Discovery of NSD2-Degraders from Novel and Selective DEL Hits.

NSD2 is a histone methyltransferase predominantly catalyzing di-methylation of histone H3 on lysine K36. Increased NSD2 activity due to mutations or fusion-events affecting the gene encoding NSD2 is considered an oncogenic event and a driver in various cancers, including multiple myelomas carrying t(4;14) chromosomal translocations and acute lymphoblastic leukemia's expressing the hyperactive NSD2 mutant E1099 K. Using DNA-encoded libraries, we have identified small molecule ligands that selectively and potently bind to the PWWP1 domain of NSD2, inhibit NSD2 binding to H3K36me2-bearing nucleosomes, but do not inhibit the methyltransferase activity. The ligands were subsequently converted to selective VHL1-recruiting NSD2 degraders and by using one of the most efficacious degraders in cell lines, we show that it leads to NSD2 degradation, decrease in K3 K36me2 levels and inhibition of cell proliferation.

Assessing sample and miRNA profile quality in serum and plasma or other biofluids.

MicroRNAs (miRNAs) constitute a class of small cellular RNAs (typically 21-23nt) that function as post-transcriptional regulators of gene expression. Current estimates indicate that more than one third of the cellular transcriptome is regulated by miRNAs, although they are relatively few in number (less than 2000 human miRNAs). The high relative stability of miRNA in common clinical tissues and biofluids (e.g. plasma, serum, urine, saliva, etc.) and the ability of miRNA expression profiles to accurately classify discrete tissue types and disease states have positioned miRNA quantification as a promising new tool for a wide range of diagnostic applications. Furthermore miRNAs have been shown to be rapidly released from tissues into the circulation with the development of pathology. To facilitate discovery and clinical development of miRNA-based biomarkers, we developed a genome-wide Locked Nucleic Acid (LNA™)-based miRNA qPCR platform with unparalleled sensitivity and robustness. The platform allows high-throughput profiling of miRNAs from important clinical sources without the need for pre-amplification. Using this system, we have profiled thousands of biofluid samples including blood derived plasma and serum. An extensive quality control (QC) system has been implemented in order to secure technical excellence and reveal any unwanted bias coming from pre-analytical or analytical variables. We present our approaches to sample and RNA QC as well as data QC and normalization. Specifically we have developed normal reference ranges for circulating miRNAs in serum and plasma as well as a hemolysis indicator based on microRNA expression.