Nancy R. Zhang

Copy Number Variants in Schizophrenia: Confirmation of Five Previous Findings and New Evidence for 3q29 Microdeletions and VIPR2 Duplications

OBJECTIVEnTo evaluate previously reported associations of copy number variants (CNVs) with schizophrenia and to identify additional associations, the authors analyzed CNVs in the Molecular Genetics of Schizophrenia study (MGS) and additional available data.nnnMETHODnAfter quality control, MGS data for 3,945 subjects with schizophrenia or schizoaffective disorder and 3,611 screened comparison subjects were available for analysis of rare CNVs (<1% frequency). CNV detection thresholds were chosen that maximized concordance in 151 duplicate assays. Pointwise and genewise analyses were carried out, as well as analyses of previously reported regions. Selected regions were visually inspected and confirmed with quantitative polymerase chain reaction.nnnRESULTSnIn analyses of MGS data combined with other available data sets, odds ratios of 7.5 or greater were observed for previously reported deletions in chromosomes 1q21.1, 15q13.3, and 22q11.21, duplications in 16p11.2, and exon-disrupting deletions in NRXN1. The most consistently supported candidate associations across data sets included a 1.6-Mb deletion in chromosome 3q29 (21 genes, TFRC to BDH1) that was previously described in a mild-moderate mental retardation syndrome, exonic duplications in the gene for vasoactive intestinal peptide receptor 2 (VIPR2), and exonic duplications in C16orf72. The case subjects had a modestly higher genome-wide number of gene-containing deletions (>100 kb and >1 Mb) but not duplications.nnnCONCLUSIONSnThe data strongly confirm the association of schizophrenia with 1q21.1, 15q13.3, and 22q11.21 deletions, 16p11.2 duplications, and exonic NRXN1 deletions. These CNVs, as well as 3q29 deletions, are also associated with mental retardation, autism spectrum disorders, and epilepsy. Additional candidate genes and regions, including VIPR2, were identified. Study of the mechanisms underlying these associations should shed light on the pathophysiology of schizophrenia.

Discovery and Optimization of a Series of Benzothiazole Phosphoinositide 3-Kinase (PI3K)/Mammalian Target of Rapamycin (mTOR) Dual Inhibitors

Phosphoinositide 3-kinase α (PI3Kα) is a lipid kinase that plays a key regulatory role in several cellular processes. The mutation or amplification of this kinase in humans has been implicated in the growth of multiple tumor types. Consequently, PI3Kα has become a target of intense research for drug discovery. Our studies began with the identification of benzothiazole compound 1 from a high throughput screen. Extensive SAR studies led to the discovery of sulfonamide 45 as an early lead, based on its in vitro cellular potency. Subsequent modifications of the central pyrimidine ring dramatically improved enzyme and cellular potency and led to the identification of chloropyridine 70. Further arylsulfonamide SAR studies optimized in vitro clearance and led to the identification of 82 as a potent dual inhibitor of PI3K and mTOR. This molecule exhibited potent enzyme and cell activity, low clearance, and high oral bioavailability. In addition, compound 82 demonstrated tumor growth inhibition in U-87 MG, A549, and HCT116 tumor xenograft models.

Discovery and Evaluation of Dual CDK1 and CDK2 Inhibitors

In eukaryotic cells, cyclin-dependent kinase (CDK) complexes regulate the temporal progression of cells through the cell cycle. Deregulation in the cell cycle is an essential component in the evolution of cancer. Here, we validate CDK1 and CDK2 as potential therapeutic targets using novel selective small-molecule inhibitors of cyclin B1/CDK1 and cyclin E2/CDK2 enzyme complexes (CDKi). Flow cytometry-based methods were developed to assess intracellular retinoblastoma (Rb) phosphorylation to show inhibition of the CDK pathway. Tumor cells treated with CDK inhibitors showed an overall decrease in cell proliferation, accumulation of cells in G1 and G2, and apoptosis in a cell line-specific manner. Although CDK inhibitors activate p53, the inhibitors were equipotent in arresting the cell cycle in isogenic breast and colon tumor cells lacking p53, suggesting the response is independent of p53. In vivo, the CDK inhibitors prevented the growth of colon and prostate tumors, blocked proliferation of tumor cells, and inhibited Rb phosphorylation. The discovery and evaluation of novel potent and selective CDK1 and CDK2 inhibitors will help delineate the role that CDK complexes play in regulating tumorigenesis.

Subsampling methods for genomic inference

Large-scale statistical analysis of data sets associated with genome sequences plays an important role in modern biology. A key component of such statistical analyses is the computation of p-values and confidence bounds for statistics defined on the genome. Currently such computation is commonly achieved through ad hoc simulation measures. The method of randomization, which is at the heart of these simulation procedures, can significantly affect the resulting statistical conclusions. Most simulation schemes introduce a variety of hidden assumptions regarding the nature of the randomness in the data, resulting in a failure to capture biologically meaningful relationships. To address the need for a method of assessing the significance of observations within large scale genomic studies, where there often exists a complex dependency structure between observations, we propose a unified solution built upon a data subsampling approach. We propose a piecewise stationary model for genome sequences and show that the subsampling approach gives correct answers under this model. We illustrate the method on three simulation studies and two real data examples.

Metastatic tumor evolution and organoid modeling implicate TGFBR2 as a cancer driver in diffuse gastric cancer

BackgroundGastric cancer is the second-leading cause of global cancer deaths, with metastatic disease representing the primary cause of mortality. To identify candidate drivers involved in oncogenesis and tumor evolution, we conduct an extensive genome sequencing analysis of metastatic progression in a diffuse gastric cancer. This involves a comparison between a primary tumor from a hereditary diffuse gastric cancer syndrome proband and its recurrence as an ovarian metastasis.ResultsBoth the primary tumor and ovarian metastasis have common biallelic loss-of-function of both the CDH1 and TP53 tumor suppressors, indicating a common genetic origin. While the primary tumor exhibits amplification of the Fibroblast growth factor receptor 2 (FGFR2) gene, the metastasis notably lacks FGFR2 amplification but rather possesses unique biallelic alterations of Transforming growth factor-beta receptor 2 (TGFBR2), indicating the divergent in vivo evolution of a TGFBR2-mutant metastatic clonal population in this patient. As TGFBR2 mutations have not previously been functionally validated in gastric cancer, we modeled the metastatic potential of TGFBR2 loss in a murine three-dimensional primary gastric organoid culture. The Tgfbr2 shRNA knockdown within Cdh1-/-; Tp53-/- organoids generates invasion in vitro and robust metastatic tumorigenicity in vivo, confirming Tgfbr2 metastasis suppressor activity.ConclusionsWe document the metastatic differentiation and genetic heterogeneity of diffuse gastric cancer and reveal the potential metastatic role of TGFBR2 loss-of-function. In support of this study, we apply a murine primary organoid culture method capable of recapitulating in vivo metastatic gastric cancer. Overall, we describe an integrated approach to identify and functionally validate putative cancer drivers involved in metastasis.

Memory acquisition and retrieval impact different epigenetic processes that regulate gene expression.

BackgroundA fundamental question in neuroscience is how memories are stored and retrieved in the brain. Long-term memory formation requires transcription, translation and epigenetic processes that control gene expression. Thus, characterizing genome-wide the transcriptional changes that occur after memory acquisition and retrieval is of broad interest and importance. Genome-wide technologies are commonly used to interrogate transcriptional changes in discovery-based approaches. Their ability to increase scientific insight beyond traditional candidate gene approaches, however, is usually hindered by batch effects and other sources of unwanted variation, which are particularly hard to control in the study of brain and behavior.ResultsWe examined genome-wide gene expression after contextual conditioning in the mouse hippocampus, a brain region essential for learning and memory, at all the time-points in which inhibiting transcription has been shown to impair memory formation. We show that most of the variance in gene expression is not due to conditioning and that by removing unwanted variance through additional normalization we are able provide novel biological insights. In particular, we show that genes downregulated by memory acquisition and retrieval impact different functions: chromatin assembly and RNA processing, respectively. Levels of histone 2A variant H2AB are reduced only following acquisition, a finding we confirmed using quantitative proteomics. On the other hand, splicing factor Rbfox1 and NMDA receptor-dependent microRNA miR-219 are only downregulated after retrieval, accompanied by an increase in protein levels of miR-219 target CAMKIIγ.ConclusionsWe provide a thorough characterization of coding and non-coding gene expression during long-term memory formation. We demonstrate that unwanted variance dominates the signal in transcriptional studies of learning and memory and introduce the removal of unwanted variance through normalization as a necessary step for the analysis of genome-wide transcriptional studies in the context of brain and behavior. We show for the first time that histone variants are downregulated after memory acquisition, and splicing factors and microRNAs after memory retrieval. Our results provide mechanistic insights into the molecular basis of cognition by highlighting the differential involvement of epigenetic mechanisms, such as histone variants and post-transcriptional RNA regulation, after acquisition and retrieval of memory.

Detecting simultaneous variant intervals in aligned sequences

Given a set of aligned sequences of independent noisy observations, we are concerned with detecting intervals where the mean values of the observations change simultaneously in a subset of the sequences. The intervals of changed means are typically short relative to the length of the sequences, the subset where the change occurs, the carriers, can be relatively small, and the sizes of the changes can vary from one sequence to another. This problem is motivated by the scientific problem of detecting inherited copy number variants in aligned DNA samples. We suggest a statistic based on the assumption that for any given interval of changed means there is a given fraction of samples that carry the change. We derive an analytic approximation for the false positive error probability of a scan, which is shown by simulations to be reasonably accurate. We show that the new method usually improves on methods that analyze a single sample at a time and on our earlier multi-sample method, which is most efficient when the carriers form a large fraction of the set of sequences. The proposed procedure is also shown to be robust with respect to the assumed fraction of carriers of the changes.

Phospshoinositide 3-Kinase (PI3K)/Mammalian Target of Rapamycin (mTOR) Dual Inhibitors: Discovery and Structure–Activity Relationships of a Series of Quinoline and Quinoxaline Derivatives

The phosphoinositide 3-kinase (PI3K) family catalyzes the ATP-dependent phosphorylation of the 3-hydroxyl group of phosphatidylinositols and plays an important role in cell growth and survival. There is abundant evidence demonstrating that PI3K signaling is dysregulated in many human cancers, suggesting that therapeutics targeting the PI3K pathway may have utility for the treatment of cancer. Our efforts to identify potent, efficacious, and orally available PI3K/mammalian target of rapamycin (mTOR) dual inhibitors resulted in the discovery of a series of substituted quinolines and quinoxalines derivatives. In this report, we describe the structure-activity relationships, selectivity, and pharmacokinetic data of this series and illustrate the in vivo pharmacodynamic and efficacy data for a representative compound.

CODEX: a normalization and copy number variation detection method for whole exome sequencing

High-throughput sequencing of DNA coding regions has become a common way of assaying genomic variation in the study of human diseases. Copy number variation (CNV) is an important type of genomic variation, but detecting and characterizing CNV from exome sequencing is challenging due to the high level of biases and artifacts. We propose CODEX, a normalization and CNV calling procedure for whole exome sequencing data. The Poisson latent factor model in CODEX includes terms that specifically remove biases due to GC content, exon capture and amplification efficiency, and latent systemic artifacts. CODEX also includes a Poisson likelihood-based recursive segmentation procedure that explicitly models the count-based exome sequencing data. CODEX is compared to existing methods on a population analysis of HapMap samples from the 1000 Genomes Project, and shown to be more accurate on three microarray-based validation data sets. We further evaluate performance on 222 neuroblastoma samples with matched normals and focus on a well-studied rare somatic CNV within the ATRX gene. We show that the cross-sample normalization procedure of CODEX removes more noise than normalizing the tumor against the matched normal and that the segmentation procedure performs well in detecting CNVs with nested structures.

Assessing intratumor heterogeneity and tracking longitudinal and spatial clonal evolutionary history by next-generation sequencing

Significance Cancer is a disease driven by rounds of genetic and epigenetic mutations that follow Darwinian evolution. The tumor for a given patient is often a mixture of multiple genotypically and phenotypically distinct cell populations. This contributes to failures of targeted therapies and to drug resistance, and thus it is important to study intratumor heterogeneity. Here, we propose Canopy, a statistical framework to reconstruct tumor phylogeny by next-generation sequencing data from temporally and/or spatially separated tumor resections from the same patient. We show that such analyses lead to the identification of potentially useful prognostic/diagnostic biomarkers and successfully recover the tumor’s evolutionary history, validated by single-cell sequencing. Canopy provides a rigorous foundation for statistical analysis of repeated sequencing data from evolving populations. Cancer is a disease driven by evolutionary selection on somatic genetic and epigenetic alterations. Here, we propose Canopy, a method for inferring the evolutionary phylogeny of a tumor using both somatic copy number alterations and single-nucleotide alterations from one or more samples derived from a single patient. Canopy is applied to bulk sequencing datasets of both longitudinal and spatial experimental designs and to a transplantable metastasis model derived from human cancer cell line MDA-MB-231. Canopy successfully identifies cell populations and infers phylogenies that are in concordance with existing knowledge and ground truth. Through simulations, we explore the effects of key parameters on deconvolution accuracy and compare against existing methods. Canopy is an open-source R package available at https://cran.r-project.org/web/packages/Canopy/.