Advances in Early Breast Cancer Risk Profiling: From Histopathology to Molecular Technologies
- PMID: 38001690
- PMCID: PMC10670146
- DOI: 10.3390/cancers15225430
Advances in Early Breast Cancer Risk Profiling: From Histopathology to Molecular Technologies
Abstract
Early breast cancer (BC) is the definition applied to breast-confined tumors with or without limited involvement of locoregional lymph nodes. While risk stratification is essential for guiding clinical decisions, it can be a complex endeavor in these patients due to the absence of comprehensive guidelines. Histopathological analysis and biomarker assessment play a pivotal role in defining patient outcomes. Traditional histological criteria such as tumor size, lymph node involvement, histological type and grade, lymphovascular invasion, and immune cell infiltration are significant prognostic indicators. In addition to the hormone receptor, HER2, and-in specific scenarios-BRCA1/2 testing, molecular subtyping through gene expression profiling provides valuable insights to tailor clinical decision-making. The emergence of "omics" technologies, applicable to both tissue and liquid biopsy samples, has broadened our arsenal for evaluating the risk of early BC. However, a pressing need remains for standardized methodologies and integrated pathological models that encompass multiple analytical dimensions. In this study, we provide a detailed examination of the existing strategies for early BC risk stratification, intending to serve as a practical guide for histopathologists and molecular pathologists.
Keywords: biomarkers; breast cancer; early breast cancer; prognostication; risk assessment.
Conflict of interest statement
G.V. has received consultation fees from Dako/Agilent, Roche, MSD Oncology, AstraZeneca, Daiichi Sankyo, Pfizer, and Eli Lilly. N.F. has received honoraria for consulting, advisory roles, speaker bureau, travel, and/or research grants from Merck Sharp & Dohme (MSD), Merck, Novartis, AstraZeneca, Roche, Menarini, Daiichi Sankyo, GlaxoSmithKline (GSK), Gilead, Adicet Bio, Sermonix, Reply, Veracyte Inc., Leica Biosystems, and Lilly. These companies had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; and/or in the decision to publish the results.
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References
-
- Harbeck N., Rastogi P., Martin M., Tolaney S.M., Shao Z.M., Fasching P.A., Huang C.S., Jaliffe G.G., Tryakin A., Goetz M.P., et al. Adjuvant abemaciclib combined with endocrine therapy for high-risk early breast cancer: Updated efficacy and Ki-67 analysis from the monarchE study. Ann. Oncol. 2021;32:1571–1581. doi: 10.1016/j.annonc.2021.09.015. - DOI - PubMed
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