Timothy K. McDaniel

Genome wide profiling of human embryonic stem cells (hESCs), their derivatives and embryonal carcinoma cells to develop base profiles of U.S. Federal government approved hESC lines

BackgroundIn order to compare the gene expression profiles of human embryonic stem cell (hESC) lines and their differentiated progeny and to monitor feeder contaminations, we have examined gene expression in seven hESC lines and human fibroblast feeder cells using Illumina® bead arrays that contain probes for 24,131 transcript probes.ResultsA total of 48 different samples (including duplicates) grown in multiple laboratories under different conditions were analyzed and pairwise comparisons were performed in all groups. Hierarchical clustering showed that blinded duplicates were correctly identified as the closest related samples. hESC lines clustered together irrespective of the laboratory in which they were maintained. hESCs could be readily distinguished from embryoid bodies (EB) differentiated from them and the karyotypically abnormal hESC line BG01V. The embryonal carcinoma (EC) line NTera2 is a useful model for evaluating characteristics of hESCs. Expression of subsets of individual genes was validated by comparing with published databases, MPSS (Massively Parallel Signature Sequencing) libraries, and parallel analysis by microarray and RT-PCR.Conclusionwe show that Illuminas bead array platform is a reliable, reproducible and robust method for developing base global profiles of cells and identifying similarities and differences in large number of samples.

Medium- to high-throughput SNP genotyping using VeraCode microbeads.

Recent breakthroughs in multiplexed SNP (single nucleotide polymorphism) genotyping technology have enabled global mapping of the relationships between genetic variation and disease. Discoveries made by such whole-genome association studies often spur further interest in surveying more focused subsets of SNPs for validation or research purposes. Here we describe a new SNP genotyping platform that is flexible in assay content and multiplexing (up to 384 analytes), and can serve medium- to high-throughput applications. The Illumina BeadXpress platform supports the GoldenGate Genotyping Assay on digitally inscribed VeraCode microbeads to allow streamlined workflow, rapid detection, unparalleled data reproducibility and consistency. Thus, it is a highly valuable tool for biomarker research and validation, pharmaceutical development, as well as the development of molecular diagnostic tests.

Good laboratory practice for clinical next-generation sequencing informatics pipelines

Amy S Gargis, Centers for Disease Control & Prevention Lisa Kalman, Centers for Disease Control & Prevention David P Bick, Medical College of Wisconsin Cristina da Silva, Emory University David P Dimmock, Medical College of Wisconsin Birgit H Funke, Partners Healthcare Personalized Medicine Sivakumar Gowrisankar, Partners Healthcare Personalized Medicine Madhuri Hegde, Emory University Shashikant Kulkarni, Washington University Christopher E Mason, Cornell University

Personalized treatment of Sézary syndrome by targeting a novel CTLA4:CD28 fusion

Matching molecularly targeted therapies with cancer subtype‐specific gene mutations is revolutionizing oncology care. However, for rare cancers this approach is problematic due to the often poor understanding of the diseases natural history and phenotypic heterogeneity, making treatment of these cancers a particularly unmet medical need in clinical oncology. Advanced Sézary syndrome (SS), an aggressive, exceedingly rare variant of cutaneous T‐cell lymphoma (CTCL) is a prototypical example of a rare cancer. Through whole genome and RNA sequencing (RNA‐seq) of a SS patients tumor we discovered a highly expressed gene fusion between CTLA4 (cytotoxic T lymphocyte antigen 4) and CD28 (cluster of differentiation 28), predicting a novel stimulatory molecule on the surface of tumor T cells. Treatment with the CTLA4 inhibitor ipilimumab resulted in a rapid clinical response. Our findings suggest a novel driver mechanism for SS, and cancer in general, and exemplify an emerging model of cancer treatment using exploratory genomic analysis to identify a personally targeted treatment option when conventional therapies are exhausted.

New Approaches for Validation of Lethal Phenotypes and Genetic Reversion in Helicobacter pylori

Because of limited genetic tools for use in Helicobacter pylori, tests routinely applied in other bacteria for demonstrating a gene’s role in viability and other phenotypes have not been applied to this organism. In a mutational study of putative response regulator genes, we aimed to develop such tools for H. pylori.

Survey of Culture, GoldenGate Assay, Universal Biosensor Assay, and 16S rRNA Gene Sequencing as Alternative Methods of Bacterial Pathogen Detection

ABSTRACT Cultivation-based assays combined with PCR or enzyme-linked immunosorbent assay (ELISA)-based methods for finding virulence factors are standard methods for detecting bacterial pathogens in stools; however, with emerging molecular technologies, new methods have become available. The aim of this study was to compare four distinct detection technologies for the identification of pathogens in stools from children under 5 years of age in The Gambia, Mali, Kenya, and Bangladesh. The children were identified, using currently accepted clinical protocols, as either controls or cases with moderate to severe diarrhea. A total of 3,610 stool samples were tested by established clinical culture techniques: 3,179 DNA samples by the Universal Biosensor assay (Ibis Biosciences, Inc.), 1,466 DNA samples by the GoldenGate assay (Illumina), and 1,006 DNA samples by sequencing of 16S rRNA genes. Each method detected different proportions of samples testing positive for each of seven enteric pathogens, enteroaggregative Escherichia coli (EAEC), enterotoxigenic E. coli (ETEC), enteropathogenic E. coli (EPEC), Shigella spp., Campylobacter jejuni, Salmonella enterica, and Aeromonas spp. The comparisons among detection methods included the frequency of positive stool samples and kappa values for making pairwise comparisons. Overall, the standard culture methods detected Shigella spp., EPEC, ETEC, and EAEC in smaller proportions of the samples than either of the methods based on detection of the virulence genes from DNA in whole stools. The GoldenGate method revealed the greatest agreement with the other methods. The agreement among methods was higher in cases than in controls. The new molecular technologies have a high potential for highly sensitive identification of bacterial diarrheal pathogens.

Open-access synthetic spike-in mRNA-seq data for cancer gene fusions.

BackgroundOncogenic fusion genes underlie the mechanism of several common cancers. Next-generation sequencing based RNA-seq analyses have revealed an increasing number of recurrent fusions in a variety of cancers. However, absence of a publicly available gene-fusion focused RNA-seq data impedes comparative assessment and collaborative development of novel gene fusions detection algorithms. We have generated nine synthetic poly-adenylated RNA transcripts that correspond to previously reported oncogenic gene fusions. These synthetic RNAs were spiked at known molarity over a wide range into total RNA prior to construction of next-generation sequencing mRNA libraries to generate RNA-seq data.ResultsLeveraging a priori knowledge about replicates and molarity of each synthetic fusion transcript, we demonstrate utility of this dataset to compare multiple gene fusion algorithms’ detection ability. In general, more fusions are detected at higher molarity, indicating that our constructs performed as expected. However, systematic detection differences are observed based on molarity or algorithm-specific characteristics. Fusion-sequence specific detection differences indicate that for applications where specific sequences are being investigated, additional constructs may be added to provide quantitative data that is specific for the sequence of interest.ConclusionsTo our knowledge, this is the first publicly available synthetic RNA-seq data that specifically leverages known cancer gene-fusions. The proposed method of designing multiple gene-fusion constructs over a wide range of molarity allows granular performance analyses of multiple fusion-detection algorithms. The community can leverage and augment this publicly available data to further collaborative development of analytical tools and performance assessment frameworks for gene fusions from next-generation sequencing data.

A somatic reference standard for cancer genome sequencing

Large-scale multiplexed identification of somatic alterations in cancer has become feasible with next generation sequencing (NGS). However, calibration of NGS somatic analysis tools has been hampered by a lack of tumor/normal reference standards. We thus performed paired PCR-free whole genome sequencing of a matched metastatic melanoma cell line (COLO829) and normal across three lineages and across separate institutions, with independent library preparations, sequencing, and analysis. We generated mean mapped coverages of 99X for COLO829 and 103X for the paired normal across three institutions. Results were combined with previously generated data allowing for comparison to a fourth lineage on earlier NGS technology. Aggregate variant detection led to the identification of consensus variants, including key events that represent hallmark mutation types including amplified BRAF V600E, a CDK2NA small deletion, a 12 kb PTEN deletion, and a dinucleotide TERT promoter substitution. Overall, common events include >35,000 point mutations, 446 small insertion/deletions, and >6,000 genes affected by copy number changes. We present this reference to the community as an initial standard for enabling quantitative evaluation of somatic mutation pipelines across institutions.

Abstract 3571: mRNA spike-in control materials for cancer fusion gene detection assays

Oncogenic fusion genes underlie the mechanism of several common cancers and also constitute or encode important diagnostic and therapeutic targets. Studies using next-generation sequencing technologies, particularly RNA sequencing (RNA-seq), have revealed a growing number of recurrent fusions in a variety of cancers. As such, establishing analytic parameters, including the limit of detection, sensitivity, and specificity of detecting fusions in tumor RNA specimens is important. We have developed reference materials useful in assessing the ability to detect fusion events in RNA or DNA samples. These consist of a set of nine synthetic poly-adenylated RNA transcripts that correspond to common cancer fusion gene sequences. These synthetic fusion RNAs can be spiked at known concentrations into total RNA in the first stage of the mRNA sample prep and used as in-line controls to evaluate the sensitivity and specificity of the detection of these mutations. As a demonstration of the utility of these controls, we performed a series of spike-in experiments to investigate performance characteristics of three commonly used fusion-detection software algorithms. Our results show all three algorithms to be capable of detecting fusions in a dose-dependent manner. The results also show differences in performance among the algorithms for detecting specific fusions. Citation Format: Winnie Liang, Stephanie JK Pond, Waibhav D. Tembe, Han-Yu Chuang, Christophe Legendre, Nancy Kim, Valerie Montel, Shukmei Wong, Timothy K. McDaniel, David Craig, John Carpten. mRNA spike-in control materials for cancer fusion gene detection assays. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3571. doi:10.1158/1538-7445.AM2014-3571

Gene Expression Profiling of Stem Cells by Microarray

Publisher Summary The most fundamental questions in human embryonic stem cell (hESC) research concern how pluripotence and differentiation are controlled. One hope is that large-scale studies comparing the gene expression of hESCs to their differentiated progeny will lead to insights about these processes. Gene expression of undifferentiated hESCs has been investigated by a variety of techniques including MPSS (massively parallel signature sequencing), SAGE (serial analysis of gene expression), EST (expressed sequence tag) scans, and hybridization-based technologies such as focused cDNA arrays and genome-wide microarray platforms. Microarray technology offers a unique combination of features that makes it well suited for most expression studies. It is comprehensive, allowing the monitoring of every annotated transcript in the human (or mouse) genome and it requires relatively little sample, approximately 100 ng (-10 000 cells) of total ribonucleic acid (RNA) for the most sensitive arrays.