Biology subjects

Moore, R.

Publications and source records attributed to Moore, R..

7 recordsLinked to original sources

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

A linear mixed model approach to study multivariate gene-environment interactions

Different environmental factors, including diet, physical activity, or external conditions can contribute to genotype-environment interactions (GxE). Although high-dimensional environmental data are increasingly available, and multiple environments have been implicated with GxE at the same loci, multi-environment tests for GxE are not established. Such joint analyses can increase power to detect GxE and improve the interpretation of these effects. Here, we propose the structured linear mixed model (StructLMM), a computationally efficient method to test for and characterize loci that interact with multiple environments. After validating our model using simulations, we apply StructLMM to body mass index in UK Biobank, where our method detects previously known and novel GxE signals. Finally, in an application to a large blood eQTL dataset, we demonstrate that StructLMM can be used to study interactions with hundreds of environmental variables.

genetics↗

bioRxiv2017

The interface of malignant and immunologic clonal dynamics in high-grade serous ovarian cancer

High-grade serous ovarian cancer exhibits extensive intratumoral heterogeneity coupled with widespread intraperitoneal disease. Despite this, metastatic spread of tumor clones is non-random, implying the existence of local microenvironmental factors that shape tumor progression. We interrogated the molecular interface between tumor-infiltrating lymphocytes (TIL) and cancer cells in 143 samples from 21 patients using whole-genome sequencing, immunohistochemistry, histologic image analysis, gene expression profiling, and T- and B-cell receptor sequencing. We identify 3 immunologic response categories, which frequently co-exist within individual patients. Furthermore, epithelial CD8+ TIL were inversely associated with malignant cell diversity, evidenced by subclonal neoepitope elimination and spatial tracking between tumor and T-cell clones. Intersecting mutational signatures and immune analysis showed that foldback inversion genomic aberrations lead to worse outcomes even in the presence of cytotoxic TIL (n=433). Thus, regional variation in immune contexture mirrors the pattern of intraperitoneal malignant spread, provoking new perspectives for treatment of this challenging disease.

cancer biology↗

bioRxiv2017

Very low depth whole genome sequencing in complex trait association studies

MotivationVery low depth sequencing has been proposed as a cost-effective approach to capture low-frequency and rare variation in complex trait association studies. However, a full characterisation of the genotype quality and association power for very low depth sequencing designs is still lacking.\n\nResultsWe perform cohort-wide whole genome sequencing (WGS) at low depth in 1,239 individuals (990 at 1x depth and 249 at 4x depth) from an isolated population, and establish a robust pipeline for calling and imputing very low depth WGS genotypes from standard bioinformatics tools. Using genotyping chip, whole-exome sequencing (WES, 75x depth) and high-depth (22x) WGS data in the same samples, we examine in detail the sensitivity of this approach, and show that imputed 1x WGS recapitulates 95.2% of variants found by imputed GWAS with an average minor allele concordance of 97% for common and low-frequency variants. In our study, 1x further allowed the discovery of 140,844 true low-frequency variants with 73% genotype concordance when compared to high-depth WGS data. Finally, using association results for 57 quantitative traits, we show that very low depth WGS is an efficient alternative to imputed GWAS chip designs, allowing the discovery of up to twice as many true association signals than the classical imputed GWAS design.\n\nSupplementary DataSupplementary Data are appended to this manuscript.

genetics↗

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↗