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

BACKGROUND: Oncogenic 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. RESULTS: Leveraging 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. CONCLUSIONS: To 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.

Survey of culture, goldengate assay, universal biosensor assay, and 16S rRNA Gene sequencing as alternative methods of bacterial pathogen detection.

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.

Genome-wide analysis of aberrant position and sequence of plasma DNA fragment ends in patients with cancer.

Genome-wide fragmentation patterns in cell-free DNA (cfDNA) in plasma are strongly influenced by cellular origin due to variation in chromatin accessibility across cell types. Such differences between healthy and cancer cells provide the opportunity for development of novel cancer diagnostics. Here, we investigated whether analysis of cfDNA fragment end positions and their surrounding DNA sequences reveals the presence of tumor-derived DNA in blood. We performed genome-wide analysis of cfDNA from 521 samples and analyzed sequencing data from an additional 2147 samples, including healthy individuals and patients with 11 different cancer types. We developed a metric based on genome-wide differences in fragment positioning, weighted by fragment length and GC content [information-weighted fraction of aberrant fragments (iwFAF)]. We observed that iwFAF strongly correlated with tumor fraction, was higher for DNA fragments carrying somatic mutations, and was higher within genomic regions affected by copy number amplifications. We also calculated sample-level means of nucleotide frequencies observed at genomic positions spanning fragment ends. Using a combination of iwFAF and nine nucleotide frequencies from three positions surrounding fragment ends, we developed a machine learning model to differentiate healthy individuals from patients with cancer. We observed an area under the receiver operative characteristic curve (AUC) of 0.91 for detection of cancer at any stage and an AUC of 0.87 for detection of stage I cancer. Our findings remained robust with as few as 1 million fragments analyzed per sample, demonstrating that analysis of fragment ends can become a cost-effective and accessible approach for cancer detection and monitoring.

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.

Cis sequence effects on gene expression.

BACKGROUND: Sequence and transcriptional variability within and between individuals are typically studied independently. The joint analysis of sequence and gene expression variation (genetical genomics) provides insight into the role of linked sequence variation in the regulation of gene expression. We investigated the role of sequence variation in cis on gene expression (cis sequence effects) in a group of genes commonly studied in cancer research in lymphoblastoid cell lines. We estimated the proportion of genes exhibiting cis sequence effects and the proportion of gene expression variation explained by cis sequence effects using three different analytical approaches, and compared our results to the literature. RESULTS: We generated gene expression profiling data at N = 697 candidate genes from N = 30 lymphoblastoid cell lines for this study and used available candidate gene resequencing data at N = 552 candidate genes to identify N = 30 candidate genes with sufficient variance in both datasets for the investigation of cis sequence effects. We used two additive models and the haplotype phylogeny scanning approach of Templeton (Tree Scanning) to evaluate association between individual SNPs, all SNPs at a gene, and diplotypes, with log-transformed gene expression. SNPs and diplotypes at eight candidate genes exhibited statistically significant (p < 0.05) association with gene expression. Using the literature as a "gold standard" to compare 14 genes with data from both this study and the literature, we observed 80% and 85% concordance for genes exhibiting and not exhibiting significant cis sequence effects in our study, respectively. CONCLUSION: Based on analysis of our results and the extant literature, one in four genes exhibits significant cis sequence effects, and for these genes, about 30% of gene expression variation is accounted for by cis sequence variation. Despite diverse experimental approaches, the presence or absence of significant cis sequence effects is largely supported by previously published studies.

Expanding the Helicobacter pylori genetic toolbox: modification of an endogenous plasmid for use as a transcriptional reporter and complementation vector.

Helicobacter pylori is an important human pathogen. However, the study of this organism is often limited by a relative shortage of genetic tools. In an effort to expand the methods available for genetic study, an endogenous H. pylori plasmid was modified for use as a transcriptional reporter and as a complementation vector. This was accomplished by addition of an Escherichia coli origin of replication, a kanamycin resistance cassette, a promoterless gfpmut3 gene, and a functional multiple cloning site to form pTM117. The promoters of amiE and pfr, two well-characterized Fur-regulated promoters, were fused to the promoterless gfpmut3, and green fluorescent protein (GFP) expression of the fusions in wild-type and delta fur strains was analyzed by flow cytometry under iron-replete and iron-depleted conditions. GFP expression was altered as expected based on current knowledge of Fur regulation of these promoters. RNase protection assays were used to determine the ability of this plasmid to serve as a complementation vector by analyzing amiE, pfr, and fur expression in wild-type and delta fur strains carrying a wild-type copy of fur on the plasmid. Proper regulation of these genes was restored in the delta fur background under high- and low-iron conditions, signifying complementation of both iron-bound and apo Fur regulation. These studies show the potential of pTM117 as a molecular tool for genetic analysis of H. pylori.

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.

BACKGROUND: In 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. RESULTS: A 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. CONCLUSION: we show that Illumina's 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.

NTera2: a model system to study dopaminergic differentiation of human embryonic stem cells.

NTera2, a human embryonal carcinoma (EC) stem cell line, shares many characteristics with human embryonic stem cells (hESCs). To determine whether NTera2 can serve as a useful surrogate for hESCs, we compared global gene expression between undifferentiated NTera2, multiple undifferentiated hESC cell lines, and their differentiated derivatives, and we showed that NTera2 cells share multiple markers with hESCs. Similar to hESCs, NTera2 cells differentiated into TH-positive cells that express dopaminergic markers including AADC, DAT, Nurr1, TrkB, TrkC, and GFRA1 when co-cultured with PA6 cells. Flow cytometry analysis showed that tyrosine hydroxylase (TH) and neural cell adhesion molecule (NCAM) expression increased, whereas SSEA4 expression decreased as cells differentiated. Medium conditioned by PA6 cells stimulated differentiation of NTera2 cells to generate TH-positive cells that expressed dopaminergic markers. Flow cytometry selected polysialylated (PSA-NCAM) cells responded to medium conditioned by PA6 cells by differentiating into TH-positive cells and expressed dopaminergic markers. Sorted cells differentiated for 4 weeks in PA6 cell conditioned media included functional neurons that responded to neurotransmitters and exhibited electronic excitability. Therefore, NTera2 cell dopaminergic neuronal differentiation and PSA-NCAM enrichment provides a useful system for the future study of hESCs.

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 disease's 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 patient's 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.

A novel, high-performance random array platform for quantitative gene expression profiling.

We have developed a new microarray technology for quantitative gene-expression profiling on the basis of randomly assembled arrays of beads. Each bead carries a gene-specific probe sequence. There are multiple copies of each sequence-specific bead in an array, which contributes to measurement precision and reliability. We optimized the system for specific and sensitive analysis of mammalian RNA, and using RNA controls of defined concentration, obtained the following estimates of system performance: specificity of 1:250,000 in mammalian poly(A(+)) mRNA; limit of detection 0.13 pM; dynamic range 3.2 logs; and sufficient precision to detect 1.3-fold differences with 95% confidence within the dynamic range. Measurements of expression differences between human brain and liver were validated by concordance with quantitative real-time PCR (R(2) = 0.98 for log-transformed ratios, and slope of the best-fit line = 1.04, for 20 genes). Quantitative performance was further verified using a mouse B- and T-cell model system. We found published reports of B- or T-cell-specific expression for 42 of 59 genes that showed the greatest differential expression between B- and T-cells in our system. All of the literature observations were concordant with our results. Our experiments were carried out on a 96-array matrix system that requires only 100 ng of input RNA and uses standard microtiter plates to process samples in parallel. Our technology has advantages for analyzing multiple samples, is scalable to all known genes in a genome, and is flexible, allowing the use of standard or custom probes in an array.