Proteomic profiling across breast cancer cell lines and models.

We performed quantitative proteomics on 60 human-derived breast cancer cell line models to a depth of ~13,000 proteins. The resulting high-throughput datasets were assessed for quality and reproducibility. We used the datasets to identify and characterize the subtypes of breast cancer and showed that they conform to known transcriptional subtypes, revealing that molecular subtypes are preserved even in under-sampled protein feature sets. All datasets are freely available as public resources on the LINCS portal. We anticipate that these datasets, either in isolation or in combination with complimentary measurements such as genomics, transcriptomics and phosphoproteomics, can be mined for the purpose of predicting drug response, informing cell line specific context in models of signalling pathways, and identifying markers of sensitivity or resistance to therapeutics.

Multiplexed and reproducible high content screening of live and fixed cells using Dye Drop.

High-throughput measurement of cells perturbed using libraries of small molecules, gene knockouts, or different microenvironmental factors is a key step in functional genomics and pre-clinical drug discovery. However, it remains difficult to perform accurate single-cell assays in 384-well plates, limiting many studies to well-average measurements (e.g., CellTiter-Glo®). Here we describe a public domain Dye Drop method that uses sequential density displacement and microscopy to perform multi-step assays on living cells. We use Dye Drop cell viability and DNA replication assays followed by immunofluorescence imaging to collect single-cell dose-response data for 67 investigational and clinical-grade small molecules in 58 breast cancer cell lines. By separating the cytostatic and cytotoxic effects of drugs computationally, we uncover unexpected relationships between the two. Dye Drop is rapid, reproducible, customizable, and compatible with manual or automated laboratory equipment. Dye Drop improves the tradeoff between data content and cost, enabling the collection of information-rich perturbagen-response datasets.

Development of CDK2 and CDK5 Dual Degrader TMX-2172.

Cyclin-dependent kinase 2 (CDK2) is a potential therapeutic target for the treatment of cancer. Development of CDK2 inhibitors has been extremely challenging as its ATP-binding site shares high similarity with CDK1, a related kinase whose inhibition causes toxic effects. Here, we report the development of TMX-2172, a heterobifunctional CDK2 degrader with degradation selectivity for CDK2 and CDK5 over not only CDK1, but transcriptional CDKs (CDK7 and CDK9) and cell cycle CDKs (CDK4 and CDK6) as well. In addition, we demonstrate that antiproliferative activity in ovarian cancer cells (OVCAR8) depends on CDK2 degradation and correlates with high expression of cyclin E1 (CCNE1), which functions as a regulatory subunit of CDK2. Collectively, our work provides evidence that TMX-2172 represents a lead for further development and that CDK2 degradation is a potentially valuable therapeutic strategy in ovarian and other cancers that overexpress CCNE1.