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1.  Screening of cell cycle fusion proteins to identify kinase signaling networks 
Cell Cycle  2015;14(8):1274-1281.
Kinase signaling networks are well-established mediators of cell cycle transitions. However, how kinases interact with the ubiquitin proteasome system (UPS) to elicit protein turnover is not fully understood. We sought a means of identifying kinase-substrate interactions to better understand signaling pathways controlling protein degradation. Our prior studies used a luciferase fusion protein to uncover kinase networks controlling protein turnover. In this study, we utilized a similar approach to identify pathways controlling the cell cycle protein p27Kip1. We generated a p27Kip1-luciferase fusion and expressed it in cells incubated with compounds from a library of pharmacologically active compounds. We then compared the relative effects of the compounds on p27Kip1-luciferase fusion stabilization. This was combined with in silico kinome profiling to identify potential kinases inhibited by each compound. This approach effectively uncovered known kinases regulating p27Kip1 turnover. Collectively, our studies suggest that this parallel screening approach is robust and can be applied to fully understand kinase-ubiquitin pathway interactions.
doi:10.1080/15384101.2015.1006987
PMCID: PMC4614911  PMID: 25606665
cell cycle; degradation; kinases; signaling networks; ubiquitin
2.  The APC/C and CK1 in the developing brain 
Oncotarget  2015;6(19):16792-16793.
PMCID: PMC4627257  PMID: 26219466
the anaphase promoting complex; neurite out-growth; granule cell progenitors; casein kinase; cell cycle exit
3.  BET bromodomain proteins are required for glioblastoma cell proliferation 
Epigenetics  2014;9(4):611-620.
Epigenetic proteins have recently emerged as novel anticancer targets. Among these, bromodomain and extra terminal domain (BET) proteins recognize lysine-acetylated histones, thereby regulating gene expression. Newly described small molecules that inhibit BET proteins BRD2, BRD3, and BRD4 reduce proliferation of NUT (nuclear protein in testis)-midline carcinoma, multiple myeloma, and leukemia cells in vitro and in vivo. These findings prompted us to determine whether BET proteins may be therapeutic targets in the most common primary adult brain tumor, glioblastoma (GBM). We performed NanoString analysis of GBM tumor samples and controls to identify novel therapeutic targets. Several cell proliferation assays of GBM cell lines and stem cells were used to analyze the efficacy of the drug I-BET151 relative to temozolomide (TMZ) or cell cycle inhibitors. Lastly, we performed xenograft experiments to determine the efficacy of I-BET151 in vivo. We demonstrate that BRD2 and BRD4 RNA are significantly overexpressed in GBM, suggesting that BET protein inhibition may be an effective means of reducing GBM cell proliferation. Disruption of BRD4 expression in glioblastoma cells reduced cell cycle progression. Similarly, treatment with the BET protein inhibitor I-BET151 reduced GBM cell proliferation in vitro and in vivo. I-BET151 treatment enriched cells at the G1/S cell cycle transition. Importantly, I-BET151 is as potent at inhibiting GBM cell proliferation as TMZ, the current chemotherapy treatment administered to GBM patients. Since I-BET151 inhibits GBM cell proliferation by arresting cell cycle progression, we propose that BET protein inhibition may be a viable therapeutic option for GBM patients suffering from TMZ resistant tumors.
doi:10.4161/epi.27906
PMCID: PMC4121371  PMID: 24496381
glioblastoma; epigenetics; bromodomain; stem cells; histones; histone acetylation mimics; temozolomide
4.  Epigenetic pathways and glioblastoma treatment 
Epigenetics  2013;8(8):785-795.
Glioblastoma multiforme (GBM) is the most common malignant adult brain tumor. Standard GBM treatment includes maximal safe surgical resection with combination radiotherapy and adjuvant temozolomide (TMZ) chemotherapy. Alarmingly, patient survival at five-years is below 10%. This is in part due to the invasive behavior of the tumor and the resulting inability to resect greater than 98% of some tumors. In fact, recurrence after such treatment may be inevitable, even in cases where gross total resection is achieved. The Cancer Genome Atlas (TCGA) research network performed whole genome sequencing of GBM tumors and found that GBM recurrence is linked to epigenetic mechanisms and pathways. Central to these pathways are epigenetic enzymes, which have recently emerged as possible new drug targets for multiple cancers, including GBM. Here we review GBM treatment, and provide a systems approach to identifying epigenetic drivers of GBM tumor progression based on temporal modeling of putative GBM cells of origin. We also discuss advances in defining epigenetic mechanisms controlling GBM initiation and recurrence and the drug discovery considerations associated with targeting epigenetic enzymes for GBM treatment.
doi:10.4161/epi.25440
PMCID: PMC3883781  PMID: 23807265
epigenetics; glioblastoma; statistical modeling; drug discovery
5.  GE-32AN INTERGRADED BIOINFORMATICS APPROACH FOR IDENTIFYING NOVEL GENE NETWORKS IN GLIOBLASTOMA 
Neuro-Oncology  2014;16(Suppl 5):v103.
Glioblastoma (GBM) is the most common and aggressive malignant brain tumor. Despite treatment advances, the median survival time is still below 2 years since recurrence is nearly universal. Therefore, the discovery of novel and specific molecular targets is needed. However, the identification of such targets is difficult given the high degree of variability among patient samples and individual sequencing analysis is needed for patient specific therapies. Identifying differentially expressed (DE) genes based on small sample sizes is yet another challenge since there is high variability among the different analysis algorithms. To circumvent this problem, we implemented a bioinformatics pipeline, which utilizes the large number of samples in TCGA as a reference to identify DE genes in an individual patient's tumor. By using this algorithm, we produced enriched single patient RNAseq DE gene lists and subsequently calculated a hypergeometric probability and correlation coefficient for every gene pair on these lists. Furthermore, by using the most significant of these pairs, we generated gene association networks. Importantly, our networks were validated utilizing protein-protein interaction studies and therefore could be used to identify patient specific combination therapies for GBM.
doi:10.1093/neuonc/nou256.31
PMCID: PMC4218197
6.  Identifying Glioblastoma Gene Networks Based on Hypergeometric Test Analysis 
PLoS ONE  2014;9(12):e115842.
Patient specific therapy is emerging as an important possibility for many cancer patients. However, to identify such therapies it is essential to determine the genomic and transcriptional alterations present in one tumor relative to control samples. This presents a challenge since use of a single sample precludes many standard statistical analysis techniques. We reasoned that one means of addressing this issue is by comparing transcriptional changes in one tumor with those observed in a large cohort of patients analyzed by The Cancer Genome Atlas (TCGA). To test this directly, we devised a bioinformatics pipeline to identify differentially expressed genes in tumors resected from patients suffering from the most common malignant adult brain tumor, glioblastoma (GBM). We performed RNA sequencing on tumors from individual GBM patients and filtered the results through the TCGA database in order to identify possible gene networks that are overrepresented in GBM samples relative to controls. Importantly, we demonstrate that hypergeometric-based analysis of gene pairs identifies gene networks that validate experimentally. These studies identify a putative workflow for uncovering differentially expressed patient specific genes and gene networks for GBM and other cancers.
doi:10.1371/journal.pone.0115842
PMCID: PMC4281219  PMID: 25551752
7.  An Ultra-High Throughput Cell-Based Screen for Wee1 Degradation Inhibitors 
Journal of biomolecular screening  2010;15(8):907-917.
The tyrosine kinase Wee1 is part of a key cellular sensing mechanism that signals completion of DNA replication, ensuring proper timing of entry into mitosis. Wee1 acts as an inhibitor of mitotic entry by phosphorylating cyclin-dependent kinase CDK1. Wee1 activity is mainly regulated at the protein level through its phosphorylation and subsequent degradation by the ubiquitin proteasome pathway. To facilitate identification of small molecules preventing Wee1 degradation, a homogeneous cell-based assay was developed using HeLa cells transiently transfected with a Wee1-Luciferase fusion protein. To insure uHTS compatibility, the assay was scaled to 1,536-well plate format and cells were transfected in bulk and cryopreserved. This miniaturized homogenous assay demonstrated robust performance, with a calculated Z′ factor of 0.65±0.05. The assay was screened against a publicly available library of ~218,000 compounds in order to identify Wee1 stabilizers. Nonselective, cytotoxic and promiscuous compounds were rapidly triaged through the use of a similarly formatted counterscreen that measured stabilization of a N-cyclin B-Luciferase fusion protein, as well as execution of viability assessment in the parental HeLa cell line. This screening campaign led to the discovery of four unrelated cell-permeable small molecules that showed selective Wee1-Luciferase stabilization with micromolar potency. One of these compounds, SID4243143, was shown to inhibit cell cycle progression, underscoring the importance of Wee1 degradation to the cell cycle. Our results suggest that this uHTS approach is suitable for identifying selective chemical probes that prevent Wee1 degradation, and generally applicable to discovering inhibitors of the ubiquitin proteasome pathway.
doi:10.1177/1087057110375848
PMCID: PMC3082437  PMID: 20660794
Wee1; degradation; stabilizer; reporter assay; transient transfection; cryopreserved cells; ubiquitin; proteasome

Results 1-7 (7)