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Conventional benign tumor excision leaves scars on the skin surface of the breast, which is unacceptable for young patients. The feasibility and clinical results of endoscopic resection of benign breast tumors through a single axillary incision via an inflatable method were evaluated., Methods: Clinicopathological data from 62 patients who underwent this procedure from June 2022 to July 2023 were retrospectively collected. The surgical success rate, number of tumors excised, operative time, intraoperative conditions, postoperative complications, and clinical outcomes were analyzed., Results: A total of 144 benign tumors were resected, and the surgical success rate was 100% (62/62). The time required to resect tumors located in the inner quadrant with larger diameters was shorter than the time to resect tumors located in the outer quadrant with smaller tumors. Sixty-two patients experienced reduced intraoperative bleeding and did not experience skin burns, incision infections, or poor healing. However, all patients experienced varying degrees of subcutaneous emphysema during the postoperative period. Fourteen patients experienced minor local effusions, and 3 patients experienced mild upper limb dysfunction, which resolved within one month. During the six-month follow-up period, there were no cases of tumor recurrence or new tumors. The ABNSW score was above 14 points, and patient satisfaction was high., Conclusion: Endoscopic resection of benign breast tumors through a single incision in the axilla via the inflatable method could quickly remove lesions larger than 3.0 cm. This method also results in hidden scars and good cosmetic effects on the shape of the breast. This is a new and effective treatment for benign breast tumors., Trial Registration: This retrospective study was registered in the National Medical Research Registry filing system ( https://www.medicalresearch.org.cn ) (No. MR-44-22-007981) and recorded in the Medical Research Division of our hospital (No. NYXJS-22-021)., Competing Interests: Declarations. Conflict of interest: All the authors declare that they have no competing interests. Ethics approval and consent to participate: This retrospective study received approval from the medical ethics committee of the Sixth Affiliated Hospital of South China University of Technology (SCUT) (ethics approval number: 2022088, approval date: 2022.5.9). Informed consent was obtained from all patients enrolled in the study. Consent for publication: The clinical data that were used in this study were authorized by each patient to be publicly published., (© 2024. Italian Society of Surgery (SIC).)

We present one of the largest cohorts of TP53-pathogenic germline variants (PGVs) associated with patients with Li-Fraumeni syndrome (n = 82) with breast tumors (19 to 76 y; median age: 35). Most had missense variants (77%), followed by large gene rearrangements (LGRs; 12%), truncating (6%), and splice-site (5%) variants. Twenty-one unique germline missense variants were found, with hotspots at codons 175, 181, 245, 248, 273, 334, and 337. Of 100 total breast tumors, 63% were invasive (mostly ductal), 30% pure ductal carcinoma in situ, 4% fibroepithelial lesions, and 3% with unknown histology. Unlike BRCA-associated tumors, approximately half of the breast cancers exhibited HER2-positivity, of which ~50% showed estrogen receptor coexpression. Pathology slides were available for review for 61 tumors (44 patients), and no significant correlation between the type of TP53 PGVs and histologic features was noted. High p53 immunohistochemistry expression (>50%) was seen in 67% of tumors tested (mostly missense variant). Null pattern (<1% cells) was seen in 2 (LGR and splicing variants carriers). Surprisingly, 2 tumors from patients with an LGR and 1 tumor from a patient with a truncating variant showed p53 overexpression (>50%). The subset of patients with the Brazilian p.R337H variant presented at a higher age than those with non-p.R337H variant (46 vs 35 y) though statistically insignificant (P = 0.071) due to an imbalance in the sample size, and were uniquely negative for HER2-overexpressing tumors. To conclude, breast cancer in carriers of TP53 PGVs has some unique clinicopathological features that suggest differential mechanisms of tumor formation. p53 immunohistochemistry cannot be used as a surrogate marker to identify germline TP53-mutated breast cancers., Competing Interests: Conflicts of Interest and Source of Funding: The authors have disclosed that they have no significant relationships with, or financial interest in, any commercial companies pertaining to this article., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Background: Breast cancer has distinct causes and prognoses in patients with premenopausal and postmenopausal status. The expression status of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) are analyzed by immunohistochemistry (IHC) to classify molecular subtypes of breast cancer among which large differences in prognosis exist., Methods: The mRNA expression of ESR1 (encoding ERα), ESR2 (encoding ERβ), PGR (encoding PR), and ERBB2 (encoding HER2) was analyzed based on menopausal status (pre- vs post-menopausal) in tumors from breast cancer patients with different receptor status, in R programming environment, using transcriptomics data from TCGA-BRCA project., Results: In ER-positive or PR-positive or HER2-negative breast tumors, ESR1 transcript levels were found to be higher in tumors from postmenopausal women than those from premenopausal women; in contrast, ESR2 transcript levels were lower in tumors from postmenopausal women than those from premenopausal women. Furthermore, PGR mRNA expression was lower in breast tumors from postmenopausal women than those from premenopausal women, only in those with ER + or PR + status. The expression of these genes between tumors from pre- and post-menopausal patients with breast cancer was also analyzed based on the combination of status of three receptors., Conclusion: Together, the results suggest that mRNA expression of ESR1, ESR2, and PGR might differ depending on menopausal status in breast tumors with certain receptor status. More importantly, the change in the expression of ESR1 and ESR2 following menopause is in the opposite directions in breast cancer patients showing the need to identify particular molecular mechanisms regulating the expression of ER isoforms post-menopause in different directions in breast cancer patients, considering the high clinical importance of these receptors in terms of the prognosis of patients with breast cancer., (© 2024. The Author(s), under exclusive licence to Federación de Sociedades Españolas de Oncología (FESEO).)

Breast tumors remain a complex and prevalent health burden impacting millions of individuals worldwide. Challenges in treatment arise from the invasive nature of traditional surgery and, in malignancies, the complexity of treating metastatic disease. The development of noninvasive treatment alternatives is critical for improving patient outcomes and quality of life. This review aims to explore the advancements and applications of focused ultrasound (FUS) technology over the past 2 decades. FUS offers a promising noninvasive, nonionizing intervention strategy in breast tumors including primary breast cancer, fibroadenomas, and metastatic breast cancer., Competing Interests: Disclosure The work of N.D. Sheybani was supported by funding from the National Institutes of Health Director’s Early Independence Award (DP5OD031846) and Wallace H. Coulter Center for Translational Research. The work of Z.E.F. Demir was supported by an NIH Cancer Training Grant (T32 CA009109)., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Benign breast tumors are a nonthreatening condition defined as abnormal cell growth within the breast without the ability to invade nearby tissue. However, benign lesions hold valuable biological information that can lead us toward better understanding of tumor biology. In this study, we have used two pathway analysis algorithms, Pathifier and gene set variation analysis (GSVA), to identify biological differences between normal breast tissue, benign tumors and malignant tumors in our clinical dataset. Our results revealed that one-third of all pathways that were significantly different between benign and malignant tumors were immune-related pathways, and 227 of them were validated by both methods and in the METABRIC dataset. Furthermore, five of these pathways (all including genes involved in cytokine and interferon signaling) were related to overall survival in cancer patients in both datasets. The cellular moieties that contribute to immune differences in malignant and benign tumors were analyzed using the deconvolution tool, CIBERSORT. The results showed that levels of some immune cells were specifically higher in benign than in malignant tumors, and this was especially the case for resting dendritic cells and follicular T-helper cells. Understanding the distinct immune profiles of benign and malignant breast tumors may aid in developing noninvasive diagnostic methods to differentiate between them in the future., (© 2024 The Authors. Molecular Oncology published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.)

Designing highly biocompatible organic semiconducting conjugated polymer dots (Pdots) with bright fluorescence and superior absorption properties in the second near-infrared window (NIR-II: 1000-1700 nm) remains a huge challenge for tumor phototheranostics. In this study, we constructed 4T1 cell membrane-coated m -PBTQ4F Pdots (CPdots) with enhanced NIR-II photoacoustic (PA) and fluorescence (FL) imaging capability for NIR-II photothermal therapy (PTT) of breast tumors. Our findings demonstrated that CPdots could specifically target breast tumors, leading to enhanced tumor accumulation after systemic administration in living mice. In addition, CPdots can not only serve as contrast agents for NIR-II PA and FL imaging for improved breast tumor detection but also generate more cytotoxic heat to improve PTT efficacy. Therefore, this pilot study opens an option avenue for developing new NIR-II Pdots with homologous targeting capability for enhanced phototheranostics of breast tumors.

The complexity and compensatory evolution of tumors weaken the effectiveness of single antitumor therapies. Therefore, multimodal combination therapies hold great promise in defeating tumors. Herein, we constructed a multi-level regulatory co-delivery system based on chemotherapy, phototherapy, and immunotherapy. Briefly, curcumin (Cur) was prepared as nanoparticles and coated with polydopamine (PDA) to form PCur-NPs, which along with an immune checkpoint inhibitor (indoximod, IND) were then loaded into a thermosensitive Pluronic F127 (F127) hydrogel to form a multifunctional nanocomposite hydrogel (PCur/IND@Gel). The in situ-formed hydrogel exhibited excellent photothermal conversion efficiency and sustained drug release behavior both in vitro and in vivo. In addition, PCur-NPs showed enhanced cellular uptake and cytotoxicity under NIR laser irradiation and induced potent immunogenic cell death (ICD). After intratumoral injection of PCur/IND@Gel, significant apoptosis in 4T1 tumors was induced, dendritic cells in lymph nodes were highly activated, potent CD8 + and CD4 + antitumor immune responses were elicited and regulative T cells in tumors were significantly reduced, which notably inhibited the tumor growth and prolonged the survive time of 4T1 tumor-bearing mice. Therefore, this injectable nanocomposite hydrogel is a promising drug co-delivery platform for chemo-photothermal-immunotherapy of breast tumors., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

"Just Accepted" papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence . This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. Purpose To evaluate and compare performance of different artificial intelligence (AI) models in differentiating between benign and malignant breast tumors on diffusion-weighted imaging (DWI), including comparison with radiologist assessments. Materials and Methods In this retrospective study, patients with breast lesions underwent 3T breast MRI from May 2019 to March 2022. In addition to T1-weighted imaging, T2-weighted imaging, and contrast-enhanced imaging, DWI was acquired five b-values (0, 200, 800, 1000, and 1500 s/mm 2 ). DWI data split into training and tuning and test sets were used for the development and assessment of AI models, including a small 2D convolutional neural network (CNN), ResNet18, EfficientNet-B0, and a 3D CNN. Performance of the DWI-based models in differentiating between benign and malignant breast tumors was compared with that of radiologists assessing standard breast MRI, with diagnostic performance assessed using receiver operating characteristic analysis. The study also examined data augmentation effects (A: random elastic deformation, B: random affine transformation/random noise, and C: mixup) on model performance. Results A total of 334 breast lesions in 293 patients (mean age [SD], 56.5 [15.1] years; all female) were analyzed. 2D CNN models outperformed the 3D CNN on the test dataset (area under the receiver operating characteristic curve [AUC] with different data augmentation methods: 0.83-0.88 versus 0.75-0.76). There was no evidence of a difference in performance between the small 2D CNN with augmentations A and B (AUC 0.88) and the radiologists (AUC 0.86) on the test dataset ( P = .64). When comparing the small 2D CNN to radiologists, there was no evidence of a difference in specificity (81.4% versus 72.1%; P = .64) or sensitivity (85.9% versus 98.8%; P = .64). Conclusion AI models, particularly a small 2D CNN, showed good performance in differentiating between malignant and benign breast tumors using DWI, without needing manual segmentation. ©RSNA, 2024.

Background and Aim Breast cancer is a leading cause of cancer-related deaths among women, and ultrasound imaging is crucial for early detection. However, variability in interpretation can affect diagnosis. Therefore, this study compared the performance of artificial neural networks (ANNs) and support vector machines (SVMs) in classifying breast tumors using ultrasound images. Method This comparative study was conducted from June 1, 2023, to June 1, 2024, using a convenience sampling method. Data were gathered from the Center for Breast Diseases at Nanakali Hospital in Erbil, Kurdistan Region of Iraq, and a publicly available dataset from Kaggle. ANN and SVM models were then applied to classify the tumors. Statistical analysis was performed using R (R Foundation for Statistical Computing, Vienna, Austria) and IBM SPSS Statistics for Windows, Version 28.0 (Released 2021; IBM Corp., Armonk, New York, United States), with performance metrics such as accuracy, sensitivity, specificity, and Kappa coefficient calculated for both models. Results The ANN model achieved an accuracy of 87.78%, with a sensitivity of 86.67% and a specificity of 88.89%. The SVM model demonstrated an accuracy of 86.67%, with a higher specificity of 95.56% but a lower sensitivity of 77.78%. Both models showed substantial agreement between predicted and actual classifications, with Kappa coefficients of 75.56% for ANN and 73.33% for SVM. The mean, skewness, and area were identified as the most important variables for the ANN model, while solidity, circularity, and perimeter were the most critical features of the SVM model. Conclusions The results indicated that ANN had a marginally higher accuracy than SVM in classifying breast tumors. It is recommended to further optimize these models for clinical use, improve the integration of machine learning in medical imaging, and expand the dataset to enhance model generalizability and robustness., Competing Interests: Human subjects: Consent for treatment and open access publication was obtained or waived by all participants in this study. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Othman Abdullah et al.)

Background: Vasculogenic mimicry (VM) is an alternative intratumoral microcirculation system that depends on the capacity of tumor cells to reorganize and grow in three-dimensional (3D) channel architectures like the capillaries formed by endothelial cells. Both VM and angiogenesis may coordinately function to feed cancer cells, allowing tumor growth. Long noncoding RNAs (lncRNAs) regulate critical cellular functions in cancer cells, including cell proliferation, apoptosis, angiogenesis, invasion, and metastasis. The lncRNA, known as actin filament-associated protein 1-antisense RNA 1 (AFAP1-AS1), has been described as an oncogene in diverse types of cancers. However, its role in VM and metastasis in triple-negative breast cancer (TNBC) is unknown., Methods: Reverse transcription and quantitative polymerase chain reaction (RT‒qPCR) experiments were performed to evaluate the expression of 10 selected lncRNAs from literature in metastatic and nonmetastatic biopsies from TNBC patients. The expression of AFAP1-AS1 was analyzed in Genotype-Tissue Expression Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) datasets. The AFAP1-AS1 expression was knocked in TNBC Hs578T cells by transfection of specific siRNAs. Channel-like formation assays were performed using 3D cultures over Matrigel in hypoxia-treated Hs578T cancer cells with diminished expression of AFAP1-AS1. The angiogenesis tests were conducted using human umbilical vein endothelial cells (HUVECs) and AFAP1-AS1- silenced Hs578T cells on 3D cell cultures. The presence of VM (CD31-/PAS+) in tumor tissues from TNBC patients with and without metastasis was assessed through immunohistochemistry using endothelial marker CD31 antibodies and periodic acid-Schiff (PAS) staining., Results: Compared with normal mammary tissues, AFAP1-AS1 expression was higher in breast cancer tissues. Moreover, AFAP1-AS1 expression was upregulated in the TNBC subtype compared to receptor-positive breast tumors. In addition, the expression of AFAP1-AS1 was correlated with the expression of the thirteen genes characteristic of a previously reported hypoxia signature. Interestingly, AFAP1-AS1 was upregulated in primary TNBC tumors from patients who developed metastasis compared with the nonmetastatic group. Functional analysis revealed that the knockdown of AFAP1-AS1 in Hs578T cells significantly impaired the hypoxia-induced VM, accompanied by a decrease in the development of 3D channel networks. Similarly, AFAP1-AS1 knockdown counteracts the angiogenic potential of cancer cells, as indicated by a reduction in the number of polygons, sprouting cells, and nodes in HUVEC cells. Remarkably, an increase in CD31-/PAS + staining of 3D channel networks in primary breast tumors from metastatic patients was found compared with the nonmetastatic group. Finally, we found that the number of blood vessels increased in the nonmetastatic group more than in the metastatic cohort., Conclusions: Our data suggested that AFAP1-AS1 controls both VM and angiogenesis in Hs578T breast cancer cells and that increased metastasis is associated with VM in TNBC patients., (© 2024. The Author(s).)

Obesity is an important risk factor for breast cancer in women before and after menopause. Adipocytes, key mediators in the tumor microenvironment, play a pivotal role in the relationship between obesity with cancer. However, the potential of dietary components in modulating this relationship remains underexplored. Genistein, a soy-derived isoflavone, has shown promise in reducing breast cancer risk, attenuating obesity-associated inflammation, and improving insulin resistance. However, there are no reports examining whether genistein has the ability to reduce the effects of obesity on breast tumor development. In this study, we constructed a mammary tumor model in ovariectomized obese mice and examined the effects of genistein on body condition and tumor growth. Moreover, the effects of genistein on the tumor microenvironment were examined via experimental observation of peritumoral adipocytes and macrophages. In addition, we further investigated the effect of genistein on adipocyte and breast cancer cell crosstalk via coculture experiments. Our findings indicate that dietary genistein significantly alleviates obesity, systemic inflammation, and metabolic disorders induced by a high-fat diet in ovariectomized mice. Notably, it also inhibits tumor growth in vivo. The impact of genistein extends to the tumor microenvironment, where it reduces the production of cancer-associated adipocytes (CAAs) and the recruitment of M2d-subtype macrophages. In vitro, genistein mitigates the transition of adipocytes into CAAs and inhibits the expression of inflammatory factors by activating PPAR-γ pathway and degrading nuclear NF-κB. Furthermore, it impedes the acquisition of invasive properties and epithelial‒mesenchymal transition in breast cancer cells under CAA-induced inflammation, disrupting the Wnt3a/β-catenin pathway. Intriguingly, the PPAR-γ inhibitor T0070907 counteracted the effects of genistein in the coculture system, underscoring the specificity of its action. Our study revealed that genistein can mitigate the adverse effects of obesity on breast cancer by modulating the tumor microenvironment. These findings provide new insights into how genistein intake and a soy-based diet can reduce breast cancer risk., (© 2024. The Author(s).)

Background: Magnetic seed localization is a novel and reliable technique for perioperative localization of non-palpable breast cancers. However, due to susceptibility artifacts, magnetic seeds cannot be in situ during response monitoring of neoadjuvant chemotherapy with MRI. Contrast-enhanced mammography (CEM) could provide an alternative modality for response monitoring while magnetic seeds are in situ . This feasibility study aimed to investigate whether implanted magnetic seeds cause imaging artifacts in CEM examinations. Methods: A phantom experiment and patient studies were conducted to assess the presence of imaging artifacts caused by magnetic seeds on CEM. Chicken breast filet phantoms containing magnetic seeds were imaged using CEM and MRI. Next, twenty women with non-palpable breast tumors scheduled for breast-conserving surgery were included and received a magnetic marker seed preoperatively. Immediately after seed implantation, postprocedural images were taken using the CEM mode on our mammography units. All images were assessed by two experienced breast radiologists for the presence of artifacts. Descriptive statistics were used to present the study results. Results: The phantom experiment revealed no imaging artifacts on CEM, whereas significant artifacts were present on MRI. This allowed us to continue with the patient studies, in which no imaging artifacts associated with magnetic seeds were observed at all. Surgical outcomes demonstrated successful retrieval of all magnetic seeds and negative surgical margins in 19 out of 20 cases. Conclusion: To the best of our knowledge, this is the first study demonstrating that the combination of CEM and magnetic seeds is feasible and does not cause any significant imaging artifacts., Competing Interests: Competing Interests: The Pintuition Seed® magnetic marker seeds utilized in this study were provided free-of-charge by Sirius Medical B.V., Eindhoven, The Netherlands. The authors have declared that no other possibly competing interest exists., (© The author(s).)

Background: Phyllodes tumors (PTs) of the breast are uncommon fibroepithelial neoplasms that tend to recur locally and may have metastatic potential. Their pathogenesis is poorly understood. Hippo signaling pathway plays an essential role in organ size control, tumor suppression, tissue regeneration and stem cell self-renewal. Hippo signaling dysfunction has been implicated in cancer. Recent evidence suggests that there is cross-talk between the Hippo signaling key proteins YAP/TAZ and the epithelial-mesenchymal transition (EMT) master regulators Snail and ZEB. In this study we aimed to investigate the expression of Hippo signaling pathway components and EMT regulators in PTs, in relation to tumor grade., Methods: Expression of Hippo signaling effector proteins YAP, TAZ and their DNA binding partner TEAD was evaluated by immunohistochemistry in paraffin-embedded tissue specimens from 86 human phyllodes breast tumors (45 benign, 21 borderline, 20 malignant), in comparison with tumor grade and with the expression of EMT-related transcription factors ZEB and Snail., Results: Nuclear immunopositivity for YAP, TAZ and TEAD was detected in both stromal and epithelial cells in PTs and was significantly higher in high grade tumors. Interestingly, there was a significant correlation between the expression of YAP, TAZ, TEAD and the expression of ZEB and SNAIL., Conclusions: Our results originally implicate Hippo signaling pathway in PTs pathogenesis and suggest that an interaction between Hippo signaling key components and EMT regulators may promote the malignant features of PTs., Competing Interests: Declaration of Competing Interest We have no conflicts of interest to disclose. The authors received no specific funding for this work., (Copyright © 2024 Elsevier GmbH. All rights reserved.)

Studies have reported overexpression of NAT1 gene for xenobiotic metabolizing arylamine N -acetyltransferase type 1 in estrogen receptor positive breast tumors, and this association has been linked to patient chemoresistance and response to tamoxifen. We probed the expression of NAT1 , using quantitative reverse transcription PCR to screen clinically characterized breast cancer tissue cDNA arrays. Primers detecting all NAT1 alternative transcripts were used, and the protocol and results are reported according to consensus guidelines. The clinical information about 166 tumor samples screened is provided, including tumor stage, estrogen and progesterone receptor status and HER2 expression. NAT1 was found to be significantly ( P  < 0.001) upregulated in hormone receptor positive vs. negative tumors. No correlation was apparent between NAT1 and tumor stage or HER2 expression. Our findings demonstrate a strong correlation between the expression of NAT1 and steroid hormone receptors in breast tumors, supporting its possible utility as a pharmacogenetic biomarker or drug target. Of the two polymorphic NAT genes, NAT1 is the one primarily expressed in breast tissue, and is subjected to regulation by two differential promoters and more than one polyadenylation signal. Hormonal factors may enhance NAT1 gene expression at the transcriptional or epigenetic level, and tamoxifen has additionally been shown to inhibit NAT1 enzymatic activity. The outcome of tamoxifen treatment is also more favorable in patients with NAT1 overexpressing tumors. The study adds to the growing body of evidence implicating NAT1 in breast cancer and its pharmacological treatment., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)

Breast radiologists encounter unusual lesions, which may not be well described in the literature. Previously based on histologic and molecular classifications, the World Health Organization (WHO) classification of tumors has become increasingly multidisciplinary. Familiarity with imaging features and basic pathology of infrequent breast lesions, as well as their current classification according to the WHO, may help the radiologist evaluate biopsy results for concordance and help direct the management of uncommon breast lesions. This review article provides a case-based review of imaging features and WHO histologic classification of rare breast tumors., (© Society of Breast Imaging 2024. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

The purpose of this study was to fuse conventional radiomic and deep features from digital breast tomosynthesis craniocaudal projection (DBT-CC) and ultrasound (US) images to establish a multimodal benign-malignant classification model and evaluate its clinical value. Data were obtained from a total of 487 patients at three centers, each of whom underwent DBT-CC and US examinations. A total of 322 patients from dataset 1 were used to construct the model, while 165 patients from datasets 2 and 3 formed the prospective testing cohort. Two radiologists with 10-20 years of work experience and three sonographers with 12-20 years of work experience semiautomatically segmented the lesions using ITK-SNAP software while considering the surrounding tissue. For the experiments, we extracted conventional radiomic and deep features from tumors from DBT-CCs and US images using PyRadiomics and Inception-v3. Additionally, we extracted conventional radiomic features from four peritumoral layers around the tumors via DBT-CC and US images. Features were fused separately from the intratumoral and peritumoral regions. For the models, we tested the SVM, KNN, decision tree, RF, XGBoost, and LightGBM classifiers. Early fusion and late fusion (ensemble and stacking) strategies were employed for feature fusion. Using the SVM classifier, stacking fusion of deep features and three peritumoral radiomic features from tumors in DBT-CC and US images achieved the optimal performance, with an accuracy and AUC of 0.953 and 0.959 [CI: 0.886-0.996], a sensitivity and specificity of 0.952 [CI: 0.888-0.992] and 0.955 [0.868-0.985], and a precision of 0.976. The experimental results indicate that the fusion model of deep features and peritumoral radiomic features from tumors in DBT-CC and US images shows promise in differentiating benign and malignant breast tumors., (© 2024. The Author(s) under exclusive licence to Society for Imaging Informatics in Medicine.)

Background: Breast cancer is one of the most common malignant tumors in women worldwide and poses a severe threat to their health. Therefore, this study examined patients who underwent breast cancer surgery, analyzed hospitalization costs and structure, and explored the impact of China Healthcare Security Diagnosis Related Groups (CHS-DRG) management on patient costs. It aimed to provide medical institutions with ways to reduce costs, optimize cost structures, reduce patient burden, and improve service efficiency., Aim: To study the CHS-DRG payment system's impact on breast cancer surgery costs., Methods: Using the CHS-DRG (version 1.1) grouping criteria, 4073 patients, who underwent the radical resection of breast malignant tumors from January to December 2023, were included in the JA29 group; 1028 patients were part of the CHS-DRG payment system, unlike the rest. Through an independent sample t -test, the length of hospital stay as well as total hospitalization, medicine and consumables, medical, nursing, medical technology, and management expenses were compared. Pearson's correlation coefficient was used to test the cost correlation., Results: In terms of hospitalization expenses, patients in the CHS-DRG payment group had lower medical, nursing, and management expenses than those in the diagnosis-related group (DRG) non-payment group. For patients in the DRG payment group, the factors affecting the total hospitalization cost, in descending order of relevance, were medicine and consumable costs, consumable costs, medicine costs, medical costs, medical technology costs, management costs, nursing costs, and length of hospital stay. For patients in the DRG non-payment group, the factors affecting the total hospitalization expenses in descending order of relevance were medicines and consumable expenses, consumable expenses, medical technology expenses, the cost of medicines, medical expenses, nursing expenses, length of hospital stay, and management expenses., Conclusion: The CHS-DRG system can help control and reduce unnecessary medical expenses by controlling medicine costs, medical consumable costs, and the length of hospital stay while ensuring medical safety., Competing Interests: Conflict-of-interest statement: The authors report that they have no relevant conflicts of interest to disclose., (©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.)

Objective: Elastography images tissue mechanical responses and infers the underlying properties to aid diagnosis and treatment response monitoring. The estimation of absolute or relative tumor properties may vary with dimensions even when the mechanical properties remain constant. Harmonic motion imaging (HMI) uses amplitude-modulated (AM) focused ultrasound to interrogate the targeted tissue's viscoelastic properties. In this study, effects of AM frequencies on HMI were investigated in terms of inclusion relative stiffness and size estimation., Methods: AM frequencies from 200 to 600 Hz in steps of 100 Hz were considered using a 5.3-kPa phantom with cylindrical inclusions (Young's modulus: 22, 31, 44, 56 kPa, and diameter: 4.8, 8.1, 13.6, 19.8 mm) to optimize the performance of HMI in characterizing tumors with the same mechanical properties and of different dimensions., Results: Consistent displacement ratios (DRs) (17.5% variation) of the inclusion to background were obtained with 200-Hz AM for breast-tumor-mimicking inclusions albeit a suboptimal inclusion size estimation obtained. 400-Hz was otherwise used for small and low-contrast inclusions (4.8 mm, 22 or 31 kPa). A linear relationship (R 2 = 0.9043) was found between the inverse DR at these frequencies and the Young's modulus ratio. 400 Hz obtained the most accurate inclusion size estimation with an overall estimation error on the lateral dimension of 0.5 mm. In vivo imaging of breast cancer patients (n = 5) was performed at 200 or 400 Hz., Conclusion: The results presented herein indicate that the HMI AM frequency could be optimized adaptively in cases of different applications, i.e., at 200 or 400 Hz, depending on whether aimed for consistent DR measurement for tumor response assessment or tumor margin delineation for surgical planning. HMI may thus be capable of predicting the pathologic endpoint of tumors in response to neoadjuvant chemotherapy (NACT) as early as 3 weeks into treatment., Competing Interests: Conflict of interest The authors declare no conflicts of interest., (Copyright © 2024 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.)

This paper presents a prototype of a portable and modular electrical impedance tomography (EIT) system for breast tumor detection. The proposed system uses MATLAB to generate three-dimensional representations of breast tissue. The modular architecture of the system allows for flexible customization and scalability. It consists of several interconnected modules. Each module can be easily replaced or upgraded, facilitating system maintenance and future enhancements. Testing of the prototype has shown promising results in preliminary screening based on experimental studies. Agar models were used for the experimental stage of this project. The 3D representations provide clinicians with valuable information for accurate diagnosis and treatment planning. Further research and refinement of the system is warranted to validate its performance in future clinical trials.

Background: Recent advancements in nanomedicine and nanotechnology have expanded the scope of multifunctional nanostructures, offering innovative solutions for targeted drug delivery and diagnostic agents in oncology and nuclear medicine. Nanoparticles, particularly those derived from natural sources, hold immense potential in overcoming biological barriers to enhance therapeutic efficacy and diagnostic accuracy. Papain, a natural plant protease derived from Carica papaya , emerges as a promising candidate for green nanotechnology-based applications due to its diverse medicinal properties, including anticancer properties., Purpose: This study presents a novel approach in nanomedicine and oncology, exploring the potential of green nanotechnology by developing and evaluating technetium-99m radiolabeled papain nanoparticles ( 99m Tc-P-NPs) for imaging breast tumors. The study aimed to investigate the efficacy and specificity of these nanoparticles in breast cancer models through preclinical in vitro and in vivo assessments., Methods: Papain nanoparticles (P-NPs) were synthesized using a radiation-driven method and underwent thorough characterization, including size, surface morphology, surface charge, and cytotoxicity assessment. Subsequently, P-NPs were radiolabeled with technetium-99m ( 99m Tc), and in vitro and in vivo studies were conducted to evaluate cellular uptake at tumor sites, along with biodistribution, SPECT/CT imaging, autoradiography, and immunohistochemistry assays, using breast cancer models., Results: The synthesized P-NPs exhibited a size mean diameter of 9.3 ± 1.9 nm and a spherical shape. The in vitro cytotoxic activity of native papain and P-NPs showed low cytotoxicity in HUVEC, MDA-MB231, and 4T1 cells. The achieved radiochemical yield was 94.2 ± 3.1% that were sufficiently stable (≥90%) for 6 h. The tumor uptake achieved in the 4T1 model was 2.49 ± 0.32% IA/g at 2 h and 1.51 ± 0.20% IA/g at 6 h. In the spontaneous breast cancer model, 1.19 ± 0.20% IA/g at 2 h and 0.86 ± 0.31% IA/g at 6 h. SPECT/CT imaging has shown substantial tumor uptake of the new nanoradiopharmaceutical and clear tumor visualization. 99m Tc-P-NPs exhibited a high affinity to tumoral cells confirmed by ex vivo autoradiography and immunohistochemistry assays., Conclusion: The findings underscore the potential of green nanotechnology-driven papain nanoparticles as promising agents for molecular imaging of breast and other tumors through SPECT/CT imaging. The results represent a substantial step forward in the application of papain nanoparticles as carriers of diagnostic and therapeutic radionuclides to deliver diagnostic/therapeutic payloads site-specifically to tumor sites for the development of a new generation of nanoradiopharmaceuticals., Competing Interests: The authors declare no conflict of interest., (© 2024 Ferreira et al.)

Here, we present a protocol for analyzing the global metabolic landscape in breast tumors for the purpose of metabolism-based patient stratification. We describe steps for analyzing 1,454 metabolic genes representing 90 metabolic pathways and subjecting them to an algorithm that calculates the deregulation score of 90 pathways in each tumor sample, thus converting gene-level information into pathway-level information. We then detail procedures for performing clustering analysis to identify metabolic subtypes and using machine learning to develop a signature representing each subtype. For complete details on the use and execution of this protocol, please refer to Iqbal et al. 1 ., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

HER2-low tumors have shown promise in response to antibody-drug conjugates (ADCs) in recent clinical trials, underscoring the need to characterize this group's clinical phenotype. In this study, we aimed to explore the clinicopathological features, survival rates, and HER2 amplicon mRNA expression of women affected with HER2-low breast cancer, compared with HER2-negative and HER2-positive groups. We included 516 breast cancer patients from Colombia, for whom we compared clinicopathological features, mRNA expression of three HER2 amplicon genes ( ERBB2, GRB7 and MIEN1 ), survival and risk of mortality between HER2-low cases (1+ or 2+ with negative in situ hybridization (ISH) result) with HER2-positive (3+ or 2+ with positive ISH test) and HER2-negative (0+) cases. A higher proportion of patients with better-differentiated tumors and a lower proliferation index were observed for HER2-low tumors compared to the HER2-positive group. Additionally, HER2-low tumors showed higher mRNA expression of the ERBB2 gene and longer overall survival rates compared to HER2-negative cases. Nonetheless, a Cox-adjusted model by ER status and clinical stage showed no statistically significant differences between these groups. Our results show differences in important clinicopathological features between HER2-low and both HER2-positive and negative tumors. Given this unique phenotype, it is crucial to evaluate the potential advantages of ADC therapies for this emerging subtype of breast cancer.

Bioluminescence imaging (BLI) is an important noninvasive optical imaging technique that has been widely used to monitor many biological processes due to its high sensitivity, resolution, and signal-to-noise ratio. However, the BLI technique based on the firefly luciferin-luciferase system is limited by the expression of exogenous luciferase and the short half-life of firefly luciferin, which pose challenges for long-term tracking in vivo. To solve the problems, here we rationally designed an intelligent strategy for persistent BLI in tumors by combining luciferase-loaded calcium phosphate nanoparticles (Luc@CaP NPs) to provide luciferase and the probe Cys(SEt)-Lys-CBT (CKCBT) to slowly produce the luciferase substrate amino luciferin (Am-luciferin). Luc@CaP NPs constructed with CaP as a carrier could enable luciferase activity to be maintained in vivo for at least 12 h. And compared to the conventional substrate luciferin, CKCBT apparently prolonged the BL time by up to 2 h through GSH-induced intracellular self-assembly and subsequent protease degradation-induced release of Am-luciferin. We anticipate that this strategy could be applied for clinical translation in more disease diagnosis and treatment in the near future.

Significance: Near-infrared optical imaging methods have shown promise for monitoring response to neoadjuvant chemotherapy (NAC) for breast cancer, with endogenous contrast coming from oxy- and deoxyhemoglobin. Spatial frequency domain imaging (SFDI) could be used to detect this contrast in a low-cost and portable format, but it has limited imaging depth. It is possible that local tissue compression could be used to reduce the effective tumor depth., Aim: To evaluate the potential of SFDI for therapy response prediction, we aim to predict how changes to tumor size, stiffness, and hemoglobin concentration would be reflected in contrast measured by SFDI under tissue compression., Approach: Finite element analysis of compression on an inclusion-containing soft material is combined with Monte Carlo simulation to predict the measured optical contrast., Results: When the effect of compression on blood volume is not considered, contrast gain from compression increases with the size and stiffness of the inclusion and decreases with the inclusion depth. With a model of reduction of blood volume from compression, compression reduces imaging contrast, an effect that is greater for larger inclusions and stiffer inclusions at shallower depths., Conclusions: This computational modeling study represents a first step toward tracking tumor changes induced by NAC using SFDI and local compression., (© 2024 The Authors.)

Background US is clinically established for breast imaging, but its diagnostic performance depends on operator experience. Computer-assisted (real-time) image analysis may help in overcoming this limitation. Purpose To develop precise real-time-capable US-based breast tumor categorization by combining classic radiomics and autoencoder-based features from automatically localized lesions. Materials and Methods A total of 1619 B-mode US images of breast tumors were retrospectively analyzed between April 2018 and January 2024. nnU-Net was trained for lesion segmentation. Features were extracted from tumor segments, bounding boxes, and whole images using either classic radiomics, autoencoder, or both. Feature selection was performed to generate radiomics signatures, which were used to train machine learning algorithms for tumor categorization. Models were evaluated using the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity and were statistically compared with histopathologically or follow-up-confirmed diagnosis. Results The model was developed on 1191 (mean age, 61 years ± 14 [SD]) female patients and externally validated on 50 (mean age, 55 years ± 15]). The development data set was divided into two parts: testing and training lesion segmentation (419 and 179 examinations) and lesion categorization (503 and 90 examinations). nnU-Net demonstrated precision and reproducibility in lesion segmentation in test set of data set 1 (median Dice score [DS]: 0.90 [IQR, 0.84-0.93]; P = .01) and data set 2 (median DS: 0.89 [IQR, 0.80-0.92]; P = .001). The best model, trained with 23 mixed features from tumor bounding boxes, achieved an AUC of 0.90 (95% CI: 0.83, 0.97), sensitivity of 81% (46 of 57; 95% CI: 70, 91), and specificity of 87% (39 of 45; 95% CI: 77, 87). No evidence of difference was found between model and human readers (AUC = 0.90 [95% CI: 0.83, 0.97] vs 0.83 [95% CI: 0.76, 0.90]; P = .55 and 0.90 vs 0.82 [95% CI: 0.75, 0.90]; P = .45) in tumor classification or between model and histopathologically or follow-up-confirmed diagnosis (AUC = 0.90 [95% CI: 0.83, 0.97] vs 1.00 [95% CI: 1.00,1.00]; P = .10). Conclusion Precise real-time US-based breast tumor categorization was developed by mixing classic radiomics and autoencoder-based features from tumor bounding boxes. ClinicalTrials.gov identifier: NCT04976257 Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Bahl in this issue.

MicroRNAs (miRNAs) are small RNAs that are often dysregulated in many diseases, including cancers. They are highly tissue-specific and stable, thus, making them particularly useful as biomarkers. As the spatial transcriptomics field advances, protocols that enable highly sensitive and spatially resolved detection become necessary to maximize the information gained from samples. This is especially true of miRNAs where the location their expression within tissue can provide prognostic value with regard to patient outcome. Equally as important as detection are ways to assess and visualize the miRNA's spatial information in order to leverage the power of spatial transcriptomics over that of traditional nonspatial bulk assays. We present a highly sensitive methodology that simultaneously quantitates and spatially detects seven miRNAs in situ on formalin-fixed paraffin-embedded tissue sections. This method utilizes rolling circle amplification (RCA) in conjunction with a dual scanning approach in nanoliter well arrays with embedded hydrogel posts. The hydrogel posts are functionalized with DNA probes that enable the detection of miRNAs across a large dynamic range (4 orders of magnitude) and a limit of detection of 0.17 zeptomoles (1.7 × 10 -4 attomoles). We applied our methodology coupled with a data analysis pipeline to K14-Cre Brca1 murine breast tumors to showcase the information gained from this approach. f/f Tp53 f/f murine breast tumors to showcase the information gained from this approach.

In breast cancer, triple negative (TN) breast cancer has most responses to immune checkpoint inhibitor (ICI) therapy. Lymphocyte infiltrate does not impact prognosis in Hormone receptor positive HER2 negative (HR + HER2-) breast tumors and few HR + HER2- tumors respond to ICI. We contrasted immune-associated gene expression between 119 TN and 475 HR + HER2- breast tumors from The Cancer Genome Atlas (TCGA) and confirmed our findings in 299 TN and 1369 HR + HER2- breast tumors in the METABRIC database. TN and HR+ HER2- tumors grouped into immune-high or -low tumors, both subtypes were represented in the immune-high group. The largest difference between the immune-high TN and HR + HER2- tumors was TN tumors had more abundant T h1 and T h2 CD4 + T cells while HR + HER2- tumors had more abundant fibroblasts (log 2 FC > 0.3; p < 10×10 -10 ). This suggests an immune-high signature is not dictated by breast cancer subtype, but fibroblast subsets associated with worse outcome were higher in the immune-high HR + HER2- tumors., Competing Interests: Authors received research funding, are employed by, and/or own stocks for the following organizations: Celgene (WC, JDA, KN, FS, MLD), Epithany (MLD), EMD Sorono (MLD), Precigen (MLD and SS), Barvarian Nordisk (MLD), Veanna (MLD and SS), IMV Inc (SS), Stanford, Burnham, Prebys (SS), and Pfizer (MLD).

Background: Accurately identifying patients with axillary pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer patients remains challenging., Purpose: To compare the feasibility of shear wave elastography (SWE) performed on breast tumors and axillary lymph nodes (LNs) in predicting the axillary status after NAC., Materials and Methods: This prospective study included a total of 319 breast cancer patients with biopsy-proven positive node who received NAC followed by axillary lymph node dissection from 2019 to 2022. The correlations between shear wave velocity (SWV) and pathologic characteristics were analyzed separately for both breast tumors and LNs after NAC. We compared the performance of SWV between breast tumors and LNs in predicting the axillary status after NAC. Additionally, we evaluated the performance of the most significantly correlated pathologic characteristic in breast tumors and LNs to investigate the pathologic evidence supporting the use of breast or axilla SWE., Results: Axillary pCR was achieved in 51.41% of patients with node-positive breast cancer. In breast tumors, there is a stronger correlation between SWV and collagen volume fraction (CVF) (r = 0.52, p < 0.001) compared to tumor cell density (TCD) (r = 0.37, p < 0.001). In axillary LNs, SWV was weakly correlated with CVF (r = 0.31, p = 0.177) and TCD (r = 0.29, p = 0.213). No significant correlation was found between SWV and necrosis proportion in breast tumors or axillary LNs. The predictive performances of both SWV and CVF for axillary pCR were found to be superior in breast tumors (AUC = 0.87 and 0.85, respectively) compared to axillary LNs (AUC = 0.70 and 0.74, respectively)., Conclusion: SWE has the ability to characterize the extracellular matrix, and serves as a promising modality for evaluating axillary LNs after NAC. Notably, breast SWE outperform axilla SWE in determining the axillary status in breast cancer patients after NAC., (© 2024. The Author(s).)

Breast carcinoma is the most common cancer in women. Nineteen different subtypes of breast carcinomas are recognized in the current WHO classification of breast tumors. Except for these subtypes, there are a number of carcinomas with special morphologic and immunohistochemical features that are not included in the 5th WHO classification, while others are considered special morphologic patterns of invasive breast carcinoma of no special type. In this manuscript, we systematically review the literature on four different subtypes of invasive breast carcinoma, namely lymphoepithelioma-like breast carcinoma, breast carcinoma with osteoclast-like giant cells, signet-ring breast carcinoma, and metaplastic breast carcinoma with melanocytic differentiation. We describe their clinicopathological characteristics, focusing on the differential diagnosis, treatment, and prognosis.

Breast cancer continues to be a major global health challenge, driving the need for effective therapeutic strategies. Cisplatin, a powerful chemotherapeutic agent, is widely used in breast cancer treatment. However, its effectiveness is often limited by systemic toxicity and the development of drug resistance. This review examines the molecular factors that influence cisplatin response and resistance, offering crucial insights for the scientific community. It highlights the significance of understanding cisplatin resistance's genetic and epigenetic contributors, which could lead to more personalized treatment approaches. Additionally, the review explores innovative strategies to counteract cisplatin resistance, including combination therapies, nanoparticle-based drug delivery systems, and targeted therapies. These approaches are under intensive investigation and promise to enhance breast cancer treatment outcomes. This comprehensive discussion is a valuable resource to advance breast cancer therapeutics and address the challenge of cisplatin resistance., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Purpose: Breast cancer's impact necessitates refined diagnostic approaches. This study develops a nomogram using radiology quantitative features from contrast-enhanced cone-beam breast CT for accurate preoperative classification of benign and malignant breast tumors., Material and Methods: A retrospective study enrolled 234 females with breast tumors, split into training and test sets. Contrast-enhanced cone-beam breast CT-images were acquired using Koning Breast CT-1000. Quantitative assessment features were extracted via 3D-slicer software, identifying independent predictors. The nomogram was constructed to preoperative differentiation benign and malignant breast tumors. Calibration curve was used to assess whether the model showed favorable correspondence with pathological confirmation. Decision curve analysis confirmed the model's superiority., Results: The study enrolled 234 female patients with a mean age of 50.2 years (SD ± 9.2). The training set had 164 patients (89 benign, 75 malignant), and the test set had 70 patients (29 benign, 41 malignant). The nomogram achieved excellent predictive performance in distinguishing benign and malignant breast lesions with an AUC of 0.940 (95% CI 0.900-0.940) in the training set and 0.970 (95% CI 0.940-0.970) in the test set., Conclusion: This study illustrates the effectiveness of quantitative radiology features derived from contrast-enhanced cone-beam breast CT in distinguishing between benign and malignant breast tumors. Incorporating these features into a nomogram-based diagnostic model allows for breast tumor diagnoses that are objective and possess good accuracy. The application of these insights could substantially increase reliability and efficacy in the management of breast tumors, offering enhanced diagnostic capability., (© 2024. Italian Society of Medical Radiology.)

Breast cancer risk factors include lifestyle, genetic-hormonal influences, and viral infections. Human papillomavirus (HPV), known primarily as the etiological agent of cervical cancer, also appears active in breast carcinogenesis, as evidenced in our study of 56 patients from northeastern Brazil. We assessed the clinical and sociodemographic characteristics, correlating them with various breast cancer tumor types. HPV detection involved amplifying the L1 region, with viral load measured using the E2/E6 ratio and viral activity indicated by E5 oncogene expression. Predominantly, patients over 56 years of age with healthy lifestyles showed a high incidence of invasive ductal carcinoma and triple-negative breast cancer. HPV was detected in 35.7% of cases, mostly HPV16, which is associated with high viral loads (80 copies per cell) and significant E5 expression. These results hint at a possible link between HPV and breast carcinogenesis, necessitating further studies to explore this association and the underlying viral mechanisms.

In breast tumors, somatic mutation frequencies in TP53 and PIK3CA vary by tumor subtype and ancestry. Emerging data suggest tumor mutation status is associated with germline variants and genetic ancestry. We aimed to identify germline variants that are associated with somatic TP53 or PIK3CA mutation status in breast tumors. A genome-wide association study was conducted in 2,850 women of European ancestry with breast cancer using TP53 and PIK3CA mutation status (positive or negative) as well as specific functional categories [e.g., TP53 gain-of-function (GOF) and loss-of-function, PIK3CA activating] as phenotypes. Germline variants showing evidence of association were selected for validation analyses and tested in multiple independent datasets. Discovery association analyses found five variants associated with TP53 mutation status with P values <1 × 10-6 and 33 variants with P values <1 × 10-5. Forty-four variants were associated with PIK3CA mutation status with P values <1 × 10-5. In validation analyses, only variants at the ESR1 locus were associated with TP53 mutation status after multiple comparisons corrections. Combined analyses in European and Malaysian populations found ESR1 locus variants rs9383938 and rs9479090 associated with the presence of TP53 mutations overall (P values 2 × 10-11 and 4.6 × 10-10, respectively). rs9383938 also showed association with TP53 GOF mutations (P value 6.1 × 10-7). rs9479090 showed suggestive evidence (P value 0.02) for association with TP53 mutation status in African ancestry populations. No other variants were significantly associated with TP53 or PIK3CA mutation status. Larger studies are needed to confirm these findings and determine if additional variants contribute to ancestry-specific differences in mutation frequency., Significance: Emerging data show ancestry-specific differences in TP53 and PIK3CA mutation frequency in breast tumors suggesting that germline variants may influence somatic mutational processes. This study identified variants near ESR1 associated with TP53 mutation status and identified additional loci with suggestive association which may provide biological insight into observed differences., (© 2024 The Authors; Published by the American Association for Cancer Research.)

Breast cancer is a heterogeneous disease, with a subpopulation of tumor cells known as breast cancer stem cells (BCSCs) with self-renewal and differentiation abilities that play a critical role in tumor initiation, progression, and therapy resistance. The tumor microenvironment (TME) is a complex area where diverse cancer cells reside creating a highly interactive environment with secreted factors, and the extracellular matrix. Autophagy, a cellular self-digestion process, influences dynamic cellular processes in the tumor TME integrating diverse signals that regulate tumor development and heterogeneity. Autophagy acts as a double-edged sword in the breast TME, with both tumor-promoting and tumor-suppressing roles. Autophagy promotes breast tumorigenesis by regulating tumor cell survival, migration and invasion, metabolic reprogramming, and epithelial-mesenchymal transition (EMT). BCSCs harness autophagy to maintain stemness properties, evade immune surveillance, and resist therapeutic interventions. Conversely, excessive, or dysregulated autophagy may lead to BCSC differentiation or cell death, offering a potential avenue for therapeutic exploration. The molecular mechanisms that regulate autophagy in BCSCs including the mammalian target of rapamycin (mTOR), AMPK, and Beclin-1 signaling pathways may be potential targets for pharmacological intervention in breast cancer. This review provides a comprehensive overview of the relationship between autophagy and BCSCs, highlighting recent advancements in our understanding of their interplay. We also discuss the current state of autophagy-targeting agents and their preclinical and clinical development in BCSCs., Competing Interests: Declaration of Interest Statement Authors disclose no conflict of interest.

Introduction: Breast cancer (BC) is one of the most common and leading causes of death in women. Therefore, early and accurate diagnosis is vital. In this study, meteorin-like (METRNL) peptide and asprosin levels were examined in breast tissue in invasive ductal carcinoma (IDC) of the breast, and the roles of these molecules in the diagnosis of BC were investigated., Methods: In this retrospective study, tissues from patients with BC in the Pathology Department Laboratory of Fırat University Faculty of Medicine, Elazığ, Turkey, were used. Samples from 30 patients were used. The control group consisted of healthy breast tissues from the same patients. The pathology group consisted of breast tissues with IDC from the same patients. Breast tissue samples from both groups were evaluated immunohistochemically for METRNL and asprosin., Results: Statistically significant differences were observed between both groups in terms of METRNL and asprosin. It was observed that METRNL and asprosin immunoreactivities were higher in breast tissues with IDC than in healthy breast tissues (p<0.001)., Conclusion: When the study results were evaluated, it was seen that there was a significant relationship between healthy breast tissues and the ones with IDC in terms of METRNL and asprosin. It is thought that both METRNL and asprosin may be really important in the future for the early diagnosis and treatment of BC., Competing Interests: Human subjects: Consent was obtained or waived by all participants in this study. Firat University Ethics Committee issued approval 2024/03-49. The study titled "The Role of Meteorin-Like Peptide and Aspirosine in Breast Tumors" was discussed by our committee. It was unanimously decided that the study complies with ethical rules. Animal subjects: All authors have confirmed that this study did not involve animal subjects or tissue. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Kocaman et al.)

Background: Breast cancer is the most common cancer among women, and ultrasound is a usual tool for early screening. Nowadays, deep learning technique is applied as an auxiliary tool to provide the predictive results for doctors to decide whether to make further examinations or treatments. This study aimed to develop a hybrid learning approach for breast ultrasound classification by extracting more potential features from local and multi-center ultrasound data., Methods: We proposed a hybrid learning approach to classify the breast tumors into benign and malignant. Three multi-center datasets (BUSI, BUS, OASBUD) were used to pretrain a model by federated learning, then every dataset was fine-tuned at local. The proposed model consisted of a convolutional neural network (CNN) and a graph neural network (GNN), aiming to extract features from images at a spatial level and from graphs at a geometric level. The input images are small-sized and free from pixel-level labels, and the input graphs are generated automatically in an unsupervised manner, which saves the costs of labor and memory space., Results: The classification AUC ROC of our proposed method is 0.911, 0.871 and 0.767 for BUSI, BUS and OASBUD. The balanced accuracy is 87.6%, 85.2% and 61.4% respectively. The results show that our method outperforms conventional methods., Conclusions: Our hybrid approach can learn the inter-feature among multi-center data and the intra-feature of local data. It shows potential in aiding doctors for breast tumor classification in ultrasound at an early stage., (© 2024. The Author(s).)

Background: The aberrant amplification of mammary luminal progenitors is at the origin of basal-like breast cancers associated with BRCA1 mutations. Integrins mediate cell-matrix adhesion and transmit mechanical and chemical signals that drive epithelial stem cell functions and regulate tumor progression, metastatic reactivation, and resistance to targeted therapies. Consistently, we have recently shown that laminin-binding integrins are essential for the expansion and differentiation of mammary luminal progenitors in physiological conditions. As over-expression of the laminin-binding α6 integrin (Itgα6) is associated with poor prognosis and reduced survival in breast cancer, we here investigate the role of Itgα6 in mammary tumorigenesis., Methods: We used Blg-Cre; Brca1 F/F ; Trp53 F/F mice, a model that phenocopies human basal-like breast cancer with BRCA1 mutations. We generated mutant mice proficient or deficient in Itgα6 expression and followed tumor formation. Mammary tumors and pretumoral tissues were characterized by immunohistochemistry, flow cytometry, RT-qPCR, Western blotting and organoid cultures. Clonogenicity of luminal progenitors from preneoplastic glands was studied in 3D Matrigel cultures., Results: We show that Itga6 deletion favors activation of p16 cell cycle inhibitor in the preneoplastic tissue. Subsequently, the amplification of luminal progenitors, the cell of origin of Brca1-deficient tumors, is restrained in Itgα6-deficient gland. In addition, the partial EMT program operating in Brca1/p53-deficient epithelium is attenuated in the absence of Itgα6. As a consequence of these events, mammary tumor formation is delayed in Itgα6-deficient mice. After tumor formation, the lack of Itgα6 does not affect tumor growth but rather alters their differentiation, resulting in reduced expression of basal cell markers., Conclusions: Our data indicate that Itgα6 has a pro-tumorigenic role in Blg-Cre; Brca1 F/F ; Trp53 F/F mice developing basal-like mammary tumors. In particular, we reveal that Itgα6 is required for the luminal progenitor expansion and the aberrant partial EMT program that precedes the formation of BRCA1 deficient tumors., (© 2024. The Author(s).)

Purpose: Black women experience the highest breast cancer mortality rate compared with women of other racial/ethnic groups. To gain a deeper understanding of breast cancer heterogeneity across diverse populations, we examined a VEGF-hypoxia gene expression signature in breast tumors from women of diverse ancestry., Experimental Design: We developed a NanoString nCounter gene expression panel and applied it to breast tumors from Nigeria (n = 182) and the University of Chicago (Chicago, IL; n = 161). We also analyzed RNA sequencing data from Nigeria (n = 84) and The Cancer Genome Atlas (TCGA) datasets (n = 863). Patient prognosis was analyzed using multiple datasets., Results: The VEGF-hypoxia signature was highest in the basal-like subtype compared with other subtypes, with greater expression in Black women compared with White women. In TCGA dataset, necrotic breast tumors had higher scores for the VEGF-hypoxia signature compared with non-necrosis tumors (P < 0.001), with the highest proportion in the basal-like subtype. Furthermore, necrotic breast tumors have higher scores for the proliferation signature, suggesting an interaction between the VEGF-hypoxia signature, proliferation, and necrosis. T-cell gene expression signatures also correlated with the VEGF-hypoxia signature when testing all tumors in TCGA dataset. Finally, we found a significant association of the VEGF-hypoxia profile with poor outcomes when using all patients in the METABRIC (P < 0.0001) and SCAN-B datasets (P = 0.002)., Conclusions: These data provide further evidence for breast cancer heterogeneity across diverse populations and molecular subtypes. Interventions selectively targeting VEGF-hypoxia and the immune microenvironment have the potential to improve overall survival in aggressive breast cancers that disproportionately impact Black women in the African Diaspora., (©2024 American Association for Cancer Research.)

Breast cancer is a heterogenous disease with various histologic subtypes, molecular profiles, behaviors, and response to therapy. After the histologic assessment and diagnosis of an invasive breast carcinoma, the use of biomarkers, multigene expression assays and mutation profiling may be used. With improved molecular assays, the identification of somatic genetic alterations in key oncogenes and tumor suppressor genes are playing an increasingly important role in many areas of breast cancer care. This review summarizes the most clinically significant somatic alterations in breast tumors and how this information is used to facilitate diagnosis, provide potential treatment options, and identify mechanisms of resistance., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Cancer is the major cause of premature death in humans worldwide, demanding more efficient therapeutics. Aberrant cell proliferation resulting from the loss of cell cycle regulation is the major hallmark of cancer, so targeting cell cycle is a promising strategy to combat cancer. However, the molecular mechanism underlying the dysregulation of cell cycle of cancer cells remains poorly understood. TMEM189, a newly identified protein, plays roles in the biosynthesis of ethanolamine plasmalogen and the regulation of autophagy. Here, we demonstrated that the expression level of TMEM189 was negatively correlated with the survival rate of the cancer patients. TMEM189 deficiency significantly suppresses the cancer cell proliferation and migration, and causes cell cycle G2/M arrest both in vitro and in vivo . Furthermore, TMEM189 depletion suppressed the growth of breast tumors in vivo . Taken together, our work indicated that TMEM189 promotes cancer progression by regulating cell cycle G2/M transition, suggesting that it is a promising target in cancer therapy., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Estrogen Receptor 1 (ESR1; also known as ERα, encoded by ESR1 gene) is the main driver and prime drug target in luminal breast cancer. ESR1 chromatin binding is extensively studied in cell lines and a limited number of human tumors, using consensi of peaks shared among samples. However, little is known about inter-tumor heterogeneity of ESR1 chromatin action, along with its biological implications. Here, we use a large set of ESR1 ChIP-seq data from 70 ESR1 + breast cancers to explore inter-patient heterogeneity in ESR1 DNA binding to reveal a striking inter-tumor heterogeneity of ESR1 action. Of note, commonly shared ESR1 sites show the highest estrogen-driven enhancer activity and are most engaged in long-range chromatin interactions. In addition, the most commonly shared ESR1-occupied enhancers are enriched for breast cancer risk SNP loci. We experimentally confirm SNVs to impact chromatin binding potential for ESR1 and its pioneer factor FOXA1. Finally, in the TCGA breast cancer cohort, we can confirm these variations to associate with differences in expression for the target gene. Cumulatively, we reveal a natural hierarchy of ESR1-chromatin interactions in breast cancers within a highly heterogeneous inter-tumor ESR1 landscape, with the most common shared regions being most active and affected by germline functional risk SNPs for breast cancer development., (© 2024 Joosten et al.; Published by Cold Spring Harbor Laboratory Press.)

Purpose: The aim of this study was to evaluate the prognostic role of p53 immunohistochemical (IHC) expression in a large cohort of patients with hormone receptors (HR)-positive/Her2-negative primary invasive breast cancer., Methods: Retrospective review of consecutive cases treated at our Breast Unit between 2003 and 2013. Patients were divided into 3 subgroups based on p53 IHC expression: null (0%), low (0.1%-49%), and high (≥50%) p53 expression., Results: A total of 1387 patients were included in the study with a median follow-up of 86 months. After adjusting for age, size, node status, lymphovascular invasion, progesterone, and Ki67 expression, only null p53 immunophenotype was associated with worse disease-free survival (DFS) (OR 1.74, 95% IC, 1.11-2.71, P = .015) and distant recurrence-free survival (DRFS) (OR 1.73, 95% IC, 1.04-2.90, P = .036). Null p53 impacted significantly DFS and DRFS also in patients with early breast cancer., Conclusions: p53 IHC expression affects survival and, thus can be a valuable tool in the management of patients with HR-positive/Her2-negative breast cancer., (© The Author(s) 2023. Published by Oxford University Press.)

Background: Although previous studies have shown that the injection of contrast agents can improve image quality, the specific impact of this on T2-weighted fat-suppressed (T2 FS) and diffusion-weighted imaging (DWI) sequences in the diagnosis of breast cancer remains incompletely understood. In particular, there is insufficient research on how contrast agents affect the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and apparent diffusion coefficient (ADC) values within these sequences, and how these changes influence the diagnosis of benign and malignant breast tumors., Methods: Breast magnetic resonance images (MRI) were obtained from 178 consecutive patients on a 3T scanner. The SNR and CNR of lesions on T2 FS sequence were calculated before and after contrast agent injection and compared. Differences between pre- and post-contrast ADC in identifying different tumor types were compared using the Kruskal-Wallis H-test and the paired comparison test. The accuracy of ADC values between pre- and post-contrast in distinguishing benign and malignant breast masses was assessed using receiver operating characteristic (ROC) curves., Results: The SNR and CNR of T2 FS sequence increased after contrast injection, and especially for invasive cancer and benign tumor, the increase was significant. For DWI, there was a slight increase or decrease of ADC values after contrast injection, but the ADC values before and after contrast had a similar effect in identifying different types of tumors. In the ROC curve analysis for assessing benign and malignant breast tumors, the area under the curve (AUC) before and after contrast showed similar results., Conclusions: Contrast agent injection can improve the SNR and CNR of T2 FS sequence, thus providing higher quality images for the diagnosis of breast lesions. Furthermore, injection of contrast agent had little effect on the ability of ADC values to identify different types of lesions and both ADC values before and after the contrast agent were able to distinguish between benign and malignant tumors with almost the same accuracy., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-23-1700/coif). S.Z. and S.Y. are employees of Shanghai United Imaging Healthcare. Na Zhang is an employee of the United Imaging Research Institute of Innovative Medical Equipment. The other authors have no conflicts of interest to declare., (2024 Quantitative Imaging in Medicine and Surgery. All rights reserved.)

Segmentation and classification of breast tumors are critical components of breast ultrasound (BUS) computer-aided diagnosis (CAD), which significantly improves the diagnostic accuracy of breast cancer. However, the characteristics of tumor regions in BUS images, such as non-uniform intensity distributions, ambiguous or missing boundaries, and varying tumor shapes and sizes, pose significant challenges to automated segmentation and classification solutions. Many previous studies have proposed multi-task learning methods to jointly tackle tumor segmentation and classification by sharing the features extracted by the encoder. Unfortunately, this often introduces redundant or misleading information, which hinders effective feature exploitation and adversely affects performance. To address this issue, we present ACSNet, a novel multi-task learning network designed to optimize tumor segmentation and classification in BUS images. The segmentation network incorporates a novel gate unit to allow optimal transfer of valuable contextual information from the encoder to the decoder. In addition, we develop the Deformable Spatial Attention Module (DSAModule) to improve segmentation accuracy by overcoming the limitations of conventional convolution in dealing with morphological variations of tumors. In the classification branch, multi-scale feature extraction and channel attention mechanisms are integrated to discriminate between benign and malignant breast tumors. Experiments on two publicly available BUS datasets demonstrate that ACSNet not only outperforms mainstream multi-task learning methods for both breast tumor segmentation and classification tasks, but also achieves state-of-the-art results for BUS tumor segmentation. Code and models are available at https://github.com/qqhe-frank/BUS-segmentation-and-classification.git., Competing Interests: Declaration of competing interest All authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Background/aim: Breast cancer remains the most prevalent type of cancer among women worldwide, and it remains the primary cause of cancer-related deaths in this demographic. Neuroendocrine breast cancer (NBC), an uncommon subtype comprising less than 1% of cases, typically occurs in older women and displays as a slow-growing, low-grade condition. NBC exhibits distinct histological patterns and immunohistochemical markers. Given the limited data on NBC, assays are required that will provide information on molecular profiling and assist in clinical decision making. The aim of the study was to investigate whether a modern Multigene Assay (MGA) could assist on treatment planning of NBC patients., Case Report: A cohort of four patients was analyzed using a MGA. The presented cases featured young, pre-menopausal women with clear NBC, lacking family history. All were lymph node-negative, with robust expression of neuroendocrine markers. Despite high hormone receptor expression, all tumors were poorly differentiated with elevated Ki67 levels. Oncotype DX analysis indicated a need for chemotherapy in three cases and not in one. This underscores the heterogeneity within NBC, emphasizing the importance of personalized treatment decisions., Conclusion: While NBC is rare and lacks extensive studies, the use of multigene assays like Oncotype DX may play a pivotal role in treatment planning, especially in cases with varying histological parameters., (Copyright © 2024, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.)

Breast cancer is the most prevalent type of cancer in women worldwide. Within breast tumors, the basal-like subtype has the worst prognosis, prompting the need for new tools to understand, detect, and treat these tumors. Certain germline-restricted genes show aberrant expression in tumors and are known as Cancer/Testis genes; their misexpression has diagnostic and therapeutic applications. Here we designed a new bioinformatic approach to examine Cancer/Testis gene misexpression in breast tumors. We identify several new markers in Luminal and HER-2 positive tumors, some of which predict response to chemotherapy. We then use machine learning to identify the two Cancer/Testis genes most associated with basal-like breast tumors: HORMAD1 and CT83. We show that these genes are expressed by tumor cells and not by the microenvironment, and that they are not expressed by normal breast progenitors; in other words, their activation occurs de novo. We find these genes are epigenetically repressed by DNA methylation, and that their activation upon DNA demethylation is irreversible, providing a memory of past epigenetic disturbances. Simultaneous expression of both genes in breast cells in vitro has a synergistic effect that increases stemness and activates a transcriptional profile also observed in double-positive tumors. Therefore, we reveal a functional cooperation between Cancer/Testis genes in basal breast tumors; these findings have consequences for the understanding, diagnosis, and therapy of the breast tumors with the worst outcomes., (© 2024. The Author(s).)