Discovery Of Gene Fusions Research Articles

Abstract A30: Integrative genomic analysis of two Ewing's sarcoma cell lines that show differential drug sensitivity

Abstract Background: Ewing's sarcoma is a rare form of highly aggressive bone tumor of children and young adults. Understanding the molecular mechanisms involved in the development of Ewing's sarcoma forms the key step in the design and development of new therapeutic interventions. Previous studies revealed that genomic alterations play an important role in oncogenesis, disease progression and response of tumors to different therapies. The recent advance of next generation sequencing-based methods provide unprecedented capabilities to scan Ewing's sarcoma genomes for changes such as mutations, insertions/deletions, copy number variations, differential gene expression and discovery of new gene fusions. In this study, we performed detailed investigation to identify the genetic basis of difference between two Ewing cell lines, RDES and SKES1, which show differential sensitivity to natural product extracts, by using RNA-seq, small RNA-seq and exome-capture-seq techniques. Methods: Transcriptomes and genomic DNA of both the Ewing's cell lines, RDES and SKES1 were prepared for paired-end sequencing on the Illumina HiSeq2000 platform using the manufacturer's protocols, for RNA-seq and exome-capture-seq respectively. The reads were aligned to the human hg19 genome assembly and the abundance of mRNAs as well as small RNAs for all annotated genes from the UCSC annotation of human genome was calculated. The count data from abundance estimation was used to compute differentially expressed genes and small RNAs between these two cell lines. Furthermore, we used deFuse for the gene fusion identification and GATK pipeline for the DNA variant analysis. Results: We studied the gene expression profiles from RNA-seq and small RNA-seq reads and identified approximately 270 and 114 differentially expressed genes and microRNAs, respectively between drug-sensitive and insensitive cell lines. Interestingly, we found that two of ABC transporters are significantly overexpressed in the resistant cell line. Moreover, many apoptotic genes show altered expression between these two cell lines. Gene fusion products were also identified from the RNA-seq analysis. Both the cell lines were found to harbor the well-known Ewing's sarcoma gene fusion EWS-FLI1. In addition to EWS-FLI1, we also discovered some new and unique gene fusion candidates in both cell lines. Furthermore, we used exome-capture sequence analysis to identify sequence variation and mutations in these two cell lines. Known mutations reported in COSMIC database and SNPs that are not included in normal populations from the 1000 genome project were carefully studied. Interestingly, some of the non-synonymous changes identified map to kinases and other known cancer-related genes. Conclusions: Our studies suggest that the difference in drug sensitivity of two Ewing's sarcoma cell-lines is probably due to the expression of ATP-dependent efflux pumps as well as alterations in the apoptotic machinery. Further studies are warranted to understand the exact molecular mechanism of drug sensitivity. Citation Format: TABREZ A. MOHAMMAD, Aparna Gorthi, Andrew Robles, Xavier Bernard, Tzu-hung Hsiao, Dawn Garcia, Zhao Lai, Susan L. Mooberry, Gail E. Tomlinson, Alexander JR Bishop, Yidong Chen. Integrative genomic analysis of two Ewing's sarcoma cell lines that show differential drug sensitivity. [abstract]. In: Proceedings of the AACR Special Conference on Pediatric Cancer at the Crossroads: Translating Discovery into Improved Outcomes; Nov 3-6, 2013; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2013;74(20 Suppl):Abstract nr A30.

Abstract 5585: Integrated DNA/RNA sequencing for discovery and orthogonal validation of expressed fusion genes in peripheral T-cell lymphomas

Abstract Background: Fusion genes, transcripts, and proteins are key drivers of hematopoietic oncogenesis and can serve as effective therapeutic targets. Among peripheral T-cell lymphomas (PTCLs), little is known about fusion genes except for those involving ALK. Discovery of fusion genes may provide therapeutic targets for PTCLs, which have poor outcomes with conventional therapy. We have developed methods for detecting candidate fusions using (1) mate-pair DNA sequencing (MPseq), an approach that spans the entire genome at a fraction of the cost of traditional whole-genome sequencing, and (2) RNA sequencing (RNAseq). Each technique has strengths, limitations, and false discovery rates. Here, we integrated results of both methods to discover and orthogonally validate expressed fusion genes in PTCLs. Methods: DNA and RNA were extracted from 49 frozen, OCT-embedded clinical PTCL specimens, including 25 anaplastic large cell lymphomas; 16 PTCLs, not otherwise specified; and 8 other PTCLs. MPseq and RNAseq were performed using Illumina library protocols and a HiSeq 2000. Detection of fusion genes and transcripts followed our published methods (Blood 2012;120:2280 and Nucleic Acids Res 2011;39:e100, respectively). Functional annotation of genes involved in fusions was performed using DAVID. Results: Of 2818 candidate chromosomal rearrangements identified by MPseq and 90 candidate fusion transcripts identified by RNAseq, 45 events were present in both datasets (mean/case, 0.9; range, 0-7). Fusions were inter-chromosomal in 16 and intra-chromosomal in 29. Annotation clusters with the highest enrichment scores related to SH2 domain-containing proteins and tyrosine kinases (including FER and MAP2K3). Seven genes were recurrently involved in fusions, including known fusion partners such as ALK and previously unreported fusion partners such as PPP1R8, a phosphatase inhibitor important for the activity of Polycomb group proteins such as EZH2. Detection of candidate events only by MPseq could be explained in part by breakpoints mapping to non-genic regions (79% of events). Detection only by RNAseq could be explained in part by unannotated transcripts spanning neighboring named genes (median intra-chromosomal distance, 0.09 MB vs. 12.7 MB for intra-chromosomal candidates identified by MPseq; p<0.0001, Wilcoxon test). Conclusions: Integrated DNA/RNA sequencing is an effective, clinically feasible tool for simultaneous discovery and orthogonal validation of expressed fusion genes. This approach yielded fusions in PTCLs involving genes with key functions in lymphocytes, including novel and recurrent fusions, some of which might be targetable with compounds currently in clinical trial. Candidate intra-chromosomal fusion transcripts not identified by MPseq may represent unrecognized isoforms or the results of novel read-through mechanisms, and merit further study. Citation Format: Andrew L. Feldman, George Vasmatzis, Yan W. Asmann, Sarah H. Johnson, Bruce W. Eckloff, Sumit Middha, Jaime I. Davila, Paul J. Kurtin, Brian K. Link, Stephen M. Ansell, James R. Cerhan. Integrated DNA/RNA sequencing for discovery and orthogonal validation of expressed fusion genes in peripheral T-cell lymphomas. [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 5585. doi:10.1158/1538-7445.AM2014-5585

Abstract 3562: Building workflows for gene fusion detection by RNA-seq

Abstract Many cancers are associated with chromosomal rearrangements, which in some cases yield fusions between disparate genes and impact cancer phenotypes. Rapid discovery of gene fusions in cancer can facilitate a deeper understanding of specific cancers and may become an important diagnostic tool in clinical settings informing decisions on cancer treatment. An attractive and cost-effective method to identify and study gene fusions is by massively-parallel RNA sequencing (RNA-seq), which provides rich transcriptome profiling data and, with appropriate computational analysis, can discover fusions between transcribed genes. Herein we present data exploring the robustness of gene fusion detection by RNA-seq on Illumina sequencing platforms with TopHat-Fusion, a RNA-seq read aligner specifically designed to detect expressed gene fusions. Using a set of synthetic fusion transcripts to spike in to human RNA samples, we demonstrate quantitative detection of gene fusions by RNA-seq. Additionally, we report the sensitivity of gene fusion discovery across different RNA-seq library preparation methods, including mRNA enrichment by poly-A selection, rRNA-depletion, and exome enrichment by targeted capture. This data helps build workflow recommendations for the detection and study of gene fusions by RNA-seq. Citation Format: Stephen Gross, Lisa Watson, Smita Pathak, Irina Khrebtukova, Gary Schroth. Building workflows for gene fusion detection by RNA-seq. [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 3562. doi:10.1158/1538-7445.AM2014-3562

Molecular genetics and cellular features of TFE3 and TFEB fusion kidney cancers.

Despite nearly two decades passing since the discovery of gene fusions involving TFE3 or TFEB in sporadic renal cell carcinoma (RCC), the molecular mechanisms underlying the renal-specific tumorigenesis of these genes remain largely unclear. The recently published findings of The Cancer Genome Atlas Network reported that five of the 416 surveyed clear cell RCC tumours (1.2%) harboured SFPQ-TFE3 fusions, providing further evidence for the importance of gene fusions. A total of five TFE3 gene fusions (PRCC-TFE3, ASPSCR1-TFE3, SFPQ-TFE3, NONO-TFE3, and CLTC-TFE3) and one TFEB gene fusion (MALAT1-TFEB) have been identified in RCC tumours and characterized at the mRNA transcript level. A multitude of molecular pathways well-described in carcinogenesis are regulated in part by TFE3 or TFEB proteins, including activation of TGFβ and ETS transcription factors, E-cadherin expression, CD40L-dependent lymphocyte activation, mTORC1 signalling, insulin-dependent metabolism regulation, folliculin signalling, and retinoblastoma-dependent cell cycle arrest. Determining which pathways are most important to RCC oncogenesis will be critical in discovering the most promising therapeutic targets for this disease.

ZFP36-FOSB fusion defines a subset of epithelioid hemangioma with atypical features.

Epithelioid hemangioma (EH) is a benign neoplasm with distinctive vasoformative features, which occasionally shows increased cellularity, cytologic atypia, and/or loco-regional aggressive growth, resulting in challenging differential diagnosis from malignant vascular neoplasms. Based on two intraosseous EH index cases with worrisome histologic features, such as the presence of necrosis, RNA sequencing was applied for possible fusion gene discovery and potential subclassification of a novel atypical EH subset. A ZFP36-FOSB fusion was detected in one case, while a WWTR1-FOSB chimeric transcript in the other, both were further validated by fluorescence in situ hybridization (FISH) and reverse transcription polymerase chain reaction (RT-PCR). These abnormalities were then screened by FISH in 44 EH from different locations with seven additional EH revealing FOSB gene rearrangements, all except one being fused to ZFP36. Interestingly, 4/6 penile EH studied showed FOSB abnormalities. Although certain atypical histologic features were observed in the FOSB-rearranged EH, including solid growth, increased cellularity, mild to moderate nuclear pleomorphism, and necrosis in 3/9 cases, no overt sarcomatous areas were discerned to objectively separate the lesions from the fusion-negative EH. No patient has developed recurrence to date, but the follow-up was relatively limited and short to draw definitive conclusions regarding behavior. Although FOSB-rearranged EH do not show significant morphologic overlap with SERPINE1-FOSB fusion-positive pseudomyogenic hemangioendothelioma, FOSB oncogenic activation is emerging as an important event in these benign and intermediate groups of vascular tumors.

A primate-specific microRNA enters the lung cancer landscape

Characterization of the lung cancer genome through unbiased next-generation sequencing has led to the discovery of new driver somatic mutations (1, 2) and gene fusions (3). Lung cancers show the second highest prevalence of somatic mutations among all cancer types, and a mutation profile that reflects the effect of chronic exposure to tobacco carcinogens, the main risk factor etiologically associated with this disease (2⇓–4). The next chapter of genomic decoding, through small RNA sequencing, brings about the discovery of primate-specific microRNAs (miRNAs) of the airway epithelium and the intriguing possibility that some may function as lung tumor suppressors (5).

Breakpoint Analysis of Transcriptional and Genomic Profiles Uncovers Novel Gene Fusions Spanning Multiple Human Cancer Types

Gene fusions, like BCR/ABL1 in chronic myelogenous leukemia, have long been recognized in hematologic and mesenchymal malignancies. The recent finding of gene fusions in prostate and lung cancers has motivated the search for pathogenic gene fusions in other malignancies. Here, we developed a “breakpoint analysis” pipeline to discover candidate gene fusions by tell-tale transcript level or genomic DNA copy number transitions occurring within genes. Mining data from 974 diverse cancer samples, we identified 198 candidate fusions involving annotated cancer genes. From these, we validated and further characterized novel gene fusions involving ROS1 tyrosine kinase in angiosarcoma (CEP85L/ROS1), SLC1A2 glutamate transporter in colon cancer (APIP/SLC1A2), RAF1 kinase in pancreatic cancer (ATG7/RAF1) and anaplastic astrocytoma (BCL6/RAF1), EWSR1 in melanoma (EWSR1/CREM), CDK6 kinase in T-cell acute lymphoblastic leukemia (FAM133B/CDK6), and CLTC in breast cancer (CLTC/VMP1). Notably, while these fusions involved known cancer genes, all occurred with novel fusion partners and in previously unreported cancer types. Moreover, several constituted druggable targets (including kinases), with therapeutic implications for their respective malignancies. Lastly, breakpoint analysis identified new cell line models for known rearrangements, including EGFRvIII and FIP1L1/PDGFRA. Taken together, we provide a robust approach for gene fusion discovery, and our results highlight a more widespread role of fusion genes in cancer pathogenesis.

Fusion genes and their discovery using high throughput sequencing

Fusion genes are hybrid genes that combine parts of two or more original genes. They can form as a result of chromosomal rearrangements or abnormal transcription, and have been shown to act as drivers of malignant transformation and progression in many human cancers. The biological significance of fusion genes together with their specificity to cancer cells has made them into excellent targets for molecular therapy. Fusion genes are also used as diagnostic and prognostic markers to confirm cancer diagnosis and monitor response to molecular therapies. High-throughput sequencing has enabled the systematic discovery of fusion genes in a wide variety of cancer types. In this review, we describe the history of fusion genes in cancer and the ways in which fusion genes form and affect cellular function. We also describe computational methodologies for detecting fusion genes from high-throughput sequencing experiments, and the most common sources of error that lead to false discovery of fusion genes.

FUSIM: a software tool for simulating fusion transcripts

BackgroundGene fusions are the result of chromosomal aberrations and encode chimeric RNA (fusion transcripts) that play an important role in cancer genesis. Recent advances in high throughput transcriptome sequencing have given rise to computational methods for new fusion discovery. The ability to simulate fusion transcripts is essential for testing and improving those tools.ResultsTo facilitate this need, we developed FUSIM (FUsion SIMulator), a software tool for simulating fusion transcripts. The simulation of events known to create fusion genes and their resulting chimeric proteins is supported, including inter-chromosome translocation, trans-splicing, complex chromosomal rearrangements, and transcriptional read through events.ConclusionsFUSIM provides the ability to assemble a dataset of fusion transcripts useful for testing and benchmarking applications in fusion gene discovery.

Multiple functions of a glioblastoma fusion oncogene

RNA sequencing facilitates the discovery of novel gene fusions in cancer. In this issue of the JCI, Parker et al. identify an FGFR3-TACC3 fusion oncogene in glioblastoma and demonstrate a novel mechanism of pathogenicity. A miR-99a binding site within the 3'-untranslated region (3'-UTR) of FGFR3 is lost, releasing FGFR3 signaling from miR-99a-dependent inhibition and greatly enhancing tumor progression relative to WT FGFR3. These results provide compelling insight into the pathogenicity of a novel fusion oncogene and suggest new therapeutic approaches for a subset of glioblastomas.

Exploration of the gene fusion landscape of glioblastoma using transcriptome sequencing and copy number data.

BackgroundRNA-seq has spurred important gene fusion discoveries in a number of different cancers, including lung, prostate, breast, brain, thyroid and bladder carcinomas. Gene fusion discovery can potentially lead to the development of novel treatments that target the underlying genetic abnormalities.ResultsIn this study, we provide comprehensive view of gene fusion landscape in 185 glioblastoma multiforme patients from two independent cohorts. Fusions occur in approximately 30-50% of GBM patient samples. In the Ivy Center cohort of 24 patients, 33% of samples harbored fusions that were validated by qPCR and Sanger sequencing. We were able to identify high-confidence gene fusions from RNA-seq data in 53% of the samples in a TCGA cohort of 161 patients. We identified 13 cases (8%) with fusions retaining a tyrosine kinase domain in the TCGA cohort and one case in the Ivy Center cohort. Ours is the first study to describe recurrent fusions involving non-coding genes. Genomic locations 7p11 and 12q14-15 harbor majority of the fusions. Fusions on 7p11 are formed in focally amplified EGFR locus whereas 12q14-15 fusions are formed by complex genomic rearrangements. All the fusions detected in this study can be further visualized and analyzed using our website: http://ivygap.swedish.org/fusions.ConclusionsOur study highlights the prevalence of gene fusions as one of the major genomic abnormalities in GBM. The majority of the fusions are private fusions, and a minority of these recur with low frequency. A small subset of patients with fusions of receptor tyrosine kinases can benefit from existing FDA approved drugs and drugs available in various clinical trials. Due to the low frequency and rarity of clinically relevant fusions, RNA-seq of GBM patient samples will be a vital tool for the identification of patient-specific fusions that can drive personalized therapy.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-14-818) contains supplementary material, which is available to authorized users.

Discovering chimeric transcripts in paired-end RNA-seq data by using EricScript

The discovery of novel gene fusions can lead to a better comprehension of cancer progression and development. The emergence of deep sequencing of trancriptome, known as RNA-seq, has opened many opportunities for the identification of this class of genomic alterations, leading to the discovery of novel chimeric transcripts in melanomas, breast cancers and lymphomas. Nowadays, few computational approaches have been developed for the detection of chimeric transcripts. Although all of these computational methods show good sensitivity, much work remains to reduce the huge number of false-positive calls that arises from this analysis. We proposed a novel computational framework, named chimEric tranScript detection algorithm (EricScript), for the identification of gene fusion products in paired-end RNA-seq data. Our simulation study on synthetic data demonstrates that EricScript enables to achieve higher sensitivity and specificity than existing methods with noticeably lower running times. We also applied our method to publicly available RNA-seq tumour datasets, and we showed its capability in rediscovering known gene fusions.

Application of next generation sequencing to human gene fusion detection: computational tools, features and perspectives

Gene fusions are important genomic events in human cancer because their fusion gene products can drive the development of cancer and thus are potential prognostic tools or therapeutic targets in anti-cancer treatment. Major advancements have been made in computational approaches for fusion gene discovery over the past 3 years due to improvements and widespread applications of high-throughput next generation sequencing (NGS) technologies. To identify fusions from NGS data, existing methods typically leverage the strengths of both sequencing technologies and computational strategies. In this article, we review the NGS and computational features of existing methods for fusion gene detection and suggest directions for future development.

Gene Fusions Associated with Recurrent Amplicons Represent a Class of Passenger Aberrations in Breast Cancer

Application of high-throughput transcriptome sequencing has spurred highly sensitive detection and discovery of gene fusions in cancer, but distinguishing potentially oncogenic fusions from random, “passenger” aberrations has proven challenging. Here we examine a distinctive group of gene fusions that involve genes present in the loci of chromosomal amplifications—a class of oncogenic aberrations that are widely prevalent in breast cancers. Integrative analysis of a panel of 14 breast cancer cell lines comparing gene fusions discovered by high-throughput transcriptome sequencing and genome-wide copy number aberrations assessed by array comparative genomic hybridization, led to the identification of 77 gene fusions, of which more than 60% were localized to amplicons including 17q12, 17q23, 20q13, chr8q, and others. Many of these fusions appeared to be recurrent or involved highly expressed oncogenic drivers, frequently fused with multiple different partners, but sometimes displaying loss of functional domains. As illustrative examples of the “amplicon-associated” gene fusions, we examined here a recurrent gene fusion involving the mediator of mammalian target of rapamycin signaling, RPS6KB1 kinase in BT-474, and the therapeutically important receptor tyrosine kinase EGFR in MDA-MB-468 breast cancer cell line. These gene fusions comprise a minor allelic fraction relative to the highly expressed full-length transcripts and encode chimera lacking the kinase domains, which do not impart dependence on the respective cells. Our study suggests that amplicon-associated gene fusions in breast cancer primarily represent a by-product of chromosomal amplifications, which constitutes a subset of passenger aberrations and should be factored accordingly during prioritization of gene fusion candidates.

Recurrent Oncogenic Mutations in CCND3 in Aggressive Lymphomas

Abstract 435The recent development of high throughput mRNA sequencing technologies has allowed major advances in the characterization and quantification of transcriptomes in human cancer. These advances include gene mutation detection, gene fusion discovery, analysis of alternative splicing events, and unbiased gene expression profiling.To comprehensively discover pathogenic sequence variants in lymphomas, we used Illumina technology to sequence mRNA of 206 lymphoma biopsies and cell lines, including 64 diffuse large B-cell lymphomas (DLBCL) of the activated B-cell-like (ABC) subtype, 71 DLBCL of the germinal center (GCB) subtype, and 41 Burkitt's lymphomas (BL). This effort uncovered a large number of mutations that were verified by Sanger sequencing.Using this methodology, we discovered somatic mutations in CCND3, encoding Cyclin D3, in 38 % of BLs, 14 % of ABC DLBCLs, and 10 % of GCB DLBCLs. These mutations stabilized the Cyclin D3 protein by altering a phosphorylation motif at Thr283 that is required for proteasomal degradation. Knockdown of CCND3 by RNA interference confirmed the oncogenic addiction to this gene in the mutated cell lines. In parallel, an RNA interference screen revealed that the cell lines that are dependent on CCND3 are also reliant on cyclin-dependent kinase 6 (CDK6), which together with Cyclin D3 regulates the G1/S transition of the cell cycle. Ectopic expression of the mutant CCND3 isoforms accelerated lymphoma cell line proliferation thereby demonstrating the oncogenic potential of these mutations.Remarkably, treatment of the CCND3/CDK6 addicted cell lines with a small molecule inhibitor of CDK 4/6 caused G1 arrest followed by apoptosis suggesting novel therapeutic strategies for these aggressive lymphomas. Disclosures:No relevant conflicts of interest to declare.

ChimeraScan: a tool for identifying chimeric transcription in sequencing data

Next generation sequencing (NGS) technologies have enabled de novo gene fusion discovery that could reveal candidates with therapeutic significance in cancer. Here we present an open-source software package, ChimeraScan, for the discovery of chimeric transcription between two independent transcripts in high-throughput transcriptome sequencing data. http://chimerascan.googlecode.com cmaher@dom.wustl.edu Supplementary data are available at Bioinformatics online.

DeFuse: An Algorithm for Gene Fusion Discovery in Tumor RNA-Seq Data

Gene fusions created by somatic genomic rearrangements are known to play an important role in the onset and development of some cancers, such as lymphomas and sarcomas. RNA-Seq (whole transcriptome shotgun sequencing) is proving to be a useful tool for the discovery of novel gene fusions in cancer transcriptomes. However, algorithmic methods for the discovery of gene fusions using RNA-Seq data remain underdeveloped. We have developed deFuse, a novel computational method for fusion discovery in tumor RNA-Seq data. Unlike existing methods that use only unique best-hit alignments and consider only fusion boundaries at the ends of known exons, deFuse considers all alignments and all possible locations for fusion boundaries. As a result, deFuse is able to identify fusion sequences with demonstrably better sensitivity than previous approaches. To increase the specificity of our approach, we curated a list of 60 true positive and 61 true negative fusion sequences (as confirmed by RT-PCR), and have trained an adaboost classifier on 11 novel features of the sequence data. The resulting classifier has an estimated value of 0.91 for the area under the ROC curve. We have used deFuse to discover gene fusions in 40 ovarian tumor samples, one ovarian cancer cell line, and three sarcoma samples. We report herein the first gene fusions discovered in ovarian cancer. We conclude that gene fusions are not infrequent events in ovarian cancer and that these events have the potential to substantially alter the expression patterns of the genes involved; gene fusions should therefore be considered in efforts to comprehensively characterize the mutational profiles of ovarian cancer transcriptomes.

Comrad: detection of expressed rearrangements by integrated analysis of RNA-Seq and low coverage genome sequence data

Comrad is a novel algorithmic framework for the integrated analysis of RNA-Seq and whole genome shotgun sequencing (WGSS) data for the purposes of discovering genomic rearrangements and aberrant transcripts. The Comrad framework leverages the advantages of both RNA-Seq and WGSS data, providing accurate classification of rearrangements as expressed or not expressed and accurate classification of the genomic or non-genomic origin of aberrant transcripts. A major benefit of Comrad is its ability to accurately identify aberrant transcripts and associated rearrangements using low coverage genome data. As a result, a Comrad analysis can be performed at a cost comparable to that of two RNA-Seq experiments, significantly lower than an analysis requiring high coverage genome data. We have applied Comrad to the discovery of gene fusions and read-throughs in prostate cancer cell line C4-2, a derivative of the LNCaP cell line with androgen-independent characteristics. As a proof of concept, we have rediscovered in the C4-2 data 4 of the 6 fusions previously identified in LNCaP. We also identified six novel fusion transcripts and associated genomic breakpoints, and verified their existence in LNCaP, suggesting that Comrad may be more sensitive than previous methods that have been applied to fusion discovery in LNCaP. We show that many of the gene fusions discovered using Comrad would be difficult to identify using currently available techniques. A C++ and Perl implementation of the method demonstrated in this article is available at http://compbio.cs.sfu.ca/.

The use of ultra-dense array CGH analysis for the discovery of micro-copy number alterations and gene fusions in the cancer genome

BackgroundMolecular alterations critical to development of cancer include mutations, copy number alterations (amplifications and deletions) as well as genomic rearrangements resulting in gene fusions. Massively parallel next generation sequencing, which enables the discovery of such changes, uses considerable quantities of genomic DNA (> 5 ug), a serious limitation in ever smaller clinical samples. However, a commonly available microarray platforms such as array comparative genomic hybridization (array CGH) allows the characterization of gene copy number at a single gene resolution using much smaller amounts of genomic DNA. In this study we evaluate the sensitivity of ultra-dense array CGH platforms developed by Agilent, especially that of the 1 million probe array (1 M array), and their application when whole genome amplification is required because of limited sample quantities.MethodsWe performed array CGH on whole genome amplified and not amplified genomic DNA from MCF-7 breast cancer cells, using 244 K and 1 M Agilent arrays. The ADM-2 algorithm was used to identify micro-copy number alterations that measured less than 1 Mb in genomic length.ResultsDNA from MCF-7 breast cancer cells was analyzed for micro-copy number alterations, defined as measuring less than 1 Mb in genomic length. The 4-fold extra resolution of the 1 M array platform relative to the less dense 244 K array platform, led to the improved detection of copy number variations (CNVs) and micro-CNAs. The identification of intra-genic breakpoints in areas of DNA copy number gain signaled the possible presence of gene fusion events. However, the ultra-dense platforms, especially the densest 1 M array, detect artifacts inherent to whole genome amplification and should be used only with non-amplified DNA samples.ConclusionsThis is a first report using 1 M array CGH for the discovery of cancer genes and biomarkers. We show the remarkable capacity of this technology to discover CNVs, micro-copy number alterations and even gene fusions. However, these platforms require excellent genomic DNA quality and do not tolerate relatively small imperfections related to the whole genome amplification.

Discovery of non-ETS gene fusions in human prostate cancer using next-generation RNA sequencing

Half of prostate cancers harbor gene fusions between TMPRSS2 and members of the ETS transcription factor family. To date, little is known about the presence of non-ETS fusion events in prostate cancer. We used next-generation transcriptome sequencing (RNA-seq) in order to explore the whole transcriptome of 25 human prostate cancer samples for the presence of chimeric fusion transcripts. We generated more than 1 billion sequence reads and used a novel computational approach (FusionSeq) in order to identify novel gene fusion candidates with high confidence. In total, we discovered and characterized seven new cancer-specific gene fusions, two involving the ETS genes ETV1 and ERG, and four involving non-ETS genes such as CDKN1A (p21), CD9, and IKBKB (IKK-beta), genes known to exhibit key biological roles in cellular homeostasis or assumed to be critical in tumorigenesis of other tumor entities, as well as the oncogene PIGU and the tumor suppressor gene RSRC2. The novel gene fusions are found to be of low frequency, but, interestingly, the non-ETS fusions were all present in prostate cancer harboring the TMPRSS2-ERG gene fusion. Future work will focus on determining if the ETS rearrangements in prostate cancer are associated or directly predispose to a rearrangement-prone phenotype.