Department of Population Sciences, City of Hope Comprehensive Cancer Center, Duarte, California, USA.
Department of Medical Engineering, California Institute of Technology, Pasadena, California, USA.
WIREs Mech Dis. 2021 Mar;13(2):e1506. doi: 10.1002/wsbm.1506. Epub 2020 Oct 1.
Over 90% of breast cancer is cured; yet there remain highly aggressive breast cancers that develop rapidly and are extremely difficult to treat, much less prevent. Breast cancers that rapidly develop between breast image screening are called "interval cancers." The efforts of our team focus on identifying multiscale integrated strategies to identify biologically aggressive precancerous breast lesions. Our goal is to identify spatiotemporal changes that occur prior to development of interval breast cancers. To accomplish this requires integration of new technology. Our team has the ability to perform single cell in situ transcriptional profiling, noncontrast biological imaging, mathematical analysis, and nanoscale evaluation of receptor organization and signaling. These technological innovations allow us to start to identify multidimensional spatial and temporal relationships that drive the transition from biologically aggressive precancer to biologically aggressive interval breast cancer. This article is categorized under: Cancer > Computational Models Cancer > Molecular and Cellular Physiology Cancer > Genetics/Genomics/Epigenetics.
超过 90%的乳腺癌是可以治愈的；但仍存在高度侵袭性的乳腺癌，这些癌症发展迅速，极难治疗，更不用说预防了。在乳房影像筛查中迅速发展的乳腺癌被称为“间期癌”。我们团队的工作重点是确定多尺度综合策略，以识别具有侵袭性的癌前乳腺病变。我们的目标是识别在间期乳腺癌发生之前发生的时空变化。要做到这一点，需要整合新技术。我们的团队有能力进行单细胞原位转录谱分析、无对比生物成像、数学分析以及受体组织和信号的纳米级评估。这些技术创新使我们能够开始识别驱动从具有侵袭性的癌前病变到具有侵袭性的间期乳腺癌的生物学转变的多维时空关系。本文属于以下类别：癌症 > 计算模型癌症 > 分子和细胞生理学癌症 > 遗传学/基因组学/表观遗传学。
