The molecular architecture of Mamestra configurata Petitrophic Matrix

The peritrophic matrix (PM) lines the insect midgut and is composed of chitin and protein. It is required for organization of digestion and for protection of epithelial cells from mechanical damage, pathogens, and toxins. The PM of Mamestra configurata (Lepidoptera: Noctuidae), bertha armyworm, a serious pest of cruciferous oilseed rape, was studied. The multilayered PM is delaminated from the anterior midgut epithelium during molting Phase II by periodic pulses and degraded during the molting Phase I stage. These events are controlled by chitin synthase-B, and chitinolytic enzymes, such as chitinase and β-N-acetylglucosaminidase. Eighty-two PM proteins were identified and classified as: i) peritrophins, ii) enzymes and iii) other proteins. Peritrophins were further classified as simple, binary, complex and repetitive according to their structural organization and phylogenetic analysis of peritrophin A domains. The expression of most genes encoding PM proteins was specific to the midgut and independent of larval feeding status, developmental stage, or PM formation. This study includes the first report of chitin deacetylase (CDA) activity in the insect midgut suggesting that the PM may contain chitosan. Digestive enzymes, such as insect intestinal lipases (IILs) and serine proteases were also associated with the PM. The IIL genes differed in their expression during larval development; however, serine protease genes were expressed continuously and serine protease activity was present in the midgut of feeding and nonfeeding stages. M. configurata IIM4, a complex peritrophin, was susceptible to degradation by Mamestra configurata nucleopolyhedrovirus-A challenge, as the first evidence of IIM degradation by an alphabaculovirus enhancin. M. configurata IIM2, a binary peritrophin, was unaffected by baculoviral challenge and such resistance of an IIM has not been reported previously. The current study is also the first demonstration of silencing by RNA interference (RNAi) of any gene encoding a PM protein, in this case M. configurata CDA1 (McCDA1) and McPM1. In addition, both in vitro and per os feeding experiments revealed McCDA1 silencing starting at 24 or 36 hours posttreatment, as one of the most successful demonstrations of RNAi in a lepidopteran

Integrative Analysis of Omics Datasets

Cancer is a disease of aberrant cell proliferation and tumour growth arising from the perturbation of the epigenetically defined, regulated and maintained cell identity by genetic mutations. It is a leading cause of death worldwide and most cancer types remain incurable. Omics technologies are quantitative analytical assays that allow high-quality and high-throughput measurements of different aspects of cellular regulation including genomics, transcriptomics, epigenomics, proteomics and metabolomics. These high-throughput technologies transformed the way cancer research is done, leading to tremendous advances in our understanding of cancer biology and modern targeted therapies. Integrative analysis of multi-omics datasets in cancer research requires use of dedicated algorithms, data analysis and visualization tools. These are developed and applied in interdisciplinary teams of scientists and clinicians working on collaborative projects. Both the technical complexities of data analysis and their integration, and the efficient independent exploration of the observations by all project partners are contemporary research challenges. This dissertation presents results addressing a broad spectrum of these questions. Chapter 1, Replacing the CNS-PNET Superentity with Four Novel Molecularly Defined Entities Driven by Structural Variants: Central nervous system primitive neuroectodermal tumours (CNS-PNETs) were a heterogeneous family of paediatric brain tumours with no histopathological markers, challenging diagnosis and poor prognosis. My work as a computational biologist contributed to the comprehensive description of this entity. In this study, we applied an integrative omics data analysis of methylomes, transcriptomes and genomes revealing that CNS-PNETs are a combination of a large group of misdiagnosed cases from other entities and four novel molecularly defined entities. I showed that these novel entities are driven by distinct and recurrent molecular drivers altered by different mechanisms of structural variants: the FOXR2 oncogene and MN1, CIC and BCOR tumour suppressors. Our results contributed to the elimination of CNS-PNETs as an officially recognized cancer entity and the recognition of four novel paediatric brain tumour entities in the World Health Organization classification of brain tumours. Chapter 2, SOPHIA, Structural Rearrangement Detection Based on Supplementary Alignments and a Population Background Model: Building on my work on structural variation in our study of CNS-PNETs, I developed the SOPHIA algorithm for detecting SVs in cancer genomes based on a large population background database and a corresponding bioinformatics tool written allowing fast detection of SVs from short read cancer genome sequencing datasets. SOPHIA later became the standard tool for structural variant detection in the DKFZ’s cancer genome analysis workflow. Chapter 3, EPISTEME, an Interactive and Integrative Platform for Analysing, Interpreting and Sharing Multi-Omics Data: During the development of SOPHIA and my research in projects analysing and interpreting structural variant data, I developed experiences analysing structural variant data detected by SOPHIA, integrating them with different omics layers such as gene expressions, interpreting, visualizing and sharing them with collaborators who were not computational scientists. Based on these experiences and using modern tools of interactive data visualization, I developed an interactive platform for integrative omics data analysis and visualization named EPISTEME, with the aim of facilitating omics data analysis by scientists with conceptual knowledge of cancer omics but no programming skills. EPISTEME is a comprehensive tool integrating genome, transcriptome, methylome and proteome data with clinical metadata in a user-friendly web-based system with in-browser statistical analyses and publication-quality vector graphics output. Chapter 4, SOPHIA-EPISTEME integration in DKFZ Cancer Genomics Projects Reveals Novel Disease Subtypes and Insights Across Cancer Types: With the integration of SOPHIA and EPISTEME in an integrative omics data analysis setting, my work identified novel oncogenes activated by enhancer hijacking and revealed novel molecularly defined subtypes in refractory multiple myeloma (MYCN enhancer hijacking via immunoglobulin rearrangements as a MYC replacement), adult acute myeloid leukaemia (MNX1 activation via enhancer hijacking putatively acting as a differentiation block mechanism) and paediatric neuroblastoma (ATOH1 activation via enhancer hijacking putatively acting as a MYCN replacement) in projects supported by the DKFZ Heidelberg Center for Personalized Oncology (DKFZ-HIPO) and the German Society for Paediatric Oncology and Haematology (GPOH) cancer research programmes

Comprehensive genomic analysis of refractory multiple myeloma reveals a complex mutational landscape associated with drug resistance and novel therapeutic vulnerabilities

The outcomes of patients with multiple myeloma (MM) refractory to immunomodulatory agents (IMiDs) and proteasome inhibitors (PIs) remain poor. In this study, we performed whole genome and transcriptome sequencing of 39 heavily pretreated relapsed/refractory MM (RRMM) patients to identify mechanisms of resistance and potential therapeutic targets. We observed a high mutational load and indications of increased genomic instability. Recurrently mutated genes in RRMM, which had not been previously reported or only observed at a lower frequency in newly diagnosed MM, included NRAS, BRAF, TP53, SLC4A7, MLLT4, EWSR1, HCFC2, and COPS3. We found multiple genomic regions with bi-allelic events affecting tumor suppressor genes and demonstrated a significant adverse impact of bi-allelic TP53 alterations on survival. With regard to potentially resistance conferring mutations, recurrently mutated gene networks included genes with relevance for PI and IMiD activity; the latter particularly affecting members of the Cereblon and the COP9 signalosome complex. We observed a major impact of signatures associated with exposure to melphalan or impaired DNA double-strand break homologous recombination repair in RRMM. The latter coincided with mutations in genes associated with PARP inhibitor sensitivity in 49% of RRMM patients; a finding with potential therapeutic implications. In conclusion, this comprehensive genomic characterization revealed a complex mutational and structural landscape in RRMM and highlights potential implications for therapeutic strategies

T‐cell prolymphocytic leukemia is associated with deregulation of oncogenic microRNAs on transcriptional and epigenetic level

Deregulation of micro(mi)-RNAs is a common mechanism in tumorigenesis. We investigated the expression of 2083 miRNAs in T-cell prolymphocytic leukemia (T-PLL). Compared to physiologic CD4+ and CD8+ T-cell subsets, 111 miRNAs were differentially expressed in T-PLL. Of these, 33 belonged to miRNA gene clusters linked to cancer. Genomic variants affecting miRNAs were infrequent with the notable exception of copy number aberrations. Remarkably, we found strong upregulation of the miR-200c/-141 cluster in T-PLL to be associated with DNA hypomethylation and active promoter marks. Our findings suggest that copy number aberrations and epigenetic changes could contribute to miRNA deregulation in T-PLL

RNA interference in Lepidoptera: an overview of successful and unsuccessful studies and implications for experimental design

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Focal structural variants revealed by whole genome sequencing disrupt the histone demethylase KDM4C in B cell lymphomas

Histone methylation-modifiers, like EZH2 and KMT2D, are recurrently altered in B-cell lymphomas. To comprehensively describe the landscape of alterations affecting genes encoding histone methylation-modifiers in lymphomagenesis we investigated whole genome and transcriptome data of 186 mature B-cell lymphomas sequenced in the ICGC MMML-Seq project. Besides confirming common alterations of KMT2D (47% of cases), EZH2 (17%), SETD1B (5%), PRDM9 (4%), KMT2C (4%), and SETD2 (4%) also identified by prior exome or RNAseq studies, we here unravel KDM4C in chromosome 9p24, encoding a histone demethylase, to be recurrently altered. Focal structural variation was the main mechanism of KDM4C alterations, which was independent from 9p24 amplification. We identified KDM4C alterations also in lymphoma cell lines including a focal homozygous deletion in a classical Hodgkin lymphoma cell line. By integrating RNAseq and genome sequencing data we predict KDM4C structural variants to result in loss-of-function. By functional reconstitution studies in cell lines, we provide evidence that KDM4C can act as tumor suppressor. Thus, we show that identification of structural variants in whole genome sequencing data adds to the comprehensive description of the mutational landscape of lymphomas and, moreover, establish KDM4C as putative tumor suppressive gene recurrently altered in subsets of B-cell derived lymphomas

The genomic and transcriptional landscape of primary central nervous system lymphoma

Primary lymphomas of the central nervous system (PCNSL) are mainly diffuse large B-cell lymphomas (DLBCLs) confined to the central nervous system (CNS). Molecular drivers of PCNSL have not been fully elucidated. Here, we profile and compare the whole-genome and transcriptome landscape of 51 CNS lymphomas (CNSL) to 39 follicular lymphoma and 36 DLBCL cases outside the CNS. We find recurrent mutations in JAK-STAT, NFkB, and B-cell receptor signaling pathways, including hallmark mutations in MYD88 L265P (67%) and CD79B (63%), and CDKN2A deletions (83%). PCNSLs exhibit significantly more focal deletions of HLA-D (6p21) locus as a potential mechanism of immune evasion. Mutational signatures correlating with DNA replication and mitosis are significantly enriched in PCNSL. TERT gene expression is significantly higher in PCNSL compared to activated B-cell (ABC)-DLBCL. Transcriptome analysis clearly distinguishes PCNSL and systemic DLBCL into distinct molecular subtypes. Epstein-Barr virus (EBV)+ CNSL cases lack recurrent mutational hotspots apart from IG and HLA-DRB loci. We show that PCNSL can be clearly distinguished from DLBCL, having distinct expression profiles, IG expression and translocation patterns, as well as specific combinations of genetic alterations