ChimeraScan: a tool for identifying chimeric transcription in sequencing data

Burkitt lymphoma beyond MYC translocation: N-MYC and DNA methyltransferases dysregulation

BACKGROUND

The oncogenic transcription factor MYC is pathologically activated in many human malignancies. A paradigm for MYC dysregulation is offered by Burkitt lymphoma, where chromosomal translocations leading to Immunoglobulin gene-MYC fusion are the crucial initiating oncogenic events. However, Burkitt lymphoma cases with no detectable MYC rearrangement but maintaining MYC expression have been identified and alternative mechanisms can be involved in MYC dysregulation in these cases.

METHODS

We studied the microRNA profile of MYC translocation-positive and MYC translocation-negative Burkitt lymphoma cases in order to uncover possible differences at the molecular level. Data was validated at the mRNA and protein level by quantitative Real-Time polymerase chain reaction and immunohistochemistry, respectively.

RESULTS

We identified four microRNAs differentially expressed between the two groups. The impact of these microRNAs on the expression of selected genes was then investigated. Interestingly, in MYC translocation-negative cases we found over-expression of DNA-methyl transferase family members, consistent to hypo-expression of the hsa-miR-29 family. This finding suggests an alternative way for the activation of lymphomagenesis in these cases, based on global changes in methylation landscape, aberrant DNA hypermethylation, lack of epigenetic control on transcription of targeted genes, and increase of genomic instability. In addition, we observed an over-expression of another MYC family gene member, MYCN that may therefore represent a cooperating mechanism of MYC in driving the malignant transformation in those cases lacking an identifiable MYC translocation but expressing the gene at the mRNA and protein levels.

CONCLUSIONS

Collectively, our results showed that MYC translocation-positive and MYC translocation-negative Burkitt lymphoma cases are slightly different in terms of microRNA and gene expression. MYC translocation-negative Burkitt lymphoma, similarly to other aggressive B-cell non Hodgkin's lymphomas, may represent a model to understand the intricate molecular pathway responsible for MYC dysregulation in cancer.

Gene fusion detection in formalin-fixed paraffin-embedded benign fibrous histiocytomas using fluorescence in situ hybridization and RNA sequencing

Benign fibrous histiocytomas (FH) can be subdivided into several morphological and clinical subgroups. Recently, gene fusions involving either one of two protein kinase C genes (PRKCB and PRKCD) or the ALK gene were described in FH. We here wanted to evaluate the frequency of PRKCB and PRKCD gene fusions in FH. Using interphase fluorescence in situ hybridization on sections from formalin-fixed paraffin-embedded (FFPE) tumors, 36 cases could be analyzed. PRKCB or PRKCD rearrangements were seen in five tumors: 1/7 regular, 0/3 aneurysmal, 0/6 cellular, 2/7 epithelioid, 0/1 atypical, 2/10 deep, and 0/2 metastatic lesions. We also evaluated the status of the ALK gene in selected cases, finding rearrangements in 3/7 epithelioid and 0/1 atypical lesions. To assess the gene fusion status of FH further, deep sequencing of RNA (RNA-Seq) was performed on FFPE tissue from eight cases with unknown gene fusion status, as well as on two FH and six soft tissue sarcomas with known gene fusions; of the latter eight positive controls, the expected fusion transcript was found in all but one, while 2/8 FH with unknown genetic status showed fusion transcripts, including a novel KIRREL/PRKCA chimera. Thus, also a third member of the PRKC family is involved in FH tumorigenesis. We conclude that gene fusions involving PRKC genes occur in several morphological (regular, cellular, aneurysmal, epithelioid) and clinical (cutaneous, deep) subsets of FH, but they seem to account for only a minority of the cases. In epithelioid lesions, however, rearrangements of PRKC or ALK were seen, as mutually exclusive events, in the majority (5/7) of cases. Finally, the study also shows that RNA-Seq is a promising tool for identifying gene fusions in FFPE tissues.

Detection of a Distinctive Genomic Signature in Rhabdoid Glioblastoma, A Rare Disease Entity Identified by Whole Exome Sequencing and Whole Transcriptome Sequencing

We analyzed the genome of a rhabdoid glioblastoma (R-GBM) tumor, a very rare variant of GBM. A surgical specimen of R-GBM from a 20-year-old woman was analyzed using whole exome sequencing (WES), whole transcriptome sequencing (WTS), single nucleotide polymorphism array, and array comparative genomic hybridization. The status of gene expression in R-GBM tissue was compared with that of normal brain tissue and conventional GBM tumor tissue. We identified 23 somatic non-synonymous small nucleotide variants with WES. We identified the BRAF V600E mutation and possible functional changes in the mutated genes, ISL1 and NDRG2. Copy number alteration analysis revealed gains of chromosomes 3, 7, and 9. We found loss of heterozygosity and focal homozygous deletion on 9q21, which includes CDKN2A and CDKN2B. In addition, WTS revealed that CDK6, MET, EZH2, EGFR, and NOTCH1, which are located on chromosomes 7 and 9, were over-expressed, whereas CDKN2A/2B were minimally expressed. Fusion gene analysis showed 14 candidate genes that may be functionally involved in R-GBM, including TWIST2, and UPK3BL. The BRAF V600E mutation, CDKN2A/2B deletion, and EGFR/MET copy number gain were observed. These simultaneous alterations are very rarely found in GBM. Moreover, the NDRG2 mutation was first identified in this study as it has never been reported in GBM. We observed a unique genomic signature in R-GBM compared to conventional GBM, which may provide insight regarding R-GBM as a distinct disease entity among the larger group of GBMs.

LAMTOR1-PRKCD and NUMA1-SFMBT1 fusion genes identified by RNA sequencing in aneurysmal benign fibrous histiocytoma with t(3;11)(p21;q13)

RNA sequencing of an aneurysmal benign fibrous histiocytoma with the karyotype 46,XY,t(3;11)(p21;q13),del(6)(p23)[17]/46,XY[2] showed that the t(3;11) generated two fusion genes: LAMTOR1-PRKCD and NUMA1-SFMBT1. RT-PCR together with Sanger sequencing verified the presence of fusion transcripts from both fusion genes. In the LAMTOR1-PRKCD fusion, the part of the PRKCD gene coding for the catalytic domain of the serine/threonine kinase is under control of the LAMTOR1 promoter. In the NUMA1-SFMBT1 fusion, the part of the SFMBT1 gene coding for two of four malignant brain tumor domains and the sterile alpha motif domain is controlled by the NUMA1 promoter. The data support a neoplastic genesis of aneurysmal benign fibrous histiocytoma and indicate a pathogenetic role for LAMTOR1-PRKCD and NUMA1-SFMBT1.

FusionCancer: a database of cancer fusion genes derived from RNA-seq data

BACKGROUND

Fusion genes are chimeric results originated from previous separate genes with aberrant functions. The resulting protein products may lead to abnormal status of expression levels, functions and action sites, which in return may cause the abnormal proliferation of cells and cancer development.

RESULTS

With the emergence of next-generation sequencing technology, RNA-seq has spurred gene fusion discovery in various cancer types. In this work, we compiled 591 recently published RNA-seq datasets in 15 kinds of human cancer, and the gene fusion events were comprehensively identified. Based on the results, a database was developed for gene fusion in cancers (FusionCancer), with the attempt to provide a user-friendly utility for the cancer research community. A flexible query engine has been developed for the acquisition of annotated information of cancer fusion genes, which would help users to determine the chimera events leading to functional changes. FusionCancer can be accessible at the following hyperlink website: http://donglab.ecnu.edu.cn/databases/FusionCancer/

CONCLUSION

To the best of our knowledge, FusionCancer is the first comprehensive fusion gene database derived only from cancer RNA-seq data.

Novel ZEB2-BCL11B Fusion Gene Identified by RNA-Sequencing in Acute Myeloid Leukemia with t(2;14)(q22;q32)

RNA-sequencing of a case of acute myeloid leukemia with the bone marrow karyotype 46,XY,t(2;14)(q22;q32)[5]/47,XY,idem,+?4,del(6)(q13q21)[cp6]/46,XY[4] showed that the t(2;14) generated a ZEB2-BCL11B chimera in which exon 2 of ZEB2 (nucleotide 595 in the sequence with accession number NM_014795.3) was fused to exon 2 of BCL11B (nucleotide 554 in the sequence with accession number NM_022898.2). RT-PCR together with Sanger sequencing verified the presence of the above-mentioned fusion transcript. All functional domains of BCL11B are retained in the chimeric protein. Abnormal expression of BCL11B coding regions subjected to control by the ZEB2 promoter seems to be the leukemogenic mechanism behind the translocation.

Genome Modeling System: A Knowledge Management Platform for Genomics

In this work, we present the Genome Modeling System (GMS), an analysis information management system capable of executing automated genome analysis pipelines at a massive scale. The GMS framework provides detailed tracking of samples and data coupled with reliable and repeatable analysis pipelines. The GMS also serves as a platform for bioinformatics development, allowing a large team to collaborate on data analysis, or an individual researcher to leverage the work of others effectively within its data management system. Rather than separating ad-hoc analysis from rigorous, reproducible pipelines, the GMS promotes systematic integration between the two. As a demonstration of the GMS, we performed an integrated analysis of whole genome, exome and transcriptome sequencing data from a breast cancer cell line (HCC1395) and matched lymphoblastoid line (HCC1395BL). These data are available for users to test the software, complete tutorials and develop novel GMS pipeline configurations. The GMS is available at https://github.com/genome/gms.

TCF12 is mutated in anaplastic oligodendroglioma

Anaplastic oligodendroglioma (AO) are rare primary brain tumours that are generally incurable, with heterogeneous prognosis and few treatment targets identified. Most oligodendrogliomas have chromosomes 1p/19q co-deletion and an IDH mutation. Here we analysed 51 AO by whole-exome sequencing, identifying previously reported frequent somatic mutations in CIC and FUBP1. We also identified recurrent mutations in TCF12 and in an additional series of 83 AO. Overall, 7.5% of AO are mutated for TCF12, which encodes an oligodendrocyte-related transcription factor. Eighty percent of TCF12 mutations identified were in either the bHLH domain, which is important for TCF12 function as a transcription factor, or were frameshift mutations leading to TCF12 truncated for this domain. We show that these mutations compromise TCF12 transcriptional activity and are associated with a more aggressive tumour type. Our analysis provides further insights into the unique and shared pathways driving AO.

A primer on precision medicine informatics

In this review, we describe key components of a computational infrastructure for a precision medicine program that is based on clinical-grade genomic sequencing. Specific aspects covered in this review include software components and hardware infrastructure, reporting, integration into Electronic Health Records for routine clinical use and regulatory aspects. We emphasize informatics components related to reproducibility and reliability in genomic testing, regulatory compliance, traceability and documentation of processes, integration into clinical workflows, privacy requirements, prioritization and interpretation of results to report based on clinical needs, rapidly evolving knowledge base of genomic alterations and clinical treatments and return of results in a timely and predictable fashion. We also seek to differentiate between the use of precision medicine in germline and cancer.

Characterization of fusion genes and the significantly expressed fusion isoforms in breast cancer by hybrid sequencing

We developed an innovative hybrid sequencing approach, IDP-fusion, to detect fusion genes, determine fusion sites and identify and quantify fusion isoforms. IDP-fusion is the first method to study gene fusion events by integrating Third Generation Sequencing long reads and Second Generation Sequencing short reads. We applied IDP-fusion to PacBio data and Illumina data from the MCF-7 breast cancer cells. Compared with the existing tools, IDP-fusion detects fusion genes at higher precision and a very low false positive rate. The results show that IDP-fusion will be useful for unraveling the complexity of multiple fusion splices and fusion isoforms within tumorigenesis-relevant fusion genes.

A novel patient-derived tumorgraft model with TRAF1-ALK anaplastic large-cell lymphoma translocation

Although anaplastic large-cell lymphomas (ALCL) carrying anaplastic lymphoma kinase (ALK) have a relatively good prognosis, aggressive forms exist. We have identified a novel translocation, causing the fusion of the TRAF1 and ALK genes, in one patient who presented with a leukemic ALK+ ALCL (ALCL-11). To uncover the mechanisms leading to high-grade ALCL, we developed a human patient-derived tumorgraft (hPDT) line. Molecular characterization of primary and PDT cells demonstrated the activation of ALK and nuclear factor kB (NFkB) pathways. Genomic studies of ALCL-11 showed the TP53 loss and the in vivo subclonal expansion of lymphoma cells, lacking PRDM1/Blimp1 and carrying c-MYC gene amplification. The treatment with proteasome inhibitors of TRAF1-ALK cells led to the downregulation of p50/p52 and lymphoma growth inhibition. Moreover, a NFkB gene set classifier stratified ALCL in distinct subsets with different clinical outcome. Although a selective ALK inhibitor (CEP28122) resulted in a significant clinical response of hPDT mice, nevertheless the disease could not be eradicated. These data indicate that the activation of NFkB signaling contributes to the neoplastic phenotype of TRAF1-ALK ALCL. ALCL hPDTs are invaluable tools to validate the role of druggable molecules, predict therapeutic responses and implement patient specific therapies.

RNA sequencing of sarcomas with simple karyotypes: identification and enrichment of fusion transcripts

Gene fusions are neoplasia-associated mutations arising from structural chromosomal rearrangements. They have a strong impact on tumor development and constitute important diagnostic markers. Malignant soft tissue tumors (sarcomas) constitute a heterogeneous group of neoplasms with >50 distinct subtypes, each of which is rare. In addition, there is considerable morphologic overlap between sarcomas and benign lesions. Several subtypes display distinct gene fusions, serving as excellent biomarkers. The development of methods for deep sequencing of the complete transcriptome (RNA-Seq) has substantially improved the possibilities for detecting gene fusions. With the aim of identifying new gene fusions of biological and clinical relevance, eight sarcomas with simple karyotypes, ie, only one or a few structural rearrangements, were subjected to massively parallel paired-end sequencing of mRNA. Three different algorithms were used to identify fusion transcripts from RNA-Seq data. Three novel (KIAA2026-NUDT11, CCBL1-ARL1, and AFF3-PHF1) and two previously known fusions (FUS-CREB3L2 and HAS2-PLAG1) were found and could be verified by other methods. These findings show that RNA-Seq is a powerful tool for detecting gene fusions in sarcomas but also suggest that it is advisable to use more than one algorithm to analyze the output data as only two of the confirmed fusions were reported by more than one of the gene fusion detection software programs. For all of the confirmed gene fusions, at least one of the genes mapped to a chromosome band implicated by the karyotype, suggesting that sarcomas with simple karyotypes constitute an excellent resource for identifying novel gene fusions.

RAP: RNA-Seq Analysis Pipeline, a new cloud-based NGS web application

Background

The study of RNA has been dramatically improved by the introduction of Next Generation Sequencing platforms allowing massive and cheap sequencing of selected RNA fractions, also providing information on strand orientation (RNA-Seq). The complexity of transcriptomes and of their regulative pathways make RNA-Seq one of most complex field of NGS applications, addressing several aspects of the expression process (e.g. identification and quantification of expressed genes and transcripts, alternative splicing and polyadenylation, fusion genes and trans-splicing, post-transcriptional events, etc.).

Moreover, the huge volume of data generated by NGS platforms introduces unprecedented computational and technological challenges to efficiently analyze and store sequence data and results.

Methods

In order to provide researchers with an effective and friendly resource for analyzing RNA-Seq data, we present here RAP (RNA-Seq Analysis Pipeline), a cloud computing web application implementing a complete but modular analysis workflow. This pipeline integrates both state-of-the-art bioinformatics tools for RNA-Seq analysis and in-house developed scripts to offer to the user a comprehensive strategy for data analysis. RAP is able to perform quality checks (adopting FastQC and NGS QC Toolkit), identify and quantify expressed genes and transcripts (with Tophat, Cufflinks and HTSeq), detect alternative splicing events (using SpliceTrap) and chimeric transcripts (with ChimeraScan). This pipeline is also able to identify splicing junctions and constitutive or alternative polyadenylation sites (implementing custom analysis modules) and call for statistically significant differences in genes and transcripts expression, splicing pattern and polyadenylation site usage (using Cuffdiff2 and DESeq).

Results

Through a user friendly web interface, the RAP workflow can be suitably customized by the user and it is automatically executed on our cloud computing environment. This strategy allows to access to bioinformatics tools and computational resources without specific bioinformatics and IT skills. RAP provides a set of tabular and graphical results that can be helpful to browse, filter and export analyzed data, according to the user needs.

Introduction to RNA-Seq and its applications to drug discovery and development

Preclinical Research RNA sequencing (RNA-Seq) is a novel high-throughput technology for comprehensive transcriptome study. It can measure the expression levels of thousands of genes simultaneously and provide insight into functional pathways and regulations in biological processes. In addition, RNA-Seq can provide copious information on alternative splicing, allele-specific expression, unannotated exons, and novel transcripts (gene or noncoding RNAs). This technology has revolutionized the way biologists examine transcriptomes and has been successfully applied in drug discovery and development, being able to identify drug-related genes, microRNAs, and fusion proteins. In this overview, we will review this technology including data analysis, and its recent applications in drug discovery and development.

Detecting and targetting oncogenic fusion proteins in the genomic era

The advent of widespread cancer genome sequencing has accelerated our understanding of the molecular aberrations underlying malignant disease at an unprecedented rate. Coupling the large number of bioinformatic methods developed to locate genomic breakpoints with increased sequence read length and a deeper understanding of coding region function has enabled rapid identification of novel actionable oncogenic fusion genes. Using examples of kinase fusions found in liquid and solid tumours, this review highlights major concepts that have arisen in our understanding of cancer pathogenesis through the study of fusion proteins. We provide an overview of recently developed methods to identify potential fusion proteins from next-generation sequencing data, describe the validation of their oncogenic potential and discuss the role of targetted therapies in treating cancers driven by fusion oncoproteins.

Chimeric RNAs as potential biomarkers for tumor diagnosis

Cancers claim millions of lives each year. Early detection that can enable a higher chance of cure is of paramount importance to cancer patients. However, diagnostic tools for many forms of tumors have been lacking. Over the last few years, studies of chimeric RNAs as biomarkers have emerged. Numerous reports using bioinformatics and screening methodologies have described more than 30,000 expressed sequence tags (EST) or cDNA sequences as putative chimeric RNAs. While cancer cells have been well known to contain fusion genes derived from chromosomal translocations, rearrangements or deletions, recent studies suggest that trans-splicing in cells may be another source of chimeric RNA production. Unlike cis-splicing, trans-splicing takes place between two pre-mRNA molecules, which are in most cases derived from two different genes, generating a chimeric non-co-linear RNA. It is possible that trans-splicing occurs in normal cells at high frequencies but the resulting chimeric RNAs exist only at low levels. However the levels of certain RNA chimeras may be elevated in cancers, leading to the formation of fusion genes. In light of the fact that chimeric RNAs have been shown to be overrepresented in various tumors, studies of the mechanisms that produce chimeric RNAs and identification of signature RNA chimeras as biomarkers present an opportunity for the development of diagnoses for early tumor detection.

Recurrent PRDM10 gene fusions in undifferentiated pleomorphic sarcoma

PURPOSE

Undifferentiated pleomorphic sarcoma (UPS) is defined as a sarcoma with cellular pleomorphism and no identifiable line of differentiation. It is typically a high-grade lesion with a metastatic rate of about one third. No tumor-specific rearrangement has been identified, and genetic markers that could be used for treatment stratification are lacking. We performed transcriptome sequencing (RNA-Seq) to search for novel gene fusions.

EXPERIMENTAL DESIGN

RNA-Seq, FISH, and/or various PCR methodologies were used to search for gene fusions and rearrangements of the PRDM10 gene in 84 soft tissue sarcomas.

RESULTS

Using RNA-Seq, two cases of UPS were found to display novel gene fusions, both involving the transcription factor PRDM10 as the 3' partner and either MED12 or CITED2 as the 5' partner gene. Further screening of 82 soft tissue sarcomas for rearrangements of the PRDM10 locus revealed one more UPS with a MED12/PRDM10 fusion. None of these genes has been implicated in neoplasia-associated gene fusions before.

CONCLUSIONS

Our results suggest that PRDM10 fusions are present in around 5% of UPS. Although the fusion-positive cases in our series showed the same nuclear pleomorphism and lack of differentiation as other UPS, it is noteworthy that all three were morphologically low grade and that none of the patients developed metastases. Thus, PRDM10 fusion-positive sarcomas may constitute a clinically important subset of UPS.

ChiTaRS 2.1--an improved database of the chimeric transcripts and RNA-seq data with novel sense-antisense chimeric RNA transcripts

Chimeric RNAs that comprise two or more different transcripts have been identified in many cancers and among the Expressed Sequence Tags (ESTs) isolated from different organisms; they might represent functional proteins and produce different disease phenotypes. The ChiTaRS 2.1 database of chimeric transcripts and RNA-Seq data (http://chitars.bioinfo.cnio.es/) is the second version of the ChiTaRS database and includes improvements in content and functionality. Chimeras from eight organisms have been collated including novel sense–antisense (SAS) chimeras resulting from the slippage of the sense and anti-sense intragenic regions. The new database version collects more than 29 000 chimeric transcripts and indicates the expression and tissue specificity for 333 entries confirmed by RNA-seq reads mapping the chimeric junction sites. User interface allows for rapid and easy analysis of evolutionary conservation of fusions, literature references and experimental data supporting fusions in different organisms. More than 1428 cancer breakpoints have been automatically collected from public databases and manually verified to identify their correct cross-references, genomic sequences and junction sites. As a result, the ChiTaRS 2.1 collection of chimeras from eight organisms and human cancer breakpoints extends our understanding of the evolution of chimeric transcripts in eukaryotes as well as their functional role in carcinogenic processes.

A novel recurrent NPM1-TYK2 gene fusion in cutaneous CD30-positive lymphoproliferative disorders

The spectrum of cutaneous CD30-positive lymphoproliferative disorders (LPDs) includes lymphomatoid papulosis and primary cutaneous anaplastic large cell lymphoma. Chromosomal translocations targeting tyrosine kinases in CD30-positive LPDs have not been described. Using whole-transcriptome sequencing, we identified a chimeric fusion involving NPM1 (5q35) and TYK2 (19p13) that encodes an NPM1-TYK2 protein containing the oligomerization domain of NPM1 and an intact catalytic domain in TYK2. Fluorescence in situ hybridization revealed NPM1-TYK2 fusions in 2 of 47 (4%) primary cases of CD30-positive LPDs and was absent in other mature T-cell neoplasms (n = 151). Functionally, NPM1-TYK2 induced constitutive TYK2, signal transducer and activator of transcription 1 (STAT1), STAT3, and STAT5 activation. Conversely, a kinase-defective NPM1-TYK2 mutant abrogated STAT1/3/5 signaling. Finally, short hairpin RNA-mediated silencing of TYK2 abrogated lymphoma cell growth. This is the first report of recurrent translocations involving TYK2, and it highlights the novel therapeutic opportunities in the treatment of CD30-positive LPDs with TYK2 translocations.

Recurrent LRP1-SNRNP25 and KCNMB4-CCND3 fusion genes promote tumor cell motility in human osteosarcoma

BACKGROUND

The identification of fusion genes such as SYT-SSX1/SSX2, PAX3-FOXO1, TPM3/TPM4-ALK and EWS-FLI1 in human sarcomas has provided important insight into the diagnosis and targeted therapy of sarcomas. No recurrent fusion has been reported in human osteosarcoma.

METHODS

Transcriptome sequencing was used to characterize the gene fusions and mutations in 11 human osteosarcomas.

RESULTS

Nine of 11 samples were found to harbor genetic inactivating alterations in the TP53 pathway. Two recurrent fusion genes associated with the 12q locus, LRP1-SNRNP25 and KCNMB4-CCND3, were identified and validated by RT-PCR, Sanger sequencing and fluorescence in situ hybridization, and were found to be osteosarcoma specific in a validation cohort of 240 other sarcomas. Expression of LRP1-SNRNP25 fusion gene promoted SAOS-2 osteosarcoma cell migration and invasion. Expression of KCNMB4-CCND3 fusion gene promoted SAOS-2 cell migration.

CONCLUSIONS

Our study represents the first whole transcriptome analysis of untreated human osteosarcoma. Our discovery of two osteosarcoma specific fusion genes associated with osteosarcoma cellular motility highlights the heterogeneity of osteosarcoma and provides opportunities for new treatment modalities.

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.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-824) contains supplementary material, which is available to authorized users.

Hotspot activating PRKD1 somatic mutations in polymorphous low-grade adenocarcinomas of the salivary glands

Polymorphous low-grade adenocarcinoma (PLGA) is the second most frequent type of malignant tumor of the minor salivary glands. We identified PRKD1 hotspot mutations encoding p.Glu710Asp in 72.9% of PLGAs but not in other salivary gland tumors. Functional studies demonstrated that this kinase-activating alteration likely constitutes a driver of PLGA.

Integrated analysis of whole-genome paired-end and mate-pair sequencing data for identifying genomic structural variations in multiple myeloma

We present a pipeline to perform integrative analysis of mate-pair (MP) and paired-end (PE) genomic DNA sequencing data. Our pipeline detects structural variations (SVs) by taking aligned sequencing read pairs as input and classifying these reads into properly paired and discordantly paired categories based on their orientation and inferred insert sizes. Recurrent SV was identified from the discordant read pairs. Our pipeline takes into account genomic annotation and genome repetitive element information to increase detection specificity. Application of our pipeline to whole-genome MP and PE sequencing data from three multiple myeloma cell lines (KMS11, MM.1S, and RPMI8226) recovered known SVs, such as heterozygous TRAF3 deletion, as well as a novel experimentally validated SPI1 - ZNF287 inter-chromosomal rearrangement in the RPMI8226 cell line.

Transcription-mediated chimeric RNAs in prostate cancer: time to revisit old hypothesis?

Chromosomal rearrangements and fusion genes play important roles in tumor development and progression. Four high-frequency prostate cancer-specific fusion genes were recently reported in Chinese cases. We attempted to confirm one of the fusion genes, USP9Y-TTTY15, by reverse transcription PCR, but detected the presence of the USP9Y-TTTY15 fusion transcript in cancer samples, nonmalignant prostate tissues, and normal tissues from other organs, demonstrating that it is a transcription-induced chimeric RNA, which is commonly produced in normal tissues. In 105 prostate cancer samples and case-matched adjacent nonmalignant tissues, we determined the expression level of USP9Y-TTTY15 and a previously reported transcription-induced chimeric RNA, SLC45A3-ELK4. The expression levels of both chimeric RNAs vary greatly in cancer and normal cells. USP9Y-TTTY15 expression is neither higher in cancer than adjacent normal tissues, nor correlated with features of advanced prostate cancer. Although the expression level of SLC45A3-ELK4 is higher in cancer than normal cells, and a dramatic increase in its expression from normal to cancer cells is correlated with advanced disease, its expression level in cancer samples alone is not correlated with any clinical parameters. These data show that both chimeric RNAs contribute less to prostate carcinogenesis than previously reported.

Pegasus: a comprehensive annotation and prediction tool for detection of driver gene fusions in cancer

Background

The extraordinary success of imatinib in the treatment of BCR-ABL1 associated cancers underscores the need to identify novel functional gene fusions in cancer. RNA sequencing offers a genome-wide view of expressed transcripts, uncovering biologically functional gene fusions. Although several bioinformatics tools are already available for the detection of putative fusion transcripts, candidate event lists are plagued with non-functional read-through events, reverse transcriptase template switching events, incorrect mapping, and other systematic errors. Such lists lack any indication of oncogenic relevance, and they are too large for exhaustive experimental validation.

Results

We have designed and implemented a pipeline, Pegasus, for the annotation and prediction of biologically functional gene fusion candidates. Pegasus provides a common interface for various gene fusion detection tools, reconstruction of novel fusion proteins, reading-frame-aware annotation of preserved/lost functional domains, and data-driven classification of oncogenic potential. Pegasus dramatically streamlines the search for oncogenic gene fusions, bridging the gap between raw RNA-Seq data and a final, tractable list of candidates for experimental validation.

Conclusion

We show the effectiveness of Pegasus in predicting new driver fusions in 176 RNA-Seq samples of glioblastoma multiforme (GBM) and 23 cases of anaplastic large cell lymphoma (ALCL). Contact: fa2306@columbia.edu.

Diverse modes of genomic alteration in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a heterogeneous disease with high mortality rate. Recent genomic studies have identified TP53, AXIN1, and CTNNB1 as the most frequently mutated genes. Lower frequency mutations have been reported in ARID1A, ARID2 and JAK1. In addition, hepatitis B virus (HBV) integrations into the human genome have been associated with HCC.

RESULTS

Here, we deep-sequence 42 HCC patients with a combination of whole genome, exome and transcriptome sequencing to identify the mutational landscape of HCC using a reasonably large discovery cohort. We find frequent mutations in TP53, CTNNB1 and AXIN1, and rare but likely functional mutations in BAP1 and IDH1. Besides frequent hepatitis B virus integrations at TERT, we identify translocations at the boundaries of TERT. A novel deletion is identified in CTNNB1 in a region that is heavily mutated in multiple cancers. We also find multiple high-allelic frequency mutations in the extracellular matrix protein LAMA2. Lower expression levels of LAMA2 correlate with a proliferative signature, and predict poor survival and higher chance of cancer recurrence in HCC patients, suggesting an important role of the extracellular matrix and cell adhesion in tumor progression of a subgroup of HCC patients.

CONCLUSIONS

The heterogeneous disease of HCC features diverse modes of genomic alteration. In addition to common point mutations, structural variations and methylation changes, there are several virus-associated changes, including gene disruption or activation, formation of chimeric viral-human transcripts, and DNA copy number changes. Such a multitude of genomic events likely contributes to the heterogeneous nature of HCC.

Assessing the hodgepodge of non-mapped reads in bacterial transcriptomes: real or artifactual RNA chimeras?

BACKGROUND

RNA sequencing methods have already altered our view of the extent and complexity of bacterial and eukaryotic transcriptomes, revealing rare transcript isoforms (circular RNAs, RNA chimeras) that could play an important role in their biology.

RESULTS

We performed an analysis of chimera formation by four different computational approaches, including a custom designed pipeline, to study the transcriptomes of M. pneumoniae and P. aeruginosa, as well as mixtures of both. We found that rare transcript isoforms detected by conventional pipelines of analysis could be artifacts of the experimental procedure used in the library preparation, and that they are protocol-dependent.

CONCLUSION

By using a customized pipeline we show that optimal library preparation protocol and the pipeline to analyze the results are crucial to identify real chimeric RNAs.

DHH-RHEBL1 fusion transcript: a novel recurrent feature in the new landscape of pediatric CBFA2T3-GLIS2-positive acute myeloid leukemia

Childhood Acute Myeloid Leukemia (AML) is a clinically and genetically heterogeneous malignant disease. Despite improvements in outcome over the past decades, the current survival rate still is approximately 60-70%. Cytogenetic, recurrent genetic abnormalities and early response to induction treatment are the main factors predicting clinical outcome. While the majority of children carry recurrent chromosomal translocations, 20% of patients do not show any recognizable cytogenetic alteration and are defined to have cytogenetically normal AML (CN-AML). This subset of patients is characterized by a significant heterogeneity in clinical outcome, which is influenced by factors only recently started to be identified. In this respect, genome-wide analyses have been used with the aim of defining the full array of genetic lesions in CN-AML. Recently, through whole-transcriptome massively parallel sequencing of seven cases of pediatric CN-AML, we identified a novel recurrent CBFA2T3-GLIS2 fusion, predicting poorer outcome. However, since the expression of CBFA2T3-GLIS2 fusion in mice is not sufficient for leukemogenesis, we speculated that further unknown abnormalities could contribute to both cancer transformation and response to treatment. Thus, we analyzed, by whole-transcriptome sequencing, 4 CBFA2T3-GLIS2-positive patients, as well as 4 CN-AML patients. We identified a new fusion transcript in the CBFA2T3-GLIS2 -positive patients, involving Desert Hedgehog (DHH), a member of Hedgehog family, and Ras Homologue Enrich in Brain Like 1 (RHEBL1), a gene coding for a small GTPase of the Ras family. Through the screening of a validation cohort of 55 additional pediatric AML patients, we globally detected DHH-RHEBL1 fusion in 8 out of 20 (40%) CBFA2T3-GLIS2- rearranged patients. Gene expression analysis performed on RNA-seq data revealed that DHH-RHEBL1 –positive patients exhibited a specific signature. These 8 patients had an 8-year overall survival worse than that of the remaining 12 CBFA2T3-GLIS2- rearranged patients not harboring DHH-RHEBL1 fusion (25% vs 55%, respectively, P =0.1). Taken together, these findings are unprecedented and indicate that the DHH-RHEBL1 fusion transcript is a novel recurrent feature in the changing landscape of CBFA2T3-GLIS2 -positive childhood AML. Moreover, it could be instrumental in the identification of a subgroup of CBFA2T3-GLIS2 -positive patients with a very poor outcome.

Expanding the computational toolbox for mining cancer genomes

High-throughput DNA sequencing has revolutionized the study of cancer genomics with numerous discoveries that are relevant to cancer diagnosis and treatment. The latest sequencing and analysis methods have successfully identified somatic alterations, including single-nucleotide variants, insertions and deletions, copy-number aberrations, structural variants and gene fusions. Additional computational techniques have proved useful for defining the mutations, genes and molecular networks that drive diverse cancer phenotypes and that determine clonal architectures in tumour samples. Collectively, these tools have advanced the study of genomic, transcriptomic and epigenomic alterations in cancer, and their association to clinical properties. Here, we review cancer genomics software and the insights that have been gained from their application.

Integrative genomic and transcriptomic characterization of papillary carcinomas of the breast

Papillary carcinoma (PC) is a rare type of breast cancer, which comprises three histologic subtypes: encapsulated PC (EPC), solid PC (SPC) and invasive PC (IPC). Microarray‐based gene expression and Affymetrix SNP 6.0 gene copy number profiling, and RNA‐sequencing revealed that PCs are luminal breast cancers that display transcriptomic profiles distinct from those of grade‐ and estrogen receptor (ER)‐matched invasive ductal carcinomas of no special type (IDC‐NSTs), and that the papillary histologic pattern is unlikely to be underpinned by a highly recurrent expressed fusion gene or a highly recurrent expressed mutation. Despite displaying similar patterns of gene copy number alterations, significant differences in the transcriptomic profiles of EPCs, SPCs and IPCs were found, and may account for their different histologic features.

Papillary carcinomas of the breast display distinctive transcriptomic profiles.

Proliferation‐related genes are expressed at low levels in papillary carcinomas.

Papillary carcinomas are unlikely to be underpinned by a highly recurrent fusion gene.

Papillary carcinomas are unlikely to be underpinned by a highly recurrent expressed mutation.

The "grep" command but not FusionMap, FusionFinder or ChimeraScan captures the CIC-DUX4 fusion gene from whole transcriptome sequencing data on a small round cell tumor with t(4;19)(q35;q13)

Whole transcriptome sequencing was used to study a small round cell tumor in which a t(4;19)(q35;q13) was part of the complex karyotype but where the initial reverse transcriptase PCR (RT-PCR) examination did not detect a CIC-DUX4 fusion transcript previously described as the crucial gene-level outcome of this specific translocation. The RNA sequencing data were analysed using the FusionMap, FusionFinder, and ChimeraScan programs which are specifically designed to identify fusion genes. FusionMap, FusionFinder, and ChimeraScan identified 1017, 102, and 101 fusion transcripts, respectively, but CIC-DUX4 was not among them. Since the RNA sequencing data are in the fastq text-based format, we searched the files using the "grep" command-line utility. The "grep" command searches the text for specific expressions and displays, by default, the lines where matches occur. The "specific expression" was a sequence of 20 nucleotides from the coding part of the last exon 20 of CIC (Reference Sequence: NM_015125.3) chosen since all the so far reported CIC breakpoints have occurred here. Fifteen chimeric CIC-DUX4 cDNA sequences were captured and the fusion between the CIC and DUX4 genes was mapped precisely. New primer combinations were constructed based on these findings and were used together with a polymerase suitable for amplification of GC-rich DNA templates to amplify CIC-DUX4 cDNA fragments which had the same fusion point found with "grep". In conclusion, FusionMap, FusionFinder, and ChimeraScan generated a plethora of fusion transcripts but did not detect the biologically important CIC-DUX4 chimeric transcript; they are generally useful but evidently suffer from imperfect both sensitivity and specificity. The "grep" command is an excellent tool to capture chimeric transcripts from RNA sequencing data when the pathological and/or cytogenetic information strongly indicates the presence of a specific fusion gene.

Recurrent read-through fusion transcripts in breast cancer

Read-through fusion transcripts that result from the splicing of two adjacent genes in the same coding orientation are a recently discovered type of chimeric RNA. We sought to determine if read-through fusion transcripts exist in breast cancer. We performed paired-end RNA-seq of 168 breast samples, including 28 breast cancer cell lines, 42 triple negative breast cancer primary tumors, 42 estrogen receptor positive (ER+) breast cancer primary tumors, and 56 non-malignant breast tissue samples. We analyzed the sequencing data to identify breast cancer associated read-through fusion transcripts. We discovered two recurrent read-through fusion transcripts that were identified in breast cancer cell lines, confirmed across breast cancer primary tumors, and were not detected in normal tissues (SCNN1A-TNFRSF1A and CTSD-IFITM10). Both fusion transcripts use canonical splice sites to join the last splice donor of the 5′ gene to the first splice acceptor of the 3′ gene, creating an in-frame fusion transcript. Western blots indicated that the fusion transcripts are translated into fusion proteins in breast cancer cells. Custom small interfering RNAs targeting the CTSD-IFITM10 fusion junction reduced expression of the fusion transcript and reduced breast cancer cell proliferation. Read-through fusion transcripts between adjacent genes with different biochemical functions represent a new type of recurrent molecular defect in breast cancer that warrant further investigation as potential biomarkers and therapeutic targets. Both breast cancer associated fusion transcripts identified in this study involve membrane proteins (SCNN1A-TNFRSF1A and CTSD-IFITM10), which raises the possibility that they could be breast cancer-specific cell surface markers.

An improved understanding of cancer genomics through massively parallel sequencing

DNA sequencing technology advances have enabled genetic investigation of more samples in a shorter time than has previously been possible. Furthermore, the ability to analyze and understand large sequencing datasets has improved due to concurrent advances in sequence data analysis methods and software tools. Constant improvements to both technology and analytic approaches in this fast moving field are evidenced by many recent publications of computational methods, as well as biological results linking genetic events to human disease. Cancer in particular has been the subject of intense investigation, owing to the genetic underpinnings of this complex collection of diseases. New massively-parallel sequencing (MPS) technologies have enabled the investigation of thousands of samples, divided across tens of different tumor types, resulting in new driver gene identification, mutagenic pattern characterization, and other newly uncovered features of tumor biology. This review will focus both on methods and recent results: current analytical approaches to DNA and RNA sequencing will be presented followed by a review of recent pan-cancer sequencing studies. This overview of methods and results will not only highlight the recent advances in cancer genomics, but also the methods and tools used to accomplish these advancements in a constantly and rapidly improving field.

Identification of recurrent SMO and BRAF mutations in ameloblastomas

Here we report the discovery of oncogenic mutations in the Hedgehog and mitogen-activated protein kinase (MAPK) pathways in over 80% of ameloblastomas, locally destructive odontogenic tumors of the jaw, by genomic analysis of archival material. Mutations in SMO (encoding Smoothened, SMO) are common in ameloblastomas of the maxilla, whereas BRAF mutations are predominant in tumors of the mandible. We show that a frequently occurring SMO alteration encoding p.Leu412Phe is an activating mutation and that its effect on Hedgehog-pathway activity can be inhibited by arsenic trioxide (ATO), an anti-leukemia drug approved by the US Food and Drug Administration (FDA) that is currently in clinical trials for its Hedgehog-inhibitory activity. In a similar manner, ameloblastoma cells harboring an activating BRAF mutation encoding p.Val600Glu are sensitive to the BRAF inhibitor vemurafenib. Our findings establish a new paradigm for the diagnostic classification and treatment of ameloblastomas.

cDNA hybrid capture improves transcriptome analysis on low-input and archived samples

The use of massively parallel sequencing for studying RNA expression has greatly enhanced our understanding of the transcriptome through the myriad ways these data can be characterized. In particular, clinical samples provide important insights about RNA expression in health and disease, yet these studies can be complicated by RNA degradation that results from the use of formalin as a clinical preservative and by the limited amounts of RNA often available from these precious samples. In this study we describe the combined use of RNA sequencing with an exome capture selection step to enhance the yield of on-exon sequencing read data when compared with RNA sequencing alone. In particular, the exome capture step preserves the dynamic range of expression, permitting differential comparisons and validation of expressed mutations from limited and FFPE preserved samples, while reducing the data generation requirement. We conclude that cDNA hybrid capture has the potential to significantly improve transcriptome analysis from low-yield FFPE material.

Characterization of the genomic features and expressed fusion genes in micropapillary carcinomas of the breast

Micropapillary carcinoma (MPC) is a rare histological special type of breast cancer, characterized by an aggressive clinical behaviour and a pattern of copy number aberrations (CNAs) distinct from that of grade- and oestrogen receptor (ER)-matched invasive carcinomas of no special type (IC-NSTs). The aims of this study were to determine whether MPCs are underpinned by a recurrent fusion gene(s) or mutations in 273 genes recurrently mutated in breast cancer. Sixteen MPCs were subjected to microarray-based comparative genomic hybridization (aCGH) analysis and Sequenom OncoCarta mutation analysis. Eight and five MPCs were subjected to targeted capture and RNA sequencing, respectively. aCGH analysis confirmed our previous observations about the repertoire of CNAs of MPCs. Sequencing analysis revealed a spectrum of mutations similar to those of luminal B IC-NSTs, and recurrent mutations affecting mitogen-activated protein kinase family genes and NBPF10. RNA-sequencing analysis identified 17 high-confidence fusion genes, eight of which were validated and two of which were in-frame. No recurrent fusions were identified in an independent series of MPCs and IC-NSTs. Forced expression of in-frame fusion genes (SLC2A1-FAF1 and BCAS4-AURKA) resulted in increased viability of breast cancer cells. In addition, genomic disruption of CDK12 caused by out-of-frame rearrangements was found in one MPC and in 13% of HER2-positive breast cancers, identified through a re-analysis of publicly available massively parallel sequencing data. In vitro analyses revealed that CDK12 gene disruption results in sensitivity to PARP inhibition, and forced expression of wild-type CDK12 in a CDK12-null cell line model resulted in relative resistance to PARP inhibition. Our findings demonstrate that MPCs are neither defined by highly recurrent mutations in the 273 genes tested, nor underpinned by a recurrent fusion gene. Although seemingly private genetic events, some of the fusion transcripts found in MPCs may play a role in maintenance of a malignant phenotype and potentially offer therapeutic opportunities.

Integrated genomic characterization reveals novel, therapeutically relevant drug targets in FGFR and EGFR pathways in sporadic intrahepatic cholangiocarcinoma

Advanced cholangiocarcinoma continues to harbor a difficult prognosis and therapeutic options have been limited. During the course of a clinical trial of whole genomic sequencing seeking druggable targets, we examined six patients with advanced cholangiocarcinoma. Integrated genome-wide and whole transcriptome sequence analyses were performed on tumors from six patients with advanced, sporadic intrahepatic cholangiocarcinoma (SIC) to identify potential therapeutically actionable events. Among the somatic events captured in our analysis, we uncovered two novel therapeutically relevant genomic contexts that when acted upon, resulted in preliminary evidence of anti-tumor activity. Genome-wide structural analysis of sequence data revealed recurrent translocation events involving the FGFR2 locus in three of six assessed patients. These observations and supporting evidence triggered the use of FGFR inhibitors in these patients. In one example, preliminary anti-tumor activity of pazopanib (in vitro FGFR2 IC₅₀≈350 nM) was noted in a patient with an FGFR2-TACC3 fusion. After progression on pazopanib, the same patient also had stable disease on ponatinib, a pan-FGFR inhibitor (in vitro, FGFR2 IC₅₀≈8 nM). In an independent non-FGFR2 translocation patient, exome and transcriptome analysis revealed an allele specific somatic nonsense mutation (E384X) in ERRFI1, a direct negative regulator of EGFR activation. Rapid and robust disease regression was noted in this ERRFI1 inactivated tumor when treated with erlotinib, an EGFR kinase inhibitor. FGFR2 fusions and ERRFI mutations may represent novel targets in sporadic intrahepatic cholangiocarcinoma and trials should be characterized in larger cohorts of patients with these aberrations.

Cholangiocarcinoma is a cancer that affects the bile ducts. Unfortunately, many patients diagnosed with cholangiocarcinoma have disease that cannot be treated with surgery or has spread to other parts of the body, thus severely limiting treatment options. New advances in drug treatment have enabled treatment of these cancers with “targeted therapy” that exploits an error in the normal functioning of a tumor cell, compared to other cells in the body, thus allowing only tumor cells to be killed by the drug. We sought to identify changes in the genetic material of cholangiocarcinoma patient tumors in order to identify potential errors in cellular functioning by utilizing cutting edge genetic sequencing technology. We identified three patient tumors possessing an FGFR2 gene that was aberrantly fused to another gene. Two of these patients were able to receive targeted therapy for FGFR2 with resulting tumor shrinkage. A fourth tumor contained an error in a gene that controls a very important cellular mechanism in cancer, termed epidermal growth factor pathway (EGFR). This patient received therapy targeting this mechanism and also demonstrated response to treatment. Thus, we have been able to utilize cutting edge technology with targeted drug treatment to personalize medical treatment for cancer in cholangiocarcinoma patients.

Recurrent rearrangements in prostate cancer: causes and therapeutic potential

DNA damage and genetic rearrangements are hallmarks of cancer. However, gene fusions as driver mutations in cancer have classically been a distinction in leukemia and other rare instances until recently with the discovery of gene fusion events occurring in 50 to 75% of prostate cancer patients. The discovery of the TMPRSS2-ERG fusion sparked an onslaught of discovery and innovation resulting in a delineation of prostate cancer via a molecular signature of gene fusion events. The increased commonality of high-throughput sequencing data coupled with improved bioinformatics approaches not only elucidated the molecular underpinnings of prostate cancer progression, but the mechanisms of gene fusion biogenesis. Interestingly, the androgen receptor (AR), already known to play a significant role in prostate cancer tumorigenesis, has recently been implicated in the processes resulting in gene fusions by inducing the spatial proximity of genes involved in rearrangements, promoting the formation of double-strand DNA breaks (DSB), and facilitating the recruitment of proteins for non-homologous end-joining (NHEJ). Our increased understanding of the mechanisms inducing genomic instability may lead to improved diagnostic and therapeutic strategies. To date, the majority of prostate cancer patients can be molecularly stratified based on their gene fusion status thereby increasing the potential for tailoring more specific and effective therapies.

An extensive evaluation of read trimming effects on Illumina NGS data analysis

Next Generation Sequencing is having an extremely strong impact in biological and medical research and diagnostics, with applications ranging from gene expression quantification to genotyping and genome reconstruction. Sequencing data is often provided as raw reads which are processed prior to analysis 1 of the most used preprocessing procedures is read trimming, which aims at removing low quality portions while preserving the longest high quality part of a NGS read. In the current work, we evaluate nine different trimming algorithms in four datasets and three common NGS-based applications (RNA-Seq, SNP calling and genome assembly). Trimming is shown to increase the quality and reliability of the analysis, with concurrent gains in terms of execution time and computational resources needed.

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.

Integrative transcriptome sequencing identifies trans-splicing events with important roles in human embryonic stem cell pluripotency

Trans-splicing is a post-transcriptional event that joins exons from separate pre-mRNAs. Detection of trans-splicing is usually severely hampered by experimental artifacts and genetic rearrangements. Here, we develop a new computational pipeline, TSscan, which integrates different types of high-throughput long-/short-read transcriptome sequencing of different human embryonic stem cell (hESC) lines to effectively minimize false positives while detecting trans-splicing. Combining TSscan screening with multiple experimental validation steps revealed that most chimeric RNA products were platform-dependent experimental artifacts of RNA sequencing. We successfully identified and confirmed four trans-spliced RNAs, including the first reported trans-spliced large intergenic noncoding RNA (“tsRMST”). We showed that these trans-spliced RNAs were all highly expressed in human pluripotent stem cells and differentially expressed during hESC differentiation. Our results further indicated that tsRMST can contribute to pluripotency maintenance of hESCs by suppressing lineage-specific gene expression through the recruitment of NANOG and the PRC2 complex factor, SUZ12. Taken together, our findings provide important insights into the role of trans-splicing in pluripotency maintenance of hESCs and help to facilitate future studies into trans-splicing, opening up this important but understudied class of post-transcriptional events for comprehensive characterization.

Endocrine-therapy-resistant ESR1 variants revealed by genomic characterization of breast-cancer-derived xenografts

To characterize patient-derived xenografts (PDXs) for functional studies, we made whole-genome comparisons with originating breast cancers representative of the major intrinsic subtypes. Structural and copy number aberrations were found to be retained with high fidelity. However, at the single-nucleotide level, variable numbers of PDX-specific somatic events were documented, although they were only rarely functionally significant. Variant allele frequencies were often preserved in the PDXs, demonstrating that clonal representation can be transplantable. Estrogen-receptor-positive PDXs were associated with ESR1 ligand-binding-domain mutations, gene amplification, or an ESR1/YAP1 translocation. These events produced different endocrine-therapy-response phenotypes in human, cell line, and PDX endocrine-response studies. Hence, deeply sequenced PDX models are an important resource for the search for genome-forward treatment options and capture endocrine-drug-resistance etiologies that are not observed in standard cell lines. The originating tumor genome provides a benchmark for assessing genetic drift and clonal representation after transplantation.

The integrated landscape of driver genomic alterations in glioblastoma

Glioblastoma is one of the most challenging forms of cancer to treat. Here we describe a computational platform that integrates the analysis of copy number variations and somatic mutations and unravels the landscape of in-frame gene fusions in glioblastoma. We found mutations with loss of heterozygosity in LZTR1, encoding an adaptor of CUL3-containing E3 ligase complexes. Mutations and deletions disrupt LZTR1 function, which restrains the self renewal and growth of glioma spheres that retain stem cell features. Loss-of-function mutations in CTNND2 target a neural-specific gene and are associated with the transformation of glioma cells along the very aggressive mesenchymal phenotype. We also report recurrent translocations that fuse the coding sequence of EGFR to several partners, with EGFR-SEPT14 being the most frequent functional gene fusion in human glioblastoma. EGFR-SEPT14 fusions activate STAT3 signaling and confer mitogen independence and sensitivity to EGFR inhibition. These results provide insights into the pathogenesis of glioblastoma and highlight new targets for therapeutic intervention.

Identification of cancer gene fusions based on advanced analysis of the human genome or transcriptome

Many gene fusions have been recognized as important diagnostic and/or prognostic markers in human malignancies. In recent years, novel gene fusions have been identified in cases without prior knowledge of the genetic background. Accompanied by a powerful computational data analysis method, new genome-wide screening approaches were used to detect cryptic genomic aberrations. This review focused on advanced genomewide screening approaches in fusion gene identification, such as microarray-based approaches, next-generation sequencing, and NanoString nCounter gene expression system. The fundamental rationale and strategy for fusion gene identification using each biotech platform are also discussed.

Long-range transcriptome sequencing reveals cancer cell growth regulatory chimeric mRNA

mRNA chimeras from chromosomal translocations often play a role as transforming oncogenes. However, cancer transcriptomes also contain mRNA chimeras that may play a role in tumor development, which arise as transcriptional or post-transcriptional events. To identify such chimeras, we developed a deterministic screening strategy for long-range sequence analysis. High-throughput, long-read sequencing was then performed on cDNA libraries from major tumor histotypes and corresponding normal tissues. These analyses led to the identification of 378 chimeras, with an unexpectedly high frequency of expression (≈2 x 10(-5) of all mRNA). Functional assays in breast and ovarian cancer cell lines showed that a large fraction of mRNA chimeras regulates cell replication. Strikingly, chimeras were shown to include both positive and negative regulators of cell growth, which functioned as such in a cell-type-specific manner. Replication-controlling chimeras were found to be expressed by most cancers from breast, ovary, colon, uterus, kidney, lung, and stomach, suggesting a widespread role in tumor development.

State of art fusion-finder algorithms are suitable to detect transcription-induced chimeras in normal tissues?

Background

RNA-seq has the potential to discover genes created by chromosomal rearrangements. Fusion genes, also known as "chimeras", are formed by the breakage and re-joining of two different chromosomes. It is known that chimeras have been implicated in the development of cancer. Few publications in the past showed the presence of fusion events also in normal tissue, but with very limited overlaps between their results. More recently, two fusion genes in normal tissues were detected using both RNA-seq and protein data.

Due to heterogeneous results in identifying chimeras in normal tissue, we decided to evaluate the efficacy of state of the art fusion finders in detecting chimeras in RNA-seq data from normal tissues.

Results

We compared the performance of six fusion-finder tools: FusionHunter, FusionMap, FusionFinder, MapSplice, deFuse and TopHat-fusion. To evaluate the sensitivity we used a synthetic dataset of fusion-products, called positive dataset; in these experiments FusionMap, FusionFinder, MapSplice, and TopHat-fusion are able to detect more than 78% of fusion genes. All tools were error prone with high variability among the tools, identifying some fusion genes not present in the synthetic dataset. To better investigate the false discovery chimera detection rate, synthetic datasets free of fusion-products, called negative datasets, were used. The negative datasets have different read lengths and quality scores, which allow detecting dependency of the tools on both these features. FusionMap, FusionFinder, mapSplice, deFuse and TopHat-fusion were error-prone. Only FusionHunter results were free of false positive. FusionMap gave the best compromise in terms of specificity in the negative dataset and of sensitivity in the positive dataset.

Conclusions

We have observed a dependency of the tools on read length, quality score and on the number of reads supporting each chimera. Thus, it is important to carefully select the software on the basis of the structure of the RNA-seq data under analysis. Furthermore, the sensitivity of chimera detection tools does not seem to be sufficient to provide results consistent with those obtained in normal tissues on the basis of fusion events extracted from published data.