Retrospective identification of patients with SRRM2-related neurodevelopmental disorder in a single tertiary children's hospital.

SRRM2-related neurodevelopmental disorder is a recently described genetic diagnosis caused by loss-of-function variants in SRRM2. In order to understand the clinical spectrum of SRRM2-related neurodevelopmental disorder, we performed a retrospective exome data and clinical chart review at a single tertiary children's hospital, Children's Hospital of Philadelphia (CHOP). Among approximately 3100 clinical exome sequencing cases performed at CHOP, we identified three patients with SRRM2 loss-of-function pathogenic variants, in addition to one patient previously described in the literature. Common clinical features include developmental delay, attention deficit hyperactivity disorder, macrocephaly, hypotonia, gastroesophageal reflux, overweight/obesity, and autism. While developmental disabilities are commonly seen in all individuals with SRRM2 variants, the degree of developmental delay and intellectual disability is variable. Our data suggest that SRRM2-related neurodevelopmental disorder can be identified in 0.3% of individuals with developmental disabilities receiving exome sequencing.

Nuclear speckleopathies: developmental disorders caused by variants in genes encoding nuclear speckle proteins.

Nuclear speckles are small, membrane-less organelles that reside within the nucleus. Nuclear speckles serve as a regulatory hub coordinating complex RNA metabolism steps including gene transcription, pre-mRNA splicing, RNA modifications, and mRNA nuclear export. Reflecting the importance of proper nuclear speckle function in regulating normal human development, an increasing number of genetic disorders have been found to result from mutations in the genes encoding nuclear speckle proteins. To denote this growing class of genetic disorders, we propose "nuclear speckleopathies". Notably, developmental disabilities are commonly seen in individuals with nuclear speckleopathies, suggesting the particular importance of nuclear speckles in ensuring normal neurocognitive development. In this review article, a general overview of nuclear speckle function, and the current knowledge of the mechanisms underlying some nuclear speckleopathies, such as ZTTK syndrome, NKAP-related syndrome, TARP syndrome, and TAR syndrome, are discussed. These nuclear speckleopathies represent valuable models to understand the basic function of nuclear speckles and how its functional defects result in human developmental disorders.

Synergy from gene expression and network mining (SynGeNet) method predicts synergistic drug combinations for diverse melanoma genomic subtypes.

Systems biology perspectives are crucial for understanding the pathophysiology of complex diseases, and therefore hold great promise for the discovery of novel treatment strategies. Drug combinations have been shown to improve durability and reduce resistance to available first-line therapies in a variety of cancers; however, traditional drug discovery approaches are prohibitively cost and labor-intensive to evaluate large-scale matrices of potential drug combinations. Computational methods are needed to efficiently model complex interactions of drug target pathways and identify mechanisms underlying drug combination synergy. In this study, we employ a computational approach, SynGeNet (Synergy from Gene expression and Network mining), which integrates transcriptomics-based connectivity mapping and network centrality analysis to analyze disease networks and predict drug combinations. As an exemplar of a disease in which combination therapies demonstrate efficacy in genomic-specific contexts, we investigate malignant melanoma. We employed SynGeNet to generate drug combination predictions for each of the four major genomic subtypes of melanoma (BRAF, NRAS, NF1, and triple wild type) using publicly available gene expression and mutation data. We validated synergistic drug combinations predicted by our method across all genomic subtypes using results from a high-throughput drug screening study across. Finally, we prospectively validated the drug combination for BRAF-mutant melanoma that was top ranked by our approach, vemurafenib (BRAF inhibitor) + tretinoin (retinoic acid receptor agonist), using both in vitro and in vivo models of BRAF-mutant melanoma and RNA-sequencing analysis of drug-treated melanoma cells to validate the predicted mechanisms. Our approach is applicable to a wide range of disease domains, and, importantly, can model disease-relevant protein subnetworks in precision medicine contexts.