Discovering cancer-associated transcripts by RNA sequencing

High-throughput sequencing of poly-adenylated RNA (RNA-Seq) in human cancers shows remarkable potential to identify uncharacterized aspects of tumor biology, including gene fusions with therapeutic significance and disease markers such as long non-coding RNA (lncRNA) species. However, the analysis of RNA-Seq data places unprecedented demands upon computational infrastructures and algorithms, requiring novel bioinformatics approaches. To meet these demands, we present two new open-source software packages - ChimeraScan and AssemblyLine - designed to detect gene fusion events and novel lncRNAs, respectively. RNA-Seq studies utilizing ChimeraScan led to discoveries of new families of recurrent gene fusions in breast cancers and solitary fibrous tumors. Further, ChimeraScan was one of the key components of the repertoire of computational tools utilized in data analysis for MI-ONCOSEQ, a clinical sequencing initiative to identify potentially informative and actionable mutations in cancer patients’ tumors. AssemblyLine, by contrast, reassembles RNA sequencing data into full-length transcripts ab initio. In head-to-head analyses AssemblyLine compared favorably to existing ab initio approaches and unveiled abundant novel lncRNAs, including antisense and intronic lncRNAs disregarded by previous studies. Moreover, we used AssemblyLine to define the prostate cancer transcriptome from a large patient cohort and discovered myriad lncRNAs, including 121 prostate cancer-associated transcripts (PCATs) that could potentially serve as novel disease markers. Functional studies of two PCATs - PCAT-1 and SChLAP1 - revealed cancer-promoting roles for these lncRNAs. PCAT1, a lncRNA expressed from chromosome 8q24, promotes cell proliferation and represses the tumor suppressor BRCA2. SChLAP1, located in a chromosome 2q31 ‘gene desert’, independently predicts poor patient outcomes, including metastasis and cancer-specific mortality. Mechanistically, SChLAP1 antagonizes the genome-wide localization and regulatory functions of the SWI/SNF chromatin-modifying complex. Collectively, this work demonstrates the utility of ChimeraScan and AssemblyLine as open-source bioinformatics tools. Our applications of ChimeraScan and AssemblyLine led to the discovery of new classes of recurrent and clinically informative gene fusions, and established a prominent role for lncRNAs in coordinating aggressive prostate cancer, respectively. We expect that the methods and findings described herein will establish a precedent for RNA-Seq-based studies in cancer biology and assist the research community at large in making similar discoveries.PHDBioinformaticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/120814/1/mkiyer_1.pd

Network and Algebraic Topology of Influenza Evolution

Evolution is a force that has molded human existence since its divergence from chimpanzees about 5.4 million years ago. In that same amount of time, an influenza virus, which replicates every six hours, would have undergone an equivalent number of generations over only a hundred years. The fast replication times of influenza, coupled with its high mutation rate, make the virus a perfect model to study real-time evolution at a mega-Darwin scale, more than a million times faster than human evolution. While recent developments in high-throughput sequencing provide an optimal opportunity to dissect their genetic evolution, a concurrent growth in computational tools is necessary to analyze the large influx of complex genomic data. In my thesis, I present novel computational methods to examine different aspects of influenza evolution. I first focus on seasonal influenza, particularly the problems that hamper public health initiatives to combat the virus. I introduce two new approaches: 1. The q2-coefficient, a method of quantifying pathogen surveillance, and 2. FluGraph, a technique that employs network topology to track the spread of seasonal influenza around the world. The second chapter of my thesis examines how mutations and reassortment combine to alter the course of influenza evolution towards pandemic formation. I highlight inherent deficiencies in the current phylogenetic paradigm for analyzing evolution and offer a novel methodology based on algebraic topology that comprehensively reconstructs both vertical and horizontal evolutionary events. I apply this method to viruses, with emphasis on influenza, but foresee broader application to cancer cells, bacteria, eukaryotes, and other taxa

Fuzzy Unheritance: A Novel Form Of Somatic Cell Inheritance That Regulates Cell Population Heterogeneity

Multi-level heterogeneity is a characteristic feature of cancer cell populations. However, how a cell population regulates and maintains its cell population heterogeneity is not well understood. Based on conventional theories of genetic inheritance, cell division is precise, where a daughter cell inherits an identical karyotype from its mother cell. Therefore, errors that are generated during cell division occur at low frequencies that take prolonged time periods to accumulate. However, the overwhelming heterogeneity found in unstable cancers is largely inconsistent with current models of genetic inheritance. In order to determine the mechanism of how heterogeneity is regulated, the pattern of inherited traits, including karyotype and growth rate, are compared in cell lines with different degrees of genome instability. Single cell and population-based assays were conducted and illustrate the following: 1) single unstable cells cannot pass a specific karyotype or growth rate and instead pass a heterogeneous array of karyotypes and growth rates; 2) genome heterogeneity is linked to other heterogeneous features of the system, like growth heterogeneity; 3) cells that are outliers dominate cell population dynamics when the cell population is unstable; and 4) the statistical average does not give an accurate portrayal of unstable cell populations. Altogether, this suggests that genome instability leads to genome replacement-mediated macro-cellular evolution that precludes the clonal expansion of a few abnormal cells; and 2) a given degree of heterogeneity can be inherited from a single cell. Because a given degree of heterogeneity is inherited, and the specific variants change between cell passages, this inheritance is termed fuzzy inheritance. According to fuzzy inheritance, rather than passing specific changes, the potential to generate genomic variation is passed. Fuzzy inheritance provides a cell population with the necessary evolvability and explains how heterogeneity is regulated and maintained in normal tissue and in cancer cells

Novel chromatin interactions by structural rearrangements and aberrant enhancer functions drive oncogenic programs in unfavorable neuroblastoma

Neuroblastoma (NB) is an embryonal tumor derived from migrating neural crest cells and can occur within the whole developing sympathetic nervous system. Recently, several comprehensive sequencing studies in NB revealed a comparatively low mutation frequency and a heterogeneous mutation spectrum. Evidence accumulates that epigenetic deregulation play a prominent role in NB. Therefore, there is an urgent need to define entity-specific enhancer and super-enhancer (SE) profiles as regulatory elements control cell identity or oncogenes in a cancer context through cell type-specific gene expression. This will identify critical oncogenic driver genes essential for NB and help to devise a targeted therapy strategy. In the present study, whole genome sequencing (WGS) analysis of a 60 NB tumor cohort identified recurrent rearrangements in close proximity to the TERT gene in up to 24% of high-risk NB cases with poor clinical outcome. ChIP-sequencing analyses revealed that strong enhancers were juxtaposed to the TERT gene by these rearrangements likely driving increased TERT expression and TERT activity in the respective cases. In addition to TERT, discovery of recurrent repositioning of SE elements explained remarkably high expression levels of MYCN, MYC oncogenes in NB cell lines. Integrative analysis of WGS-based rearrangement data and RNA-seq based expression data in a cohort of 111 NB tumors allowed to identify highly upregulated genes in proximity to breakpoints. This approach located several other enhancer-hijacking candidate oncogenes including IGF2BP1 and ATOH1 in NB tumors and cell lines. Subsequent ChIP-seq analysis of the affected tumors and cell lines confirmed that highly active SE regions were juxtaposed to the oncogenes, which likely drives their high expression. Finally, physical interactions of juxtaposed enhancer elements with the oncogene promoters were confirmed by chromatin interaction analyses (4C-seq) in cell lines. Intriguingly, a lineage-specific SE region downstream of HAND2 and upstream of the FBXO8 gene locus was recurrently involved in the above mentioned rearrangements. In a set of 60 NB tumor specimen and 23 NB cell lines, the present study identified groups of tissue-specific SEs and associated target genes based on histone mark H3K27ac ChIP-seq data. In depth bioinformatic analysis of the enhancer data retrieved three gene signatures, associated with previously established clinico-biological association, namely MYCN-amplified, high-risk- and low-risk MYCN non-amplified. Intriguingly, a fourth SE-defined NB subgroup was resolved, as defined by a gene signature highly associated with mesenchymal (Mes) gene ontology terms. This subgroup was reproducibly recovered by an analogue and extended approach based on RNA-seq expression of SEs assigned signature genes and further proved its stability by its consistent presence in NB cell lines and tumors. Importantly, the Mes signature was associated with relapsed NB cases as well as with increased RAS and JUN/FOS signature expression. For the first time, integration of SE and expression data of primary tumors enabled the establishment of an NB entity and NB subgroup-specific regulome resulting in the definition and subsequent functional validation of subgroup-specific core-regulatory networks. Taken together, with the discovery of recurrent rearrangements of SE elements activating the TERT gene, the present study provides initial evidence for “enhancer hijacking” in NB tumors. The identification of further recurrent oncogene rearrangements involving known NB oncogenes MYC and MYCN in cell lines and as well as new candidates IGF2BP1 and ATOH1 in NB tumors demonstrates that recurrence of enhancer hijacking in vivo is not restricted to TERT. Importantly, the present study reveals the first entity and subgroup-specific SE landscape including assigned target genes and downstream core transcription factor networks based on ChIP-seq analyses in a large cohort of tumors. This study identifies several critical NB cancer genes, which may open a therapeutic window for selective inhibition of those dysregulated key genes

Discovery and Characterization of Recurrent Gene Fusions in Prostate Cancer.

Recurrent chromosomal rearrangements have been well characterized in hematologic and mesenchymal malignancies, but not in common carcinomas. A novel bioinformatics algorithm termed Cancer Outlier Profile Analysis (COPA) was developed to analyze DNA microarray data for genes markedly over-expressed (“outliers”) in a subset of cases. COPA identified the ETS family members ERG and ETV1 as high-ranking outliers in multiple prostate cancer profiling studies. In cases with outlier expression of ERG or ETV1, recurrent gene fusions of the 5’ untranslated region of the prostate-specific, androgen-induced gene TMPRSS2 to the respective ETS family member were identified. In vitro studies in cancer cell lines demonstrated that androgen-responsive promoter elements of TMPRSS2 mediate the aberrant ETS family member over-expression. Subsequent interrogation of all ETS family members in prostate cancer profiling studies identified outlier expression of ETV4 in two of 98 cases. In one such case, ETV4 over-expression was confirmed and a fusion of the TMPRSS2 and ETV4 loci was identified. A large scale profiling and integrated molecular concepts analysis demonstrated that ETS rearrangement-positive and -negative tumors have distinct transcriptional programs, with loss at 6q21 as a possible defining genetic event in ETS negative prostate cancers. While TMPRSS2:ERG fusions are predominant, fewer TMPRSS2:ETV1 cases were identified than would be expected based on the frequency of ETV1 outlier expression. Through characterizing additional ETV1 outlier cases, novel 5’ fusion partners defining distinct functional classes of ETS gene rearrangements were identified. These include fusions involving androgen-stimulated, androgen-repressed and androgen-insensitive 5’ partners. As the commonality of ETS rearrangements is aberrant over-expression, in vitro and in vivo recapitulation demonstrated that ETV1 or ERG over-expression in benign prostate cells and the mouse prostate confers neoplastic phenotypes. Together, this work suggests a pathogenetically important role for recurrent chromosomal rearrangements in a common epithelial tumor and has important implications in the molecular diagnosis and treatment of prostate cancer. Deregulation of ETS family member expression through gene fusions appears to be a generalized mechanism for prostate cancer development in the majority of cases. Additionally, other common epithelial tumors may be driven by uncharacterized gene rearrangements.Ph.D.Molecular & Cellular PathologyUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/57601/2/tomlinss_1.pd

Novel Oncogenic Drivers in Pediatric Gliomagenesis

Pediatric high-grade gliomas (pHGGs), with a two-year survival rate of less than 20%, are some of the most aggressive human cancers. This dissertation begins with our analysis of 127 pHGGs, including brainstem (BS) and non-brainstem (NBS) tumors, from 118 patients using next-generation sequencing technologies. Nearly one-third of BS-HGGs, also known as diffuse intrinsic pontine gliomas (DIPGs), harbored somatic heterozygous missense mutations in ACVR1, coding for a receptor serine-threonine kinase involved in bone morphogenetic protein (BMP) signaling. These alterations led to gain-of-function as evidenced by increased phosphorylation of downstream targets in primary astrocytes and zebrafish embryo ventralization. Whole-genome sequencing and RNASeq revealed that nearly half of our cohort contained structural variants. We identified recurrent gene fusions preserving the kinase domain of the neurotrophin family of receptor tyrosine kinases (NTRK) including three novel fusions and two fusions previously described in other tumor types. NTRK fusion genes were identified in 40% of infant (\u3c3 years of age) NBS-HGGs, and 7% of pHGG overall. We also found that infants have significantly reduced mutation burdens when compared to pHGGs in older children, suggesting a small number of oncogenic mutations are required in infant tumors. These findings, coupled with the observation that infants have a better prognosis than non-infants, make infant NBS tumors a distinct subgroup of pHGG. NTRK gene fusions also occur in pediatric low-grade glioma (pLGG) and adult glioblastoma but are not as enriched as they are in infant NBS-HGG, and adult glioblastoma and non-infant pHGGs exhibit higher mutation rates than infant tumors. NTRK fusion genes are therefore gliomagenic drivers throughout various development settings; yet it appears as if gliomas driven by the same oncogenic lesion can vary in tumor phenotype as a function of contextual differences. With this in mind, we used genetically engineered mice with a NTRK gene fusion knock-in allele to generate HGG in vivo. Given that tumor is evident by early postnatal life (P5), this is, to our knowledge, the first report of a bona fide spontaneous pHGG model. The second part of this dissertation is the characterization of these tumors

Genomic basis for RNA alterations in cancer

Transcript alterations often result from somatic changes in cancer genomes. Various forms of RNA alterations have been described in cancer, including overexpression, altered splicing and gene fusions; however, it is difficult to attribute these to underlying genomic changes owing to heterogeneity among patients and tumour types, and the relatively small cohorts of patients for whom samples have been analysed by both transcriptome and whole-genome sequencing. Here we present, to our knowledge, the most comprehensive catalogue of cancer-associated gene alterations to date, obtained by characterizing tumour transcriptomes from 1,188 donors of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). Using matched whole-genome sequencing data, we associated several categories of RNA alterations with germline and somatic DNA alterations, and identified probable genetic mechanisms. Somatic copy-number alterations were the major drivers of variations in total gene and allele-specific expression. We identified 649 associations of somatic single-nucleotide variants with gene expression in cis, of which 68.4% involved associations with flanking non-coding regions of the gene. We found 1,900 splicing alterations associated with somatic mutations, including the formation of exons within introns in proximity to Alu elements. In addition, 82% of gene fusions were associated with structural variants, including 75 of a new class, termed 'bridged' fusions, in which a third genomic location bridges two genes. We observed transcriptomic alteration signatures that differ between cancer types and have associations with variations in DNA mutational signatures. This compendium of RNA alterations in the genomic context provides a rich resource for identifying genes and mechanisms that are functionally implicated in cancer