A comprehensive transcriptional portrait of human cancer cell lines.

Tumor-derived cell lines have served as vital models to advance our understanding of oncogene function and therapeutic responses. Although substantial effort has been made to define the genomic constitution of cancer cell line panels, the transcriptome remains understudied. Here we describe RNA sequencing and single-nucleotide polymorphism (SNP) array analysis of 675 human cancer cell lines. We report comprehensive analyses of transcriptome features including gene expression, mutations, gene fusions and expression of non-human sequences. Of the 2,200 gene fusions catalogued, 1,435 consist of genes not previously found in fusions, providing many leads for further investigation. We combine multiple genome and transcriptome features in a pathway-based approach to enhance prediction of response to targeted therapeutics. Our results provide a valuable resource for studies that use cancer cell lines.

Discriminative motif analysis of high-throughput dataset.

MOTIVATION: High-throughput ChIP-seq studies typically identify thousands of peaks for a single transcription factor (TF). It is common for traditional motif discovery tools to predict motifs that are statistically significant against a naïve background distribution but are of questionable biological relevance. RESULTS: We describe a simple yet effective algorithm for discovering differential motifs between two sequence datasets that is effective in eliminating systematic biases and scalable to large datasets. Tested on 207 ENCODE ChIP-seq datasets, our method identifies correct motifs in 78% of the datasets with known motifs, demonstrating improvement in both accuracy and efficiency compared with DREME, another state-of-art discriminative motif discovery tool. More interestingly, on the remaining more challenging datasets, we identify common technical or biological factors that compromise the motif search results and use advanced features of our tool to control for these factors. We also present case studies demonstrating the ability of our method to detect single base pair differences in DNA specificity of two similar TFs. Lastly, we demonstrate discovery of key TF motifs involved in tissue specification by examination of high-throughput DNase accessibility data. AVAILABILITY: The motifRG package is publically available via the bioconductor repository. CONTACT: yzizhen@fhcrc.org SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Integrative analysis of two cell lines derived from a non-small-lung cancer patient--a panomics approach.

Cancer cells derived from different stages of tumor progression may exhibit distinct biological properties, as exemplified by the paired lung cancer cell lines H1993 and H2073. While H1993 was derived from chemo-naive metastasized tumor, H2073 originated from the chemo-resistant primary tumor from the same patient and exhibits strikingly different drug response profile. To understand the underlying genetic and epigenetic bases for their biological properties, we investigated these cells using a wide range of large-scale methods including whole genome sequencing, RNA sequencing, SNP array, DNA methylation array, and de novo genome assembly. We conducted an integrative analysis of both cell lines to distinguish between potential driver and passenger alterations. Although many genes are mutated in these cell lines, the combination of DNA- and RNA-based variant information strongly implicates a small number of genes including TP53 and STK11 as likely drivers. Likewise, we found a diverse set of genes differentially expressed between these cell lines, but only a fraction can be attributed to changes in DNA copy number or methylation. This set included the ABC transporter ABCC4, implicated in drug resistance, and the metastasis associated MET oncogene. While the rich data content allowed us to reduce the space of hypotheses that could explain most of the observed biological properties, we also caution there is a lack of statistical power and inherent limitations in such single patient case studies.

Comparison of endogenous and overexpressed MyoD shows enhanced binding of physiologically bound sites.

BACKGROUND: Transcription factor overexpression is common in biological experiments and transcription factor amplification is associated with many cancers, yet few studies have directly compared the DNA-binding profiles of endogenous versus overexpressed transcription factors. METHODS: We analyzed MyoD ChIP-seq data from C2C12 mouse myotubes, primary mouse myotubes, and mouse fibroblasts differentiated into muscle cells by overexpression of MyoD and compared the genome-wide binding profiles and binding site characteristics of endogenous and overexpressed MyoD. RESULTS: Overexpressed MyoD bound to the same sites occupied by endogenous MyoD and possessed the same E-box sequence preference and co-factor site enrichments, and did not bind to new sites with distinct characteristics. CONCLUSIONS: Our data demonstrate a robust fidelity of transcription factor binding sites over a range of expression levels and that increased amounts of transcription factor increase the binding at physiologically bound sites.

Genome and transcriptome sequencing of lung cancers reveal diverse mutational and splicing events.

Lung cancer is a highly heterogeneous disease in terms of both underlying genetic lesions and response to therapeutic treatments. We performed deep whole-genome sequencing and transcriptome sequencing on 19 lung cancer cell lines and three lung tumor/normal pairs. Overall, our data show that cell line models exhibit similar mutation spectra to human tumor samples. Smoker and never-smoker cancer samples exhibit distinguishable patterns of mutations. A number of epigenetic regulators, including KDM6A, ASH1L, SMARCA4, and ATAD2, are frequently altered by mutations or copy number changes. A systematic survey of splice-site mutations identified 106 splice site mutations associated with cancer specific aberrant splicing, including mutations in several known cancer-related genes. RAC1b, an isoform of the RAC1 GTPase that includes one additional exon, was found to be preferentially up-regulated in lung cancer. We further show that its expression is significantly associated with sensitivity to a MAP2K (MEK) inhibitor PD-0325901. Taken together, these data present a comprehensive genomic landscape of a large number of lung cancer samples and further demonstrate that cancer-specific alternative splicing is a widespread phenomenon that has potential utility as therapeutic biomarkers. The detailed characterizations of the lung cancer cell lines also provide genomic context to the vast amount of experimental data gathered for these lines over the decades, and represent highly valuable resources for cancer biology.

Genetic and epigenetic determinants of neurogenesis and myogenesis.

The regulatory networks of differentiation programs have been partly characterized; however, the molecular mechanisms of lineage-specific gene regulation by highly similar transcription factors remain largely unknown. Here we compare the genome-wide binding and transcription profiles of NEUROD2-mediated neurogenesis with MYOD-mediated myogenesis. We demonstrate that NEUROD2 and MYOD bind a shared CAGCTG E box motif and E box motifs specific for each factor: CAGGTG for MYOD and CAGATG for NEUROD2. Binding at factor-specific motifs is associated with gene transcription, whereas binding at shared sites is associated with regional epigenetic modifications but is not as strongly associated with gene transcription. Binding is largely constrained to E boxes preset in an accessible chromatin context that determines the set of target genes activated in each cell type. These findings demonstrate that the differentiation program is genetically determined by E box sequence, whereas cell lineage epigenetically determines the availability of E boxes for each differentiation program.

DUX4 activates germline genes, retroelements, and immune mediators: implications for facioscapulohumeral dystrophy.

Facioscapulohumeral dystrophy (FSHD) is one of the most common inherited muscular dystrophies. The causative gene remains controversial and the mechanism of pathophysiology unknown. Here we identify genes associated with germline and early stem cell development as targets of the DUX4 transcription factor, a leading candidate gene for FSHD. The genes regulated by DUX4 are reliably detected in FSHD muscle but not in controls, providing direct support for the model that misexpression of DUX4 is a causal factor for FSHD. Additionally, we show that DUX4 binds and activates LTR elements from a class of MaLR endogenous primate retrotransposons and suppresses the innate immune response to viral infection, at least in part through the activation of DEFB103, a human defensin that can inhibit muscle differentiation. These findings suggest specific mechanisms of FSHD pathology and identify candidate biomarkers for disease diagnosis and progression.

The effects of hepatitis B virus integration into the genomes of hepatocellular carcinoma patients.

Hepatitis B virus (HBV) infection is a leading risk factor for hepatocellular carcinoma (HCC). HBV integration into the host genome has been reported, but its scale, impact and contribution to HCC development is not clear. Here, we sequenced the tumor and nontumor genomes (>80× coverage) and transcriptomes of four HCC patients and identified 255 HBV integration sites. Increased sequencing to 240× coverage revealed a proportionally higher number of integration sites. Clonal expansion of HBV-integrated hepatocytes was found specifically in tumor samples. We observe a diverse collection of genomic perturbations near viral integration sites, including direct gene disruption, viral promoter-driven human transcription, viral-human transcript fusion, and DNA copy number alteration. Thus, we report the most comprehensive characterization of HBV integration in hepatocellular carcinoma patients. Such widespread random viral integration will likely increase carcinogenic opportunities in HBV-infected individuals.

Differential gene expression in benign prostate epithelium of men with and without prostate cancer: evidence for a prostate cancer field effect.

BACKGROUND: Several malignancies are known to exhibit a "field effect," whereby regions beyond tumor boundaries harbor histologic or molecular changes that are associated with cancer. We sought to determine if histologically benign prostate epithelium collected from men with prostate cancer exhibits features indicative of premalignancy or field effect. EXPERIMENTAL DESIGN: Prostate needle biopsies from 15 men with high-grade (Gleason 8-10) prostate cancer and 15 age- and body mass index-matched controls were identified from a biospecimen repository. Benign epithelia from each patient were isolated by laser capture microdissection. RNA was isolated, amplified, and used for microarray hybridization. Quantitative PCR was used to determine the expression of specific genes of interest. Alterations in protein expression were analyzed through immunohistochemistry. RESULTS: Overall patterns of gene expression in microdissected benign prostate-associated benign epithelium (BABE) and cancer-associated benign epithelium (CABE) were similar. Two genes previously associated with prostate cancer, PSMA and SSTR1, were significantly upregulated in the CABE group (false discovery rate <1%). Expression of other prostate cancer-associated genes, including ERG, HOXC4, HOXC5, and MME, were also increased in CABE by quantitative reverse transcription-PCR, although other genes commonly altered in prostate cancer were not different between the BABE and CABE samples. The expression of MME and PSMA proteins on immunohistochemistry coincided with their mRNA alterations. CONCLUSION: Gene expression profiles between benign epithelia of patients with and without prostate cancer are very similar. However, these tissues exhibit differences in the expression levels of several genes previously associated with prostate cancer development or progression. These differences may comprise a field effect and represent early events in carcinogenesis.

Genome-wide MyoD binding in skeletal muscle cells: a potential for broad cellular reprogramming.

Recent studies have demonstrated that MyoD initiates a feed-forward regulation of skeletal muscle gene expression, predicting that MyoD binds directly to many genes expressed during differentiation. We have used chromatin immunoprecipitation and high-throughput sequencing to identify genome-wide binding of MyoD in several skeletal muscle cell types. As anticipated, MyoD preferentially binds to a VCASCTG sequence that resembles the in vitro-selected site for a MyoD:E-protein heterodimer, and MyoD binding increases during differentiation at many of the regulatory regions of genes expressed in skeletal muscle. Unanticipated findings were that MyoD was constitutively bound to thousands of additional sites in both myoblasts and myotubes, and that the genome-wide binding of MyoD was associated with regional histone acetylation. Therefore, in addition to regulating muscle gene expression, MyoD binds genome wide and has the ability to broadly alter the epigenome in myoblasts and myotubes.

Data standards for flow cytometry.

Flow cytometry (FCM) is an analytical tool widely used for cancer and HIV/AIDS research, and treatment, stem cell manipulation and detecting microorganisms in environmental samples. Current data standards do not capture the full scope of FCM experiments and there is a demand for software tools that can assist in the exploration and analysis of large FCM datasets. We are implementing a standardized approach to capturing, analyzing, and disseminating FCM data that will facilitate both more complex analyses and analysis of datasets that could not previously be efficiently studied. Initial work has focused on developing a community-based guideline for recording and reporting the details of FCM experiments. Open source software tools that implement this standard are being created, with an emphasis on facilitating reproducible and extensible data analyses. As well, tools for electronic collaboration will assist the integrated access and comprehension of experiments to empower users to collaborate on FCM analyses. This coordinated, joint development of bioinformatics standards and software tools for FCM data analysis has the potential to greatly facilitate both basic and clinical research--impacting a notably diverse range of medical and environmental research areas.

Combined cDNA array comparative genomic hybridization and serial analysis of gene expression analysis of breast tumor progression.

To identify genetic changes involved in the progression of breast carcinoma, we did cDNA array comparative genomic hybridization (CGH) on a panel of breast tumors, including 10 ductal carcinoma in situ (DCIS), 18 invasive breast carcinomas, and two lymph node metastases. We identified 49 minimal commonly amplified regions (MCRs) that included known (1q, 8q24, 11q13, 17q21-q23, and 20q13) and several uncharacterized (12p13 and 16p13) regional copy number gains. With the exception of the 17q21 (ERBB2) amplicon, the overall frequency of copy number alterations was higher in invasive tumors than that in DCIS, with several of them present only in invasive cancer. Amplification of candidate loci was confirmed by quantitative PCR in breast carcinomas and cell lines. To identify putative targets of amplicons, we developed a method combining array CGH and serial analysis of gene expression (SAGE) data to correlate copy number and expression levels for each gene within MCRs. Using this approach, we were able to distinguish a few candidate targets from a set of coamplified genes. Analysis of the 12p13-p12 amplicon identified four putative targets: TEL/ETV6, H2AFJ, EPS8, and KRAS2. The amplification of all four candidates was confirmed by quantitative PCR and fluorescence in situ hybridization, but only H2AFJ and EPS8 were overexpressed in breast tumors with 12p13 amplification compared with a panel of normal mammary epithelial cells. These results show the power of combined array CGH and SAGE analysis for the identification of candidate amplicon targets and identify H2AFJ and EPS8 as novel putative oncogenes in breast cancer.

Association of valproate-induced teratogenesis with histone deacetylase inhibition in vivo.

Chemically induced birth defects are an important public health and human problem. Here we use Xenopus and zebrafish as models to investigate the mechanism of action of a well-known teratogen, valproic acid (VPA). VPA is a drug used in treatment of epilepsy and bipolar disorder but causes spina bifida if taken during pregnancy. VPA has several biochemical activities, including inhibition of histone deacetylases (HDACs). To investigate the mechanism of action of VPA, we compared its effects in Xenopus and zebrafish embryos with those of known HDAC inhibitors and noninhibitory VPA analogs. We found that VPA and other HDAC inhibitors cause very similar and characteristic developmental defects whereas VPA analogs with poor inhibitory activity in vivo have little teratogenic effect. Unbiased microarray analysis revealed that the effects of VPA and trichostatin A (TSA), a structurally unrelated HDAC inhibitor, are strikingly concordant. The concordance is apparent both by en masse correlation of fold-changes and by detailed similarity of dose-response profiles of individual genes. Together, the results demonstrate that the teratogenic effects of VPA are very likely mediated specifically by inhibition of HDACs.

Bioconductor: open software development for computational biology and bioinformatics.

The Bioconductor project is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics. The goals of the project include: fostering collaborative development and widespread use of innovative software, reducing barriers to entry into interdisciplinary scientific research, and promoting the achievement of remote reproducibility of research results. We describe details of our aims and methods, identify current challenges, compare Bioconductor to other open bioinformatics projects, and provide working examples.

Genomic representations using concatenates of Type IIB restriction endonuclease digestion fragments.

We have developed a method for genomic representation using Type IIB restriction endonucleases. Representation by concatenation of restriction digests, or RECORD, is an approach to sample the fragments generated by cleavage with these enzymes. Here, we show that the RECORD libraries may be used for digital karyotyping and for pathogen identification by computational subtraction.

Open source software for the analysis of microarray data.

DNA microarray assays represent the first widely used application that attempts to build upon the information provided by genome projects in the study of biological questions. One of the greatest challenges with working with microarrays is collecting, managing, and analyzing data. Although several commercial and noncommercial solutions exist, there is a growing body of freely available, open source software that allows users to analyze data using a host of existing techniques and to develop their own and integrate them within the system. Here we review three of the most widely used and comprehensive systems, the statistical analysis tools written in R through the Bioconductor project (http://www.bioconductor.org), the Java-based TM4 software system available from The Institute for Genomic Research (http://www.tigr.org/software), and BASE, the Web-based system developed at Lund University (http://base.thep.lu.se).