乳腺癌
医学
个性化医疗
精密医学
背景(考古学)
靶向治疗
放射治疗
癌症
激素疗法
肿瘤科
内科学
重症监护医学
医学物理学
生物信息学
病理
古生物学
生物
作者
Sylvie Rodrigues-Ferreira,Clara Nahmias
出处
期刊:Cancer Letters
[Elsevier]
日期:2022-07-16
卷期号:545: 215828-215828
被引量:27
标识
DOI:10.1016/j.canlet.2022.215828
摘要
Breast cancer is one of the most frequent malignancies among women worldwide. Based on clinical and molecular features of breast tumors, patients are treated with chemotherapy, hormonal therapy and/or radiotherapy and more recently with immunotherapy or targeted therapy. These different therapeutic options have markedly improved patient outcomes. However, further improvement is needed to fight against resistance to treatment. In the rapidly growing area of research for personalized medicine, predictive biomarkers - which predict patient response to therapy - are essential tools to select the patients who are most likely to benefit from the treatment, with the aim to give the right therapy to the right patient and avoid unnecessary overtreatment. The search for predictive biomarkers is an active field of research that includes genomic, proteomic and/or machine learning approaches. In this review, we describe current strategies and innovative tools to identify, evaluate and validate new biomarkers. We also summarize current predictive biomarkers in breast cancer and discuss companion biomarkers of targeted therapy in the context of precision medicine.
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