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• W2129759851 abstract "Breast cancer is a heterogeneous disease, which comprises several molecular and genetic subtypes, each with characteristic clinicobiologic behavior and imaging patterns. Traditional classification of breast cancer is based on the histopathologic features but offers limited prognostic value. Novel molecular characterization of breast cancer with cellular markers has allowed a new classification that offers prognostic value, with predictive categories of disease aggressiveness. These molecular signatures also open the door to personalized therapeutic options, with new receptor-targeted therapies. For example, invasive cancer subtypes such as the luminal A and B subtypes show better prognosis and response to hormone receptor–targeted therapies compared with the triple-negative subtypes; on the other hand, triple-negative tumors respond better than luminal tumors to chemotherapy. Tumors that display amplification of the oncogene ERBB2 (also known as the HER2/neu oncogene) respond to drugs directed against this oncogene, such as trastuzumab. The imaging aspects of tumors correlate with molecular subgroups, as well as other pathologic features such as nuclear grade. Smooth tumor margins at mammography may be suggestive of a triple-negative breast cancer, and a human epidermal growth factor receptor 2 (HER2)–positive tumor is characteristically a spiculated mass with calcifications. Low-grade ductal carcinoma in situ (DCIS) is better detected with mammography, although magnetic resonance (MR) imaging may allow better characterization of high-grade DCIS. MR imaging diffusion sequences show higher values for the apparent diffusion coefficient for triple-negative and HER2-positive subtypes, compared with luminal A and B tumors. MR imaging is also a useful tool in the prediction of tumor response after chemotherapy, especially for triple-negative and HER2-positive subtypes. ©RSNA, 2014" @default.
• W2129759851 created "2016-06-24" @default.
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• W2129759851 date "2014-09-01" @default.
• W2129759851 modified "2023-10-12" @default.
• W2129759851 title "Molecular Classification of Infiltrating Breast Cancer: Toward Personalized Therapy" @default.
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• W2129759851 doi "https://doi.org/10.1148/rg.345130049" @default.
• W2129759851 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/25208275" @default.
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