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.

On the existence and functionality of topologically associating domains

Genomes across a wide range of eukaryotic organisms fold into higher-order chromatin domains. Topologically associating domains (TADs) were originally discovered empirically in low-resolution Hi-C heat maps representing ensemble average interaction frequencies from millions of cells. Here, we discuss recent advances in high-resolution Hi-C, single-cell imaging experiments, and functional genetic studies, which provide an increasingly complex view of the genome's hierarchical structure-function relationship. On the basis of these new findings, we update the definitions of distinct classes of chromatin domains according to emerging knowledge of their structural, mechanistic and functional properties.

Synthetic molecular recognition nanosensor paint for microalbuminuria

Microalbuminuria is an important clinical marker of several cardiovascular, metabolic, and other diseases such as diabetes, hypertension, atherosclerosis, and cancer. The accurate detection of microalbuminuria relies on albumin quantification in the urine, usually via an immunoturbidity assay; however, like many antibody-based assessments, this method may not be robust enough to function in global health applications, point-of-care assays, or wearable devices. Here, we develop an antibody-free approach using synthetic molecular recognition by constructing a polymer to mimic fatty acid binding to the albumin, informed by the albumin crystal structure. A single-walled carbon nanotube, encapsulated by the polymer, as the transduction element produces a hypsochromic (blue) shift in photoluminescence upon the binding of albumin in clinical urine samples. This complex, incorporated into an acrylic material, results in a nanosensor paint that enables the detection of microalbuminuria in patient samples and comprises a rapid point-of-care sensor robust enough to be deployed in resource-limited settings.