Biology subjects

Marra, M. A.

Publications and source records attributed to Marra, M. A..

16 recordsLinked to original sources

bioRxiv2026

Allele-specific chromatin modifications of HPV-associated extrachromosomal DNAs in cervical cancer

Cervical cancer, a human papillomavirus (HPV) driven malignancy, is the fourth deadliest cancer in females. Approximately 25% of primary cervical cancers contain circular structures called extrachromosomal DNAs (ecDNAs), which can be entirely composed of human DNA (human-only ecDNAs) or a combination of HPV and human DNA sequences (HPV-human hybrid ecDNAs). Human-only ecDNAs harbour cancer-driving oncogenes, but epigenetic differences between human-only and HPV-human hybrid ecDNAs are unexplored. Here we report that 30% of cervical cancers contained at least one ecDNA. HPV-human hybrid ecDNAs contained more active enhancers and promoters than human-only ecDNAs and invariably contained the HPV oncogenes E6 and E7. These ecDNAs also contained an allelic hypomethylation region associated with putative human promoters, as well as enrichments for motifs associated with recombination hotspots. By leveraging long-read WGS phasing data to separate ChIP-seq data into alleles, we revealed allele-specific peaks in enhancers and promoters on ecDNAs, of which HPV-human hybrid ecDNAs contained a higher density. Overall, we found HPV-human hybrid and human-only ecDNAs differed in their regulation, often at an allele-specific level. Our study more firmly establishes the importance of epigenome disruption in cervical cancer and how structural variation, particularly surrounding HPV integration sites, may shape the surrounding regulatory architecture.

genomics↗

bioRxiv2026

Recovering biological structure in sparse single-cell proteomics with GIRAFI

Single-cell proteomics (SCP) based on liquid-chromatography mass-spectrometry resolves protein-level cellular heterogeneity, but interpretation remains limited by detection-linked sparsity. SCP profiles continuous, peptide-derived intensities and has lower throughput than single-cell RNA sequencing, making denoising methods for large-scale, count-based transcriptomics difficult to apply. Here we present GIRAFI, a graph-informed statistical learning framework that imputes missing values and reveals reproducible cell states by constraining inference to dataset-aware, prior-knowledge-informed protein neighborhoods. We evaluated GIRAFI across SCP datasets spanning diverse biological/technical contexts. In masking-based recovery experiments and cell-type-specific protein-protein interaction inference, GIRAFI outperformed existing methods, and matched bulk proteomics comparisons corroborated recovery accuracy and ablations supported the graph-informed design. Beyond reduced replicate- and source-associated technical structure, GIRAFI recovered ground-truth cell-type annotations, improved cell state-resolved pathway analysis, and enabled trajectory inference consistent with known time courses. These results establish graph-constrained imputation as an effective strategy for improving SCP robustness, biological structure, interpretation, and cross-dataset comparability.

bioinformatics↗

bioRxiv2023

Genomic structures and regulation patterns at HPV integration sites in cervical cancer

Human papillomavirus (HPV) integration has been implicated in transforming HPV infection into cancer, but its genomic consequences have been difficult to study using short-read technologies. To resolve the dysregulation associated with HPV integration, we performed long-read sequencing on 63 cervical cancer genomes. We identified six categories of integration events based on HPV-human genomic structures. Of all HPV integrants, defined as two HPV-human breakpoints bridged by an HPV sequence, 24% contained variable copies of HPV between the breakpoints, a phenomenon we termed heterologous integration. Analysis of DNA methylation within and in proximity to the HPV genome at individual integration events revealed relationships between methylation status of the integrant and its orientation and structure. Dysregulation of the human epigenome and neighboring gene expression in cis with the HPV-integrated allele was observed over megabase-ranges of the genome. By elucidating the structural, epigenetic, and allele-specific impacts of HPV integration, we provide insight into the role of integrated HPV in cervical cancer.

genomics↗

bioRxiv2022

GRETA: an R package for mapping in silico genetic interaction and essentiality networks

SummaryMapping genetic interaction and essentiality networks in human cell lines have been used to identify vulnerabilities of cells carrying specific genetic alterations and to associate novel functions to genes, respectively. In vitro and in vivo genetic screens to decipher these networks are resource-intensive, limiting the throughput of samples that can be analyzed. In this application note, we provide an R package we call Genetic inteRaction and EssentialiTy mApper (GRETA). GRETA is an accessible tool for in silico genetic interaction screens and essentiality network analyses using publicly available data, requiring only basic R programming knowledge. Availability and implementationThe R package, GRETA, is licensed under GNU General Public License v3.0 and freely available at https://github.com/ytakemon/GRETA and https://doi.org/10.5281/zenodo.6940757, with documentation and tutorial. A Singularity container is also available at https://cloud.sylabs.io/library/ytakemon/greta/greta. Contactmmarra@bcgsc.ca Supplemental informationSupplemental materials are available at Bioinformatics online. Issue sectionSystems biology

bioinformatics↗

bioRxiv2021

Ploidetect enables pan-cancer analysis of the causes and impacts of chromosomal instability

Cancers routinely exhibit chromosomal instability that results in copy number variants (CNVs), namely changes in the abundance of genomic material. Unfortunately, the detection of these variants in cancer genomes is difficult. We present Ploidetect, a software package that effectively identifies CNVs within whole-genome sequenced tumors. Ploidetect utilizes a coarse-to-fine segmentation approach which yields highly contiguous segments while allowing for focal CNVs to be detected with high sensitivity. We benchmark Ploidetect against popular CNV tools using synthetic data, cell line data, and real-world metastatic tumor data, and find an improvement in sensitivity and accuracy while maintaining low levels of oversegmentation. We show that the improved CNV sensitivity enables Ploidetect to recover recurrent homozygous deletions and genes associated with chromosomal instability in a multi-cancer cohort of 687 patients. Using highly contiguous CNV calls afforded by Ploidetect, we also demonstrate the use of segment N50 as a novel metric for the measurement of chromosomal instability within tumor biopsies. We propose that increasingly accurate determination of CNVs is critical for their productive study in cancer, and our work demonstrates advances made possible by progress in this regard.

cancer biology↗

bioRxiv2021

Genome-Wide Detection of Imprinted Differentially Methylated Regions Using Nanopore Sequencing

Imprinting is a critical part of normal embryonic development in mammals, controlled by defined parent-of-origin (PofO) differentially methylated regions (DMRs) known as imprinting control regions. As we and others have shown, direct nanopore sequencing of DNA provides a mean to detect allelic methylation and to overcome the drawbacks of methylation array and short-read technologies. Here we leverage publicly-available nanopore sequence data for 12 standard B-lymphocyte cell lines to present the first genome-wide mapping of imprinted intervals in humans using this technology. We were able to phase 95% of the human methylome and detect 94% of the well-characterized imprinted DMRs. In addition, we found 28 novel imprinted DMRs (12 germline and 16 somatic), which we confirmed using whole-genome bisulfite sequencing (WGBS) data. Analysis of WGBS data in mus musculus, rhesus macaque, and chimpanzee suggested that 12 of these are conserved. We also detected subtle parental methylation bias spanning several kilobases at seven known imprinted clusters. These results expand the current state of knowledge of imprinting, with potential applications in the clinic. We have also demonstrated that nanopore long reads, can reveal imprinting using only parent-offspring trios, as opposed to the large multi - generational pedigrees that have previously been required.

genomics↗

bioRxiv2021

Single-cell landscapes of primary glioblastomas and matched organoids and cell lines reveal variable retention of inter- and intra-tumor heterogeneity

Glioblastomas (GBMs) are aggressive primary malignant brain tumors characterized by extensive levels of inter- and intra-tumor genetic and phenotypic heterogeneity. Patient-derived organoids (PDOs) have recently emerged as useful models to study such heterogeneity. Here, we present bulk exome as well as single-cell genome and transcriptome profiles of primary IDH wild type GBMs from ten patients, including two recurrent tumors, as well as PDOs and brain tumor-initiating cell (BTIC) lines derived from these patients. We find that PDOs are genetically similar to and variably retain gene expression characteristics of their parent tumors. At the phenotypic level, PDOs appear to exhibit similar levels of transcriptional heterogeneity as their parent tumors, whereas BTIC lines tend to be enriched for cells in a more uniform transcriptional state. The datasets introduced here will provide a valuable resource to help guide experiments using GBM-derived organoids, especially in the context of studying cellular heterogeneity.

cancer biology↗

bioRxiv2021

A Platform for Oncogenomic Reporting and Interpretation

Manual interpretation of variants remains rate limiting in precision oncology. The increasing scale and complexity of molecular data generated from comprehensive sequencing of cancer samples requires advanced interpretative platforms as precision oncology expands beyond individual patients to entire populations. To address this unmet need, we created the Platform for Oncogenomic Reporting and Interpretation (PORI), comprising an analytic framework created to facilitate the interpretation and reporting of somatic variants in cancer. PORI is unique in its integration of reporting and graph knowledge base tools combined with support for manual curation at the reporting stage. PORI represents one of the first open-source platform alternatives to commercial reporting solutions suitable for comprehensive genomic data sets in precision oncology. We demonstrate the utility of PORI by matching 9,961 TCGA tumours to the graph knowledge base, revealing that 88.2% have at least one potentially targetable alteration, and making available reports describing select individual samples.

bioinformatics↗

bioRxiv2019

Coding and regulatory drivers of mantle cell lymphoma identified through exome and genome sequencing

Mantle cell lymphoma (MCL) is an uncommon B-cell non-Hodgkin lymphoma (NHL) that is incurable with standard therapies. The genetic drivers of this cancer have not been firmly established and the features known to contribute to differences in clinical course remain limited. To extend our understanding of the biological pathways involved in this malignancy, we performed a large-scale genomic analysis of MCL using data from 51 exomes alongside previously published exome cohorts. To confirm our findings, we re-sequenced the genes identified in the exome cohort in 212 MCL tumors, each having clinical follow-up data. We confirmed the prognostic association of TP53 and NOTCH1 mutations and further nominate two additional genes, EWSR1 and MEF2B, whose mutation respectively associated with poor and good outcome. Our sequencing revealed novel recurrent mutations including a unique missense hot spot in MEF2B and a pattern of non-coding mutations surrounding a single exon of the HNRNPH1 gene. We sequenced the whole genomes of 34 MCLs to confirm the focal nature of HNRNPH1 mutations. Using RNA-seq data from 110 of these cases, we identified a functional role for recurrent non-coding HNRNPH1 mutations in disrupting an auto-regulatory feedback mechanism. Overall, we identified three novel MCL-related genes with roles in RNA trafficking or splicing, namely DAZAP1, EWSR1, and HNRNPH1. Taken together, these data strongly implicate a role for aberrant regulation of splicing in MCL pathobiology.\n\nKey pointsO_LIRNA-binding proteins with roles in regulating alternative splicing, DAZAP1, EWSR1, HNRNPH1, are frequently mutated in MCL\nC_LIO_LIThe majority of recurrent somatic HNRNPH1 mutations are intronic and HNRNPH1 exhibits self-regulation through alternative splicing\nC_LI

genomics↗

bioRxiv2019

Loss of CIC promotes mitotic dysregulation and chromosome segregation defects

CIC encodes a transcriptional repressor and MAPK signalling effector that is inactivated by loss-of-function mutations in several cancer types, consistent with a role as a tumour suppressor. Here, we used bioinformatic, genomic, and proteomic approaches to investigate CICs interaction networks. We observed both previously identified and novel candidate interactions between CIC and SWI/SNF complex members, and also observed novel interactions between CIC and cell cycle regulators and RNA processing factors. We found that CIC loss is associated with an increased frequency of mitotic defects in human cell lines and an in vivo mouse model and with dysregulated expression of mitotic regulators. We also observed aberrant splicing in CIC-deficient cell lines predominantly at 3 and 5 untranslated regions of genes, including genes involved in MAPK signalling, DNA repair, and cell cycle regulation. Our study thus characterises the complexity of CICs functional network and describes the effect of its loss on cell cycle regulation, mitotic integrity, and transcriptional splicing, thereby expanding our understanding of CICs potential roles in cancers. In addition, our work exemplifies how multi-omic, network-based analyses can be used to uncover novel insights into the interconnected functions of pleiotropic genes/proteins across cellular contexts. Simple summaryCapicua (CIC) is a gene that is frequently mutated in several cancer types, including stomach cancers and certain subtypes of brain tumours and sarcomas. CIC, the protein encoded by the CIC gene, has been shown to play a multitude of roles in both normal and cancer cell functions; however, most studies exploring these roles focus on a single aspect of CIC function and may therefore overlook complex interconnected activities in which CIC is involved. In this study, we have used multiple complementary approaches to obtain a broader view of CICs complex functional networks. We observed novel interactions (genetic or physical) between CIC and genes/proteins involved in various aspects of cellular function, including regulation of cell division and processing of RNA molecules. Altogether, our work characterises the complexity of CICs functional network and expands our understanding of its potential roles in cancer.

cancer biology↗

bioRxiv2018

High-resolution structural genomics reveals new therapeutic vulnerabilities in glioblastoma

We investigated the role of 3D genome architecture in instructing functional properties of glioblastoma stem cells (GSCs) by generating the highest-resolution 3D genome maps to-date for this cancer. Integration of DNA contact maps with chromatin and transcriptional profiles identified specific mechanisms of gene regulation, including individual physical interactions between regulatory regions and their target genes. Residing in structurally conserved regions in GSCs was CD276, a gene known to play a role in immuno-modulation. We show that, unexpectedly, CD276 is part of a stemness network in GSCs and can be targeted with an antibody-drug conjugate to curb self-renewal, a key stemness property. Our results demonstrate that integrated structural genomics datasets can be employed to rationally identify therapeutic vulnerabilities in self-renewing cells.\n\nSIGNIFICANCEIn adult GBM, GSCs act as therapy-resistant reservoirs to nucleate tumor recurrence. New therapeutic approaches that target these cell populations hold the potential of significantly improving patient care and overall prognosis for this always-lethal cancer. Our work describes new links between 3D genome architecture and stemness properties in GSCs. In particular, through integration of multiple genomics and structural genomics datasets, we found an unexpected connection between immune-related genes and self-renewal programs in GBM. Among these, we show that targeting CD276 with knockdown strategies or specific antibody-drug conjugates achieve suppression of self-renewal. Strategies to target CD276+ cells are currently in clinical trials for solid tumors. Our results indicate that CD276-targeting agents could be deployed in GBM to specifically target GSC populations.\n\nHIGHLIGHTSO_LIWe generated high (sub-5 kb) resolution Hi-C maps for stem-like cells from GBM patients.\nC_LIO_LIIntegration of Hi-C and genomics datasets dissects mechanisms of gene regulation.\nC_LIO_LI3D genomes poise immune-related genes, including CD276, for expression.\nC_LIO_LITargeting CD276 curbs self-renewal properties of GBM cells.\nC_LI

cancer biology↗

bioRxiv2018

Subclonal architecture, evolutionary trajectories and patterns of inheritance of germline variants in pediatric glioblastoma

Pediatric glioblastoma (pGBM) is a lethal cancer with no effective therapies. Intratumoral genetic heterogeneity and mode of tumor evolution have not been systematically addressed for this cancer. Whole-genome sequencing of germline-tumor pairs showed that pGBM is characterized by intratumoral genetic heterogeneity and consequent subclonal architecture. We found that pGBM undergoes extreme evolutionary trajectories, with primary and recurrent tumors having different subclonal compositions. Analysis of variant allele frequencies supported a model of tumor growth involving slow-cycling cancer stem cells that give rise to fast-proliferating progenitor-like cells and to non-dividing cells. pGBM patients germlines had subclonal structural variants, some of which underwent dynamic frequency fluctuations during tumor evolution. By sequencing germlines of mother-father-patient trios, we found that inheritance of deleterious germline variants from healthy parents cooperate with de novo germline and somatic events to the tumorigenic process. Our studies therefore challenge the current notion that pGBM is a relatively homogeneous molecular entity.

cancer biology↗

bioRxiv2018

Resource: Scalable whole genome sequencing of 40,000 single cells identifies stochastic aneuploidies, genome replication states and clonal repertoires

Essential features of cancer tissue cellular heterogeneity such as negatively selected genome topologies, sub-clonal mutation patterns and genome replication states can only effectively be studied by sequencing single-cell genomes at scale and high fidelity. Using an amplification-free single-cell genome sequencing approach implemented on commodity hardware (DLP+) coupled with a cloud-based computational platform, we define a resource of 40,000 single-cell genomes characterized by their genome states, across a wide range of tissue types and conditions. We show that shallow sequencing across thousands of genomes permits reconstruction of clonal genomes to single nucleotide resolution through aggregation analysis of cells sharing higher order genome structure. From large-scale population analysis over thousands of cells, we identify rare cells exhibiting mitotic mis-segregation of whole chromosomes. We observe that tissue derived scWGS libraries exhibit lower rates of whole chromosome anueploidy than cell lines, and loss of p53 results in a shift in event type, but not overall prevalence in breast epithelium. Finally, we demonstrate that the replication states of genomes can be identified, allowing the number and proportion of replicating cells, as well as the chromosomal pattern of replication to be unambiguously identified in single-cell genome sequencing experiments. The combined annotated resource and approach provide a re-implementable large scale platform for studying lineages and tissue heterogeneity.

genomics↗

bioRxiv2018

Childhood cerebellar tumors mirror conserved fetal transcriptional programs

The study of the origin and development of cerebellar tumours has been hampered by the complexity and heterogeneity of cerebellar cells that change over the course of development. We used single-cell transcriptomics to study >60,000 cells from the developing murine cerebellum, and show that different molecular subgroups of childhood cerebellar tumors mirror the transcription of cells from distinct, temporally restricted cerebellar lineages. Sonic Hedgehog medulloblastoma transcriptionally mirrors the granule cell hierarchy as expected, whereas Group 3 medulloblastoma resemble Nestin+ve stem cells, Group 4 medulloblastomas resemble unipolar brush cells, and PFA/PFB ependymoma and cerebellar pilocytic astrocytoma resemble the prenatal gliogenic progenitor cells. Furthermore, single-cell transcriptomics of human childhood cerebellar tumors demonstrates that many bulk tumors contain a mixed population of cells with divergent differentiation. Our data highlight cerebellar tumors as a disorder of early brain development, and provide a proximate explanation for the peak incidence of cerebellar tumors in early childhood.

cancer biology↗

bioRxiv2017

Genome-wide discovery of somatic coding and regulatory variants in Diffuse Large B-cell Lymphoma

Diffuse large B-cell lymphoma (DLBCL) is an aggressive cancer originating from mature B-cells. Many known driver mutations are over-represented in one of its two molecular subgroups, knowledge of which has aided in the development of therapeutics that target these features. The heterogeneity of DLBCL determined through prior genomic analysis suggests an incomplete understanding of its molecular aetiology, with a limited diversity of genetic events having thus far been attributed to the activated B-cell (ABC) subgroup. Through an integrative genomic analysis we uncovered genes and non-coding loci that are commonly mutated in DLBCL including putative regulatory sequences. We implicate recurrent mutations in the 3UTR of NFKBIZ as a novel mechanism of oncogene deregulation and found small amplifications associated with over-expression of FC-{gamma} receptor genes. These results inform on mechanisms of NF-{kappa}B pathway activation in ABC DLBCL and may reveal a high-risk population of patients that might not benefit from standard therapeutics.

genomics↗

bioRxiv2017

Comprehensive characterization of pediatric acute myeloid leukemia reveals novel molecular features and age-specific interactions

We present the molecular landscape of pediatric acute myeloid leukemia (AML), characterizing nearly 1,000 participants in Childrens Oncology Group (COG) AML trials. The COG/NCI TARGET AML initiative assessed cases by whole-genome, targeted DNA, mRNA, miRNA sequencing and CpG methylation profiling. Validated DNA variants revealed diverse, infrequent mutations with fewer than 40 genes mutated in >2% of cases. In contrast, somatic structural variants, including novel gene fusions and focal MBNL1, ZEB2, and ELF1 deletions, were disproportionately prevalent in young as compared to adult patients. Conversely, DNMT3A and TP53 mutations, common in adults, are conspicuously absent from virtually all pediatric cases. Novel GATA2, FLT3, and CBL mutations, recurrent MYC-ITD, NRAS, KRAS, and WT1 mutations are frequent in pediatric AML. Deletions, mutations, and promoter DNA hypermethylation convergently impact Wnt signaling, Polycomb repression, innate immune cell interactions, and a cluster of zinc finger genes associated with KMT2A rearrangements. These results highlight the need for, and facilitate the development of age-tailored targeted therapies for the treatment of pediatric AML.

cancer biology↗