Use of Microfluidics to Prepare Lipid-Based Nanocarriers.

Lipid-based nanoparticles (LBNPs) are an important tool for the delivery of a diverse set of drug cargoes, including small molecules, oligonucleotides, and proteins and peptides. Despite their development over the past several decades, this technology is still hindered by issues with the manufacturing processes leading to high polydispersity, batch-to-batch and operator-dependent variability, and limits to the production volumes. To overcome these issues, the use of microfluidic techniques in the production of LBNPs has sharply increased over the past two years. Microfluidics overcomes many of the pitfalls seen with conventional production methods, leading to reproducible LBNPs at lower costs and higher yields. In this review, the use of microfluidics in the preparation of various types of LBNPs, including liposomes, lipid nanoparticles, and solid lipid nanoparticles for the delivery of small molecules, oligonucleotides, and peptide/protein drugs is summarized. Various microfluidic parameters, as well as their effects on the physicochemical properties of LBNPs, are also discussed.

Structural variants drive context-dependent oncogene activation in cancer.

Higher-order chromatin structure is important for the regulation of genes by distal regulatory sequences1,2. Structural variants (SVs) that alter three-dimensional (3D) genome organization can lead to enhancer-promoter rewiring and human disease, particularly in the context of cancer3. However, only a small minority of SVs are associated with altered gene expression4,5, and it remains unclear why certain SVs lead to changes in distal gene expression and others do not. To address these questions, we used a combination of genomic profiling and genome engineering to identify sites of recurrent changes in 3D genome structure in cancer and determine the effects of specific rearrangements on oncogene activation. By analysing Hi-C data from 92 cancer cell lines and patient samples, we identified loci affected by recurrent alterations to 3D genome structure, including oncogenes such as MYC, TERT and CCND1. By using CRISPR-Cas9 genome engineering to generate de novo SVs, we show that oncogene activity can be predicted by using 'activity-by-contact' models that consider partner region chromatin contacts and enhancer activity. However, activity-by-contact models are only predictive of specific subsets of genes in the genome, suggesting that different classes of genes engage in distinct modes of regulation by distal regulatory elements. These results indicate that SVs that alter 3D genome organization are widespread in cancer genomes and begin to illustrate predictive rules for the consequences of SVs on oncogene activation.