Afzal Muhammad Zubair, Vahdat Linda T
Medical Oncology, Comprehensive Breast Program, Dartmouth Cancer Center, Lebanon, NH 03755, USA.
Medical Oncology and Hematology (Interim), Dartmouth Cancer Center, Lebanon, NH 03755, USA.
J Pers Med. 2024 Jul 3;14(7):719. doi: 10.3390/jpm14070719.
Breast cancer is the most common cancer among women in the world as well as in the United States. Molecular and histological differentiation have helped clinicians optimize treatments with various therapeutics, including hormonal therapy, chemotherapy, immunotherapy, and radiation therapy. Recently, immunotherapy has become the standard of care in locally advanced triple-negative breast cancer and an option across molecular subtypes for tumors with a high tumor mutation burden. Despite the advancements in personalized medicine directing the management of localized and advanced breast cancers, the emergence of resistance to these therapies is the leading cause of death among breast cancer patients. Therefore, there is a critical need to identify and validate predictive biomarkers to direct treatment selection, identify potential responders, and detect emerging resistance to standard therapies. Areas of active scientific and clinical research include novel personalized and predictive biomarkers incorporating tumor microenvironment, tumor immune profiling, molecular characterization, and histopathological differentiation to predict response and the potential emergence of resistance.
乳腺癌是全球以及美国女性中最常见的癌症。分子和组织学分化有助于临床医生利用各种疗法优化治疗方案,包括激素疗法、化疗、免疫疗法和放射疗法。最近,免疫疗法已成为局部晚期三阴性乳腺癌的标准治疗方法,并且对于肿瘤突变负荷高的肿瘤,在各个分子亚型中也是一种选择。尽管在指导局部和晚期乳腺癌治疗的个性化医疗方面取得了进展,但对这些疗法产生耐药性仍是乳腺癌患者死亡的主要原因。因此,迫切需要识别和验证预测性生物标志物,以指导治疗选择、识别潜在的反应者,并检测对标准疗法新出现的耐药性。活跃的科学和临床研究领域包括结合肿瘤微环境、肿瘤免疫谱分析、分子特征和组织病理学分化的新型个性化和预测性生物标志物,以预测反应和耐药性的潜在出现。