Characteristic effect of hydroxyurea on the higher-order structure of DNA and gene expression.

Hydroxyurea (HU; hydroxycarbamide) is a chemotherapy medication used to treat various types of cancer and other diseases such as sickle cell anemia. HU inhibits DNA synthesis by targeting ribonucleotide reductase (RNR). Recent studies have suggested that HU also causes oxidative stress in living systems. In the present study, we investigated if HU could directly affect the activity and/or conformation of DNA. We measured in vitro gene expression in the presence of HU by adapting a cell-free luciferase assay. HU exhibited a bimodal effect on gene expression, where promotion or inhibition were observed at lower or higher concentrations (mM range), respectively. Using atomic force microscopy (AFM), the higher-order structure of DNA was revealed to be partially-thick with kinked-branching structures after HU was added. An elongated coil conformation was observed by AFM in the absence of HU. Single DNA molecules in bulk aqueous solution under fluctuating Brownian motion were imaged by fluorescence microscopy (FM). Both spring and damping constants, mechanical properties of DNA, increased when HU was added. These experimental investigations indicate that HU directly interacts with DNA and provide new insights into how HU acts as a chemotherapeutic agent and targets other diseases.

Integration of Computational Pipeline to Streamline Efficacious Drug Nomination and Biomarker Discovery in Glioblastoma.

Glioblastoma multiforme (GBM) is the deadliest, most heterogeneous, and most common brain cancer in adults. Not only is there an urgent need to identify efficacious therapeutics, but there is also a great need to pair these therapeutics with biomarkers that can help tailor treatment to the right patient populations. We built patient drug response models by integrating patient tumor transcriptome data with high-throughput cell line drug screening data as well as Bayesian networks to infer relationships between patient gene expression and drug response. Through these discovery pipelines, we identified agents of interest for GBM to be effective across five independent patient cohorts and in a mouse avatar model: among them are a number of MEK inhibitors (MEKis). We also predicted phosphoglycerate dehydrogenase enzyme (PHGDH) gene expression levels to be causally associated with MEKi efficacy, where knockdown of this gene increased tumor sensitivity to MEKi and overexpression led to MEKi resistance. Overall, our work demonstrated the power of integrating computational approaches. In doing so, we quickly nominated several drugs with varying known mechanisms of action that can efficaciously target GBM. By simultaneously identifying biomarkers with these drugs, we also provide tools to select the right patient populations for subsequent evaluation.

RNA splicing analysis deciphers developmental hierarchies and reveals therapeutic targets in adult glioma.

Widespread alterations in RNA alternative splicing (AS) have been identified in adult gliomas. However, their regulatory mechanism, biological significance, and therapeutic potential remain largely elusive. Here, using a computational approach with both bulk and single-cell RNA-Seq, we uncover a prognostic AS signature linked with neural developmental hierarchies. Using advanced iPSC glioma models driven by glioma driver mutations, we show that this AS signature could be enhanced by EGFRvIII and inhibited by in situ IDH1 mutation. Functional validations of 2 isoform switching events in CERS5 and MPZL1 show regulations of sphingolipid metabolism and SHP2 signaling, respectively. Analysis of upstream RNA binding proteins reveals PTBP1 as a key regulator of the AS signature where targeting of PTBP1 suppresses tumor growth and promotes the expression of a neuron marker TUJ1 in glioma stem-like cells. Overall, our data highlights the role of AS in affecting glioma malignancy and heterogeneity and its potential as a therapeutic vulnerability for treating adult gliomas.

Stem cell modeling of nervous system tumors.

Nervous system tumors, particularly brain tumors, represent the most common tumors in children and one of the most lethal tumors in adults. Despite decades of research, there are few effective therapies for these cancers. Although human nervous system tumor cells and genetically engineered mouse models have served as excellent platforms for drug discovery and preclinical testing, they have limitations with respect to accurately recapitulating important aspects of the pathobiology of spontaneously arising human tumors. For this reason, attention has turned to the deployment of human stem cell engineering involving human embryonic or induced pluripotent stem cells, in which genetic alterations associated with nervous system cancers can be introduced. These stem cells can be used to create self-assembling three-dimensional cerebral organoids that preserve key features of the developing human brain. Moreover, stem cell-engineered lines are amenable to xenotransplantation into mice as a platform to investigate the tumor cell of origin, discover cancer evolutionary trajectories and identify therapeutic vulnerabilities. In this article, we review the current state of human stem cell models of nervous system tumors, discuss their advantages and disadvantages, and provide consensus recommendations for future research.