Search Results (307)

Background: Breast cancer is the most prevalent malignancy among women globally. In Romania, it is the most frequent form of cancer affecting women, with approximately 12,000 new cases diagnosed annually, and the second most common cause of cancer-related mortality, second only to lung cancer. Methods: This study looked at 79 breast cancer patients from Oltenia, concentrating on epidemiology, histology, diagnostic features, and treatments. Patients were chosen based on inclusion criteria such as histopathologically verified diagnosis, availability of clinical and treatment data, and follow-up information. The analyzed biological material consisted of tissue samples taken from the breast parenchyma and axillary lymph nodes. Even though not the primary subject of this paper, all patients underwent immunohistochemical (IHC) evaluation both preoperatively and postoperatively. Results: We found invasive ductal carcinoma to be the predominant type, while ductal carcinoma in situ (DCIS) and mixed types were rare. We performed cross-tabulations of metastasis versus nodal status and age versus therapy type; none reached significance (all p > 0.05), suggesting observed differences were likely due to chance. A chi-square test comparing surgical interventions (breast-conserving vs. mastectomy) in patients who did or did not receive chemotherapy showed, χ² = 3.17, p = 0.367, indicating that chemotherapy did not significantly influence surgical choice. Importantly, adjuvant chemotherapy and radiotherapy were used at similar rates across age groups, whereas neoadjuvant hormonal (endocrine) therapy was more common in older patients (but without statistical significance). Conclusions: Finally, we discussed the consequences of individualized care and early detection. Romania’s shockingly low screening rate, which contributes to delayed diagnosis, emphasizes the importance of improved population medical examination and tailored treatment options. Also, the country has one of the lowest rates of mammography uptake in Europe and no systematic population screening program. Full article

Purpose: This study aimed to develop a predictive nomogram integrating AI-based BI-RADS lexicons and lesion-to-nipple distance (LND) ultrasound features to differentiate mass-type ductal carcinoma in situ (DCIS) from invasive ductal carcinoma (IDC) visible on ultrasound. Methods: The final study cohort consisted of 170 women with 175 pathologically confirmed malignant breast lesions, including 26 cases of DCIS and 149 cases of IDC. LND and AI-based features from the S-Detect system (BI-RADS lexicons) were analyzed. Rare features were consolidated into broader categories to enhance model stability. Data were split into training (70%) and validation (30%) sets. Logistic regression identified key predictors for an LND nomogram. Model performance was evaluated using receiver operating characteristic (ROC) curves, 1000 bootstrap resamples, and calibration curves to assess discrimination and calibration. Results: Multivariate logistic regression identified smaller lesion size, irregular shape, LND ≤ 3 cm, and non-hypoechoic echogenicity as independent predictors of DCIS. These variables were integrated into the LND nomogram, which demonstrated strong discriminative performance (AUC = 0.851 training; AUC = 0.842 validation). Calibration was excellent, with non-significant Hosmer-Lemeshow tests (p = 0.127 training, p = 0.972 validation) and low mean absolute errors (MAE = 0.016 and 0.034, respectively), supporting the model’s accuracy and reliability. Conclusions: The AI-based comprehensive nomogram demonstrates strong reliability in distinguishing mass-type DCIS from IDC, offering a practical tool to enhance non-invasive breast cancer diagnosis and inform preoperative planning. Full article

Of breast cancers, the triple-negative subtype (TNBC) is characterized by aggressive behavior, poor prognosis and limited treatment options due to its high molecular heterogeneity. Since insufficient programmed cell death response is a major hallmark of cancer, here we searched for apoptosis-related biomarkers of prognostic potential in TNBC. The expression of the pro-apoptotic caspase 8, cytochrome c, caspase 3, the anti-apoptotic BCL2 and the caspase-independent mediator, apoptosis-inducing factor-1 (AIF1; gene AIFM1) was tested in TNBC both in silico at transcript and protein level using KM-Plotter, and in situ in our clinical TNBC cohort of 103 cases using immunohistochemistry. Expression data were correlated with overall survival (OS), recurrence-free survival (RFS) and distant metastasis-free survival (DMFS). We found that elevated expression of the executioner apoptotic factors AIF1 and caspase 3, and of BCL2, grants significant OS advantage within TNBC, both at the mRNA and protein level, particularly for chemotherapy-treated vs untreated patients. The dominantly cytoplasmic localization of AIF1 and cleaved-caspase 3 proteins in primary TNBC suggests that chemotherapy may recruit them from the cytoplasmic/mitochondrial stocks to contribute to improved patient survival in proportion to their expression. Our results suggest that testing for the expression of AIF1, caspase 3 and BCL2 may identify partly overlapping TNBC subgroups with favorable prognosis, warranting further research into the potential relevance of apoptosis-targeting treatment strategies. Full article

Accurate preoperative distinction between in situ and invasive Breast Cancer (BC) is critical for clinical decision-making and treatment planning. Radiomics and Machine Learning (ML) have shown promise in enhancing diagnostic performance from breast MRI, yet their application to this specific task remains underexplored. The aim of this study was to evaluate the performance of several ML classifiers, trained on radiomic features extracted from DCE–MRI and supported by basic clinical information, for the classification of in situ versus invasive BC lesions. In this study, we retrospectively analysed 71 post-contrast DCE–MRI scans (24 in situ, 47 invasive cases). Radiomic features were extracted from manually segmented tumour regions using the PyRadiomics library, and a limited set of basic clinical variables was also included. Several ML classifiers were evaluated in a Leave-One-Out Cross-Validation (LOOCV) scheme. Feature selection was performed using two different strategies: Minimum Redundancy Maximum Relevance (MRMR), mutual information. Axial 3D rotation was used for data augmentation. Support Vector Machine (SVM), K Nearest Neighbors (KNN), Random Forest (RF), and Extreme Gradient Boosting (XGBoost) were the best-performing models, with an Area Under the Curve (AUC) ranging from 0.77 to 0.81. Notably, KNN achieved the best balance between sensitivity and specificity without the need for data augmentation. Our findings confirm that radiomic features extracted from DCE–MRI, combined with well-validated ML models, can effectively support the differentiation of in situ vs. invasive breast cancer. This approach is quite robust even in small datasets and may aid in improving preoperative planning. Further validation on larger cohorts and integration with additional imaging or clinical data are recommended. Full article

Background/Objectives: Thirty to fifty percent of ductal carcinoma in situ (DCIS) cases are high-grade and at risk of progressing to invasive carcinoma. The most important treatment-related risk factor for recurrence is the presence of residual DCIS. The aim of our study was to evaluate the relationship between size and imaging features on preoperative mammography and magnetic resonance imaging (MRI) and histopathological size and nuclear grade in patients with pure DCIS. Methods: Between 2015 and 2023, 90 patients who underwent surgery for DCIS, had no microinvasive/invasive component, and underwent a preoperative mammography and MRI were included in this study. Results: DCIS was detected in 91.1% of patients using mammography and 95.5% using MRI. Microcalcifications (MCs) were most common in mammography (85.4%). Thin pleomorphic and thin linear branching MCs were detected in 42% of high-grade DCIS, while amorphous (42%) MCs were most common in low-grade DCIS. In low-grade DCIS cases, a grouped distribution of MCs was observed most commonly (69%). There was a statistically significant difference between DCIS groups in terms of MC morphology and distribution (p = 0.043, p = 0.005, respectively). Diffusion restriction on MRI was associated with high-grade DCIS (p = 0.043). The tumor size was greater than the pathological size and correlated poorly with mammography and moderately with MRI. Conclusions: Compared to mammography, MRI is more effective in detecting and estimating the size of DCIS. Both methods overestimate tumor size compared to histopathological size. The nuclear grade is associated with a poor prognosis and local recurrence in DCIS. Full article

Breast cancer invasion and subsequent metastasis to distant tissues occur when cancer cells lose cell–cell contact, develop a migrating phenotype, and invade the basement membrane (BM) and the extracellular matrix (ECM) to penetrate blood and lymphatic vessels. The identification of the mechanisms which induce the development from a ductal carcinoma in situ (DCIS) to a minimally invasive breast carcinoma (MIBC) is an emerging area of research in understanding tumor invasion and metastatic potential. To investigate the progression from DCIS to MIBC, we analyzed peritumoral collagen architecture using correlative scanning electron microscopy (SEM) on histological sections from human biopsies. In DCIS, the peritumoral collagen organizes into concentric lamellae (‘circular fibers’) parallel to the ducts. Within each lamella, type I collagen fibrils align in parallel, while neighboring lamellae show orthogonal fiber orientation. The concentric lamellar arrangement of collagen may physically constrain cancer cell migration, explaining the lack of visible tumor cell invasion into the peritumoral ECM in DCIS. A lamellar dissociation or the development of small inter fiber gaps allowed isolated breast cancer cell invasion and exosomes infiltration in the DCIS microenvironment. The radially arranged fibers observed in the peri-tumoral microenvironment of MIBC biopsies develop from a bending of the circular fibers of DCIS and drive a collective cancer cell invasion associated with an intense immune cell infiltrate. Type I collagen fibrils represent the peri-tumoral nano-environment which can play a mechanical role in regulating the development from DCIS to MIBC. Collectively, it is plausible to suggest that the ECM effectors implicated in breast cancer progression released by the interplay between cancer, stromal, and/or immune cells, and degrading inter fiber/fibril hydrophilic ECM components of the peritumoral ECM, may serve as key players in promoting the dissociation of the concentric collagen lamellae. Full article

Background/Objectives: Accurately correlating mammographic findings with corresponding histopathologic features is considered one of the essential aspects of mammographic evaluation, guiding the next steps in cancer management and preventing overdiagnosis. The objective of this study was to evaluate patterns of mammographic microcalcifications and their association with histopathological findings related to various breast tumors. Methods: 110 out of 3603 women had microcalcification of BIRADS 3 or higher and were subjected to stereotactic/ultrasound (USG) guided biopsies, and hook-wire localization excision procedures. Ultrasound and mammography images were reviewed by experienced radiologists using the standard American College of Radiology Breast-Imaging Reporting and Data System (ACR BI-RADS). Results: Our study showed that features with a high positive predictive value (PPV) of breast malignancy were heterogeneous (75%), fine linear/branching pleomorphic microcalcifications (66.7%), linear (100%), and segmental distributions (57.1%). Features that showed a higher risk of association with ductal carcinoma in situ (DCIS) were fine linear/branching pleomorphic (odds ratio (OR): 3.952), heterogeneous microcalcifications (OR: 3.818), segmental (OR: 5.533), linear (OR: 3.696), and regional (OR: 2.929) distributions. Furthermore, the features with higher risks associated with invasive carcinoma had heterogeneous (OR: 2.022), fine linear/branching pleomorphic (OR: 1.187) microcalcifications, linear (OR: 6.2), and regional (OR: 2.543) distributions. The features of associated masses in mammograms that showed a high PPV of malignancy had high density (75%), microlobulation (100%), and spiculated margins (75%). Conclusions: We concluded that specific patterns and distributions of microcalcifications were indeed associated with a higher risk of malignancy. Those with fine linear or branching pleomorphic and segmental distribution were at a higher risk of DCIS, whereas those with heterogeneous morphology with a linear distribution were at a higher risk of invasive carcinoma. Full article

Background/Objectives: Breast cancer tumors possess intratumoral heterogeneity (ITH), which is associated with therapeutic resistance. Tumors with high ITH exhibit human epidermal growth factor receptor 2 (HER2) heterogeneity, affecting the effectiveness of HER2-targeted therapies. Our recent study identified HER2 ITH as an independent prognostic factor for poor outcomes in HER2-positive breast cancer. We here investigated the association between HER2 ITH and anti-HER2 neoadjuvant chemotherapy (NAC) resistance. Methods: This study included 97 patients with primary HER2-positive breast cancer treated with anti-HER2 NAC. Breast tumor samples were obtained from vacuum-assisted breast biopsy before NAC. HER2 gene amplification was assessed using fluorescence in situ hybridization (FISH), and HER2 gene copy number histograms were generated. Using the Gaussian mixture model, histogram data were analyzed and categorized into the high (HH) and low HER2 heterogeneity (LH) groups. The association between HER2 ITH and treatment response was evaluated using the pathological complete response (pCR) rate. Results: Of the 97 patients, 18 (18.6%) and 79 (81.4%) were classified into the HH and LH groups, respectively. The pCR rate in the HH group was significantly lower at 28% (5/18) than that in the LH group at 65% (51/79) (p < 0.01). Multivariate analysis of pathological parameters revealed that the most significant predictor of pCR rate was HER2 ITH (p = 0.02). Conclusions: HER2 ITH assessment may be valuable in predicting therapeutic outcomes in HER2-positive breast cancer. Our novel approach of the HER2 ITH method using FISH histograms could serve as a useful tool for predicting anti-HER2 NAC resistance. Full article

Background: Breast cancer remains a critical health concern worldwide, with histopathological analysis of tissue biopsies serving as the clinical gold standard for diagnosis. Manual evaluation of histopathology images is time-intensive and requires specialized expertise, often resulting in variability in diagnostic outcomes. In silver in situ hybridization (SISH) images, accurate nuclei detection is essential for precise histo-scoring of HER2 gene expression, directly impacting treatment decisions. Methods: This study presents a scalable and automated deep learning framework for nuclei detection in HER2-SISH whole slide images (WSIs), utilizing a novel dataset of 100 expert-marked regions extracted from 20 WSIs collected at the University of Malaya Medical Center (UMMC). The proposed two-stage approach combines a pretrained Stardist model with image processing-based annotations, followed by fine tuning on our domain-specific dataset to improve generalization. Results: The fine-tuned model achieved substantial improvements over both the pretrained Stardist model and a conventional watershed segmentation baseline. Quantitatively, the proposed method attained an average F1-score of 98.1% for visual assessments and 97.4% for expert-marked nuclei, outperforming baseline methods across all metrics. Additionally, training and validation performance curves demonstrate stable model convergence over 100 epochs. Conclusions: These results highlight the robustness of our approach in handling the complex morphological characteristics of SISH-stained nuclei. Our framework supports pathologists by offering reliable, automated nuclei detection in HER2 scoring workflows, contributing to diagnostic consistency and efficiency in clinical pathology. Full article

Breast cancer is a leading cause of cancer-related mortality worldwide, requiring efficient diagnostic tools for early detection and monitoring. Human epidermal growth factor receptor 2 (HER2) is a key biomarker for breast cancer classification, typically assessed using immunohistochemistry (IHC). However, IHC requires invasive biopsies and time-intensive laboratory procedures. In this study, we present a biosensor integrated with a reusable printed circuit board (PCB) and functionalized glucose test strips designed for rapid and non-invasive HER2 detection in saliva. The biosensor achieved a limit of detection of 10⁻¹⁵ g/mL, 4 to 5 orders of magnitude more sensitive than the enzyme-linked immunosorbent assay (ELISA), with a sensitivity of 95/dec and a response time of 1 s. In addition to HER2, the biosensor also detects cancer antigen 15-3 (CA15-3), another clinically relevant breast cancer biomarker. The CA15-3 test demonstrated an equally low limit of detection, 10⁻¹⁵ g/mL, and a higher sensitivity, 190/dec, further validated using human saliva samples. Clinical validation using 29 saliva samples confirmed our biosensor’s ability to distinguish between healthy, in situ breast cancer, and invasive breast cancer patients. The system, which integrates a Bluetooth Low-Energy (BLE) module, enables remote monitoring, reduces hospital visits, and enhances accessibility for point-of-care and mobile screening applications. This ultra-sensitive, rapid, and portable biosensor can serve as a promising alternative for breast cancer detection and monitoring, particularly in rural and underserved communities. Full article

Ductal carcinoma in situ (DCIS) is the most common form of non-invasive breast cancer and a recognized precursor to invasive ductal carcinoma (IDC). Although DCIS itself is confined to the milk duct and not immediately life-threatening, its potential for progression to invasive disease necessitates careful clinical management. The increased detection of DCIS due to advancements in imaging and widespread screening programs has raised critical questions regarding its classification, prognosis, and optimal treatment strategies. While most cases exhibit indolent behavior, others harbor molecular characteristics that drive malignant transformation. A key challenge lies in distinguishing low-risk DCIS, which may never progress, from aggressive cases requiring intervention. Tumor microenvironment dynamics, immune cell infiltration, and molecular alterations, including hormone receptor (HR) status, human epidermal growth factor 2 (HER2) expression, and genetic mutations, play crucial roles in determining disease trajectory. This review explores the biological and molecular mechanisms underlying DCIS progression, with an emphasis on myoepithelial cells, tumor-infiltrating lymphocytes, and microenvironmental factors. By integrating recent findings, this article aims to refine risk stratification approaches and guide future strategies for personalized DCIS management. Improved prognostic biomarkers and targeted therapeutic interventions could help optimize treatment decisions, balancing the need for effective cancer prevention while minimizing overtreatment in low-risk patients. Full article

Background/Objectives: Breast cancer is the most common malignant neoplasm in women and the leading cause of cancer-related death. Approximately 50% of HER2-negative breast cancers exhibit low expression of this protein (HER2-low). Trastuzumab deruxtecan (T-DXd) is an antibody-drug conjugate targeting the HER2 receptor which has shown benefit in patients with HER2-low metastatic breast cancer in the DESTINY-Breast04 study. However, few data are available on its efficacy in real-world practice. Methods: We conducted a retrospective multicenter national study (eight centers) including patients with advanced HER2-low breast cancer (immunohistochemistry 1+ or 2+/ in situ hybridization negative) who started T-DXd treatment between January 2022 and March 2024. Patients had received at least one previous line of treatment. The primary endpoint was real-world progression-free survival (rwPFS) in patients with metastatic HER2-low breast cancer treated with T-DXd. The secondary endpoints were real-world overall survival (OS) and objective response rate (ORR). Results: The study included 35 patients (34 female and 1 male patient), with a median age of 54 years at the start of T-DXd. All patients had an ECOG-PS 0–1, and 26 patients (74%) had hormone receptor (HR)-positive disease. The median number of prior lines of treatment was 4 [1–7], and 23 patients (65.8%) had metastases in three or more sites. With a median follow-up of 7.8 months, rwPFS was 6 months (95% CI, 2.3–9.7), and OS was 15 months (95% CI, 4.7–25.3). In HR-positive patients, the median rwPFS was 6 months (95% CI, 1.2–10.7), compared to 4 months (95% CI, 2.1–5.9) in HR-negative patients. The overall ORR was 52.9%. Adverse events of grade 3 or higher were neutropenia (2.9%) and fatigue (2.9%). Conclusions: This study provides real-world data on T-DXd in the treatment of advanced HER2-low breast cancer. It is noteworthy that the population was heavily pre-treated and had a higher proportion of HR-negative patients, which may explain the lower efficacy compared to the DESTINY-Breast04 study. Full article

Perineural invasion (PNI) is a well-recognized histopathologic feature in multiple malignancies; however, its significance in breast cancer remains relatively underexplored. This review provides a synopsis of the current knowledge on PNI in breast cancer, discussing its histopathologic features, molecular mechanisms, diagnostic challenges, and clinical relevance. PNI is most frequently observed in high-grade invasive ductal carcinoma (IDC), particularly in triple-negative and HER2-positive subtypes. It is also seen in special histological subtypes such as mixed, metaplastic, and invasive micropapillary carcinomas. Mechanistically, PNI involves tumor–neural interactions, including neurotrophic factor signaling and epithelial–mesenchymal transition, contributing to tumor progression and potential locoregional recurrence (LRR). While PNI is linked to adverse prognosis in other tumors, its independent role remains unclear in breast cancer due to limited large-scale studies. Therefore, further investigation into its prognostic significance and potential therapeutic implications is needed. Future research should focus on refining diagnostic criteria and assessing targeted therapies to mitigate PNI-associated progression. This review summarizes the current knowledge on perineural invasion (PNI) in breast cancer, addressing its histological features, molecular mechanisms, diagnostic challenges, and clinical implications. Full article

Accurately determining HER2 status is essential for breast cancer treatment. We developed an AI-integrated in-house application for automated Dual bright-field (BF) in situ hybridization (ISH) analysis on whole slide images (WSIs), although optimal scanning conditions remain unclear. We evaluated scanners and optimized scanning protocols for clinical application. Ten de-identified invasive breast carcinoma cases, with HER2 immunohistochemistry and FISH results, were analyzed using three scanners and six scanning protocols. WSIs scanned by Scanner ‘A’ have 0.12 µm/pixel with 0.95 NA (A1) and 1.2 NA (A2); Scanner ‘B’ have 0.08 µm/pixel (B1); 0.17 µm/pixel (B2); and 0.17 µm/pixel with extended focus (1.4 µm step size and three layers) (B3); Scanner ‘C’ has 0.26 µm/pixel (C1) resolution. Results showed scanning protocols A1, A2, B2, and B3 yielded HER2 gene amplification status and ASCO/CAP ISH group results consistent with manual FISH as the ground truth. However, protocol C demonstrated poor concordance due to nuclei detection failure in six cases. The AI-integrated application achieved the best performance using scanning protocols with optimized resolutions of 0.12 µm/pixel and 0.17 µm/pixel with extended focus. This study highlights the importance of scanner selection in AI-based HER2 assessment and demonstrates that optimized scanning parameters enhance the accuracy and reliability of automated Dual BF ISH analysis. Full article

Cancerization of lobules (COL) is defined as the involvement of lobular acini by ductal carcinoma in situ (DCIS). Whether it represents a morphological variation in DCIS or a secondary extension of DCIS into lobules is debatable. The relation between COL and the probability of invasion is conflicting among different studies. We assessed if COL is a predictor of adverse pathological outcomes in mastectomy specimens. We reviewed the clinicopathological data of patients who underwent partial or total mastectomy for DCIS during a 3-year period (January 2015 until December 2017). Pathological parameters and follow-up data were collected. Whole-tissue hematoxylin and eosin (H&E) slides were reviewed and re-evaluated for COL. Cases with COL were stained immunohistochemically for E-cadherin and p120 to confirm the ductal phenotype of the neoplasms. In total, 171 mastectomies were identified including 65 specimens with pure DCIS and 106 specimens with DCIS with invasive carcinoma. COL was identified in 73 specimens. COL was significantly associated with adverse pathological outcomes including higher DCIS nuclear grade (p-value = 0.006), central (expansive “comedo”) necrosis (p-value = 0.008), presence of DCIS within or less than 2 mm from the surgical resection margin(s) (p-value = 0.004), higher percentage of blocks/slides with DCIS (p-value < 0.001), and extensive intraductal component (EIC) (applicable in cases with invasion) (p-value < 0.001). Invasion was seen in approximately two-thirds of the cases regardless of the presence of COL, with no statistical significance. Ninety-eight patients achieved 60 months of follow-up, of which only one patient developed local DCIS recurrence and had COL and EIC. Four other patients developed metastatic disease related to the invasive component. While other studies have previously hypothesized that COL may be associated with a worse pathological outcome at mastectomy, our results show that it may indeed be a measure of a higher disease burden representing EIC; however, it is not associated with an increased risk of detecting invasive carcinoma. Full article