Caleb F. Davis

Large expansion of the ATTCT pentanucleotide repeat in spinocerebellar ataxia type 10

Spinocerebellar ataxia type 10 (SCA10; MIM 603516; refs 1,2) is an autosomal dominant disorder characterized by cerebellar ataxia and seizures. The gene SCA10 maps to a 3.8-cM interval on human chromosome 22q13–qter (refs 1,2). Because several other SCA subtypes show trinucleotide repeat expansions, we examined microsatellites in this region. We found an expansion of a pentanucleotide (ATTCT) repeat in intron 9 of SCA10 in all patients in five Mexican SCA10 families. There was an inverse correlation between the expansion size, up to 22.5 kb larger than the normal allele, and the age of onset (r2=0.34, P=0.018). Analysis of 562 chromosomes from unaffected individuals of various ethnic origins (including 242 chromosomes from Mexican persons) showed a range of 10 to 22 ATTCT repeats with no evidence of expansions. Our data indicate that the new SCA10 intronic ATTCT pentanucleotide repeat in SCA10 patients is unstable and represents the largest microsatellite expansion found so far in the human genome.

Genetic Disruption of Cortical Interneuron Development Causes Region- and GABA Cell Type-Specific Deficits, Epilepsy, and Behavioral Dysfunction

The generation of properly functioning circuits during brain development requires precise timing of cell migration and differentiation. Disruptions in the developmental plan may lead to neurological and psychiatric disorders. Neocortical circuits rely on inhibitory GABAergic interneurons, the majority of which migrate from subcortical sources. We have shown that the pleiotropic molecule hepatocyte growth factor/scatter factor (HGF/SF) mediates interneuron migration. Mice with a targeted mutation of the gene encoding urokinase plasminogen activator receptor (uPAR), a key component in HGF/SF activation and function, have decreased levels of HGF/SF and a 50% reduction in neocortical GABAergic interneurons at embryonic and perinatal ages. Disruption of interneuron development leads to early lethality in most models. Thus, the long-term consequences of such perturbations are unknown. Mice of theuPAR−/− strain survive until adulthood, and behavior testing demonstrates that they have an increased anxiety state. TheuPAR−/− strain also exhibits spontaneous seizure activity and higher susceptibility to pharmacologically induced convulsions. The neocortex of the adultuPAR−/− mouse exhibits a dramatic region- and subtype-specific decrease in GABA-immunoreactive interneurons. Anterior cingulate and parietal cortical areas contain 50% fewer GABAergic interneurons compared with wild-type littermates. However, interneuron numbers in piriform and visual cortical areas do not differ from those of normal mice. Characterization of interneuron subpopulations reveals a near complete loss of the parvalbumin subtype, with other subclasses remaining intact. These data demonstrate that a single gene mutation can selectively alter the development of cortical interneurons in a region- and cell subtype-specific manner, with deficits leading to long-lasting changes in circuit organization and behavior.

Stargazin and Other Transmembrane AMPA Receptor Regulating Proteins Interact with Synaptic Scaffolding Protein MAGI-2 in Brain

The spatial coordination of neurotransmitter receptors with other postsynaptic signaling and structural molecules is regulated by a diverse array of cell-specific scaffolding proteins. The synaptic trafficking of AMPA receptors by the stargazin protein in some neurons, for example, depends on specific interactions between the C terminus of stargazin and the PDZ [postsynaptic density-95 (PSD-95)/Discs large/zona occludens-1] domains of membrane-associated guanylate kinase scaffolding proteins PSD-93 or PSD-95. Stargazin [Cacng2 (Ca2+ channel γ2 subunit)] is one of four closely related proteins recently categorized as transmembrane AMPA receptor regulating proteins (TARPs) that appear to share similar functions but exhibit distinct expression patterns in the CNS. We used yeast two-hybrid screening to identify MAGI-2 (membrane associated guanylate kinase, WW and PDZ domain containing 2) as a novel candidate interactor with the cytoplasmic C termini of the TARPs. MAGI-2 [also known as S-SCAM (synaptic scaffolding molecule)] is a multi-PDZ domain scaffolding protein that interacts with several different ligands in brain, including PTEN (phosphatase and tensin homolog), dasm1 (dendrite arborization and synapse maturation 1), dendrin, axin, β- and δ-catenin, neuroligin, hyperpolarization-activated cation channels, β1-adrenergic receptors, and NMDA receptors. We confirmed that MAGI-2 coimmunoprecipitated with stargazin in vivo from mouse cerebral cortex and used in vitro assays to localize the interaction to the C-terminal -TTPV amino acid motif of stargazin and the PDZ1, PDZ3, and PDZ5 domains of MAGI-2. Expression of stargazin recruited MAGI-2 to cell membranes and cell–cell contact sites in transfected HEK-293T cells dependent on the presence of the stargazin -TTPV motif. These experiments identify MAGI-2 as a strong candidate for linking TARP/AMPA receptor complexes to a wide range of other postsynaptic molecules and pathways and advance our knowledge of protein interactions at mammalian CNS synapses.

Genome-wide high-density SNP linkage search for glioma susceptibility loci: results from the Gliogene Consortium

Gliomas, which generally have a poor prognosis, are the most common primary malignant brain tumors in adults. Recent genome-wide association studies have shown that inherited susceptibility plays a role in the development of glioma. Although first-degree relatives of patients exhibit a two-fold increased risk of glioma, the search for susceptibility loci in familial forms of the disease has been challenging because the disease is relatively rare, fatal, and heterogeneous, making it difficult to collect sufficient biosamples from families for statistical power. To address this challenge, the Genetic Epidemiology of Glioma International Consortium (Gliogene) was formed to collect DNA samples from families with two or more cases of histologically confirmed glioma. In this study, we present results obtained from 46 U.S. families in which multipoint linkage analyses were undertaken using nonparametric (model-free) methods. After removal of high linkage disequilibrium single-nucleotide polymorphism, we obtained a maximum nonparametric linkage score (NPL) of 3.39 (P = 0.0005) at 17q12-21.32 and the Z-score of 4.20 (P = 0.000007). To replicate our findings, we genotyped 29 independent U.S. families and obtained a maximum NPL score of 1.26 (P = 0.008) and the Z-score of 1.47 (P = 0.035). Accounting for the genetic heterogeneity using the ordered subset analysis approach, the combined analyses of 75 families resulted in a maximum NPL score of 3.81 (P = 0.00001). The genomic regions we have implicated in this study may offer novel insights into glioma susceptibility, focusing future work to identify genes that cause familial glioma.

Somatic cancer variant curation and harmonization through consensus minimum variant level data.

BackgroundTo truly achieve personalized medicine in oncology, it is critical to catalog and curate cancer sequence variants for their clinical relevance. The Somatic Working Group (WG) of the Clinical Genome Resource (ClinGen), in cooperation with ClinVar and multiple cancer variant curation stakeholders, has developed a consensus set of minimal variant level data (MVLD). MVLD is a framework of standardized data elements to curate cancer variants for clinical utility. With implementation of MVLD standards, and in a working partnership with ClinVar, we aim to streamline the somatic variant curation efforts in the community and reduce redundancy and time burden for the interpretation of cancer variants in clinical practice.MethodsWe developed MVLD through a consensus approach by i) reviewing clinical actionability interpretations from institutions participating in the WG, ii) conducting extensive literature search of clinical somatic interpretation schemas, and iii) survey of cancer variant web portals. A forthcoming guideline on cancer variant interpretation, from the Association of Molecular Pathology (AMP), can be incorporated into MVLD.ResultsAlong with harmonizing standardized terminology for allele interpretive and descriptive fields that are collected by many databases, the MVLD includes unique fields for cancer variants such as Biomarker Class, Therapeutic Context and Effect. In addition, MVLD includes recommendations for controlled semantics and ontologies. The Somatic WG is collaborating with ClinVar to evaluate MVLD use for somatic variant submissions. ClinVar is an open and centralized repository where sequencing laboratories can report summary-level variant data with clinical significance, and ClinVar accepts cancer variant data.ConclusionsWe expect the use of the MVLD to streamline clinical interpretation of cancer variants, enhance interoperability among multiple redundant curation efforts, and increase submission of somatic variants to ClinVar, all of which will enhance translation to clinical oncology practice.

Focused Analysis of Exome Sequencing Data for Rare Germline Mutations in Familial and Sporadic Lung Cancer

Introduction The association between smoking‐induced chronic obstructive pulmonary disease (COPD) and lung cancer (LC) is well documented. Recent genome‐wide association studies (GWAS) have identified 28 susceptibility loci for LC, 10 for COPD, 32 for smoking behavior, and 63 for pulmonary function, totaling 107 nonoverlapping loci. Given that common variants have been found to be associated with LC in genome‐wide association studies, exome sequencing of these high‐priority regions has great potential to identify novel rare causal variants. Methods To search for disease‐causing rare germline mutations, we used a variation of the extreme phenotype approach to select 48 patients with sporadic LC who reported histories of heavy smoking—37 of whom also exhibited carefully documented severe COPD (in whom smoking is considered the overwhelming determinant)—and 54 unique familial LC cases from families with at least three first‐degree relatives with LC (who are likely enriched for genomic effects). Results By focusing on exome profiles of the 107 target loci, we identified two key rare mutations. A heterozygous p.Arg696Cys variant in the coiled‐coil domain containing 147 (CCDC147) gene at 10q25.1 was identified in one sporadic and two familial cases. The minor allele frequency (MAF) of this variant in the 1000 Genomes database is 0.0026. The p.Val26Met variant in the dopamine &bgr;‐hydroxylase (DBH) gene at 9q34.2 was identified in two sporadic cases; the minor allele frequency of this mutation is 0.0034 according to the 1000 Genomes database. We also observed three suggestive rare mutations on 15q25.1: iron‐responsive element binding protein neuronal 2 (IREB2); cholinergic receptor, nicotinic, alpha 5 (neuronal) (CHRNA5); and cholinergic receptor, nicotinic, beta 4 (CHRNB4). Conclusions Our results demonstrated highly disruptive risk‐conferring CCDC147 and DBH mutations.

Identifying Gene Disruptions in Novel Balanced de novo Constitutional Translocations in Childhood Cancer Patients by Whole Genome Sequencing

Purpose:We applied whole-genome sequencing (WGS) to children diagnosed with neoplasms and found to carry apparently balanced constitutional translocations to discover novel genic disruptions.Methods:We applied the structural variation (SV) calling programs CREST, BreakDancer, SV-STAT, and CGAP-CNV, and we developed an annotative filtering strategy to achieve nucleotide resolution at the translocations.Results:We identified the breakpoints for t(6;12)(p21.1;q24.31), disrupting HNF1A in a patient diagnosed with hepatic adenomas and maturity-onset diabetes of the young (MODY). Translocation as the disruptive event of HNF1A, a gene known to be involved in MODY3, has not been previously reported. In a subject with Hodgkin lymphoma and subsequent low-grade glioma, we identified t(5;18)(q35.1;q21.2), disrupting both SLIT3 and DCC, genes previously implicated in both glioma and lymphoma.Conclusion:These examples suggest that implementing clinical WGS in the diagnostic workup of patients with novel but apparently balanced translocations may reveal unanticipated disruption of disease-associated genes and aid in prediction of the clinical phenotype.Genet Med 17 10, 831–835.

SV-STAT accurately detects structural variation via alignment to reference-based assemblies

BackgroundGenomic deletions, inversions, and other rearrangements known collectively as structural variations (SVs) are implicated in many human disorders. Technologies for sequencing DNA provide a potentially rich source of information in which to detect breakpoints of structural variations at base-pair resolution. However, accurate prediction of SVs remains challenging, and existing informatics tools predict rearrangements with significant rates of false positives or negatives.ResultsTo address this challenge, we developed ‘Structural Variation detection by STAck and Tail’ (SV-STAT) which implements a novel scoring metric. The software uses this statistic to quantify evidence for structural variation in genomic regions suspected of harboring rearrangements. To demonstrate SV-STAT, we used targeted and genome-wide approaches. First, we applied a custom capture array followed by Roche/454 and SV-STAT to three pediatric B-lineage acute lymphoblastic leukemias, identifying five structural variations joining known and novel breakpoint regions. Next, we detected SVs genome-wide in paired-end Illumina data collected from additional tumor samples. SV-STAT showed predictive accuracy as high as or higher than leading alternatives. The software is freely available under the terms of the GNU General Public License version 3 at https://gitorious.org/svstat/svstat.ConclusionsSV-STAT works across multiple sequencing chemistries, paired and single-end technologies, targeted or whole-genome strategies, and it complements existing SV-detection software. The method is a significant advance towards accurate detection and genotyping of genomic rearrangements from DNA sequencing data.

Abstract 4600: Target exome sequencing for disease-causing rare mutations in familial and sporadic lung cancer

Background: Recent genome-wide association studies (GWAS) have identified 28 susceptibility loci for Lung cancer (LC), 32 loci for smoking behavior, 10 loci for chronic obstructive pulmonary disease (COPD), 63 loci for pulmonary function and related phenotypes, totaling 107 GWAS susceptibility loci (as of November 2014). Given the common variants that have been found to be associated with LC in GWAS, targeted-region exome sequencing provides a cost-effective approach for further investigation of high-priority regions of the genome and has the great potential to identify rare causal variants in GWAS loci. Patients and Methods: Using an extreme phenotype approach, we selected 48 sporadic LC patients reporting heavy smoking histories with the presence of severe COPD in whom environmental factors are considered overwhelming, and 54 familial LC cases from families with at least three first-degree relatives with LC who are likely enriched for genomic signal, to search for the disease-causing rare mutations within the target 107 GWAS loci using exome sequencing data. Results: By focusing on exome profiles of these target 107 loci, we identified two disease-causing rare mutations on 6p21.32 TNXB p. Arg504His and 10q25.1 CCDC147 p.Arg696Cys. The homozygous Arg504His mutation presented in four familial and one sporadic LC cases. Notably, the minor allele frequency (MAF) of this variant in Caucasians from 1000 Genomes is very rare ( Conclusion: Our target exome sequencing results demonstrate novel highly disruptive LC risk-conferring TNXB and CCDC147 mutations. Since the rare variants have appreciable effects on disease risk prediction, families and patients may warrant screening for mutations in TNXB and CCDC147 (if validated) to assess their potential LC risk. Citation Format: Yanhong Liu, Farrah Kheradmand, Michael Scheurer, Caleb Davis, David Wheeler, Edwin Silverman, Shete Sanjay, Spiridon Tsavachidis, Georgina Armstrong, Elena Kupert, Marshall Anderson, Yafang Li, Claudio Pikielny, Joan E. Bailey-Wilson, Ming You, Colette Gaba, Mariza DeAndrade, Diptasri Mandal, Claire Simpson, Susan Pinney, Christopher Amos, Margaret Spitz. Target exome sequencing for disease-causing rare mutations in familial and sporadic lung cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4600. doi:10.1158/1538-7445.AM2015-4600

Abstract 5589: Molecular signatures of in vitro drug response in lung cancer.

We are developing in vitro drug response signatures based on profiling of mRNA (Illumina WG6-V3 arrays), DNA mutation (COSMIC and deep sequencing), DNA copy number (Illumina Human1M-Duov3 SNP array) and DNA methylation (Illumina HumanMethylation450) from lung cancer cell lines to predict which drugs a patient9s tumor is most likely to respond to. We have generated drug response phenotypes (MTS colorimetric assays) for ∼25 standard, targeted, and new chemotherapy agents and combinations for ∼ 100 non-small cell lung cancer (NSCLC) lines. All assays were done in triplicates or more and were very reproducible over time (r > 0.8). More than 10,000 MTS assays were generated and we designed a high-throughput database software named DIVISA (Database of In VItro Sensitivity Assays) for the purpose of storing and analyzing these assays. Some drugs showed a wide range of sensitivities (> 10,000-fold in IC50 values) and IC50 clustering indicates that drug response phenotypes can be grouped according to drug types. As part of a joint NCI SPORE, NCI SPECS, and DOD PROSPECT effort we have collected 275 clinically annotated frozen tumors with drug response information including 94 that represent lung cancer resection followed by adjuvant treatment. These specimens have also been profiled on Illumina expression arrays to formally test the clinical relevance of the tumor cell line signatures, and to verify that the signatures predict for response only in the presence of treatment and thus are not prognostic of survival in the absence of treatment. In addition, we have 3 primary tumor datasets totaling 96 specimens with EGFR mutation information, thus providing a validation set for EGFR tyrosine kinase inhibitor signatures. Using a weighted voting classification, cell line signatures predicted drug response in primary tumors with accuracies of ∼65% for targeted therapy (EGFR) but with somewhat lower accuracies for platin/taxane therapies suggesting that cell line predictive signatures may be better suited for targeted drugs. To facilitate translation to clinical trials we are working with High Throughput Genomics (HTG) to develop quantitative mRNA profiles that are performed on formalin fixed paraffin embedded (FFPE) material on a platform that can be transferred to a CLIA certified environment. These studies thus provide a preclinical human tumor model platform for systematically testing new drugs and for developing signatures to guide their most efficient use in early clinical tests. Funded by University of Texas SPORE in Lung Cancer (P50CA70907) and NCI SPECS Lung Cancer (CA114771). Citation Format: Luc Girard, Michael Peyton, Ignacio Wistuba, Yang Xie, Rachel Greer, Milind B. Suraokar, Carmen Behrens, Guanghua Xiao, John Heymach, David A. Wheeler, Caleb F. Davis, Kenneth Huffman, David S. Shames, Kevin R. Coombes, Adi F. Gazdar, David CL Lam, David G. Beer, John D. Minna. Molecular signatures of in vitro drug response in lung cancer. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 5589. doi:10.1158/1538-7445.AM2013-5589