenocarcinoma derived from various primaries, including the breast, colon, pancreaticobiliary, lung, tubo-ovarian, and stomach. Results: The expression rates of these immunomarkers were significantly higher in metastatic cancers originating from the breast than other primaries. In TNBC, TRPS-1 (80.00%) and MGP (65.00%) exhibited higher positivity rates compared to GATA-3 (40.00%). Additionally, our data suggest that an immunohistochemical panel comprising MGP, GATA-3, and TRPS-1 significantly enhances the detection of metastatic breast cancer in effusion cytology specimens, including TNBC in particular. When considering dual-marker positivity, the diagnostic accuracy was found to be 89.29% across all breast cancer subtypes and 92.93% for TNBC. Conclusions: MGP appears to be a robust marker for identifying metastatic breast cancer in malignant effusions, especially TNBC. MGP notably enhances diagnostic accuracy when incorporated together with GATA-3 and TRPS-1 in an immunohistochemical panel.

Abstract PO4-15-01: A multi-center prospective cohort study to evaluate the presence of circulating tumor cells using the Epic Sciences platform among women with metastatic breast cancer

Abstract Background: The presence of tumor cells (or their components) in the blood of women with a history of early breast cancer has the potential to herald the development of metastatic recurrence at its earliest stages. Such early detection could potentially lead to novel prevention strategies, but it requires a sensitive assay. Objective: To use the Epic Sciences platform to detect and enumerate CTCs in blood samples from patients with an established diagnosis of metastatic breast cancer (MBC), prior to initiation of 1st line systemic therapy in the metastatic setting. Methods: We conducted a multi-center prospective cohort study to evaluate the presence of CTCs using the Epic Sciences platform among patients with a new diagnosis of MBC. Men or women age 18 to 85 were included, irrespective of breast cancer subtype. Patients with a prior or concurrent malignancy whose natural history or treatment had the potential to interfere with the detection of MBC in a liquid biopsy were excluded. A one-time blood draw was performed before patients received any local or systemic therapy in the metastatic setting. In addition, those with recurrent disease must have been off any systemic adjuvant therapy for ≥3 weeks prior to blood collection. Two 5 mL blood samples were obtained for CTC identification and enumeration. CTC identification was based on immunofluorescence analysis using Epic Sciences platform as previously described (Ueno et al 2017). The presence of CTCs was correlated with clinical and pathological features, which were abstracted from medical records and pathology reports. The association between the presence of CTCs and clinical/pathologic characteristics was tested using Fisher’s exact test for categorical variables and t-test or Wilcoxon rank sum tests for numerical variables. All analyses were performed using the R software package. Results: 100 patients were recruited between February 2021 and January 2023 at five academic oncology centres in Ontario and Quebec, Canada. 95 patients had evaluable blood for analysis and 5 did not due to blood age and/or insufficient blood volume. Six patients were excluded after providing a blood sample because tissue biopsy ultimately revealed a 2nd primary tumor (n=4) or benign tissue (n=2). Hence, 89 patients with a clinical diagnosis of MBC and with evaluable blood for CTC analyses were ultimately included in our cohort. The average age of patients was 61 years. Most patients (n=49, 55%) had a prior history of early breast cancer, 38 (43%) had de-novo metastatic disease and prior breast cancer history was unknown for 2 patients. 50 (66%) of patients had visceral metastatic disease. The most common sites of metastases included bone (62%), lung (30%), liver (29%) and lymph nodes (17%). 63 of 89 patients (71%) had detectable CTCs at baseline, prior to any local or systemic treatment in the metastatic setting. The median number of detectable CTCs per 5mL sample was 2 (IQR 8.5) and the range was 0 – 12,798. Twenty nine of 89 (33%) patients had 5 or more CTCs detected per 5ml blood. The proportion of patients with detectable CTCs was numerically highest (n=39/51, 76%) among patients with hormone receptor (HR)+/HER2-ve breast cancer, followed by HER2+ (n=16/22, 73%) and triple negative (n=8/13, 62%) disease. Associations between CTC detection with prior history of early breast cancer, sites of metastatic disease and disease burden will also be presented. Conclusions: Approximately 3 in 4 women with newly diagnosed metastatic breast cancer have detectable CTCs using the Epic Sciences platform prior to initiation of first line systemic therapy. CTCs may be a promising tool for the monitoring of breast cancer recurrence and will be investigated in an ongoing Canadian prospective observational study that aims to elucidate biomarkers of late breast cancer recurrence. Citation Format: Katarzyna Jerzak, Pamela Goodwin, Marguerite Ennis, Christine Brezden-Masley, Nathaniel Bouganim, Mark Basik, Arushi Jain, Giuseppe Di Caro, Rick Wenstrup, Nadine Hartmann, Megan Slade, Ana Elisa Lohmann. A multi-center prospective cohort study to evaluate the presence of circulating tumor cells using the Epic Sciences platform among women with metastatic breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-15-01.

Dual-microRNA-Controlled Electrochemiluminescence Biosensor for Breast Cancer Diagnosis and Supplemental Identification of Breast Cancer Metastasis.

Breast cancer remains the most frequently diagnosed cancer globally, and the metastasis of this malignancy is the primary cause of mortality in breast cancer patients. Hence, prompt diagnosis and timely detection of metastatic breast cancer are critical for effective therapeutic intervention. Both progression and metastasis of this malignancy are closely associated with aberrant expression of specific microRNAs (miRNAs) and enzymes. To facilitate breast cancer diagnosis and concomitant identification of metastatic breast cancer, we have engineered an innovative electrochemiluminescence (ECL)-based sensing platform integrated with enzyme-free DNA amplification circuits for dual functionality. Specifically, microRNA-21 (miR-21) is employed as a biomarker for breast cancer, and miR-21 induces the quenching of the ECL signal from luminophores via a strategically designed catalytic three-hairpin assembly (CTHA) circuit. Subsequently, miR-105 levels are measured via toehold-mediated strand displacement reactions (TSDR). Here, miR-105 restores the initially quenched ECL signal, enabling the assessment of the metastatic propensity. Our experimental data demonstrate that the devised ECL biosensor offers broad linear detection ranges and low detection limits for both miR-21 and miR-105. Importantly, our novel platform was also successfully validated by using cellular and serum samples. This biosensor not only discriminates breast cancer cell lines MCF-7 and MDA-MB-231 from nonbreast cancer cells like HepG2, TPC-1, and HeLa, but it also distinguishes between malignant MCF-7 and metastatic MDA-MB-231 cells. Consequently, our novel approach holds significant promise for clinical applications and precise cancer screening.

Histopathological Image Classification Using Convolutional Neural Networks for Detection of Metastatic Breast Cancer in Lymph Nodes

Breast cancer is currently one of the most diagnosed oncological diseases worldwide, with thousands of new cases per year. Early detection and identifying its progression are key to overcoming the mortality rate. A recurrent test, to determine how far the disease has spread throughout the patient’s body, is the histological analysis of the sentinel lymph node near the breast. Although an expert pathologist performs this, it is usually an exhausting and time-consuming task, with a high possibility of error. This work presents a method to detect breast cancer metastasis through histological imaging of sentinel lymph nodes using convolutional neural networks. In this study, the performance of three models DenseNet-121, DenseNet-169 and DenseNet-201 are tested and compared. Experimental results indicated that the accuracy, precision, sensitivity and specificity (97.93%, 97.4%, 97.48% and 98.24%) of DenseNet-201 could reduce pathologist errors during the diagnostic process or serve as a second opinion tool.

Application of Biosensors in Detecting Breast Cancer Metastasis.

Breast cancer has garnered global attention due to its high incidence worldwide, and even more noteworthy is that approximately 90% deaths due to breast cancer are attributed to cancer metastasis. Therefore, the early diagnosis of breast cancer metastasis holds significant importance for reducing mortality outcomes. Biosensors play a crucial role in the early detection of metastatic breast cancer due to their advantages, such as ease of use, portability, and real-time analysis capabilities. This review primarily described various types of sensors for detecting breast cancer metastasis based on biomarkers and cell characteristics, including electrochemical, optical, and microfluidic chips. We offered detailed descriptions of the performance of these various biosensors and made comparisons between them. Furthermore, we described the pathology of breast cancer and summarized commonly used biomarkers for metastatic breast cancer. Finally, we discussed the advantages of current-stage biosensors and the challenges that need to be addressed, as well as prospects for their future development.

Circulatory Level of Inflammatory Cytoskeleton Signaling Regime Proteins in Cancer Invasion and Metastasis.

Early detection of metastatic breast cancer (MBC) is a serious issue for the healthcare system. It is essential to develop potential non-invasive, low-cost molecular biomarkers. The present study explored specific serum proteins of inflammatory, MAPK, and cytoskeletal signaling pathways involved in the progression of MBC to establish a panel of blood-based diagnostic and prognostic biomarkers. Healthy-control (HC), non-metastatic (NM), and metastatic (M) (pre- and post-therapy) breast cancer (BC) patients were recruited. LOX5, Rac1, Rac1b, p38α, phospho-p38α (Y182), LIMK1, phospho-LIMK1 (T508), cofilin1, and phospho-cofilin1 (S3) were quantified in the serum of the study group by real-time label-free surface plasmon resonance technology and verified by Western blot. Proteins were found to be significantly elevated in the serum of BC patients compared to HC and also higher in M compared to NM, which further downregulated in post-therapy M patients. Elevation of phospho-LIMK1 and phospho-cofilin1, which are critical for M, was also indicated in the serum level and can differentiate from NM. Receiver operating characteristics (ROC) derived area under the curve (AUC) (0.9) is very strong to differentiate between HC and BC. Moreover, the combined ROC of 3 molecules phospho-LIMK, p38α, and phospho-p38α were found to be a potent predictive panel of biomarkers between M and NM with AUC0.95. The panel of inflammatory cytoskeleton signaling regime proteins specified in this study can have significant clinical utility for diagnosis as well as prognosis of MBC at an early stage. The study may have a high translational value in a simple and cost-effective way by avoiding frequent CT/PET scans.

Detection of Metastatic Breast Cancer from Whole-Slide Pathology Images Using an Ensemble Deep-Learning Method

Background: Metastasis is the main cause of death toll among breast cancer patients. Since current approaches for diagnosis of lymph node metastases are time-consuming, deep learning (DL) algorithms with more speed and accuracy are explored for effective alternatives. Methods: A total of 220025 whole-slide pictures from patients’ lymph nodes were classified into two cohorts: testing and training. For metastatic cancer identification, we employed hybrid convolutional network models. The performance of our diagnostic system was verified using 57458 unlabeled images that utilized criteria that included accuracy, sensitivity, specificity, and P-value. Results: The DL-based system that was automatically and exclusively capable of quantifying and identifying metastatic lymph nodes was engineered. Quantification was made with 98.84% accuracy. Moreover, the precision of VGG16 and Recall was 92.42% and 91.25%, respectively. Further experiments demonstrated that metastatic cancer differentiation levels could influence the recognition performance. Conclusion: Our engineered diagnostic complex showed an elevated level of precision and efficiency for lymph node diagnosis. Our innovative DL-based system has a potential to simplify pathological screening for metastasis in breast cancer patients.

Breast cancer diagnosis based on detecting lymph node metastases using deep learning

Introduction: Automated detection of metastatic breast cancer from whole slide images of lymph nodes utilizing a deep convolutional neural network was proposed in this study. Methods: The dataset is taken from the PatchCamelyon subset, which contains 220,025 images divided into training, validation, and testing sets at a ratio of 60:20:20. The pretrained ResNet50 model was utilized, and transfer learning was subsequently applied to adjust the weights of the model. To elevate the model performance, the evaluation metrics were assessed by the accuracy score, confusion matrix, receiver operating characteristic (ROC) curve, and area under the ROC curve (AUC) score. Results: As a result, the proposed algorithm obtained high performance, with scores over 95% in all the evaluation methods, especially the AUC score, which achieved 0.989. Moreover, the model is validated in a testing set with the test-time augmentation (TTA) technique to enhance prediction quality and reduce generalization error. Conclusion: Overall, the proposed model achieves high accuracy when applying transfer learning. The results prove that the trained Resnet50 model can extract useful information from small cells in histopathologic images for breast cancer detection.

Development of a Multi-target Protein Biomarker Assay for Circulating Tumor Cells.

We report a highly sensitive and selective CNT-switch liquid biopsy platform that detects and quantifies protein biomarker expressions from circulating tumor cells in blood for early detection of metastatic breast cancer and its relapse. This platform first isolates and enriches more than 99% of tumor cells with an off-chip micro-size membrane filtration technique and then conducts on-chip detection of the membrane and internal protein biomarkers of the tumor cells with high sensitivity and selectivity. High sensitivity is achieved with complete association of the antibody-antigen-antibody (Ab-Ag-Ab) complex by precisely and rapidly assembling carbon nanotubes (CNTs) across two parallel electrodes via sequential DC electrophoresis and dielectrophoresis (DEP) deposition. Each bridged CNT acts as a switch that connects the electrodes and closes the circuit to generate an electrical signal. The high selectivity is achieved with a critical hydrodynamic shear rate that irreversibly removes non-target linkers of the aligned CNTs. At present, we are able to detect the protein biomarkers from 5 spiked breast cancer tumor cells of different types within 7.5ml of human blood samples. This demonstrates the potential of this platform as an inexpensive and noninvasive alternative to MRI scans and tissue biopsies currently used to detect early metastatic breast cancer and its relapse.

Abstract P3-01-07: Early detection of metastatic breast cancer through gene expression and cell heterogeneity at an engineered metastatic niche

Abstract Background: Current technology limits the detection of metastatic lesions until the patient becomes symptomatic or radiological evidence is identified, and thus invasive cancer cells are not detectable prior to their colonization in distant organs. We have developed a biomaterial implant that serves as a synthetic metastatic niche that recruits tumor cells prior to their accumulation in the lung, a natural metastatic niche. We aimed to dissect the heterogeneity of stromal and immune cells at the synthetic and lung metastatic niches over time, thereby identifying changes in cell populations, phenotypes, and gene expression that could be used for the molecular staging of metastatic disease. Methods: Porous polycaprolactone scaffolds (5 mm diameter x 2 mm height) were implanted subcutaneously into Balb/c mice two weeks before triple negative murine breast cancer cells (4T1) were inoculated into the mammary fat pad. We tracked disease progression in the lung from a pre-metastatic niche (7 days post-inoculation) to micrometastases (14 days) to overt metastatic disease (21 days). Ten genes were selected from the TaqManTM Open Array Mouse Inflammation Panel to develop a PCR-based signature and single value decomposition (SVD) score in the scaffold that successfully delineated metastatic staging. Furthermore, the scaffold and lung were analyzed through single cell RNA-sequencing (Drop-seq) to identify heterogeneity and contributions of each cell type. Results: Ten genes were identified from Open Array of the scaffolds that directly correlated to disease stage in the lungs – S100a8, S100a9, Pglyrp1, Ltf, Camp, Ela2, and Chi3l3 increased with metastatic progression, while Bmp15, Ccl22 and Ccr7 decreased. SVD was applied to establish a single score from the scaffold that could be used for accurate molecular staging. Scaffolds were scored on a scale from 0 to 1, where a value of 0.2 – 0.3 generally correlated to pre-metastatic disease, 0.4 - 0.8 indicated micrometastases and 0.8 – 1.0 demarked metastasis. This model successfully predicted disease stage with an area under the curve of 0.878. When the scaffold-derived gene signature was applied to the lung metastases (21 days), the output was comparable to the scaffold, further demonstrating the physiological relevance of the implants. Single cell analysis indicated that the genes in the signature were primarily expressed by macrophages and neutrophils. After 7 days, 22% of macrophages and 83% of neutrophils were classified as tumor associated cells in the scaffold. In contrast, only 16% of macrophages and 44% of neutrophils in the lung were tumor associated at this time point. These findings support the hypothesis that the scaffolds could be used as early surrogates for the pre-metastatic niche, becoming responsive prior to their biological metastatic counterpart. Moreover, this finding was demonstrated through changes in T cell phenotype, specifically loss of cytotoxic Cd8+ T cells. After 7 days, Cd8+ T cells in the scaffolds decreased by 35%. Whereas Cd8+ T cells in the lungs decreased by 35% after 14 days. Conclusions: A biomaterial scaffold was employed as a synthetic niche that recruits metastatic tumor cells. These scaffolds established a molecular signature of metastatic breast cancer using a 10-gene panel. Additionally, single cell analysis identified the cell types that induce this signature and the disease-associated changes that occur in the scaffold earlier than the lung. In summary, we have shown the potential of a biomaterial scaffold to act as a surrogate metastatic niche that can be used to delineate disease progression and understand the role of specific cell types in the formation of this niche. Mechanistic investigation into the synthetic niche may identify novel therapeutic targets that could be activated to inhibit the advent of metastasis. Citation Format: Sophia M Orbach, Robert S Oakes, Michael D Brooks, Grace G Bushnell, Pridvi Kandagatla, Max S Wicha, Jacqueline S Jeruss, Lonnie D Shea. Early detection of metastatic breast cancer through gene expression and cell heterogeneity at an engineered metastatic niche [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P3-01-07.

Presymptomatic detection of metastatic breast cancer using Non-Invasive Prenatal Testing (NIPT)

Presymptomatic detection of metastatic breast cancer using Non-Invasive Prenatal Testing (NIPT)

An augmented reality microscope with real-time artificial intelligence integration for cancer diagnosis.

The microscopic assessment of tissue samples is instrumental for the diagnosis and staging of cancer, and thus guides therapy. However, these assessments demonstrate considerable variability and many regions of the world lack access to trained pathologists. Though artificial intelligence (AI) promises to improve the access and quality of healthcare, the costs of image digitization in pathology and difficulties in deploying AI solutions remain as barriers to real-world use. Here we propose a cost-effective solution: the augmented reality microscope (ARM). The ARM overlays AI-based information onto the current view of the sample in real time, enabling seamless integration of AI into routine workflows. We demonstrate the utility of ARM in the detection of metastatic breast cancer and the identification of prostate cancer, with latency compatible with real-time use. We anticipate that the ARM will remove barriers towards the use of AI designed to improve the accuracy and efficiency of cancer diagnosis.

Artificial Intelligence-Based Breast Cancer Nodal Metastasis Detection: Insights Into the Black Box for Pathologists.

Nodal metastasis of a primary tumor influences therapy decisions for a variety of cancers. Histologic identification of tumor cells in lymph nodes can be laborious and error-prone, especially for small tumor foci. To evaluate the application and clinical implementation of a state-of-the-art deep learning-based artificial intelligence algorithm (LYmph Node Assistant or LYNA) for detection of metastatic breast cancer in sentinel lymph node biopsies. Whole slide images were obtained from hematoxylin-eosin-stained lymph nodes from 399 patients (publicly available Camelyon16 challenge dataset). LYNA was developed by using 270 slides and evaluated on the remaining 129 slides. We compared the findings to those obtained from an independent laboratory (108 slides from 20 patients/86 blocks) using a different scanner to measure reproducibility. LYNA achieved a slide-level area under the receiver operating characteristic (AUC) of 99% and a tumor-level sensitivity of 91% at 1 false positive per patient on the Camelyon16 evaluation dataset. We also identified 2 "normal" slides that contained micrometastases. When applied to our second dataset, LYNA achieved an AUC of 99.6%. LYNA was not affected by common histology artifacts such as overfixation, poor staining, and air bubbles. Artificial intelligence algorithms can exhaustively evaluate every tissue patch on a slide, achieving higher tumor-level sensitivity than, and comparable slide-level performance to, pathologists. These techniques may improve the pathologist's productivity and reduce the number of false negatives associated with morphologic detection of tumor cells. We provide a framework to aid practicing pathologists in assessing such algorithms for adoption into their workflow (akin to how a pathologist assesses immunohistochemistry results).

102P - Functional characterization of mammagliobin-1 isoform in breast cancer

Background: Since 2007, oncologists have been using the GeneSearchTM Breast Lymph Node (BLN) Assay for the detection of metastatic breast cancer. This test detects the presence of Mammaglobin-1 (MGB1) expression in lymph nodes of breast cancer patients. Although MGB1 is overexpressed in 90% of breast cancers, its aberrant expression and function in breast cancer tissue is still misunderstood. We have recently reported the first evidence for MGB1 as potent induction of breast cancer malignancy and disease progression. More precisely, loss of MGB1 expression correlates with a decrease of cell proliferation, spheroid formation, migration, and invasion capacities of breast cancer cells. Concomitantly, we also show that MGB1 expression activates pro-malignant signaling cascades leading to epithelial to mesenchymal transitioning (EMT). More interestingly, we have also discovered new MGB1 gene products that result from transcript editing. The objective of this research is to elucidate the role of MGB1 gene products in breast cancer, we set out to investigate and characterize MGB1 isoforms in breast cancer cell processes. Methods: MGB1 isoforms were identified by 3’and 5’-RACE assays and next generation sequencing using the minion platform. The novel MGB1 gene products were subsequently cloned. Results: In total, we have identified 7 different MGB1 product variants. We strongly believe that each MGB1 product has a specific cellular role, which leads to breast cancer malignancy and disease progression. To perform loss and gain of function experiments, we are genetic engineering breast cancer models that specifically code and express individual MGB1 variants with and without tracking epitope tags. Conclusions: This study will elucidate the molecular and cellular mechanism leading to breast cancer progression. MGB1 variants may provide new avenues for therapeutic or prognostic strategies. Legal entity responsible for the study: N/A Funding: Mitacs Globalink, Baxter and Alma Ricard, Canadian Institute of Health Research, Beatrice Hunter Cancer Research Institute, New Brunswick Health Research Institute, O'Brien Foundation, Canadian Breast Cancer Foundation, Atlantic Canada Opportunities Agency, Université de Moncton Campus Moncton Disclosure: All authors have declared no conflicts of interest.

Filtration based assessment of CTCs and CellSearch\xae based assessment are both powerful predictors of prognosis for metastatic breast cancer patients

BackgroundThe assessment of circulating tumor cells (CTCs) has been shown to enable monitoring of treatment response and early detection of metastatic breast cancer (MBC) recurrence. The aim of this study was to compare a well-established CTC detection method based on immunomagnetic isolation with a new, filtration-based platform.MethodsIn this prospective study, two 7.5 ml blood draws were obtained from 60 MBC patients and CTC enumeration was assessed using both the CellSearch® and the newly developed filtration-based platform. We analyzed the correlation of CTC-positivity between both methods and their ability to predict prognosis. Overall survival (OS) was calculated and Kaplan-Meier curves were estimated with thresholds of ≥1 and ≥5 detected CTCs.ResultsThe CTC positivity rate of the CellSearch® system was 56.7% and of the filtration-based platform 66.7%. There was a high correlation of CTC enumeration obtained with both methods. The OS for patients without detected CTCs, regardless of the method used, was significantly higher compared to patients with one or more CTCs (p < 0.001). The median OS of patients with no CTCs vs. ≥ 1 CTC assessed by CellSearch® was 1.83 years (95% CI: 1.63–2.02) vs. 0.74 years (95% CI: 0.51–1.52). If CTCs were detected by the filtration-based method the median OS times were 1.88 years (95% CI: 1.74–2.03) vs. 0.59 years (95% CI: 0.38–0.80).ConclusionsThe newly established EpCAM independently filtration-based system is a suitable method to determine CTC counts for MBC patients. Our study confirms CTCs as being strong predictors of prognosis in our population of MBC patients.

Abstract 1807: Exosomal NM23 facilitates pro-angiogenic communication between triple-negative breast cancer cells and their vascular targets

Abstract Functional interactions between primary tumor cells and their vascular targets orchestrate the formation of a metastatic milieu enriched with oxygen and metabolic substrates. These interactions have been largely attributed to the activation of VEGF receptor pathways through localized tumor-mediated release of VEGF, in addition to indirect receptor phosphorylation. However, pro-angiogenic events are known to occur in the absence of VEGF and alternative pathways resulting in dual activation of neovascularization and enhanced vascular permeability are of growing interest. Our lab has previously shown that triple-negative human breast cancer (MDA-MB-231) cells elaborate exosomes carrying NM23, a nucleoside diphosphate kinase (eNDPK) that is suggested to act as an upstream mediator of vasodilation and pro-angiogenic activity through its action of elevating extracellular ADP/ATP levels. To further elucidate the role of eNDPK in breast cancer signaling and metastasis, we show that 231-exosomes induce a pro-angiogenic phenotype in both human umbilical vein and murine pulmonary endothelial cells. Treatment with an NDPK-specific inhibitor and an antagonist to the ADP/ATP-activated P2Y1 receptor results in amelioration of pro-angiogenic characteristics. Further, we report the development and application of a novel murine implant model to demonstrate increased specificity of 231 exosome targeting to pulmonary endothelial cells over unrelated cell lines. These results suggest the involvement of exosomes and eNDPK in pro-angiogenic communication between metastatic breast cancer cells and their vascular targets. Exosomes elaborated by these cells specifically target pulmonary endothelium in vivo, mirroring the organotropic nature of breast cancer metastasis. Implication of eNDPK in angiogenesis and metastasis may challenge current and invasive treatment methods in favor of developing novel small molecule inhibitors of eNDPK signaling. Lastly, eNDPK can be explored as a potential biomarker for early detection of metastatic breast cancer as it uniquely appears in the serum of patients with breast cancer and not in the serum of individuals with unrelated pathologies. Citation Format: Suzann Duan, Senny Nordmeier, Iain L. Buxton. Exosomal NM23 facilitates pro-angiogenic communication between triple-negative breast cancer cells and their vascular targets [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1807. doi:10.1158/1538-7445.AM2017-1807

Tumor markers in the early detection of tumor recurrence in breast cancer patients: CA 125, CYFRA 21-1, HER2 shed antigen, LDH and CRP in combination with CEA and CA 15-3

BackgroundKinetics of CA 15-3 and CEA have a high specificity in the early detection of metastatic breast cancer (MBC). However, this high specificity is associated with a lack of sensitivity. To decrease the number of false negative patients, the additional diagnostic potential of an extended panel of biomarkers was evaluated. MethodsThis analysis was performed as part of a large follow-up study (1998–2010) evaluating 813 patients with a median follow-up of 63months.After primary therapy, all patients underwent tumor marker monitoring for CEA and CA 15-3 at 6-week intervals. A reproducible previously defined increase (≥100%) based on the individual baseline value of each patient was considered as a strong indicator of MBC. For the present analysis, we retrospectively evaluated 1011 blood samples from 95 patients. Forty-seven of these had metastatic disease for the first time at the time of this evaluation, while the remaining 48 patients showed no evidence of disease. The sera of these patients were additionally assessed for the following parameters: cancer antigen (CA) 125, cytokeratin-19 soluble fragment (CYFRA 21-1), HER2 shed antigen, lactate-dehydrogenase (LDH) and C-reactive protein (CRP). Results26 of 47 patients with MBC showed a reproducible tumor marker increase of at least CEA and/or CA 15-3 (55.3%, true-positive). The remaining 21 patients with MBC showed no increase in CEA or CA 15-3 (44.7%, false negative, FN). By combining all markers mentioned above, 41 of 47 patients with MBC showed a reproducible marker increase with a sensitivity of 87.2% and specificity of 100%. ConclusionThis retrospective analysis indicates that a panel of biomarkers can increase the sensitivity of the CA 15-3/CEA combination without loss of specificity. The combined use is therefore helpful for early detection of MBC.

Sonographic Detection of Metastatic Breast Cancer in the Liver

Sonography is an effective imaging modality for detecting the presence of breast cancer that has metastasized to other organs. Early determination of the presence of these metastatic lesions has proved essential in improving the survival of patients with this disease. This case study presents a patient who was diagnosed with breast cancer, treated, and considered cancer free 9 months prior to the sonogram presented. Within these 9 months, the breast cancer had metastasized to the liver, where it was initially detected on a right upper quadrant sonogram, evaluated further by computed tomography, and definitively diagnosed by histopathology following core needle biopsy.

Comparison of three different molecular assays for the detection and molecular characterization of circulating tumor cells in breast cancer

Objective Comparison of three different molecular assays for the detection and molecular characterization of circulating tumor cells in breast cancer. Methods The retrospective study compared three different molecular assays to detect CTC in the peripheral blood of 30 healthy individuals and 71 benign breast disease patients and 83 early and 84 metastatic breast cancer patients.All samples were collected at the outpatient, inpatient and physical examination department of Sichuan Provincial People's Hospital from January 2011 to June 2014. The same cDNAs were analyzed by: singleplex RT–qPCR assay for BCL–2, multiplex RT–qPCR for BCL–2, HER–2, HMAM, and a commercially available molecular assay (AdnaTest BreastCancer) for GA733–2, MUC–1, HER–2. The positive of CTC were compared among healthy individuals and benign breast disease patients and breast cancer patients. Chi square test was used to compare the expression of gene markers among the three groups, and the agreement of Kappa test was used to evaluate the method. Results (1) Detection rates of early breast cancer by single RT–qPCR, Adna kits and multiple RT–qPCR were 13.3%, 16.9% and 18.1%, respectively, and the detection of metastatic breast cancer were 31.0%, 42.9% and 35.7%, respectively. There were significant differences in the positive of CTC by three molecular assays between healthy individuals and benign breast disease patients and early breast cancer patients (The test values were 4.235 and 4.301, 5.367 and 5.474, 5.894 and 6.023 respectively, P 0.05). There were significant differences between metastasis breast cancer patients and healthy individuals and benign breast disease patients and early breast cancer patients (The test values were 8.429, 7.553 and 7.061; 10.24, 9.025 and 8.745; 9.658, 8.417 and 8.201 respectively, P<0.05). (2) In early breast cancer: The concordance between AdnaTest and single RT–qPCR was 79.5% while between AdnaTest and multiplex RT–qPCR was 77.1%.No agreement was found among them (The test values were 1.065 and 1.871, P were 0.371 and 0.258). The concordance between single RT–qPCR and multiplex RT–qPCR was 80.7%.No agreement was found between them (The test values was 2.814, P was 0.156). (3) In patients with overt metastasis: The concordance between AdnaTest and single RT–qPCR was 78.6%(The test values was 10.986). While between AdnaTest and multiplex RT–qPCR was 80.9%(The test values was 9.251). Agreements were found among them (P was 0.002 and 0.005 respectively). The concordance between single and multiplex RT–qPCR was 88.1%(The test values was 12.364). Agreement was found between them (P was 0.001). Conclusions No correlations were found among different molecular methods to detect CTC in the early primary breast cancer, but correlations were found in the metastatic breast cancer, suggesting that different rate of CTC caused by the number of CTC and its heterogeneity should be considered to the clinical diagnosis and treatment of breast cancer while molecular method is used.(Chin J Lab Med, 2015, 38: 666–671) Key words: Breast neoplasms; Neoplastic cells, circulating; Tumor markers, biological; Reverse transcriptase polymerase chain reaction

Diagnostic efficacy of CA 15-3 and CEA in the early detection of metastatic breast cancer—A retrospective analysis of kinetics on 743 breast cancer patients

ObjectiveWe investigated the diagnostic capacity of CEA and CA 15-3 kinetics for the early detection of metastatic disease in comparison to fixed cut off values. MethodsIn a retrospective analysis, a total of 743 patients with early breast cancer and available baseline values of CEA and CA 15-3 were included. A reproducible increase of 100% of single or combined markers was considered as a strong indicator of metastatic disease. Results187 patients developed metastatic disease and 556 remained disease-free. On the basis of tumor marker kinetics, we reached a specificity of >98% for both biomarkers and a sensitivity of 40.6% for CEA alone, 55.6% for CA 15-3 alone and 66.3% for the combination of both markers. Using fixed cut-off values (CEA: 4ng/mL, CA 15-3: 30U/mL) we ended up with a specificity of 86.3% and a sensitivity of 70.6% for the combination of CEA and CA 15-3. Using higher cut-off values (CEA: 6ng/mL, CA 15-3: 60U/mL) we reached a specificity of 96.9% and a sensitivity of 49.7% for the combination. ConclusionWe conclude that the interpretation of these markers in follow-up using individual baseline values and kinetics leads to a significant superior profile of specificity and sensitivity.