Clonal Decomposition and DNA Replication States Defined by Scaled Single-Cell Genome Sequencing.

Accurate measurement of clonal genotypes, mutational processes, and replication states from individual tumor-cell genomes will facilitate improved understanding of tumor evolution. We have developed DLP+, a scalable single-cell whole-genome sequencing platform implemented using commodity instruments, image-based object recognition, and open source computational methods. Using DLP+, we have generated a resource of 51,926 single-cell genomes and matched cell images from diverse cell types including cell lines, xenografts, and diagnostic samples with limited material. From this resource we have defined variation in mitotic mis-segregation rates across tissue types and genotypes. Analysis of matched genomic and image measurements revealed correlations between cellular morphology and genome ploidy states. Aggregation of cells sharing copy number profiles allowed for calculation of single-nucleotide resolution clonal genotypes and inference of clonal phylogenies and avoided the limitations of bulk deconvolution. Finally, joint analysis over the above features defined clone-specific chromosomal aneuploidy in polyclonal populations.

A Hematogenous Route for Medulloblastoma Leptomeningeal Metastases.

While the preponderance of morbidity and mortality in medulloblastoma patients are due to metastatic disease, most research focuses on the primary tumor due to a dearth of metastatic tissue samples and model systems. Medulloblastoma metastases are found almost exclusively on the leptomeningeal surface of the brain and spinal cord; dissemination is therefore thought to occur through shedding of primary tumor cells into the cerebrospinal fluid followed by distal re-implantation on the leptomeninges. We present evidence for medulloblastoma circulating tumor cells (CTCs) in therapy-naive patients and demonstrate in vivo, through flank xenografting and parabiosis, that medulloblastoma CTCs can spread through the blood to the leptomeningeal space to form leptomeningeal metastases. Medulloblastoma leptomeningeal metastases express high levels of the chemokine CCL2, and expression of CCL2 in medulloblastoma in vivo is sufficient to drive leptomeningeal dissemination. Hematogenous dissemination of medulloblastoma offers a new opportunity to diagnose and treat lethal disseminated medulloblastoma.

The genetic basis and cell of origin of mixed phenotype acute leukaemia.

Mixed phenotype acute leukaemia (MPAL) is a high-risk subtype of leukaemia with myeloid and lymphoid features, limited genetic characterization, and a lack of consensus regarding appropriate therapy. Here we show that the two principal subtypes of MPAL, T/myeloid (T/M) and B/myeloid (B/M), are genetically distinct. Rearrangement of ZNF384 is common in B/M MPAL, and biallelic WT1 alterations are common in T/M MPAL, which shares genomic features with early T-cell precursor acute lymphoblastic leukaemia. We show that the intratumoral immunophenotypic heterogeneity characteristic of MPAL is independent of somatic genetic variation, that founding lesions arise in primitive haematopoietic progenitors, and that individual phenotypic subpopulations can reconstitute the immunophenotypic diversity in vivo. These findings indicate that the cell of origin and founding lesions, rather than an accumulation of distinct genomic alterations, prime tumour cells for lineage promiscuity. Moreover, these findings position MPAL in the spectrum of immature leukaemias and provide a genetically informed framework for future clinical trials of potential treatments for MPAL.

Fate mapping of human glioblastoma reveals an invariant stem cell hierarchy.

Human glioblastomas harbour a subpopulation of glioblastoma stem cells that drive tumorigenesis. However, the origin of intratumoural functional heterogeneity between glioblastoma cells remains poorly understood. Here we study the clonal evolution of barcoded glioblastoma cells in an unbiased way following serial xenotransplantation to define their individual fate behaviours. Independent of an evolving mutational signature, we show that the growth of glioblastoma clones in vivo is consistent with a remarkably neutral process involving a conserved proliferative hierarchy rooted in glioblastoma stem cells. In this model, slow-cycling stem-like cells give rise to a more rapidly cycling progenitor population with extensive self-maintenance capacity, which in turn generates non-proliferative cells. We also identify rare 'outlier' clones that deviate from these dynamics, and further show that chemotherapy facilitates the expansion of pre-existing drug-resistant glioblastoma stem cells. Finally, we show that functionally distinct glioblastoma stem cells can be separately targeted using epigenetic compounds, suggesting new avenues for glioblastoma-targeted therapy.

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 sub-5-kb resolution 3D genome maps by in situ Hi-C. Contact maps at sub-5-kb resolution allow identification of individual DNA loops, domain organization, and large-scale genome compartmentalization. We observed differences in looping architectures among GSCs from different patients, suggesting that 3D genome architecture is a further layer of inter-patient heterogeneity for glioblastoma. Integration of DNA contact maps with chromatin and transcriptional profiles identified specific mechanisms of gene regulation, including the convergence of multiple super enhancers to individual stemness genes within individual cells. We show that the number of loops contacting a gene correlates with elevated transcription. These results indicate that stemness genes are hubs of interaction between multiple regulatory regions, likely to ensure their sustained expression. Regions of open chromatin common among the GSCs tested were poised for expression of immune-related genes, including CD276 We demonstrate that this gene is co-expressed with stemness genes in GSCs and that CD276 can be targeted with an antibody-drug conjugate to eliminate self-renewing cells. Our results demonstrate that integrated structural genomics data sets can be employed to rationally identify therapeutic vulnerabilities in self-renewing cells.

Comprehensive genomic profiling of glioblastoma tumors, BTICs, and xenografts reveals stability and adaptation to growth environments.

Glioblastoma multiforme (GBM) is the most deadly brain tumor, and currently lacks effective treatment options. Brain tumor-initiating cells (BTICs) and orthotopic xenografts are widely used in investigating GBM biology and new therapies for this aggressive disease. However, the genomic characteristics and molecular resemblance of these models to GBM tumors remain undetermined. We used massively parallel sequencing technology to decode the genomes and transcriptomes of BTICs and xenografts and their matched tumors in order to delineate the potential impacts of the distinct growth environments. Using data generated from whole-genome sequencing of 201 samples and RNA sequencing of 118 samples, we show that BTICs and xenografts resemble their parental tumor at the genomic level but differ at the mRNA expression and epigenomic levels, likely due to the different growth environment for each sample type. These findings suggest that a comprehensive genomic understanding of in vitro and in vivo GBM model systems is crucial for interpreting data from drug screens, and can help control for biases introduced by cell-culture conditions and the microenvironment in mouse models. We also found that lack of MGMT expression in pretreated GBM is linked to hypermutation, which in turn contributes to increased genomic heterogeneity and requires new strategies for GBM treatment.

Genome-wide discovery of somatic coding and noncoding mutations in pediatric endemic and sporadic Burkitt lymphoma.

Although generally curable with intensive chemotherapy in resource-rich settings, Burkitt lymphoma (BL) remains a deadly disease in older patients and in sub-Saharan Africa. Epstein-Barr virus (EBV) positivity is a feature in more than 90% of cases in malaria-endemic regions, and up to 30% elsewhere. However, the molecular features of BL have not been comprehensively evaluated when taking into account tumor EBV status or geographic origin. Through an integrative analysis of whole-genome and transcriptome data, we show a striking genome-wide increase in aberrant somatic hypermutation in EBV-positive tumors, supporting a link between EBV and activation-induced cytidine deaminase (AICDA) activity. In addition to identifying novel candidate BL genes such as SIN3A, USP7, and CHD8, we demonstrate that EBV-positive tumors had significantly fewer driver mutations, especially among genes with roles in apoptosis. We also found immunoglobulin variable region genes that were disproportionally used to encode clonal B-cell receptors (BCRs) in the tumors. These include IGHV4-34, known to produce autoreactive antibodies, and IGKV3-20, a feature described in other B-cell malignancies but not yet in BL. Our results suggest that tumor EBV status defines a specific BL phenotype irrespective of geographic origin, with particular molecular properties and distinct pathogenic mechanisms. The novel mutation patterns identified here imply rational use of DNA-damaging chemotherapy in some patients with BL and targeted agents such as the CDK4/6 inhibitor palbociclib in others, whereas the importance of BCR signaling in BL strengthens the potential benefit of inhibitors for PI3K, Syk, and Src family kinases among these patients.

Sources of erroneous sequences and artifact chimeric reads in next generation sequencing of genomic DNA from formalin-fixed paraffin-embedded samples.

Tissues used in pathology laboratories are typically stored in the form of formalin-fixed, paraffin-embedded (FFPE) samples. One important consideration in repurposing FFPE material for next generation sequencing (NGS) analysis is the sequencing artifacts that can arise from the significant damage to nucleic acids due to treatment with formalin, storage at room temperature and extraction. One such class of artifacts consists of chimeric reads that appear to be derived from non-contiguous portions of the genome. Here, we show that a major proportion of such chimeric reads align to both the 'Watson' and 'Crick' strands of the reference genome. We refer to these as strand-split artifact reads (SSARs). This study provides a conceptual framework for the mechanistic basis of the genesis of SSARs and other chimeric artifacts along with supporting experimental evidence, which have led to approaches to reduce the levels of such artifacts. We demonstrate that one of these approaches, involving S1 nuclease-mediated removal of single-stranded fragments and overhangs, also reduces sequence bias, base error rates, and false positive detection of copy number and single nucleotide variants. Finally, we describe an analytical approach for quantifying SSARs from NGS data.

MAVIS: merging, annotation, validation, and illustration of structural variants.

Summary: Reliably identifying genomic rearrangements and interpreting their impact is a key step in understanding their role in human cancers and inherited genetic diseases. Many short read algorithmic approaches exist but all have appreciable false negative rates. A common approach is to evaluate the union of multiple tools increasing sensitivity, followed by filtering to retain specificity. Here we describe an application framework for the rapid generation of structural variant consensus, unique in its ability to visualize the genetic impact and context as well as process both genome and transcriptome data. Availability and implementation: http://mavis.bcgsc.ca. Supplementary information: Supplementary data are available at Bioinformatics online.

Native bacterial communities and Listeria monocytogenes survival in soils collected from the Lower Mainland of British Columbia, Canada.

Soil is an important reservoir for Listeria monocytogenes, a foodborne pathogen implicated in numerous produce-related outbreaks. Our objectives were to (i) compare the survival of L. monocytogenes among three soils, (ii) compare the native bacterial communities across these soils, and (iii) investigate relationships between L. monocytogenes survival, native bacterial communities, and soil properties. Listeria spp. populations were monitored on PALCAM agar in three soils inoculated with L. monocytogenes (∼5 × 106 CFU/g): conventionally farmed (CS), grassland transitioning to conventionally farmed (TS), and uncultivated grassland (GS). Bacterial diversity of the soils was analyzed using 16S rRNA targeted amplicon sequencing. A 2 log reduction of Listeria spp. was observed in all soils within 10 days, but at a significantly lower rate in GS (Fisher's least significant difference test; p < 0.05). Survival correlated with increased moisture and a neutral pH. GS showed the highest microbial diversity. Acidobacteria was the dominant phylum differentiating CS and TS from GS, and was negatively correlated with pH, carbon, nitrogen, and moisture. High moisture content and neutral pH are likely to increase the ability of L. monocytogenes to persist in soil. This study confirmed that native bacterial communities and short-term survival of L. monocytogenes varies across soils.

Large-scale profiling of microRNAs for The Cancer Genome Atlas.

The comprehensive multiplatform genomics data generated by The Cancer Genome Atlas (TCGA) Research Network is an enabling resource for cancer research. It includes an unprecedented amount of microRNA sequence data: ~11 000 libraries across 33 cancer types. Combined with initiatives like the National Cancer Institute Genomics Cloud Pilots, such data resources will make intensive analysis of large-scale cancer genomics data widely accessible. To support such initiatives, and to enable comparison of TCGA microRNA data to data from other projects, we describe the process that we developed and used to generate the microRNA sequence data, from library construction through to submission of data to repositories. In the context of this process, we describe the computational pipeline that we used to characterize microRNA expression across large patient cohorts.

Increasing quality, throughput and speed of sample preparation for strand-specific messenger RNA sequencing.

BACKGROUND: RNA-Sequencing (RNA-seq) is now commonly used to reveal quantitative spatiotemporal snapshots of the transcriptome, the structures of transcripts (splice variants and fusions) and landscapes of expressed mutations. However, standard approaches for library construction typically require relatively high amounts of input RNA, are labor intensive, and are time consuming. METHODS: Here, we report the outcome of a systematic effort to optimize and streamline steps in strand-specific RNA-seq library construction. RESULTS: This work has resulted in the identification of an optimized messenger RNA isolation protocol, a potent reverse transcriptase for cDNA synthesis, and an efficient chemistry and a simplified formulation of library construction reagents. We also present an optimization of bead-based purification and size selection designed to maximize the recovery of cDNA fragments. CONCLUSIONS: These developments have allowed us to assemble a rapid high throughput pipeline that produces high quality data from amounts of total RNA as low as 25 ng. While the focus of this study is on RNA-seq sample preparation, some of these developments are also relevant to other next-generation sequencing library types.

Genomic and Cytogenetic Characterization of a Balanced Translocation Disrupting NUP98.

A 41-year-old Asian woman with bilateral renal angiomyolipomas (AML) was incidentally identified to have a balanced translocation, 46,XX,t(11;12)(p15.4;q15). She had no other features or family history to suggest a diagnosis of tuberous sclerosis. Her healthy daughter had the same translocation and no renal AML at the age of 3 years. Whole-genome sequencing was performed on genomic maternal DNA isolated from blood. A targeted de novo assembly was then conducted with ABySS for chromosomes 11 and 12. Sanger sequencing was used to validate the translocation breakpoints. As a result, genomic characterization of chromosomes 11 and 12 revealed that the 11p breakpoint disrupted the NUP98 gene in intron 1, causing a separation of the promoter and transcription start site from the rest of the gene. The translocation breakpoint on chromosome 12q was located in a gene desert. NUP98 has not yet been associated with renal AML pathogenesis, but somatic NUP98 alterations are recurrently implicated in hematological malignancies, most often following a gene fusion event. We also found evidence for complex structural events involving chromosome 12, which appear to disrupt the TDG gene. We identified a TDGP1 partially processed pseudogene at 12p12.1, which adds complexity to the de novo assembly. In conclusion, this is the first report of a germline constitutional structural chromosome rearrangement disrupting NUP98 that occurred in a generally healthy woman with bilateral renal AML.

Developmental timing of mutations revealed by whole-genome sequencing of twins with acute lymphoblastic leukemia.

Acute lymphoblastic leukemia (ALL) is the major pediatric cancer. At diagnosis, the developmental timing of mutations contributing critically to clonal diversification and selection can be buried in the leukemia's covert natural history. Concordance of ALL in monozygotic, monochorionic twins is a consequence of intraplacental spread of an initiated preleukemic clone. Studying monozygotic twins with ALL provides a unique means of uncovering the timeline of mutations contributing to clonal evolution, pre- and postnatally. We sequenced the whole genomes of leukemic cells from two twin pairs with ALL to comprehensively characterize acquired somatic mutations in ALL, elucidating the developmental timing of all genetic lesions. Shared, prenatal, coding-region single-nucleotide variants were limited to the putative initiating lesions. All other nonsynonymous single-nucleotide variants were distinct between tumors and, therefore, secondary and postnatal. These changes occurred in a background of noncoding mutational changes that were almost entirely discordant in twin pairs and likely passenger mutations acquired during leukemic cell proliferation.

Variation at 10p12.2 and 10p14 influences risk of childhood B-cell acute lymphoblastic leukemia and phenotype.

Acute lymphoblastic leukemia (ALL) is the major pediatric cancer diagnosed in economically developed countries with B-cell precursor (BCP)-ALL, accounting for approximately 70% of ALL. Recent genome-wide association studies (GWAS) have provided the first unambiguous evidence for common inherited susceptibility to BCP-ALL, identifying susceptibility loci at 7p12.2, 9p21.3, 10q21.2, and 14q11.2. To identify additional BCP-ALL susceptibility loci, we conducted a GWAS and performed a meta-analysis with a published GWAS totaling 1658 cases and 4723 controls, with validation in 1449 cases and 1488 controls. Combined analysis identified novel loci mapping to 10p12.2 (rs10828317, odds ratio [OR] = 1.23; P = 2.30 × 10(-9)) and 10p14 marked by rs3824662 (OR = 1.31; P = 8.62 × 10(-12)). The single nucleotide polymorphism rs10828317 is responsible for the N215S polymorphism in exon 7 of PIP4K2A, and rs3824662 localizes to intron 3 of the transcription factor and putative tumor suppressor gene GATA3. The rs10828317 association was shown to be specifically associated with hyperdiploid ALL, whereas the rs3824662-associated risk was confined to nonhyperdiploid non-TEL-AML1 + ALL. The risk allele of rs3824662 was correlated with older age at diagnosis (P < .001) and significantly worse event-free survivorship (P < .0001). These findings provide further insights into the genetic and biological basis of inherited genetic susceptibility to BCP-ALL and the influence of constitutional genotype on disease development.

FGFR2 genotype and risk of radiation-associated breast cancer in Hodgkin lymphoma.

Women treated at young ages with supradiaphragmatic radiotherapy for Hodgkin lymphoma (HL) have a highly increased risk of breast cancer. For personalized advice and follow-up regimens for patients, information is needed on how the radiotherapy-related risk is affected by other breast cancer risk factors. Genome-wide association studies have identified 14 independently replicated common single nucleotide polymorphisms that influence breast cancer risk. To examine whether these variants contribute to risk of radiation-associated breast cancer in HL, we analyzed 2 independent case-control series, from the United Kingdom and The Netherlands, totaling 693 HL patients, 232 with breast cancer and 461 without. rs1219648, which annotates the FGFR2 gene, was associated with risk in both series (combined per-allele odds ratio = 1.59, 95% confidence interval: 1.26-2.02; P = .000111). These data provide evidence that genetic variation in FGFR2 influences radiation-induced breast cancer risk.

The silent mutational landscape of infant MLL-AF4 pro-B acute lymphoblastic leukemia.

Over 90% of infants (< 1-year-old) diagnosed with leukemia have pro-B acute lymphoblastic leukemia (ALL) containing the MLL-AF4 fusion. When compared with other forms of paediatric ALL affecting later B-cell differentiation, MLL-AF4 pro-B is associated with a dismal prognosis with a typical 5-year disease-free survival of <20%. MLL-AF4 may be sufficient on its own for leukemogenesis or the gene-fusion product may alternatively predispose transformed cells to global genetic instability, enhancing the acquisition of additional key mutations. To gain insight into the genomic landscape of infant MLL-AF4 pro-B ALL we performed whole genome sequencing of diagnostic leukemic blasts and matched germline samples from three MLL-AF4 pro-B ALL infants. Our analysis revealed few somatic changes (copy number abnormalities, loss of heterozygosity, or single nucleotide variants), demonstrating that only a very small number of mutations are necessary to generate infant MLL-leukemia.

Whole genome and transcriptome integrated analyses guide clinical care of pediatric poor prognosis cancers.

The role for routine whole genome and transcriptome analysis (WGTA) for poor prognosis pediatric cancers remains undetermined. Here, we characterize somatic mutations, structural rearrangements, copy number variants, gene expression, immuno-profiles and germline cancer predisposition variants in children and adolescents with relapsed, refractory or poor prognosis malignancies who underwent somatic WGTA and matched germline sequencing. Seventy-nine participants with a median age at enrollment of 8.8 y (range 6 months to 21.2 y) are included. Germline pathogenic/likely pathogenic variants are identified in 12% of participants, of which 60% were not known prior. Therapeutically actionable variants are identified by targeted gene report and whole genome in 32% and 62% of participants, respectively, and increase to 96% after integrating transcriptome analyses. Thirty-two molecularly informed therapies are pursued in 28 participants with 54% achieving a clinical benefit rate; objective response or stable disease ≥6 months. Integrated WGTA identifies therapeutically actionable variants in almost all tumors and are directly translatable to clinical care of children with poor prognosis cancers.

Chromosome 7p11.2 (EGFR) variation influences glioma risk.

While gliomas are the most common primary brain tumors, their etiology is largely unknown. To identify novel risk loci for glioma, we conducted genome-wide association (GWA) analysis of two case-control series from France and Germany (2269 cases and 2500 controls). Pooling these data with previously reported UK and US GWA studies provided data on 4147 glioma cases and 7435 controls genotyped for 424 460 common tagging single-nucleotide polymorphisms. Using these data, we demonstrate two statistically independent associations between glioma and rs11979158 and rs2252586, at 7p11.2 which encompasses the EGFR gene (population-corrected statistics, P(c) = 7.72 × 10(-8) and 2.09 × 10(-8), respectively). Both associations were independent of tumor subtype, and were independent of EGFR amplification, p16INK4a deletion and IDH1 mutation status in tumors; compatible with driver effects of the variants on glioma development. These findings show that variation in 7p11.2 is a determinant of inherited glioma risk.