ReviewPathobiology : journal of immunopathology, molecular and cellular biology2011
The changing role of pathology in breast cancer diagnosis and treatment.
Review in Pathobiology : journal of immunopathology, molecular and cellular biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers, 1 of them a synthesis that pooled it.
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Who cites it
46 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Association Between Meningioma and Breast Cancer: A Systematic Review and Meta-analysis.JAMA network open · 2023Pooled it
- Article
- Development of a machine learning model for automatic data extraction from breast cancer pathology reports.Scientific reports · 2025Article
- Natural language processing for local, regional, and distant breast cancer relapse identification in pathology reports.Breast cancer research and treatment · 2025Article
- A Low-Cost Optomechatronic Diffuse Optical Mammography System for 3D Image Reconstruction: Proof of Concept.Diagnostics (Basel, Switzerland) · 2025Article
- Discordance in Immunohistochemistry Results in Breast Pathologies: Effect of Chemotherapy, Specimen Characteristics, or Pathology Center?Clinical Medicine Insights. Oncology · 2025Article
- Defining the optimal Ki67 cutoff values for survival prediction in neoadjuvant chemotherapy-treated patients with breast cancer.Frontiers in surgery · 2025Article
- Performance of externally validated machine learning models based on histopathology images for the diagnosis, classification, prognosis, or treatment outcome prediction in female breast cancer: A systematic review.Journal of pathology informatics · 2024Review
- Tissue Expression of Growth Differentiation Factor 11 in Patients with Breast Cancer.Diagnostics (Basel, Switzerland) · 2024Article
- In-silico study of novel dimeric flavonoid (OC251FR2) isolated from the seeds ofIn silico pharmacology · 2024Article
- Unravelling heterogeneous effects of cancer‑associated fibroblasts on poor prognosis markers in breast cancer EM‑G3 cell line:Oncology reports · 2024Article
- Preparing Data for Artificial Intelligence in Pathology with Clinical-Grade Performance.Diagnostics (Basel, Switzerland) · 2023Review
- Identification of tumor tissue in thin pathological samples via femtosecond laser-induced breakdown spectroscopy and machine learning.Scientific reports · 2023Article
- Functionalized liposomes for targeted breast cancer drug delivery.Bioactive materials · 2023Review
- Rapid Diagnosis of Ductal Carcinoma In Situ and Breast Cancer Based on Raman Spectroscopy of Serum Combined with Convolutional Neural Network.Bioengineering (Basel, Switzerland) · 2023Article
- The Potential of Antibody Technology and Silver Nanoparticles for Enhancing Photodynamic Therapy for Melanoma.Biomedicines · 2022Review
- Breast Cancer-Epidemiology, Classification, Pathogenesis and Treatment (Review of Literature).Cancers · 2022Review
- Genome profiles of pathologist-defined cell clusters by multiregional LCM and G&T-seq in one triple-negative breast cancer patient.Cell reports. Medicine · 2021Article
- Detection and recognition of ultrasound breast nodules based on semi-supervised deep learning: a powerful alternative strategy.Quantitative imaging in medicine and surgery · 2021Article
- Precision Oncology Beyond Genomics: The Future Is Here-It Is Just Not Evenly Distributed.Cells · 2021Review
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Abstract
Pathological examination has been the gold standard for diagnosis in cancer and its role has also included the elucidation of etiology, pathogenesis, clinicopathological correlation, and prognostication. The advent of newer technologies and the realization that breast cancer is heterogeneous has shifted the focus to prognostication, with increased attention being paid to the identification of morphological features and immunohistochemical markers of prognostic relevance. However, despite the massive efforts invested in the identification of immunohistochemical biomarkers in breast cancer the majority have not proven to be of value in multivariate analyses and only estrogen receptor, progesterone receptor, and Her2/neu expression have remained essential components of pathological examination. These 3 markers were initially employed for prognostication but their role in treatment also rendered them of predictive value. Newer molecular methods, especially high-throughput technologies, have shown that even morphologically similar subtypes of breast cancer can show molecular heterogeneity; moreover, infiltrating ductal carcinoma can be separated into at least 4 molecular subtypes designated luminal (ER+, PR+, and Her2/neu-), Her2 overexpressing (ER-, PR-, and Her2/neu+), basal-like (ER-, PR-, Her2/neu-, and CK5/6+, EGFR+), and normal breast-like (ER-, PR-, and Her2/neu-), each with different clinical outcomes. The importance of proliferative gene expression in these subtypes has been demonstrated and surrogate immunohistochemical markers include ER, PR, Her2/neu, and Ki67 for the more expensive molecular tests. Molecular technologies, importantly, have not only provided further insights into the heterogeneity of breast cancer but have also opened new avenues for treatment through the identification of signaling molecules important in the proliferation and survival of the neoplastic cells. The treatment of cancer thus shifts from the conventional approach of 'one size fits all' to one of personalized treatment tailored to the specific characteristics of the tumor. Pathologists continue to play their traditional role in diagnosis but, as purveyors of the excised tissue, pathologists now have the additional role of identifying biomarkers responsive to therapeutic manipulation, thus playing an inextricable role as diagnostic oncologists in the management of breast cancer.
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