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PURPOSE: Electronic health records (EHRs) are valuable information repositories that offer insights for enhancing clinical research on breast cancer (BC) using real-world data. The objective of this study was to develop a natural language processing (NLP) model specifically designed to extract structured data from BC pathology reports written in natural language. METHODS: During the initial phase, the algorithm's development cohort comprised 193 pathology reports from 116 patients with BC from 2012 to 2016. A rule-based NLP algorithm was applied to extract 26 variables for analysis and was compared with the manual extraction of data performed by both a data entry specialist and an oncologist. Following the first approach, the data set was expanded to include 513 reports, and a Named Entity Recognition (NER)-NLP model was trained and evaluated using K-fold cross-validation. RESULTS: The first approach led to a concordance analysis, which revealed an 82.9% agreement between the algorithm and the oncologist, whereas the concordance between the data entry specialist and the oncologist was 90.8%. The second training approach introduced the definition of an NER-NLP model, in which the accuracy showed remarkable potential (97.8%). Notably, the model demonstrated remarkable performance, especially for parameters such as estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, and Ki-67 (F1-score 1.0). CONCLUSION: The present study aligns with the rapidly evolving field of artificial intelligence (AI) applications in oncology, seeking to expedite the development of complex cancer databases and registries. The results of the model are currently undergoing postprocessing procedures to organize the data into tabular structures, facilitating their utilization in real-world clinical and research endeavors.
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Algoritmos , Neoplasias da Mama , Registros Eletrônicos de Saúde , Processamento de Linguagem Natural , Humanos , Neoplasias da Mama/patologia , Neoplasias da Mama/diagnóstico , Feminino , Pessoa de Meia-Idade , Idoso , Adulto , Mineração de Dados/métodosRESUMO
Secondary neoplastic lesions in lymph nodes are predominantly metastases from solid tumors, whereas primary lymph node hemangiomas are exceptionally uncommon, with only 24 well-documented cases in the literature. Histologically, they are characterized by endothelial cells that may appear flattened or enlarged, with variable vascular density, and the presence of stromal elements. Notably, the concurrent presence of a primary hemangioma and a metastasis from breast cancer - the latter being the most prevalent secondary lesion in axillary lymph nodes - represents an unprecedented observation. The unique case presented herein underscores the exceptional rarity of primary lymph node hemangiomas and demonstrates for the first time their possible coexistence with breast cancer metastasis within the same axillary lymph node. In sharing and discussing this case study, we pay homage to Professor Juan Rosai, whose work in redefining rare and complex diagnoses continues to enlighten our understanding of lymph node vascular lesions.
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Neoplasias da Mama , Hemangioma , Linfonodos , Metástase Linfática , Humanos , Feminino , Neoplasias da Mama/patologia , Hemangioma/patologia , Linfonodos/patologia , Pessoa de Meia-IdadeRESUMO
Effective risk assessment in early breast cancer is essential for informed clinical decision-making, yet consensus on defining risk categories remains challenging. This paper explores evolving approaches in risk stratification, encompassing histopathological, immunohistochemical, and molecular biomarkers alongside cutting-edge artificial intelligence (AI) techniques. Leveraging machine learning, deep learning, and convolutional neural networks, AI is reshaping predictive algorithms for recurrence risk, thereby revolutionizing diagnostic accuracy and treatment planning. Beyond detection, AI applications extend to histological subtyping, grading, lymph node assessment, and molecular feature identification, fostering personalized therapy decisions. With rising cancer rates, it is crucial to implement AI to accelerate breakthroughs in clinical practice, benefiting both patients and healthcare providers. However, it is important to recognize that while AI offers powerful automation and analysis tools, it lacks the nuanced understanding, clinical context, and ethical considerations inherent to human pathologists in patient care. Hence, the successful integration of AI into clinical practice demands collaborative efforts between medical experts and computational pathologists to optimize patient outcomes.
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PURPOSE: To compare the diagnostic performance (detection, assessment of correct disease extent and multifocality/centricity) of Contrast-Enhanced Mammography (CEM) Versus Breast Magnetic Resonance (MRI) in the study of lobular neoplasms. METHODS: We retrospectively selected all the patients who underwent surgery for a lobular breast neoplasm, either an in situ or an invasive tumor, and had undergone both breast CEM and MRI examinations during the pre-surgical planning. Wilcoxon Signed Rank test was performed to assess the differences between size measurements using the different methods and the post-surgical pathological measurements, considered the gold standard. The agreement in identifying multifocality/multicentricity among the different methods and the pathology was assessed using the Kappa statistics. RESULTS: We selected 19 patients, of which one presented a bilateral neoplasm. Then, the images of these 19 patients were analyzed, for a total of 52 malignant breast lesions. We found no significant differences between the post-surgical pathological size of the lesions and the calculated size with CEM and MRI (p-value of the difference respectively 0.71 and 0.47). In all 20 cases, neoplasm detection was possible both with CEM and MRI. CEM and MRI showed an excellent ability to identify multifocal and multicentric cases (K statistic equal to 0.93 for both the procedures), while K statistic was 0.11 and 0.59 for FFDM and US, respectively. CONCLUSION: The findings of this study suggest that CEM is a reliable imaging technique in the preoperative setting of patients with lobular neoplasm, with comparable results to breast MRI.
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Neoplasias da Mama , Humanos , Feminino , Neoplasias da Mama/diagnóstico por imagem , Neoplasias da Mama/cirurgia , Estudos Retrospectivos , Meios de Contraste , Mamografia/métodos , Imageamento por Ressonância Magnética/métodos , Espectroscopia de Ressonância Magnética , Sensibilidade e EspecificidadeRESUMO
Since the release of the DESTINY-Breast04 (DB-04) trial findings in June 2022, the field of pathology has seen a renaissance of HER2 as a predictive biomarker in breast cancer. The trial focused on patients with metastatic breast cancer who were classified as "HER2-low," i.e., those with immunohistochemistry (IHC) HER2 1 + or 2 + and negative in situ hybridization (ISH) results. The study revealed that treating these patients with trastuzumab deruxtecan (T-DXd) instead of the oncologist's chosen chemotherapy led to outstanding improvements in survival. This has challenged the existing binary HER2 pathological classification system, which categorized tumors as either positive (overexpression/amplification) or negative, as per the ASCO/CAP 2018 guideline reaffirmed by ASCO/CAP 2023 guideline update. Given that DB-04 excluded patients with HER2 IHC score 0 status, the results of the ongoing DB-06 trial may shed further light on the potential benefits of T-DXd therapy for these patients. Roughly half of all breast cancers are estimated to belong to the HER2-low category, which does not represent a distinct or specific subtype of cancer. Instead, it encompasses a diverse group of tumors that exhibit clinical, morphological, immunohistochemical, and molecular variations. However, HER2-low offers a distinctive biomarker status that identifies a specific therapeutic regimen (i.e., T-DXd) linked to a favorable prognosis in breast cancer. This unique association emphasizes the importance of accurately identifying these tumors. Differentiating between a HER2 IHC score 0 and score 1 + has not been clinically significant until now. To ensure accurate classification and avoid misdiagnosis, it is necessary to adopt standardized procedures, guidelines, and specialized training for pathologists in interpreting HER2 expression in the lower spectrum. Additionally, the utilization of artificial intelligence holds promise in supporting this endeavor. Here, we address the current state of the art and unresolved issues in assessing HER2-low status, with a particular emphasis on the score 0. We explore the dilemma surrounding the exclusion of HER2-zero patients from potentially beneficial therapy based on traditional HER2 testing. Additionally, we examine the clinical context, considering that DB-04 primarily involved heavily pretreated late-stage metastatic breast cancers. We also delve into emerging evidence suggesting that extrapolating HER2-low status from the original diagnosis may lead to misleading results. Finally, we provide recommendations for conducting high-quality testing and propose a standardized pathology report in compliance with 2023 ASCO/CAP updates and 2023 ESMO consensus statements on HER2-low breast cancer.
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Neoplasias da Mama , Receptor ErbB-2 , Humanos , Feminino , Hibridização in Situ Fluorescente/métodos , Receptor ErbB-2/genética , Neoplasias da Mama/metabolismo , Inteligência Artificial , Hibridização In Situ , Biomarcadores TumoraisRESUMO
Triple-negative breast cancer (TNBC) poses a significant challenge in terms of prognosis and disease recurrence. The limited treatment options and the development of resistance to chemotherapy make it particularly difficult to manage these patients. However, recent research has been shifting its focus towards biomarker-based approaches for TNBC, with a particular emphasis on the tumor immune landscape. Immune biomarkers in TNBC are now a subject of great interest due to the presence of tumor-infiltrating lymphocytes (TILs) in these tumors. This characteristic often coincides with the presence of PD-L1 expression on both neoplastic cells and immune cells within the tumor microenvironment. Furthermore, a subset of TNBC harbor mismatch repair deficient (dMMR) TNBC, which is frequently accompanied by microsatellite instability (MSI). All of these immune biomarkers hold actionable potential for guiding patient selection in immunotherapy. To fully capitalize on these opportunities, the identification of additional or complementary biomarkers and the implementation of highly customized testing strategies are of paramount importance in TNBC. In this regard, this article aims to provide an overview of the current state of the art in immune-related biomarkers for TNBC. Specifically, it focuses on the various testing methodologies available and sheds light on the immediate future perspectives for patient selection. By delving into the advancements made in understanding the immune landscape of TNBC, this study aims to contribute to the growing body of knowledge in the field. The ultimate goal is to pave the way for the development of more personalized testing strategies, ultimately improving outcomes for TNBC patients.
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Breast cancer is the most frequently diagnosed malignancy worldwide and the leading cause of cancer-related death among women. Brain metastases are a primary contributor to mortality, as they often go undetected until late stages due to their dormant nature. Moreover, the clinical management of brain metastases is complicated by the relevant issue of blood-brain barrier penetration. The molecular pathways involved in the formation, progression, and colonization of primary breast tumors and subsequent brain metastases are diverse, posing significant hurdles due to the heterogeneous nature of breast cancer subtypes. Despite advancements in primary breast cancer treatments, the prognosis for patients with brain metastases remains poor. In this review, we aim to highlight the biological mechanisms of breast cancer brain metastases by evaluating multi-step genetic pathways and to discuss currently available and emerging treatment strategies to propose a prospective overview of the management of this complex disease.
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Neoplasias Encefálicas , Neoplasias da Mama , Feminino , Humanos , Neoplasias da Mama/genética , Neoplasias da Mama/terapia , Neoplasias da Mama/metabolismo , Estudos Prospectivos , Neoplasias Encefálicas/genética , Neoplasias Encefálicas/terapia , Prognóstico , Mama/patologiaRESUMO
Metaplastic breast cancer (MpBC) is a rare and aggressive histologic subtype of breast cancer (BC) characterized by the presence of at least two cellular types, commonly epithelial and mesenchymal components. Despite growing evidence that MpBC is a unique entity, it has long been treated as a variant of nonspecial type (NST) BC. MpBC typically shows the phenotype of triple-negative breast cancer (TNBC), but compared to NST-TNBC, it is a relatively chemorefractory tumor associated with worse outcomes. Therefore, there is an urgent need to develop management guidelines specifically for MpBC to improve the prognosis of patients with early MpBC. This expert consensus aims to guide diagnosis and standardize clinical management of early MpBC among treating physicians. We provide guidance on the challenging radiological and pathological diagnosis of MpBC. Evidence on the involvement of genetic predisposition in the development of MpBC is also explored. We emphasize the importance of a multidisciplinary approach for the treatment of patients with early MpBC. The optimal surgery and radiotherapy approach is presented, as well as the opportunity offered by novel therapeutic approaches to increase treatment response in this chemoresistant subtype. Appropriate management of patients with MpBC is critical to reduce the high risk of local and distant recurrence that characterizes this disease.
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Neoplasias da Mama , Neoplasias de Mama Triplo Negativas , Humanos , Feminino , Neoplasias de Mama Triplo Negativas/terapia , Neoplasias de Mama Triplo Negativas/tratamento farmacológico , Consenso , Prognóstico , Neoplasias da Mama/diagnóstico , Neoplasias da Mama/terapia , Neoplasias da Mama/patologiaRESUMO
Various tumors rely on post-translational modifications (PTMs) to promote invasiveness and angiogenesis and to reprogram cellular energetics to abate anti-cancer immunity. Among PTMs, fucosylation is a particular type of glycosylation that has been linked to different aspects of immune and hormonal physiological functions as well as hijacked by many types of tumors. Multiple tumors, including breast cancer, have been linked to dismal prognoses and increased metastatic potential due to fucosylation of the glycan core, namely core-fucosylation. Pre-clinical studies have examined the molecular mechanisms regulating core-fucosylation in breast cancer models, its negative prognostic value across multiple disease stages, and the activity of in vivo pharmacological inhibition, instructing combinatorial therapies and translation into clinical practice. Throughout this review, we describe the role of fucosylation in solid tumors, with a particular focus on breast cancer, as well as physiologic conditions on the immune system and hormones, providing a view into its potential as a biomarker for predicating or predicting cancer outcomes, as well as a potential clinical actionability as a biomarker.
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Neoplasias da Mama , Humanos , Feminino , Glicosilação , Neoplasias da Mama/tratamento farmacológico , Processamento de Proteína Pós-Traducional , BiomarcadoresRESUMO
Context: Medullary thyroid carcinoma (MTC) is a malignant neuroendocrine neoplasm that may spread to lymph nodes before the primary tumor is diagnosed; moreover, distant metastases are already present in about 10% of patients at diagnosis. Serum calcitonin (Ctn) usually reflects the spread of disease, thus orienting the extent of surgery and predicting the possibility of biochemical remission. Tumor size and vascular invasion are important prognostic factors, but little is known on the relationship between other histopathological features, such as the presence of a tumor capsule, and long term outcome of MTC. Purpose: To evaluate the prevalence of encapsulated tumors among MTCs and the association of tumor capsule with a favorable outcome after surgery. Methods: A retrospective observational single-center study was conducted together with a narrative review of the available literature. Results: Among 44 patients (27 female, 17 male; median age: 56 years) with MTC (6 hereditary, 37 sporadic) followed up at our center in the last four years (median follow-up: 29.2 months), seven (15.9%) showed an encapsulated tumor at histology and a clinical remission after surgery. None of them had nodal metastases and median preoperative Ctn (398 pg/mL, IQR 126.5-7336) did not differ significantly from that of the 14 patients (31.8%) with persistent disease after surgery (787 pg/mL, IQR 340.5-2905.5; p=0.633), although their tumor size was significantly higher (median 33 mm versus 16 mm respectively, p=0.036). Among patients with preoperative Ctn levels above 500 pg/mL (n=11), only two (18.2%) showed undetectable Ctn levels during follow-up, both having an encapsulated MTC (OR 0.000, p=0.02). Notably, they were two similar cases of large MTC (> 3 cm) with extensive hyalinization and calcification, associated with very high Ctn levels (> 13'500 and 1'100 pg/mL, respectively) but no nodal nor distant metastases, in complete remission after surgery although one of them carried the aggressive M918T somatic RET mutation. Conclusion: MTC rarely shows a tumor capsule, which seems to correlate with a better prognosis and absence of nodal metastases, regardless of RET or RAS mutational status. Among encapsulated MTCs (E-MTC), Ctn levels and tumor size are not predictive of persistence of disease after surgery.
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Carcinoma Neuroendócrino , Neoplasias da Glândula Tireoide , Carcinoma Neuroendócrino/patologia , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Prognóstico , Estudos Retrospectivos , Neoplasias da Glândula Tireoide/diagnóstico , Neoplasias da Glândula Tireoide/genética , Neoplasias da Glândula Tireoide/cirurgiaRESUMO
We present a case of a woman with epidermal growth factor receptor (EGFR)-mutated lung adenocarcinoma who received gefitinib for 2 years and obtained a partial response. The patient then developed liver metastasis and a breast lesion, displaying high estrogen receptor (ER) expression and harboring the same EGFR mutation. From the radiological studies, it was not possible to make a differential diagnosis between primary breast cancer and breast metastasis from lung cancer. After the removal of the breast nodule, thanks to the clinical history, radiology, and above all, molecular and immunohistochemical investigations, a diagnosis of breast metastasis from lung adenocarcinoma was made. This case emphasizes the importance of a comprehensive clinical, pathological, and molecular analysis in the differential diagnosis between primary breast cancer and metastases from extramammary tumor to guide adequate treatment decision making.