Department of Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115.
Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA 02142.
Proc Natl Acad Sci U S A. 2023 Jan 3;120(1):e2206751120. doi: 10.1073/pnas.2206751120. Epub 2022 Dec 27.
Although antibodies targeting specific tumor-expressed antigens are the standard of care for some cancers, the identification of cancer-specific targets amenable to antibody binding has remained a bottleneck in development of new therapeutics. To overcome this challenge, we developed a high-throughput platform that allows for the unbiased, simultaneous discovery of antibodies and targets based on phenotypic binding profiles. Applying this platform to ovarian cancer, we identified a wide diversity of cancer targets including receptor tyrosine kinases, adhesion and migration proteins, proteases and proteins regulating angiogenesis in a single round of screening using genomics, flow cytometry, and mass spectrometry. In particular, we identified BCAM as a promising candidate for targeted therapy in high-grade serous ovarian cancers. More generally, this approach provides a rapid and flexible framework to identify cancer targets and antibodies.
尽管针对特定肿瘤表达抗原的抗体是某些癌症的标准治疗方法，但能够与抗体结合的癌症特异性靶标的确立一直是新疗法开发的瓶颈。为了克服这一挑战，我们开发了一种高通量平台，该平台允许基于表型结合谱进行抗体和靶标的无偏同时发现。我们将该平台应用于卵巢癌，在一轮使用基因组学、流式细胞术和质谱的筛选中，发现了广泛的癌症靶标，包括受体酪氨酸激酶、黏附和迁移蛋白、蛋白酶以及调节血管生成的蛋白。特别是，我们将 BCAM 鉴定为高级别浆液性卵巢癌靶向治疗的一个有前途的候选物。更一般地说，这种方法为鉴定癌症靶标和抗体提供了一个快速而灵活的框架。
