MBRS-59. SINGLE-CELL WHOLE-GENOME SEQUENCING DISSECTS INTRA-TUMOURAL GENOMIC HETEROGENEITY AND CLONAL EVOLUTION IN CHILDHOOD MEDULLOBLASTOMA

Abstract Medulloblastomas harbor clinically-significant intra-tumoral heterogeneity for key biomarkers (e.g. MYC/MYCN, β-catenin). Recent studies have characterized transcriptional heterogeneity at the single-cell level, however the underlying genomic copy number and mutational architecture remains to be resolved. We therefore sought to establish the intra-tumoural genomic heterogeneity of medulloblastoma at single-cell resolution. Copy number patterns were dissected by whole-genome sequencing in 1024 single cells isolated from multiple distinct tumour regions within 16 snap-frozen medulloblastomas, representing the major molecular subgroups (WNT, SHH, Group3, Group4) and genotypes (i.e. MYC amplification, TP53 mutation). Common copy number driver and subclonal events were identified, providing clear evidence of copy number evolution in medulloblastoma development. Moreover, subclonal whole-arm and focal copy number alterations covering important genomic loci (e.g. on chr10 of SHH patients) were detected in single tumour cells, yet undetectable at the bulk-tumor level. Spatial copy number heterogeneity was also common, with differences between clonal and subclonal events detected in distinct regions of individual tumours. Mutational analysis of the cells allowed dissection of spatial and clonal heterogeneity patterns for key medulloblastoma mutations (e.g. CTNNB1, TP53, SMARCA4, PTCH1) within our cohort. Integrated copy number and mutational analysis is underway to establish their inter-relationships and relative contributions to clonal evolution during tumourigenesis. In summary, single-cell analysis has enabled the resolution of common mutational and copy number drivers, alongside sub-clonal events and distinct patterns of clonal and spatial evolution, in medulloblastoma development. We anticipate these findings will provide a critical foundation for future improved biomarker selection, and the development of targeted therapies.

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SCCNV: a software tool for identifying copy number variation from single-cell whole-genome sequencing

10.1101/535807 ◽

2019 ◽

Cited By ~ 2

Author(s):

Xiao Dong ◽

Lei Zhang ◽

Xiaoxiao Hao ◽

Tao Wang ◽

Jan Vijg

Keyword(s):

Copy Number Variation ◽

Whole Genome Sequencing ◽

Single Cell ◽

Genome Sequencing ◽

Copy Number ◽

De Novo ◽

Single Cells ◽

Software Tool ◽

Whole Genome ◽

Number Variation

AbstractBackgroundIdentification of de novo mutations from cell populations requires single-cell whole-genome sequencing (SCWGS). Although many experimental protocols of SCWGS have been developed, few computational tools are available for downstream analysis of different types of somatic mutations, including copy number variation (CNV).ResultsWe developed SCCNV, a software tool for detecting CNVs from whole genome-amplified single cells. SCCNV is a read-depth based approach with adjustment for the whole-genome amplification bias.ConclusionsWe demonstrate its performance by analyzing data collected from most of the single-cell amplification methods, including DOP-PCR, MDA, MALBAC and LIANTI. SCCNV is freely available at https://github.com/biosinodx/SCCNV.

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Abstract 2394: Scalable, rapid and affordable low-pass whole genome sequencing method for single-cell copy-number profiling on LM-PCR based WGA products

10.1158/1538-7445.am2016-2394 ◽

2016 ◽

Author(s):

Genny Buson ◽

Paola Tononi ◽

Claudio Forcato ◽

Francesca Fontana ◽

Gianni Medoro ◽

...

Keyword(s):

Whole Genome Sequencing ◽

Single Cell ◽

Genome Sequencing ◽

Copy Number ◽

Whole Genome ◽

Sequencing Method ◽

Low Pass

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Abstract PO-018: Single cell whole genome sequencing reveals the dynamics of copy number instability at the earliest stages of cancer evolution

10.1158/1538-7445.tumhet2020-po-018 ◽

2020 ◽

Author(s):

Alexander M. Frankell ◽

Sebastian Hobor ◽

Maise Al-bakir ◽

Eva Grönroos ◽

Charles Swanton

Keyword(s):

Whole Genome Sequencing ◽

Single Cell ◽

Genome Sequencing ◽

Copy Number ◽

Whole Genome ◽

Cancer Evolution

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Digital-WGS: Automated, highly efficient whole-genome sequencing of single cells by digital microfluidics

Science Advances ◽

10.1126/sciadv.abd6454 ◽

2020 ◽

Vol 6 (50) ◽

pp. eabd6454

Author(s):

Qingyu Ruan ◽

Weidong Ruan ◽

Xiaoye Lin ◽

Yang Wang ◽

Fenxiang Zou ◽

...

Keyword(s):

Sample Preparation ◽

Whole Genome Sequencing ◽

Single Cell ◽

Genome Sequencing ◽

Single Cells ◽

Digital Microfluidics ◽

Dropout Rate ◽

Great Promise ◽

Whole Genome ◽

Exogenous Dna

Single-cell whole-genome sequencing (WGS) is critical for characterizing dynamic intercellular changes in DNA. Current sample preparation technologies for single-cell WGS are complex, expensive, and suffer from high amplification bias and errors. Here, we describe Digital-WGS, a sample preparation platform that streamlines high-performance single-cell WGS with automatic processing based on digital microfluidics. Using the method, we provide high single-cell capture efficiency for any amount and types of cells by a wetted hydrodynamic structure. The digital control of droplets in a closed hydrophobic interface enables the complete removal of exogenous DNA, sufficient cell lysis, and lossless amplicon recovery, achieving the low coefficient of variation and high coverage at multiple scales. The single-cell genomic variations profiling performs the excellent detection of copy number variants with the smallest bin of 150 kb and single-nucleotide variants with allele dropout rate of 5.2%, holding great promise for broader applications of single-cell genomics.

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Submegabase copy number variations arise during cerebral cortical neurogenesis as revealed by single-cell whole-genome sequencing

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1812702115 ◽

2018 ◽

Vol 115 (42) ◽

pp. 10804-10809 ◽

Cited By ~ 18

Author(s):

Suzanne Rohrback ◽

Craig April ◽

Fiona Kaper ◽

Richard R. Rivera ◽

Christine S. Liu ◽

...

Keyword(s):

Whole Genome Sequencing ◽

Single Cell ◽

Genome Sequencing ◽

Copy Number ◽

Cortical Development ◽

Building Blocks ◽

Copy Number Variations ◽

Whole Genome ◽

Mature Brain ◽

The Brain

Somatic copy number variations (CNVs) exist in the brain, but their genesis, prevalence, forms, and biological impact remain unclear, even within experimentally tractable animal models. We combined a transposase-based amplification (TbA) methodology for single-cell whole-genome sequencing with a bioinformatic approach for filtering unreliable CNVs (FUnC), developed from machine learning trained on lymphocyte V(D)J recombination. TbA–FUnC offered superior genomic coverage and removed >90% of false-positive CNV calls, allowing extensive examination of submegabase CNVs from over 500 cells throughout the neurogenic period of cerebral cortical development in Mus musculus. Thousands of previously undocumented CNVs were identified. Half were less than 1 Mb in size, with deletions 4× more common than amplification events, and were randomly distributed throughout the genome. However, CNV prevalence during embryonic cortical development was nonrandom, peaking at midneurogenesis with levels triple those found at younger ages before falling to intermediate quantities. These data identify pervasive small and large CNVs as early contributors to neural genomic mosaicism, producing genomically diverse cellular building blocks that form the highly organized, mature brain.

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Composite Single Cell Genetics and Clonal Phylogeny in Acute Lymphoblastic Leukaemia

Blood ◽

10.1182/blood.v120.21.122.122 ◽

2012 ◽

Vol 120 (21) ◽

pp. 122-122

Author(s):

Nicola E Potter ◽

Luca Ermini ◽

Elli Papaemmanuil ◽

Gowri Vijayaraghavan ◽

Ian Titley ◽

...

Keyword(s):

Single Cell ◽

Genome Sequencing ◽

Copy Number ◽

Experimental Error ◽

Genetic Architecture ◽

Single Cells ◽

Point Mutations ◽

Whole Genome ◽

Copy Number Alterations ◽

Leukaemic Cells

Abstract Abstract 122 Cancer clone development is widely regarded as an evolutionary or Darwinian process of genetic diversification and natural (or therapeutic) selection within tissue ecosystems. Emerging studies are providing strong evidence that dynamic and complex branching sub-clonal genetic architectures are a common feature of cancer (Greaves M and Maley CC Nature 2012). This complexity may underpin the intransigence of advanced cancer to therapeutic control, particularly as the critical 'driver' cells – cancer or leukaemic stem cells, also appear to be genetically diverse within individual patients (Anderson K et al Nature 2011, Notta F et al Nature 2011). Sub-clonal architecture can only be fully determined through the study of large numbers of single cells uniformly sampled from the individual cancer of interest and assessed for composite genotype. Various technologies and approaches from fluorescent in situ hybridisation (FISH) to whole-genome sequencing of single cells have been applied to cancer and leukaemic cells but each approach has limitations. We have developed a novel multiplex microfluidic Q-PCR approach that allows unbiased single cell sampling, high throughput analysis of hundreds of individual cells and simultaneous detection of multiple genetic alterations in a single cell, including fusion genes, DNA copy number alterations (CNAs) and sequence-based mutations. As a proof of principle study we have applied this technique to REH, an acute lymphoblastic leukaemia (ALL) cell line that harbors the ETV6-RUNX1 fusion and a SNP in the EPO receptor gene, which we used as a surrogate mutation. We further determined a detailed sub-clonal genetic architecture for two ETV6-RUNX1 positive ALL patient samples with multiple point mutations and copy number alterations (determined by whole-genome sequencing) by interrogating approximately 400 flow cytometry sorted single cells with validation by FISH and standard sequencing. Briefly, single cells were lysed prior to multiplex specific (DNA) target amplification (STA) and Q-PCR using the 96.96 dynamic microfluidic array and the BioMarkï HD (Fluidigm, UK). Phylogenetic trees were constructed using maximum parsimony with PAUP analysis software. Interrogation of REH revealed that all single cells registered the ETV6-RUNX1 fusion and EPO receptor SNP, but 42% of cells gained either 1 or 2 additional copies of chromosome 21. Patient sample data revealed branching sub-clonal architectures in Case A in which all leukaemic cells harbored the fusion with additional point mutations but only sub-clones showed CNAs. In contrast, the sub-clonal architecture of Case B showed that whilst the ETV6-RUNX1 fusion was the earliest (or universal) genomic event, CNAs were relatively early events preceding the acquisition of point mutations (Figure 1). In both cases, the numerically predominant sub-clone harbored both point mutations and CNAs in addition to the presumptive initiating lesion, ETV6-RUNX1. These detailed and complex sub-clonal architectures would be masked by other genetic techniques. Single cell genetics coupled with deep genome sequencing is now technically feasible and provides an accurate portrait of the dynamic clonal complexity in leukaemia (and other cancers). Variegated genetics and clonal complexity in individual leukaemias has important implications for our understanding of molecular pathogenesis and for therapeutic targeting. Figure 1. This sub-clonal genetic architecture depicts the branching structure found for Case B, illustrating that in this case the ETV6-RUNX1 fusion was the earliest genomic event, followed by CNAs and the acquisition of point mutations. Those populations highlighted grey are within the experimental error rate but potentially true populations. Figure 1. This sub-clonal genetic architecture depicts the branching structure found for Case B, illustrating that in this case the ETV6-RUNX1 fusion was the earliest genomic event, followed by CNAs and the acquisition of point mutations. Those populations highlighted grey are within the experimental error rate but potentially true populations. Disclosures: No relevant conflicts of interest to declare.

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Prevalence and tissue concordance of BRCA2 copy number loss evaluated by single-cell, shallow whole genome sequencing of circulating tumor cells (CTCs) in castration-resistant prostate cancer (CRPC).

Journal of Clinical Oncology ◽

10.1200/jco.2020.38.15_suppl.5531 ◽

2020 ◽

Vol 38 (15_suppl) ◽

pp. 5531-5531

Author(s):

Ethan Barnett ◽

Joseph Schonhoft ◽

Nikolaus D. Schultz ◽

Jerry Lee ◽

Samir Zaidi ◽

...

Keyword(s):

Prostate Cancer ◽

Whole Genome Sequencing ◽

Single Cell ◽

Tumor Cells ◽

Circulating Tumor Cells ◽

Genome Sequencing ◽

Copy Number ◽

Cellular Heterogeneity ◽

Cancer Tissue ◽

Whole Genome

5531 Background: Genomic studies have shown that up to 25% of prostate cancer tissue specimens harbor alterations in DNA Damage Repair (DDR) genes, which may sensitize the tumor to poly ADP-ribose polymerase inhibitors (PARPi). Trials evaluating PARPi in patients with DDR deficiencies have shown varied response rates and differences regarding which genomic alterations predict for sensitivity to these agents, with the majority of objective responses seen in BRCA2-altered tumors. These results highlight the need to develop biomarker assays which can predict benefit from PARPi therapy. Tissue and cell-free DNA (cfDNA) have been the most utilized sources of tumor material for analysis in this setting, but success rates of obtaining sufficient tumor for analysis from bone are low and detecting tumor-derived copy number variants (CNVs) in cfDNA is challenging. Circulating tumor cells (CTCs) represent an alternate source of genetic information, for which assays are available to isolate and sequence individual cells in a manner that eliminates background noise from stroma and healthy cells, while capturing inter-cellular heterogeneity. Methods: Blood samples, collected from 138 progressing metastatic CRPC patients within 30 days of a pre-treatment biopsy intended for sequencing using MSK-IMPACT, were sent to EPIC Sciences for CTC analysis. Detected CTCs underwent single cell, low pass whole genome sequencing. Prevalence and concordance of BRCA2 copy-loss, regardless of whether single copy or homozygous, was compared in matched tissue and CTC samples. Results: BRCA2 copy-loss was identified in 21% (23/108) and 50% (58/115) of successfully sequenced tissue and CTC samples, respectively. In the 58 patients with CTC-detected BRCA2 loss, BRCA2 loss was detected in 36% (220/565) of the sequenced CTCs, representing a median of 46% (range 4-100%) of CTCs found in each individual sample. When both sequencing assays were successful, BRCA2 loss was detected in CTCs in 84% (16/19) of the tissue-positive cases, whereas tissue sequencing detected BRCA2 loss in 35% (16/46) of CTC-positive cases. Conclusions: Data from this study supports the notion that single-cell CTC sequencing can detect BRCA2 copy-loss at a high frequency, including cases that were negative in tissue, while also characterizing inter-cellular heterogeneity. Further studies will investigate whether CTC BRCA2 copy-loss can predict the likelihood of response to PARPi.

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