Malignant Breast Research Articles

Shear wave elastography of the breast—Immunohistopathology and molecular subtype comparisons

AbstractIntroductionThis study evaluated the shear wave elastography (SWE) in kilopascals (kPa) and metres per second (m/s) of immunohistochemical (IHC) factors, molecular subtypes, and the relationship between Kiel‐67 (Ki67) and IHC factors to explore their prognostic significance in malignant breast cancer.MethodsThis single‐centre study included 303 patients with 405 solid breast lesions, biopsied and examined using B‐mode ultrasound and SWE. Elastography mean (Emean), maximum (Emax), and ratio (Eratio) variables in kPa and m/s were calculated for each lesion.ResultsAmong 405 samples, 114 malignant lesions were identified. In IHC comparisons, only the E ratio (m/s) showed a significant difference, with Ki67 high significantly greater than Ki67 low (p = 0.016). Molecular subtype comparisons using kPa and m/s values revealed significant differences in Emean and Emax (p < 0.05), with HER2+ subtypes showing the highest values. Correlation analyses showed a significant relationship between Ki67 and molecular subtypes for Eratio in both kPa and m/s (p < 0.05). Triple‐negative cytokeratin (CK5/6) positive was significantly greater than CK5/6 negative for Eratio in kPa (14.1 ± 3.9 vs. 7.9 ± 0.7, p = 0.029) and m/s (3.7 ± 0.5 vs. 2.8 ± 0.4, p = 0.021).ConclusionBoth kPa and m/s SWE variables identify similar yet slightly different results for prognostic IHC factors and molecular subtypes. Examining both kPa and m/s SWE variables may be useful as a non‐invasive method for predicting IHC factors and molecular subtypes to characterise breast lesions before biopsy or surgery.

Ultrasound Multimodality Examination Improves the Diagnostic Efficiency of Non-Mass-Like Breast Lesions

This study is focused on ultrasound multimodality examination, which refers to the combined use of three ultrasound examination modalities, ultrasound (US), acoustic radiation force impulse (ARFI) imaging, and contrast-enhanced ultrasound (CEUS). The purpose of this study is to analyze the value of applying ultrasound multimodality examination in the differential diagnosis of benign and malignant breast non-mass-like lesions (NMLs). Cases of breast NMLs were analyzed retrospectively, and the nature of all the lesions was verified by pathological examination. Based on the gray-scale ultrasound image characteristics, the cases were classified into types Ⅰ to Ⅴ, and type Ⅰ and type Ⅱ were further classified into 4 subtypes, Ⅰa, Ⅰb, Ⅱa, and Ⅱb, according to whether there was also calcification, and the proportion of malignant cases in each subtype was statistically analyzed. Logistic regression models of US, US+ARFI, US+CEUS, and US+ARFI+CEUS for the diagnosis of malignant cases were established, ROC curves were drawn, the area under the curve (AUC) was calculated, and comparisons were made accordingly. The detection rate of malignant NMLs without calcification (atypical malignant NMLs) by the combination examination of US, ARFI, and CEUS was analyzed. A total of 407 cases were included in the study. All subjects were female, aged 22 to 81 years, with the average age being (47.0±11.0) years. There were 220 benign cases and 187 malignant cases. Ranked from the highest to the lowest, the malignancy proportion of the different types was Ⅰb>Ⅱb>Ⅲ>Ⅴ>Ⅰa>Ⅱa>Ⅳ. The malignant proportion of the low echo area with calcification was significantly higher than that of the lesions without calcification. The AUC (95% confidence interval [CI]) for diagnosing malignant cases with the logistic regression models of US, US+ARFI, US+CEUS, and US+ARFI+CEUS were 0.895 (0.862-0.927), 0.908 (0.878-0.937), 0.921 (0.893-0.948), and 0.927 (0.902-0.952), respectively. Comparison of the AUC of the 4 regression models showed significant differences (P<0.001). The detection rate of US for NMLs without calcification was 80.7%. When US was used in combination with ARFI and CEUS, 86.4% of the malignant NMLs lesions without calcification could be detected if the lesion CEUS score was 4 or 5 points or if shear-wave velocity (SWV)≥4.28 m/s. Breast NMLs with calcification show high risks of malignancy, and a pathological examination is always recommended for a conclusive diagnosis. Ultrasound multimodality examination can improve the diagnostic accuracy of breast NML without calcification.

Estrogen Signals through ERβ in Breast Cancer; What We Have Learned since the Discovery of the Receptor.

Estrogen receptor (ER) β (ERβ) is the second ER subtype that mediates the effects of estrogen in target tissues along with ERα that represents a validated biomarker and target for endocrine therapy in breast cancer. ERα was the only known ER subtype until 1996 when the discovery of ERβ opened a new chapter in endocrinology and prompted a thorough reevaluation of the estrogen signaling paradigm. Unlike the oncogenic ERα, ERβ has been proposed to function as a tumor suppressor in breast cancer, and extensive research is underway to uncover the full spectrum of ERβ activities and elucidate its mechanism of action. Recent studies have relied on new transgenic models to capture effects in normal and malignant breast that were not previously detected. They have also benefited from the development of highly specific synthetic ligands that are used to demonstrate distinct mechanisms of gene regulation in cancer. As a result, significant new information about the biology and clinical importance of ERβ is now available, which is the focus of discussion in the present article.

Combination of Breast Ultrasound With Magnetic Resonance Imaging in the Diagnosis of Non-mass-like Breast Lesions Detected on Ultrasound: A New Integrated Strategy to Improve Diagnostic Performance

The aim of the work described here was to evaluate the diagnostic performance of a new integrated strategy using breast ultrasound (US) combined with magnetic resonance imaging (MRI) to differentiate benign and malignant breast non-mass-like lesions (NMLs) detected on US. From October 2017 to January 2021, 183 NMLs detected on US that had undergone MRI examinations were included in this respective study. Pathological results were used as the reference standard. The integrated diagnostic strategy of breast US combined with MRI based on a combination of MRI Breast Imaging Reporting and Data System (BI-RADS) with discriminant sonographic indicators highly associated with malignancy was established and validated in a cohort of 61 women. The diagnostic performances of US, MRI and the combined method were calculated and compared. In the training set, the area under the receiver operating characteristic curve (AUC), sensitivity and specificity of US, MRI and the integrated diagnostic strategy using US combined with MRI for NMLs were 0.730, 93.7% and 52.3%; 0.849, 94.7% and 75.0%; and 0.901, 92.6% and 87.5%, respectively. Compared with US or MRI alone, the integrated diagnostic strategy significantly increased the AUC (p < 0.001, p=0.007) and specificity (p < 0.001, p=0.034) while maintaining high sensitivity (p=0.774, p=0.551). In the validation set, the integrated strategy of US combined with MRI (AUC=0.899) also had good performance compared with US (AUC=0.728) or MRI (AUC=0.838). The integrated diagnostic strategy of US combined with MRI exhibited good performance for breast NMLs compared with either modality used alone, which can improve the diagnostic specificity while maintaining high sensitivity.

Detection of Early Myocardial Dysfunction by Imaging Biomarkers in Cancer Patients Undergoing Photon Beam vs. Proton Beam Radiotherapy: A Prospective Study.

1. Background: We sought to determine acute and subacute changes in cardiac function after proton beam (PBT) and photon beam (PhT) radiotherapy (RT) using conventional and two-dimensional speckle tracking echocardiography (2D-STE) in patients with malignant breast and thoracic tumors. 2. Methods: Between March 2016 and March 2017, 70 patients with breast or thoracic cancer were prospectively enrolled and underwent transthoracic echocardiography with comprehensive strain analysis at pretreatment, mid-treatment, end of treatment, and 3 months after RT. 3. Results: PBT was used to treat 44 patients; PhT 26 patients. Mean ± SD age was 55 ± 12 years; most patients (93%) were women. The median (interquartile range) of the mean heart dose was lower in the PBT than the PhT group (47 [27-79] vs. 217 [120-596] cGy, respectively; p < 0.001). Ejection fraction did not change in either group. Only the PhT group had reduced systolic tissue Doppler velocities at 3 months. 2D-STE showed changes in endocardial and epicardial longitudinal, radial, and circumferential early diastolic strain rate (SRe) in patients undergoing PhT (global longitudinal SRe, pretreatment vs. end of treatment (p = 0.04); global circumferential SRe, pretreatment vs. at 3-month follow-up (p = 0.003); global radial SRe, pretreatment vs. at 3-month follow-up (p = 0.02) for endocardial values). Epicardial strain values decreased significantly only in patients treated with PhT. Patients in the PhT group had a significant decrease in epicardial global longitudinal systolic strain rate (GLSRs) (epicardial GLSRs, at baseline vs. at end of treatment [p = 0.009]) and in GCSRe and GRSRe (epicardial GCSRe, at baseline vs. at 3-month follow-up (p = 0.02); epicardial GRSRe, at baseline vs. at 3-month follow-up (p = 0.03)) during treatment and follow-up. No changes on 2D-STE were detected in the PBT group. 4. Conclusions: Patients who underwent PhT but not PBT had reduced tissue Doppler velocities and SRe values during follow-up, suggesting early myocardial relaxation abnormalities. PBT shows promise as a cardiac-sparing RT technology.

Diagnostic value of mammography density of breast masses by using deep learning.

In order to explore the relationship between mammographic density of breast mass and its surrounding area and benign or malignant breast, this paper proposes a deep learning model based on C2FTrans to diagnose the breast mass using mammographic density. This retrospective study included patients who underwent mammographic and pathological examination. Two physicians manually depicted the lesion edges and used a computer to automatically extend and segment the peripheral areas of the lesion (0, 1, 3, and 5mm, including the lesion). We then obtained the mammary glands' density and the different regions of interest (ROI). A diagnostic model for breast mass lesions based on C2FTrans was constructed based on a 7: 3 ratio between the training and testing sets. Finally, receiver operating characteristic (ROC) curves were plotted. Model performance was assessed using the area under the ROC curve (AUC) with 95% confidence intervals (CI), sensitivity, and specificity. In total, 401 lesions (158 benign and 243 malignant) were included in this study. The probability of breast cancer in women was positively correlated with age and mass density and negatively correlated with breast gland classification. The largest correlation was observed for age (r = 0.47). Among all models, the single mass ROI model had the highest specificity (91.8%) with an AUC = 0.823 and the perifocal 5mm ROI model had the highest sensitivity (86.9%) with an AUC= 0.855. In addition, by combining the cephalocaudal and mediolateral oblique views of the perifocal 5mm ROI model, we obtained the highest AUC (AUC = 0.877P < 0.001). Deep learning model of mammographic density can better distinguish benign and malignant mass-type lesions in digital mammography images and may become an auxiliary diagnostic tool for radiologists in the future.

The application of clinical variable-based nomogram in predicting overall survival in malignant phyllodes tumors of the breast.

Background: We aimed to explore prognostic risk factors in patients with malignant phyllodes tumors (PTs) of the breast and construct a survival prediction model. Methods: The Surveillance, Epidemiology, and End Results database was used to collect information on patients with malignant breast PTs from 2004 to 2015. The patients were randomly divided into training and validation groups using R software. Univariate and multivariate Cox regression analyses were used to screen out independent risk factors. Then, a nomogram model was developed in the training group and validated in the validation group, and the prediction performance and concordance were evaluated. Results: The study included 508 patients with malignant PTs of the breast, including 356 in the training group and 152 in the validation group. Univariate and multivariate Cox proportional hazard regression analyses showed that age, tumor size, tumor stage, regional lymph node metastasis (N), distant metastasis (M) and tumor grade were independent risk factors for the 5-year survival rate of patients with breast PTs in the training group (p < 0.05). These factors were used to construct the nomogram prediction model. The results showed that the C-indices of the training and validation groups were 0.845 (95% confidence interval [CI] 0.802-0.888) and 0.784 (95% CI 0.688-0.880), respectively. The calibration curves of the two groups were close to the ideal 45° reference line and showed good performance and concordance. Receiver operating characteristic and decision curve analysis curves showed that the nomogram has better predictive accuracy than other clinical factors. Conclusion: The nomogram prediction model constructed in this study has good predictive value. It can effectively assess the survival rates of patients with malignant breast PTs, which will aid in the personalized management and treatment of clinical patients.

An effective convolutional neural network for classification of benign and malignant breast and thyroid tumors from ultrasound images.

Breast and thyroid cancers are the two most common cancers among women worldwide. The early clinical diagnosis of breast and thyroid cancers often utilizes ultrasonography. Most of the ultrasound images of breast and thyroid cancer lack specificity, which reduces the accuracy of ultrasound clinical diagnosis. This study attempts to develop an effective convolutional neural network (E-CNN) for the classification of benign and malignant breast and thyroid tumors from ultrasound images. The 2-Dimension (2D) ultrasound images of 1052 breast tumors were collected, and 8245 2D tumor images were obtained from 76 thyroid cases. We performed tenfold cross-validation on breast and thyroid data, with a mean classification accuracy of 0.932 and 0.902, respectively. In addition, the proposed E-CNN was applied to classify and evaluate 9297 mixed images (breast and thyroid images). The mean classification accuracy was 0.875, and the mean area under the curve (AUC) was 0.955. Based on data in the same modality, we transferred the breast model to classify typical tumor images of 76 patients. The finetuning model achieved a mean classification accuracy of 0.945, and a mean AUC of 0.958. Meanwhile, the transfer thyroid model realized a mean classification accuracy of 0.932, and a mean AUC of 0.959, on 1052 breast tumor images. The experimental results demonstrate the ability of the E-CNN to learn the features and classify breast and thyroid tumors. Besides, it is promising to classify benign and malignant tumors from ultrasound images with the transfer model under the same modality.

Clinical-radiomic models based on digital breast tomosynthesis images: a preliminary investigation of a predictive tool for cancer diagnosis.

This study aimed to develop a clinical-radiomic model based on radiomic features extracted from digital breast tomosynthesis (DBT) images and clinical factors that may help to discriminate between benign and malignant breast lesions. A total of 150 patients were included in this study. DBT images acquired in the setting of a screening protocol were used. Lesions were delineated by two expert radiologists. Malignity was always confirmed by histopathological data. The data were randomly divided into training and validation set with an 80:20 ratio. A total of 58 radiomic features were extracted from each lesion using the LIFEx Software. Three different key methods of feature selection were implemented in Python: (1) K best (KB), (2) sequential (S), and (3) Random Forrest (RF). A model was therefore produced for each subset of seven variables using a machine-learning algorithm, which exploits the RF classification based on the Gini index. All three clinical-radiomic models show significant differences (p < 0.05) between malignant and benign tumors. The area under the curve (AUC) values of the models obtained with three different feature selection methods were 0.72 [0.64,0.80], 0.72 [0.64,0.80] and 0.74 [0.66,0.82] for KB, SFS, and RF, respectively. The clinical-radiomic models developed by using radiomic features from DBT images showed a good discriminating power and hence may help radiologists in breast cancer tumor diagnoses already at the first screening.

The Role of Isoflavones in the Prevention of Breast Cancer and Prostate Cancer

This narrative review summarizes epidemiological studies on breast cancer and prostate cancer with an overview of their global incidence distribution to investigate the relationship between these diseases and diet. The biological properties, mechanisms of action, and available data supporting the potential role of isoflavones in the prevention of breast cancer and prostate cancer are discussed. Studies evaluating the effects of isoflavones in tissue cultures of normal and malignant breast and prostate cells, as well as the current body of research regarding the effects of isoflavones attained through multiple modifications of cellular molecular signaling pathways and control of oxidative stress, are summarized. Furthermore, this review compiles literature sources reporting on the following: (1) levels of estrogen in breast and prostate tissue; (2) levels of isoflavones in the normal and malignant tissue of these organs in European and Asian populations; (3) average concentrations of isoflavones in the secretion of these organs (milk and semen). Finally, particular emphasis is placed on studies investigating the effect of isoflavones on tissues via estrogen receptors (ER).

Determining whether the diagnostic value of B-ultrasound combined with contrast-enhanced ultrasound and shear wave elastography in breast mass-like and non-mass-like lesions differs: a diagnostic test.

Mass-like (ML) and non-mass-like (NML) are two manifestations of breast lesions on ultrasound. Contrast-enhanced ultrasound (CEUS) can make up for the limitation of B-ultrasound (US) in the observation of focal blood flow, and shear wave elastography (SWE) can supplement the hardness information of the lesion. The present study aimed to analyze the characteristic manifestations of US, CEUS, and SWE in NML and ML breast and evaluate whether the diagnostic performance of these three ultrasound techniques differs in terms of differentiating between benign and malignant breast lesions. From January to August 2021, 382 patients (417 breast lesions) underwent US, CEUS, and SWE examinations. Of these, 204 women (218 breast lesions) were included in our study due to subsequent biopsy or surgery with pathological findings. The patients were divided into ML and NML groups according to the ultrasound characteristics, and the differences in multimodal ultrasound performance between benign and malignant NML and benign and malignant ML breast lesions were compared. The diagnostic performance of US, US + CEUS, US + SWE, US + CEUS + SWE for ML, NML and all breast lesions was evaluated by analyzing sensitivity, specificity and area under receiver operating characteristic (ROC) curve (AUC). Pathologically, the 218 lesions included 96 malignant and 122 benign breast lesions. The sensitivity and specificity of US + CEUS + SWE in all lesion groups, ML group and NML group were 92.7% and 90.2%, 95.9% and 90.3%, 91.3% and 79.3%, respectively. In all breast group, AUCs of US + CEUS, US + SWE, US + CEUS + SWE were statistically different from AUC of US (P=0.0010, 0.0001, 0.0001). In the ML group, the AUC of US + CEUS, US + SWE, US + CEUS + SWE were statistically different from that of US (P=0.0120, 0.0008, 0.0002). In the NML group, there was a statistical difference between US + SWE and US AUC (P=0.0149). US, CEUS, and SWE have an important diagnostic value for benign and malignant ML and NML breast lesions. Multimodal ultrasound combined with US, CEUS, and SWE can improve the diagnostic efficacy in distinguishing between benign and malignant ML and NML lesions.

Взаимодействие внеклеточных ловушек нейтрофилов и антифосфолипидных антител у онкологических больных

Activation of NETosis processes has been detected in numerous autoimmune and non-autoimmune diseases with increasing concentrations of antiphospholipid antibodies (APA). Neutrophil extracellular traps (NETs) are an important activator of the coagulation cascade and an integral component of arterial and venous clots in cancer patients. Therefore, APA and NETs may be the links in the pathogenesis of thrombosis in cancer patients. Objective. To evaluate the severity of NETosis, hemostatic system activation and APA circulation (anti-β2-glycoprotein 1 (anti-β2-GPI)) in cancer patients. Design. A prospective controlled interventional non-randomized study. Patients and methods. This study included 144 patients who were divided into two groups: the study group – 111 patients aged 34–72 years with malignant breast and gynecological diseases of stages I–III (endometrial cancer, n = 25; ovarian cancer, n = 36; cervical cancer, n = 17; breast cancer, n = 33), and the control group – 33 healthy women. Prior to therapy, serum concentrations of NETosis markers – citrullinated histone H3 (citH3) and human myeloperoxidase antigen (MPO:Ag), markers of hemostatic activation (D-dimer and thrombin-antithrombin complex), and anti-β2-GPI antibodies were assessed. Results. Anti-β2-GPI antibodies were significantly more common in patients with ovarian cancer compared to controls. A significant correlation between the circulation of anti-β2-GPI and the concentration of MPO:Ag was also detected in these patients. All patients in the study group showed a significant increase in the markers of NETosis and hemostatic activation compared to controls. The revealed correlation between the concentrations of NETosis markers and anti-β2-GPI antibodies in ovarian cancer suggests a possible pathogenetic role of APA in the progression of ovarian cancer and NETs-mediated prothrombotic state against the background of APA circulation. It can be assumed that APA formed in cancer patients may be one of the triggers of NETosis. NETosis itself contributes to the development of thrombotic events and stimulates further synthesis of APA. Perhaps it is the activation of NETosis that explains the worse prognosis in cancer patients with APA circulation. Conclusion. The results of this study improve the understanding of interactions between the immune and hemostatic systems. Further research is needed to determine the role of APA in NETosis, as well as the role of NETosis and APA circulation in tumor progression, metastasis, and cancer-associated thrombosis. Key words: neutrophil extracellular traps, NETosis, antiphospholipid antibodies, cancer, neutrophils, anti-β2-GPI

Single cell atlas identifies lipid-processing and immunomodulatory endothelial cells in healthy and malignant breast

Since a detailed inventory of endothelial cell (EC) heterogeneity in breast cancer (BC) is lacking, here we perform single cell RNA-sequencing of 26,515 cells (including 8433 ECs) from 9 BC patients and compare them to published EC taxonomies from lung tumors. Angiogenic ECs are phenotypically similar, while other EC subtypes are different. Predictive interactome analysis reveals known but also previously unreported receptor-ligand interactions between ECs and immune cells, suggesting an involvement of breast EC subtypes in immune responses. We also identify a capillary EC subtype (LIPEC (Lipid Processing EC)), which expresses genes involved in lipid processing that are regulated by PPAR-γ and is more abundant in peri-tumoral breast tissue. Retrospective analysis of 4648 BC patients reveals that treatment with metformin (an indirect PPAR-γ signaling activator) provides long-lasting clinical benefit and is positively associated with LIPEC abundance. Our findings warrant further exploration of this LIPEC/PPAR-γ link for BC treatment.

Abstract 20: Cancer incidence in the U.S. military: An updated analysis

Abstract Background: Active duty military service members and the general US population differ in several ways related to cancer occurrence. This study aimed to update and expand our previous study which compared incidence of six cancers between the U.S. military and general populations. Methods: Cancers included in this study were pathologically confirmed malignant lung, colorectal, testicular, prostate, cervical and breast tumors diagnosed 1990-2013. The study populations were men and women aged 20-59 in the US active duty military and the population in nine areas covered by the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) cancer registry program. Military data were from the Department of Defense’s Automated Central Tumor Registry (ACTUR) and Defense Manpower Data Center. Age adjusted rates in ACTUR and SEER and incidence rate ratios (IRR) and 95% confidence intervals (95% CI) comparing ACTUR to SEER were calculated. Comparisons were made by sex, race, and cancer stage. Results: Age adjusted incidence rates of colorectal cancer were significantly lower in ACTUR than SEER among White (IRR 0.78; 95% CI 0.72-0.84) and Black men (IRR 0.86; 95% CI 0.74-1.00), respectively. Lung cancer incidence was lower in ACTUR than SEER among White (IRR 0.55; 95% CI 0.49-0.62) and Black men (IRR 0.34; 95% CI 0.26-0.42) and White women (IRR 0.74; 95% CI 0.53-0.98). Whites in ACTUR had significantly lower incidence of testicular cancer (IRR 0.92; 95% CI 0.88-0.96). Lower incidence of cervical cancer in ACTUR was observed among both Whites (IRR 0.82; 95% CI 0.69-0.97) and Blacks (IRR 0.39; 95% CI 0.27-0.54). Incidence of prostate cancer was higher in ACTUR than SEER among both Whites (IRR 2.31; 95% CI 2.18-2.45) and Blacks (IRR 2.35; 95% CI 2.13-2.58). Results by tumor stage showed similar results between the ACTUR and SEER populations for regional and distant tumors, while no differences between the two were observed for localized tumors, except in the case of prostate cancer. Incidence of localized and regional prostate tumors was higher in ACTUR than SEER, while there was no significant difference in distant tumors. Conclusion: Active duty service members had lower age adjusted incidence rates of colorectal, lung, testicular, and cervical cancers, but higher rates of prostate cancer than the general US population. While these findings may result from the combined effects of many factors, the lower incidence in the military may be associated with healthier status of service members. In addition, universal health care for active duty military may lead to earlier diagnosis of some tumors, such as prostate cancer, in the military. Disclaimer: The contents of this publication are the sole responsibility of the authors and do not necessarily reflect the views, opinions or policies of USUHS, HJF, the DoD or the Departments of the Army, Navy or Air Force. Mention of trade names, commercial products or organizations does not imply endorsement by the US Government. Citation Format: Julie A. Bytnar, Katherine A. McGlynn, Craig D. Shriver, Kangmin Zhu. Cancer incidence in the U.S. military: An updated analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 20.

Abstract 1071: Efficacy of targeted osmotic lysis using pulsed electric field stimulation compared to paclitaxel for treating murine, triple-negative breast carcinoma

Abstract Targeted osmotic lysis (TOL), the concurrent stimulation of voltage-gated sodium channels (VGSCs) and blockade of Na+ pumps, kills up to 100% of highly malignant, human and murine breast cancer cells in vitro and slows the growth of murine breast cancer homografts and increases survival of the hosts in vivo when compared to homografts treated with negative controls. In this study we compared the efficacy of TOL and paclitaxel, a current standard chemotherapeutic agent for treating advanced murine breast cancer, as a positive control. For this, BALB/c mice with 4T1 homografts were treated with TOL alone, paclitaxel alone or with a combination regimen of paclitaxel and TOL. For TOL, mice received 8 hourly doses (3 mg/kg) of digoxin on 2 successive days. Upon reaching steady-state levels (dose 5) the mice were exposed to 4 X 30 minutes of pulsed electric field stimulation (18 V/m, 10 ms pulses, 15 interstimulus intervals) hourly for a total of 2 hours of stimulation. Alternatively, mice received paclitaxel (20 mg/kg) by i.p. injection. Mice that were treated concurrently with TOL and paclitaxel received paclitaxel 2 days prior to treatment with TOL. Groups of mice that received digoxin alone, stimulation alone, paclitaxel + digoxin, paclitaxel + stimulation or vehicle alone served as negative controls. Initially, the homografts were measured daily and then every other day with a digital caliper until criteria for humane endpoint euthanasia were met. The mean time to meeting criteria for humane endpoint euthanasia in mice treated with paclitaxel alone (2 days) was identical to that observed in the negative controls. Mice treated with TOL alone, on average, met criteria at post-treatment day 5, whereas administration of paclitaxel two days before TOL reduced the effectiveness of TOL, decreasing mean survival to day 3 post-treatment. Immunohistochemical evidence indicated that paclitaxel’s effect on tubulin may impede the transport and insertion of channels into the cell membrane, thereby reducing the channel density and the effectiveness of TOL. By contrast, the administration of TOL either before or after treatment with paclitaxel improved host survival. Normal tissues were unaffected. These results are evidence that TOL is equal to or better than paclitaxel for increasing survival of murine hosts with advanced breast cancer when TOL is administered before or between paclitaxel dosing cycles. Sequential use of TOL may well improve survival, but simultaneous administration of paclitaxel and TOL will likely reduce TOL’s adjunctive benefit. Because of the conserved nature of the sodium channel/sodium pump mechanism, the comparable efficacy to TOL to a currently approved treatment and the favorable adverse effect profile, we submit that TOL warrants further study as a promising option for treating individuals with advanced neoplastic disease. Citation Format: Harry J. Gould, Kelly J. Sherman, Dennis Paul. Efficacy of targeted osmotic lysis using pulsed electric field stimulation compared to paclitaxel for treating murine, triple-negative breast carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1071.

Response to neoadjuvant chemotherapy in breast cancer: do microRNAs matter?

BackgroundConventionally, breast cancer (BC) prognosis and prediction of response to therapy are based on TNM staging, histological and molecular subtype, as well as genetic alterations. The role of various epigenetic factors has been elucidated in carcinogenesis. However, it is still unknown to what extent miRNAs affect the response to neoadjuvant chemotherapy (NACT). This pilot study is focused on evaluating the role of miR-34a, miR-124a, miR-155, miR-137 and miR-373 in response to NACT.MethodsThat was a prospective study enrolling 34 patients with histologically confirmed BC of II-III stages. The median age of patients was 53 (47–59.8) years old, 70.6% of whom were HR-positive. MiRs levels were measured in the primary tumor before and after NACT. The response to therapy was assessed after surgery using the Miller-Payne scoring system. To establish the role of miRs in modulating response to NACT the Cox model was applied for analysis.ResultsBC demonstrated a great variability of miRs expression before and after NACT with no strong links to tumor stage and molecular subtype. Only miR-124a and miR-373 demonstrated differential expression between malignant and normal breast tissues before and after therapy though these distinctions did not impact response to NACT. Besides miR-124a and miR-137 levels after NACT were found to be dependent on HR status. While miR-124a levels increased (p = 0.021) in the tumor tissue, the expression of miR-137 was downregulated (p = 0.041) after NACT in HR positive BC.ConclusionsThe study revealed differences in miR-124a and miR-373 expression after NACT in primary BC tissues. Although miRs levels did not impact the response to NACT, we found miR-124a and miR-137 levels to be related to hormonal sensitivity of BC.

Diagnostic value of Doppler imaging for malignant non-mass breast lesions: with different diagnostic criteria for older and younger women: first results.

To evaluate and optimize the additional diagnostic value of Doppler imaging for malignant NMLs detected by US. The characteristics of 233 NMLs in Doppler imaging were analyzed, and different Adler grades of intralesional vessels were selected as the diagnostic cutoffs on Doppler imaging: grade 1 in the full cohort and in women < 40 years, and grade 0 in women ≥40 years. The diagnostic performance of US and US + Doppler imaging were calculated and compared with that of mammography. The AUC of US + Doppler was larger than that of US alone in each group (P < 0.001). In the full cohort, addition of Doppler imaging increased specificity of US, but decreased sensitivity. However, by use of different diagnostic cutoffs in the two subgroups, it was possible to achieve high sensitivity and specificity simultaneously, which were 100% and 75.8% in women < 40 years, 94.7% and 69.5% in women ≥40 years, respectively. The AUC + Doppler was comparable to that of mammography in the full cohort and in women ≥40 years. In women < 40 years, the AUC of the combination was larger than that of mammography (P < 0.001). Doppler imaging, with different Adler grades used as cutoffs in older versus younger women, can improve the specificity of US for the diagnosis of malignant NMLs without losing sensitivity. In younger women, US + Doppler imaging may be better than mammography.

Is there a threshold for red cell distribution width to predict malignancy in breast masses?

Red cell distribution width (RDW) has been shown to have predictive properties in different diseases as well as solid cancers. We aimed to investigate the discriminative properties of RDW in benign and malignant breast lesions. In a retrospective cohort study the files of patients who underwent surgery for fibroadenomas (Group A) and breast cancer with axillary lymph node metastasis (Group B) were reviewed. The pathology reports and laboratory parameters and demographics of the patients were recorded for comparison. The patients were later excluded if they had an hemoglobin level below 12 mg/dl and the outliers were removed for a comparison. Seventy-six patients in the fibroadenoma group and 62 patients in the breast malignancy group were compared for the RDW levels to predict the presence of malignancy. Receiver operating characteristic curves were plotted for RDW and a threshold for prediction of malignancy was calculated. The difference in RDW levels between group A and group B was found to be significant, 13,10% (IQR 12.60 -13.70) versus 13,80% (IQR 13.10-14.40) respectively, P = 0,00. The area under the curve was 0.71 (95% confidence interval 0.62 to 0.79), P = 0,00. For the threshold of 13,75 the positive predictive value was 67.35 (95% CI 55.72 to 77.17) and negative predictive value was 67.42 (95% CI 60.76% to 73.44). The RDW levels, after adjusted for anemia, were found to have a positive prediction for malignancy in more than two thirds of the patients for the level of 13.75%.

Diagnostic role of dynamic contrast-enhanced magnetic resonance imaging in differentiating breast lesions.

This study aimed to assess the diagnostic role of perfusion weighted image (DCE-PWI) to differentiate benign from malignant breast lesions. The study comprised 32 women who had mammography and/or breast ultrasonography findings that were clinically questionable. All patients were fasting during the magnetic resonance imaging (MRI) test to avoid nausea or dynamic contrast-enhanced vomiting from the contrast medium. In this study, we observed the form of the dynamic curve (time and signal intensity curve) type I (persistent curve) was noted in 12 lesions (37.5%): 10 lesions were benign and two lesions were malignant; type II (plateau curve) was noted in eight lesions (25%): three lesions were benign and five lesions were malignant, and type III (washout curve) noted in 12 lesions (37.5%): one lesion was benign and 11 lesions were malignant. The dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) perfusion technique plays an important role in differentiating benign and malignant tumors in breast cancer.

Automatic identification of triple negative breast cancer in ultrasonography using a deep convolutional neural network

Triple negative (TN) breast cancer is a subtype of breast cancer which is difficult for early detection and the prognosis is poor. In this paper, 910 benign and 934 malignant (110 TN and 824 NTN) B-mode breast ultrasound images were collected. A Resnet50 deep convolutional neural network was fine-tuned. The results showed that the averaged area under the receiver operating characteristic curve (AUC) of discriminating malignant from benign ones were 0.9789 (benign vs. TN), 0.9689 (benign vs. NTN). To discriminate TN from NTN breast cancer, the AUC was 0.9000, the accuracy was 88.89%, the sensitivity was 87.5%, and the specificity was 90.00%. It showed that the computer-aided system based on DCNN is expected to be a promising noninvasive clinical tool for ultrasound diagnosis of TN breast cancer.