Exome Datasets Research Articles

Landscape of warfarin and clopidogrel pharmacogenetic variants in Qatari population from whole exome datasets.

Pharmacogenetic landscapes of commonly used antiplatelet drugs, warfarin and clopidogrel have been studied in-depth in many countries. However, there is a paucity of data to understand their patterns in the Arab populations. We analyzed the whole exome sequencing datasets of 100 Qatar individuals available in public domain with this perspective. We characterized the allelic distribution of variants routinely tested for warfarin and clopidogrel. We additionally evaluated the population stratification and its effect on allele frequency distribution. Our analysis points to ethnic differences in the frequency distribution even for the small population studied. This is one of the first and most comprehensive pharmacogenetic maps of variants associated with warfarin and clopidogrel for an Arab population, which can help tailor the drug dosage to the population.

An adaptive rule-based classifier for mining big biological data

In this paper, we introduce a new adaptive rule-based classifier for multi-class classification of biological data, where several problems of classifying biological data are addressed: overfitting, noisy instances and class-imbalance data. It is well known that rules are interesting way for representing data in a human interpretable way. The proposed rule-based classifier combines the random subspace and boosting approaches with ensemble of decision trees to construct a set of classification rules without involving global optimisation. The classifier considers random subspace approach to avoid overfitting, boosting approach for classifying noisy instances and ensemble of decision trees to deal with class-imbalance problem. The classifier uses two popular classification techniques: decision tree and k-nearest-neighbor algorithms. Decision trees are used for evolving classification rules from the training data, while k-nearest-neighbor is used for analysing the misclassified instances and removing vagueness between the contradictory rules. It considers a series of k iterations to develop a set of classification rules from the training data and pays more attention to the misclassified instances in the next iteration by giving it a boosting flavour. This paper particularly focuses to come up with an optimal ensemble classifier that will help for improving the prediction accuracy of DNA variant identification and classification task. The performance of proposed classifier is tested with compared to well-approved existing machine learning and data mining algorithms on genomic data (148 Exome data sets) of Brugada syndrome and 10 real benchmark life sciences data sets from the UCI (University of California, Irvine) machine learning repository. The experimental results indicate that the proposed classifier has exemplary classification accuracy on different types of biological data. Overall, the proposed classifier offers good prediction accuracy to new DNA variants classification where noisy and misclassified variants are optimised to increase test performance.

OpEx - a validated, automated pipeline optimised for clinical exome sequence analysis.

We present an easy-to-use, open-source Optimised Exome analysis tool, OpEx (http://icr.ac.uk/opex) that accurately detects small-scale variation, including indels, to clinical standards. We evaluated OpEx performance with an experimentally validated dataset (the ICR142 NGS validation series), a large 1000 exome dataset (the ICR1000 UK exome series), and a clinical proband-parent trio dataset. The performance of OpEx for high-quality base substitutions and short indels in both small and large datasets is excellent, with overall sensitivity of 95%, specificity of 97% and low false detection rate (FDR) of 3%. Depending on the individual performance requirements the OpEx output allows one to optimise the inevitable trade-offs between sensitivity and specificity. For example, in the clinical setting one could permit a higher FDR and lower specificity to maximise sensitivity. In contexts where experimental validation is not possible, minimising the FDR and improving specificity may be a preferable trade-off for slightly lower sensitivity. OpEx is simple to install and use; the whole pipeline is run from a single command. OpEx is therefore well suited to the increasing research and clinical laboratories undertaking exome sequencing, particularly those without in-house dedicated bioinformatics expertise.

Abstract 847: Molecular characterization of breast tumor T-cell infiltration in exome datasets

Abstract Tumors are heterogeneous, containing tumor-infiltrating lymphocytes (TILs) which presence has been associated with favorable prognosis in multiple tumor types. Importantly, most of the T-cell specificity for tumor neo-antigen lies in a unique sequence of DNA (CDR3) resulting from the recombination of the V, D, and J segments of the T-cell receptor beta (TCRB clonotype). The Cancer Genome Atlas (TCGA) is the most comprehensive molecular dataset of tumors but does not include detailed information about TILs or tumor immunity in general. In order to characterize the T-cell infiltration in public cancer genomic datasets, we hypothesize that such a unique CDR3 DNA fragment can be recovered from bulk tumor genome-wide DNA or RNA sequencing and that the information can be used for clinical association studies. We first establish the feasibility of the approach by comparing the deep CDR3 sequencing (ImmunoSeq) and CDR3 reads recovered in tumor exome data. The clonotypes were detected using three CDR3 read detection tools and results were compared to the ImmunoSeq results. Each tool identifies between 10 and 38 reads. As expected, most of the CDR3 reads are misaligned to the naïve reference genome (60% clipped). Across all three tools, we identify 26 unique clonotypes, 15 of which are detected in the ImmunoSeq experiment. IMSEQ shows the strongest overlap with the other tools (13/14 clonotypes) and with ImmunoSeq (9/14 clonotypes) showing that our strategy identifies bona fide CDR3 reads from exome datasets. We applied the approach to a cohort of 1,078 TCGA samples. We identified CDR3 reads in 473 samples which are more likely to have a higher fraction of TILs as detected by histological review (p = 1.14×10-8). Using the RNA-seq datasets, 906 samples had CDR3 reads and also associated with higher TIL content (p = 4.41×10-6). Tumors with CDR3 reads in both DNA and RNA datasets tend have a higher TIL fraction. A set of 66 tumors shares a unique TCRâ clonotype with however no association with tumor subtypes or HLA haplotype. When restricted to Her2+ tumors, high CDR3 read counts, but not high fraction of TILs, was associated with better overall survival (p = 0.016), suggesting that CDR3 reads are predictive of anti-Her2 response. In contrast, the presence of CDR3 reads in Her2- tumors is not prognostic. A detailed analysis of 22 immune meta-gene expression signatures in these samples complements CDR3 reads information and suggests mechanisms of immune-tolerance. Our results demonstrate the feasibility of identifying genetic evidence of T-cells in bulk tumor samples using deep sequencing, providing information about the T-cell abundance and clonal identity. This novel type of tumor immune biomarker enriches the comprehensive dataset collected through TCGA, and reveals correlations with other molecular features and clinical outcomes. Citation Format: Olivier Harismendy, Eric D. Levy, Valentine Garate-Calderon, Brian Woo, Ricardo Armisen. Molecular characterization of breast tumor T-cell infiltration in exome datasets. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 847.

Abstract 87: Clustered somatic mutations are frequent in transcription factor binding motifs in melanoma and other cutaneous malignancies

Abstract We sought to explore the etiology, frequency and clinicopathologic associations of clustered noncoding hotspot mutations in cutaneous malignancies (melanoma, basal cell carcinoma (BCC) and Merkel cell carcinoma (MCC)). We did so by applying a sliding window approach which identified clusters in melanoma whole exome and genome sequencing data. These regions were then evaluated for recurrence in other skin malignancies by using whole exome data from BCC and MCC samples; motifs were extracted using a maximum expectation algorithm. We then sequenced 170 annotated melanoma clinical samples using a targeted amplicon panel which permitted analysis of clinicopathological correlations. Numerous recurrent clustered hotspot mutations were identified in melanoma whole exome and genome data sets in proximal promoters, with some gene-associated clusters present in up to 25% of cases. Mutations were clustered around canonical ETS and SP1 transcription factor binding sites and had a clear UV signature. These promoter mutations correlated with overall mutation load and NF1 mutation status, and showed significant enrichment in specific melanoma subtypes (desmoplastic and lentigo maligna melanoma), sun exposed anatomical locations, male gender, ulceration and increasing age. Identical clusters were identified in BCC and MCC samples, including several previously annotated in melanoma. In conclusion, we identify a novel class of mutation in cutaneous malignancies which rather than being defined by a particular genomic position are related to a position in a transcription factor binding motif. These mutations are also independent of cell of origin. Clinicopathologic correlation and mutation analysis support an etiologic role for chronic UV irradiation. Citation Format: Andrew J. Colebatch, Leon di Stefano, Stephen Q. Wong, Anthony T. Papenfuss, Grant A. McArthur. Clustered somatic mutations are frequent in transcription factor binding motifs in melanoma and other cutaneous malignancies. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 87.

Abstract 5293: NCI Office of Cancer Genomics: Generating publicly available data and resources for the advancement of precision medicine

Abstract The Office of Cancer Genomics (OCG), within the National Cancer Institute, supports cutting-edge genomics and translational research to advance the molecular understanding of cancer, with the ultimate goal of improving clinical outcomes through precision medicine. OCG-supported cancer research initiatives generate and analyze comprehensive genomics datasets, and translate these data into tools, resources, and clinically-relevant information. OCG currently supports three complimentary initiatives, each uniquely collaborative and innovative. The Cancer Genome Characterization Initiative (CGCI) and the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) Initiative collect high quality, clinically annotated, tumor and normal matched tissue samples for both discovery and validation cohorts. These initiatives aim to identify therapeutic targets and biomarkers in some malignancies prevalent in HIV-positive individuals and high-risk pediatric cancers. Samples are analyzed by whole genome, whole exome, and transcriptome sequencing and datasets are available to the research community in ways that protect patient privacy. The Cancer Target Discovery and Development (CTD⁁2) Network combines computational approaches, high-throughput functional assays, and high content small molecule and genetic screens to accelerate the translation of genomic data into discoveries that will inform patient-specific cancer treatments. The Network develops bioinformatics and analysis tools, generates diverse datasets, and further validates subsets of these data. All resources, datasets (https://ctd2.nci.nih.gov/dataPortal/), and validated results (http://ctd2-dashboard.nci.nih.gov/) are openly available to the research community. Data, analytical tools, and resources generated by OCG initiatives are made publicly available and can be accessed through the OCG website (https://ocg.cancer.gov/). Investigators can use and analyze the data according to their research interests. In addition, datasets generated by OCG-supported programs can serve as valuable resources for those seeking to validate genomic findings. For this poster presentation we will present the most up-to-date information about what data and resources are available, and how to access them. The use of OCG datasets and resources by the research community will further the collaborative goal of enabling precision medicine in the clinic. Citation Format: Nadia L. Jaber, Jessica N. Mazerik, Jaime M. Guidry Auvil, Subhashini Jagu, Nicholas Griner, Martin Ferguson, Daniela S. Gerhard. NCI Office of Cancer Genomics: Generating publicly available data and resources for the advancement of precision medicine. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 5293.

MSeqDR: A Centralized Knowledge Repository and Bioinformatics Web Resource to Facilitate Genomic Investigations in Mitochondrial Disease.

MSeqDR is the Mitochondrial Disease Sequence Data Resource, a centralized and comprehensive genome and phenome bioinformatics resource built by the mitochondrial disease community to facilitate clinical diagnosis and research investigations of individual patient phenotypes, genomes, genes, and variants. A central Web portal (https://mseqdr.org) integrates community knowledge from expert-curated databases with genomic and phenotype data shared by clinicians and researchers. MSeqDR also functions as a centralized application server for Web-based tools to analyze data across both mitochondrial and nuclear DNA, including investigator-driven whole exome or genome dataset analyses through MSeqDR-Genesis. MSeqDR-GBrowse genome browser supports interactive genomic data exploration and visualization with custom tracks relevant to mtDNA variation and mitochondrial disease. MSeqDR-LSDB is a locus-specific database that currently manages 178 mitochondrial diseases, 1,363 genes associated with mitochondrial biology or disease, and 3,711 pathogenic variants in those genes. MSeqDR Disease Portal allows hierarchical tree-style disease exploration to evaluate their unique descriptions, phenotypes, and causative variants. Automated genomic data submission tools are provided that capture ClinVar compliant variant annotations. PhenoTips will be used for phenotypic data submission on deidentified patients using human phenotype ontology terminology. The development of a dynamic informed patient consent process to guide data access is underway to realize the full potential of these resources.

Identification of Rare Variants in ATP8B4 as a Risk Factor for Systemic Sclerosis by Whole-Exome Sequencing.

To determine the contribution of rare variants as genetic modifiers of the expressivity, penetrance, and severity of systemic sclerosis (SSc). We performed whole-exome sequencing of 78 European American patients with SSc, including 35 patients without pulmonary arterial hypertension (PAH) and 43 patients with PAH. Association testing of case-control probability for rare variants was performed using the unified sequence kernel association test with optimal kernel weighting and small sample adjustment by comparing all SSc patients with a reference population of 3,179 controls from the Exome Sequencing Project 5,500 exome data set. Replication genotyping was performed in an independent sample of 3,263 patients (415 patients with SSc and 2,848 controls). We conducted expression profiling of messenger RNA from 61 SSc patients (19 without PAH and 42 with PAH) and 41 corresponding controls. The ATP8B4 gene was associated with a significant increase in the risk of SSc (P = 2.77 × 10(-7)). Among the 64 ATP8B4 variants tested, a single missense variant, c.1308C>G (F436L, rs55687265), provided the most compelling evidence of association (P = 9.35 × 10(-10), odds ratio [OR] 6.11), which was confirmed in the replication cohort (P = 0.012, OR 1.86) and meta-analysis (P = 1.92 × 10(-7), OR 2.5). Genes involved in E3 ubiquitin-protein ligase complex (ASB10) and cyclic nucleotide gated channelopathies (CNGB3) as well as HLA-DRB5 and HSPB2 (heat-shock protein 27) provided additional evidence of association (P < 10(-5)). Differential ATP8B4 expression was observed among the SSc patients compared to the controls (P = 0.0005). ATP8B4 may represent a putative genetic risk factor for SSc and pulmonary vascular complications.

Abstract A1-06: Recurrent mutations of hormone-positive breast cancer and association with outcome

Abstract Background: Relationships between recurrent somatic mutations and outcome in estrogen receptor positive (ER+) breast cancer have not been extensively studied as the original discovery efforts were from either heterogeneously treated patients or follow up was too brief. Targeted massively parallel sequencing (MPS) analysis was therefore conducted on DNA extracted from archived formalin-fixed breast primaries from a cohort of over 600 patents from British Columbia treated with five years of adjuvant tamoxifen monotherapy and followed for over 10 years (Nielsen et al CCR 16:5222, 2010). Methods: Genes were selected for targeted sequencing by meta-analysis of five large-scale breast cancer sequencing studies and manual review of breast cancer literature. In total, 83 genes were identified and 3286 probes were designed to tile across all known exons. Minimum starting input DNA was 50ng (mean=189.1ng). Illumina sequencing libraries were constructed, indexed, pooled, and enriched for target sequences by hybrid-capture followed by paired-end 100bp reads. The Genome Modeling System was used to perform single-tumor somatic variant prediction. Variant calls were filtered to include only targeted regions and exclude variants with global minor allele frequencies greater than 0.1% in unmatched non-tumor samples from 1000 genomes, NHLBI exome, and TCGA datasets. Kaplan-Meier univariate and multivariate survival analyses (including mutation status, clinical features and intrinsic subtype by qPCR) were performed for breast-cancer-specific and relapse free survival. Results: A total of 625 samples met minimum quality controls of 80% targeted space covered at 20X or greater. On average, each sample had 332M aligned bases and a mean coverage of 134.3X. In total, 3,628 variants were identified including 2,066 missense, 188 nonsense, and 298 frame shift insertions or deletions. Novel hot spots for recurrent mutation were identified in several genes including a splice site mutation in CBFB. Results indicate significant associations between mutation status and improved survival for MAP3K1, ERBB3, ARID1B, PIK3CA and SMG1 or worse survival for DDR1, NF1, FOXC1 and TP53. Six Y537S/C, two E380Q and 5 potentially novel ligand-binding-domain mutations were identified in ESR1. Such mutations were recently reported to be associated with resistance to hormone therapy but were discovered here in as many as 2.1% of pre-treatment samples. Analysis will be presented regarding the use of relapse events to differentiate passenger from driver events. Conclusion: Multiple recurrently mutated genes have both positive and negative associations with prognosis in tamoxifen monotherapy treated breast cancer populations. Associations with poor outcome suggest that DDR1, NF1 and FOXC1 are high priorities for pharmacological interventions. Citation Format: Obi L. Griffith, Malachi Griffith, Nicholas C. Spies, Jingqin Luo, Jasreet Hundal, Christopher A. Miller, David E. Larson, Robert Fulton, Shuzhen Liu, Samuel Leung, Richard K. Wilson, Torsten O. Nielsen, Elaine R. Mardis, Matthew J. Ellis. Recurrent mutations of hormone-positive breast cancer and association with outcome. [abstract]. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1):Abstract nr A1-06.

SPP2 Mutations Cause Autosomal Dominant Retinitis Pigmentosa.

Retinitis pigmentosa (RP) shows progressive loss of photoreceptors involved with heterogeneous genetic background. Here, by exome sequencing and linkage analysis on a Chinese family with autosomal dominant RP, we identified a putative pathogenic variant, p.Gly97Arg, in the gene SPP2, of which expression was detected in multiple tissues including retina. The p.Gly97Arg was absent in 800 ethnically matched chromosomes and 1400 in-house exome dataset, and was located in the first of the two highly conserved disulfide bonded loop of secreted phosphoprotein 2 (Spp-24) encoded by SPP2. Overexpression of p.Gly97Arg and another signal peptide mutation, p.Gly29Asp, caused cellular retention of both endogenous wild type and exogenous mutants in vitro, and primarily affected rod photoreceptors in zebrafish mimicking cardinal feature of RP. Taken together, our data indicate that the two mutations of SPP2 have dominant negative effects and cellular accumulation of Spp-24 might be particularly toxic to photoreceptors and/or retinal pigment epithelium. SPP2 has a new role in retinal degeneration.

Pilot whole-exome sequencing of a German early-onset Alzheimer's disease cohort reveals a substantial frequency of PSEN2 variants

Early-onset Alzheimer's disease (EOAD) accounts for 1%–2% of all Alzheimer's disease (AD) subjects, with large variation in the reported genetic contribution of known dementia genes. In this pilot study, we genetically characterized a German EOAD cohort (23 subjects) by whole-exome sequencing, capturing variants in all recognized AD and frontotemporal dementia genes. After variant filtering, we identified 7 events of altogether 6 different rare variants in 6 subjects, including 4 novel variants. Four of the 6 variants, observed in 5 different index subjects (5/23 = 22%), were considered to be possibly pathogenic. These included 2 presenilin 2 (PSEN2) variants (p.N141I—previously denoted as a Volga German variant, observed in 2 index subjects; and p.L238P), 1 amyloid precursor protein (p.I716M), and 1 presenilin 1 (ΔE9). Using a control exome data set of 96 ethnically matched neurodegenerative disease controls (Parkinson's disease), we identified only 1 variant (PSEN2 p.T18M) (1%), demonstrating a significantly higher mutational burden in the EOAD group (p > 0.0001). Our findings demonstrate a substantial frequency of variants in dementia genes in EOAD, including several seemingly “sporadic” subjects. This indicates that heritability in EOAD might be higher than assumed. The finding of 3 subjects carrying potential pathogenic PSEN2 variants suggests that, in specific populations PSEN2 variants might be as frequent as (or more frequent than) presenilin 1, for example, in German populations which are influenced by Volga German heritage. Variants in AD genes were also associated with rare phenotypes such as frontal AD or primary progressive aphasia, demonstrating the need to screen AD genes in frontotemporal dementia-like phenotypes.

Large-scale TUBB4A mutational screening in isolated dystonia and controls.

Mutations in TUBB4A have recently been implicated in two seemingly different disease entities, namely DYT4-isolated dystonia and hypomyelination with atrophy of the basal ganglia and cerebellum (H-ABC), a disorder characterized by considerable clinical variability. While several follow-up studies confirmed the importance of TUBB4A mutations in the development of H-ABC, their contribution to isolated dystonia remains uncertain. We screened the TUBB4A coding regions in a large population of 709 isolated dystonia patients of German/Austrian ancestry as well as in 376 ancestry-matched control subjects by means of Sanger sequencing and high-resolution melting. In addition, we assessed the overall frequency of rare non-synonymous TUBB4A genetic variation in the huge exome dataset released by the Exome Aggregation Consortium (ExAC). We were unable to identify any possibly pathogenic sequence alteration in either patients or controls. According to ExAC, the overall prevalence of rare missense and loss-of-function alleles in the TUBB4A gene can be estimated at ∼1:706. In accordance with previous work, our data indicate that TUBB4A coding mutations do not play a critical role in the broad population of isolated dystonia patients. Rather, isolated dystonia as seen in DYT4 might be an exceptional feature occurring in the heterogeneous phenotypic spectrum due to TUBB4A mutations.

Unique Genetic and Survival Characteristics of Invasive Mucinous Adenocarcinoma of the Lung

Invasive mucinous adenocarcinoma is a unique histologic subtype of lung cancer, and our knowledge of its genetic and clinical characteristics is rapidly evolving. Here, we present next- generation sequencing analysis of nucleotide variant and fusion events along with clinical follow-up in a series of lung mucinous adenocarcinoma. We collected 72 mucinous adenocarcinomas from the United States and Korea. All had been previously assessed for KRAS and EGFR mutations. For KRAS wild-type cases (n = 30), we performed deep targeted next-generation sequencing for gene fusions and nucleotide variants and correlated survival and other clinical features. As expected, KRAS mutations were the most common alteration found (63% of cases); however, the distribution of nucleotide position alterations was more similar to that observed in gastrointestinal tumors than other lung tumors. Within the KRAS-negative cases, we found numerous potentially targetable gene fusions and mutations, including CD74-NRG1, VAMP2-NRG1, TRIM4-BRAF, TPM3-NTRK1, and EML4-ALK gene fusions and ERBB2, BRAF, and PIK3CA mutations. Unexpectedly, we found only two cases with TP53 mutation, which is much lower than observed in lung adenocarcinomas in general. The overall mutation burden was low in histologically confirmed mucinous adenocarcinomas from the public The Cancer Genome Atlas exome data set, regardless of smoking history, suggesting a link between TP53 status and mutation burden in mucinous tumors. There was no significant difference for recurrence-free survival between stage-matched mucinous and nonmucinous adenocarcinomas. It was notable that all recurrence sites were in the lungs for completely resected cases. Our data suggest that mucinous adenocarcinoma is typified by (1) frequent KRAS mutations and a growing list of gene fusions, but rare TP53 mutations, (2) a low mutation burden overall, and (3) a recurrence-free survival similar to stage-matched nonmucinous tumors, with recurrences limited to the lungs.

Multidisciplinary nephrogenetic outpatient clinic combined with diagnostic exome sequencing for improved diagnostics and treatment

Single gene disorders are estimated to account for ~30% of children and ~10% of adult patients attending renal outpatient services. For mutation detection by exome sequencing, deep phenotyping, reverse phenotyping and family history information are important. A multidisciplinary nephrogenetic outpatient clinic for children and adult patients with (genetic) kidney diseases has been established by a team of (pediatric) nephrologists and a clinical geneticist in the Radboudumc. Clinical exome sequencing for a broad spectrum of isolated- and syndromic renal (ciliary) disorders has been developed. The approach consists of a two-tier analysis in which the first step is to screen for pathogenic variants in genes that are known to be mutated in renal diseases (170 genes) or (renal) ciliopathies (125 genes). If causative mutations are not identified in the first step, the complete exome data set can be analysed with informed consent. The first results with the renal disease gene panel in 35 unrelated patients with undiagnosed renal disease led to pathogenic mutations in the CC2D2A, CLCN5, NPHP1 and UMOD gene, detected in four cases and in six other cases likely pathogenic variants needed follow-up studies. Further analysis of the complete exome data set in 13 patients, revealed possible pathogenic mutations in two cases. While variant and copy number variation analysis in the rest of exome is expected to further increase diagnostic yield, we can already conclude that the combination of the multidisciplinary outpatient clinic with diagnostic exome sequencing provides a powerful tool for detecting causative mutations of renal disease.

Comparison of GENCODE and RefSeq gene annotation and the impact of reference geneset on variant effect prediction.

BackgroundA vast amount of DNA variation is being identified by increasingly large-scale exome and genome sequencing projects. To be useful, variants require accurate functional annotation and a wide range of tools are available to this end. McCarthy et al recently demonstrated the large differences in prediction of loss-of-function (LoF) variation when RefSeq and Ensembl transcripts are used for annotation, highlighting the importance of the reference transcripts on which variant functional annotation is based.ResultsWe describe a detailed analysis of the similarities and differences between the gene and transcript annotation in the GENCODE and RefSeq genesets. We demonstrate that the GENCODE Comprehensive set is richer in alternative splicing, novel CDSs, novel exons and has higher genomic coverage than RefSeq, while the GENCODE Basic set is very similar to RefSeq. Using RNAseq data we show that exons and introns unique to one geneset are expressed at a similar level to those common to both. We present evidence that the differences in gene annotation lead to large differences in variant annotation where GENCODE and RefSeq are used as reference transcripts, although this is predominantly confined to non-coding transcripts and UTR sequence, with at most ~30% of LoF variants annotated discordantly. We also describe an investigation of dominant transcript expression, showing that it both supports the utility of the GENCODE Basic set in providing a smaller set of more highly expressed transcripts and provides a useful, biologically-relevant filter for further reducing the complexity of the transcriptome.ConclusionsThe reference transcripts selected for variant functional annotation do have a large effect on the outcome. The GENCODE Comprehensive transcripts contain more exons, have greater genomic coverage and capture many more variants than RefSeq in both genome and exome datasets, while the GENCODE Basic set shows a higher degree of concordance with RefSeq and has fewer unique features. We propose that the GENCODE Comprehensive set has great utility for the discovery of new variants with functional potential, while the GENCODE Basic set is more suitable for applications demanding less complex interpretation of functional variants.

Oncogenic activation of the PI3-kinase p110β isoform via the tumor-derived PIK3Cβ(D1067V) kinase domain mutation.

Activation of the phosphoinositide 3-kinase (PI3K) pathway occurs widely in human cancers. Although somatic mutations in the PI3K pathway genes PIK3CA and PTEN are known to drive PI3K pathway activation and cancer growth, the significance of somatic mutations in other PI3K pathway genes is less clear. Here, we establish the signaling and oncogenic properties of a recurrent somatic mutation in the PI3K p110β isoform that resides within its kinase domain (PIK3Cβ(D1067V)). We initially observed PIK3Cβ(D1067V) by exome sequencing analysis of an EGFR-mutant non-small cell lung cancer (NSCLC) tumor biopsy from a patient with acquired erlotinib resistance. On the basis of this finding, we hypothesized that PIK3Cβ(D1067V) might function as a novel tumor-promoting genetic alteration, and potentially an oncogene, in certain cancers. Consistent with this hypothesis, analysis of additional tumor exome data sets revealed the presence of PIK3Cβ(D1067V) at low frequency in other patient tumor samples (including renal cell carcinoma, glioblastoma multiforme, head and neck squamous cell carcinoma, melanoma, thyroid carcinoma and endometrial carcinoma). Functional studies revealed that PIK3Cβ(D1067V) promoted PI3K pathway signaling, enhanced cell growth in vitro, and was sufficient for tumor formation in vivo. Pharmacologic inhibition of PIK3Cβ with TGX-221 (isoform-selective p110β inhibitor) specifically suppressed growth in patient-derived renal-cell carcinoma cells with endogenous PIK3Cβ(D1067V) and in NIH-3T3 and human EGFR-mutant lung adenocarcinoma cells engineered to express this mutant PI3K. In the EGFR-mutant lung adenocarcinoma cells, expression of PIK3Cβ(D1067V) also promoted erlotinib resistance. Our data establish a novel oncogenic form of PI3K, revealing the signaling and oncogenic properties of PIK3Cβ(D1067V) and its potential therapeutic relevance in cancer. Our findings provide new insight into the genetic mechanisms underlying PI3K pathway activation in human tumors and indicate that PIK3Cβ(D1067V) is a rational therapeutic target in certain cancers.

Abstract S1-02: Prognostic effects of gene mutation in estrogen receptor positive breast cancer

Abstract Background: Relationships between recurrent somatic mutations and outcome in estrogen receptor positive (ER+) breast cancer has not been extensively studied as the original discovery efforts were from either heterogeneously treated patients or follow up was too brief. Targeted massively parallel sequencing (MPS) analysis was therefore conducted on DNA extracted from archived formalin-fixed breast primaries from a cohort of over 600 patents from British Columbia treated with five years of adjuvant tamoxifen monotherapy and followed for over 10 years (Nielsen et al CCR 16:5222, 2010). Methods: Genes were selected for targeted sequencing by meta-analysis of five large-scale breast cancer sequencing studies and manual review of breast cancer literature. In total 83 genes were identified and 3286 probes were designed to tile across all known exons. Minimum starting input DNA was 50ng (mean=189.1ng). Illumina sequencing libraries were constructed, indexed, pooled, and enriched for target sequences by hybrid-capture followed by paired-end 100bp reads. The Genome Modeling System was used to perform single-tumor somatic variant prediction. Variant calls were filtered to include only targeted regions and exclude variants with global mutant allele frequencies greater than 0.1% in 1000 genomes or NHLBI exome datasets. Kaplan-Meier analysis and multivariable analysis (clinical features and intrinsic subtype by qPCR) was performed for breast-cancer-specific and relapse free survival. Results: A total of 638 samples met minimum quality controls of 80% targeted space covered at 20X or greater. On average each sample had 332M of aligned bases and a mean coverage of 134.3X. In total 7,159 variants were identified including 3,696 missense, 494 nonsense, and 1,047 frameshift insertions or deletions. Preliminary results indicate significant associations between mutation status and improved survival for PIK3CA, ARID1B, ERBB3, MAP3K1 and GATA3 or worse survival for PTEN, DDR1, TP53 and JAK2. Five Y537N/C, two E380Q and 5 potentially novel ligand-binding-domain mutations were identified in ESR1. Such mutations were recently reported to be associated with resistance to hormone therapy but were discovered here in as much as 1.9% of pre-treatment samples. Analysis will be presented regarding the use of relapse events to differentiate passenger from driver mutations. Conclusion. Multiple recurrently mutated genes have both positive and negative associations with prognosis in tamoxifen montherapy treated breast cancer populations. Associations with poor outcome suggest that PTEN, DDR1, and JAK2 are high priorities for pharmacological interventions. Table 1: Mutations and survival in ER+ breast cancerGeneP-ValueHazard RatioPTEN0.0022.11PIK3CA0.0070.69DDR10.0082.41ARID1B0.010.57ERBB30.020.36MAP3K10.010.5TP530.041.48GATA30.040.44JAK20.052.1 Citation Format: Obi L Griffith, Malachi Griffith, Jingqin Luo, Jasreet Hundall, Christopher A Miller, David E Larson, Robert Fulton, Richard K Wilson, Shuzhen Liu, Samuel Leung, Torsten O Nielsen, Elaine R Mardis, Matthew J Ellis. Prognostic effects of gene mutation in estrogen receptor positive breast cancer [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr S1-02.

A simple strategy for reducing false negatives in calling variants from single-cell sequencing data.

Due to the growth of interest in single-cell genomics, computational methods for distinguishing true variants from artifacts are highly desirable. While special attention has been paid to false positives in variant or mutation calling from single-cell sequencing data, an equally important but often neglected issue is that of false negatives derived from allele dropout during the amplification of single cell genomes. In this paper, we propose a simple strategy to reduce the false negatives in single-cell sequencing data analysis. Simulation results show that this method is highly reliable, with an error rate of 4.94×10-5, which is orders of magnitude lower than the expected false negative rate (~34%) estimated from a single-cell exome dataset, though the method is limited by the low SNP density in the human genome. We applied this method to analyze the exome data of a few dozen single tumor cells generated in previous studies, and extracted cell specific mutation information for a small set of sites. Interestingly, we found that there are difficulties in using the classical clonal model of tumor cell growth to explain the mutation patterns observed in some tumor cells.

Reply: Evaluation of exome sequencing variation in undiagnosed ataxias

Sir, Erin Sandford and colleagues raise three main concerns that they believe undermine the likely causal nature of some of the genetic variants we detected by exome sequencing undiagnosed patients with ataxia (Pyle et al. , 2015): 1. Some of our proposed pathogenic variants have a minor allele frequency (MAF) of >0.01 in the population. Although useful as an initial guide, the 1% MAF is an arbitrary cut-off designed to rapidly filter-out common polymorphic genetic variants from a large exome data set. However, this must be done with care for several reasons. First, allele frequencies vary from database to database, and throughout the world. To choose their example, c.709C>T p.Pro237Ser in Patients P15 and P16 has a MAF = 0.0153 in the US-based ESP6500 (their Table 1), which contrasts with our local population (MAF = 0.0052), and the UK-based 1000 Genomes project (MAF = 0.0064). To our mind it would be ridiculous to reject this variant as non-pathogenic because one database documents a MAF > 0.01. Surely the important point here is …

Two PALB2 germline mutations found in both BRCA1+ and BRCAx familial breast cancer.

Partner and localizer of BRCA2 (PALB2), plays an important functional role in DNA damage repair. Recent studies indicate that germline mutations in PALB2 predispose individuals to a high risk of developing familial breast cancer. Therefore, comprehensive identification of PALB2 germline mutations is potentially important for understanding their roles in tumorigenesis and for testing their potential utility as clinical targets. Most of the previous studies of PALB2 have focused on familial breast cancer cases with normal/wild-type BRCA1 and BRCA2 (BRCAx). We hypothesize that PALB2 genetic mutations also exist in individuals with BRCA mutations (BRCA+). To test this hypothesis, PALB2 germline mutations were screened in 107 exome data sets collected from familial breast cancer families who were either BRCA1+ or BRCAx. Two novel heterozygous mutations predicted to alter the function of PALB2 were identified (c.2014G>C, p.E672Q and c.2993G>A, p.G998E). Notably, both of these mutations co-existed in BRCA1+ and BRCA1x families. These studies show that mutations in PALB2 can occur independent of the status of BRCA1 mutations, and they highlight the importance to include BRCA1+ families in PALB2 mutation screens.