scholarly journals Quantifying the Influence of Mutation Detection on Tumour Subclonal Reconstruction

2018 ◽  
Author(s):  
Lydia Y. Liu ◽  
Vinayak Bhandari ◽  
Adriana Salcedo ◽  
Shadrielle M. G. Espiritu ◽  
Quaid D. Morris ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Cancer Cells ◽  
Clinical Outcomes ◽  
Cancer Cell ◽  
Genome Sequencing ◽  
Somatic Mutations ◽  
Mutation Detection ◽  
Cell Populations ◽  
Whole Genome ◽  
Prostate Cancers

AbstractWhole-genome sequencing can be used to estimate subclonal populations in tumours and this intra-tumoural heterogeneity is linked to clinical outcomes. Many algorithms have been developed for subclonal reconstruction, but their variabilities and consistencies are largely unknown. We evaluated sixteen pipelines for reconstructing the evolutionary histories of 293 localized prostate cancers from single samples, and eighteen pipelines for the reconstruction of 10 tumours with multi-region sampling. We show that predictions of subclonal architecture and timing of somatic mutations vary extensively across pipelines. Pipelines show consistent types of biases, with those incorporating SomaticSniper and Battenberg preferentially predicting homogenous cancer cell populations and those using MuTect tending to predict multiple populations of cancer cells. Subclonal reconstructions using multi-region sampling confirm that single-sample reconstructions systematically underestimate intra-tumoural heterogeneity, predicting on average fewer than half of the cancer cell populations identified by multi-region sequencing. Overall, these biases suggest caution in interpreting specific architectures and subclonal variants.

scholarly journals Quantifying the influence of mutation detection on tumour subclonal reconstruction

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Lydia Y. Liu ◽  
Vinayak Bhandari ◽  
Adriana Salcedo ◽  
Shadrielle M. G. Espiritu ◽  
Quaid D. Morris ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Cancer Cells ◽  
Clinical Outcomes ◽  
Cancer Cell ◽  
Genome Sequencing ◽  
Somatic Mutations ◽  
Mutation Detection ◽  
Cell Populations ◽  
Whole Genome ◽  
Prostate Cancers

AbstractWhole-genome sequencing can be used to estimate subclonal populations in tumours and this intra-tumoural heterogeneity is linked to clinical outcomes. Many algorithms have been developed for subclonal reconstruction, but their variabilities and consistencies are largely unknown. We evaluate sixteen pipelines for reconstructing the evolutionary histories of 293 localized prostate cancers from single samples, and eighteen pipelines for the reconstruction of 10 tumours with multi-region sampling. We show that predictions of subclonal architecture and timing of somatic mutations vary extensively across pipelines. Pipelines show consistent types of biases, with those incorporating SomaticSniper and Battenberg preferentially predicting homogenous cancer cell populations and those using MuTect tending to predict multiple populations of cancer cells. Subclonal reconstructions using multi-region sampling confirm that single-sample reconstructions systematically underestimate intra-tumoural heterogeneity, predicting on average fewer than half of the cancer cell populations identified by multi-region sequencing. Overall, these biases suggest caution in interpreting specific architectures and subclonal variants.

DNA Sequencing of a Murine Acute Promyelocytic Leukemia (APL) Genome Using Next Generation Technology.

Blood ◽  
2009 ◽  
Vol 114 (22) ◽  
pp. 3965-3965
Author(s):  
Lukas D. Wartman ◽  
Li Ding ◽  
David E. Larson ◽  
Michael D. McLellan ◽  
Heather Schmidt ◽  
...  
Keyword(s):  
Mouse Model ◽  
Dna Sequencing ◽  
Whole Genome Sequencing ◽  
Acute Promyelocytic Leukemia ◽  
Genome Sequencing ◽  
Somatic Mutations ◽  
Promyelocytic Leukemia ◽  
The Other ◽  
Whole Genome ◽  
Base Pairs

Abstract Abstract 3965 Poster Board III-901 We have recently established that whole genome sequencing is a valid, unbiased approach that can identify novel candidate mutations that may be important for AML pathogenesis (Ley et al Nature 2008, Mardis et al NEJM 2009). Acute promyelocytic leukemia (APL, FAB M3 AML) is a subtype of AML characterized by the t(15;17)(q22;q11.2) translocation that creates an oncogenic fusion gene, PML-RARA. Our laboratory has previously modeled APL in a mouse in an effort to understand the genetic events that lead to the disease. In our knockin mouse model, a human PML-RARA cDNA was targeted to the 5' untranslated region of the mouse cathepsin G gene on chromosome 14 (mCG-PR). The targeting vector was transfected into the RW-4 embryonic stem cell line, derived from a 129/SvJ mouse. The transfected RW-4 cells were injected into C57Bl/6 blastocysts, and chimeric offspring were bred to C57Bl/6 mice. F1 129/SvJ x C57Bl/6 mice were subsequently backcrossed onto the B6/Taconic background for 10 generations before establishing a tumor watch. About 60% of the mCG-PR mice in the Bl/6 background develop a disease that closely resembles APL only after a latent period of 7-18 months, suggesting that additional progression mutations are required for APL development. Array-based genomic techniques (expression array studies and high resolution CGH) have revealed some recurring genetic alterations that may be relevant for progression (i.e. an interstitial deletion of chromosome 2, trisomy 15, etc.), but gene-specific progression mutations have not yet been identified. To begin to identify these mutations in an unbiased fashion, we sequenced a cytogenetically normal, diploid mouse APL genome using massively parallel DNA sequencing via the Illumina platform. Since the tumor arose in a highly inbred mouse strain, we predicted that 15x coverage of the genome (approximately 40 billion base pairs of sequence) would be necessary to identify >90% of the heterozygous somatic mutations. We generated 2 Illumina paired-end libraries (insert sizes of 300-350 bp and 550-600 bp) and generated 59.64 billion base pairs of sequence with 3 full sequencing runs; the reads that successfully mapped generated 15.6x coverage. The sequence data predicted 87,778 heterozygous Single Nucleotide Variants (SNVs) compared to the mouse C57Bl6/J reference sequence, and 23,439 homozygous SNVs. Of the predicted heterozygous SNVs, 695 were non-synonymous (missense or nonsense, or altering a canonical splice site). Thus far, 80 of these putative non-synonymous SNVs have been further analyzed using Sanger sequencing of the original tumor DNA vs. pooled B6/Taconic spleen DNA and pooled129/SvJ spleen DNA as controls. 37/80 were shown to be false positive calls, and 37 were inherited SNPs from residual regions of the129/SvJ genome. 6/80 were present only in the tumor genome, and were candidate somatic mutations. These 6 were screened in 89 additional murine APL tumor samples derived from the same mouse model. Mutations in the Jarid2 (L915I) and Capns2 (N149S) genes occurred only in the proband, and are therefore of uncertain significance. 4/6 mutations were found in additional samples; 3 of these mutations were derived from a common ancestor of the proband and the other affected mice, and were therefore not relevant for pathogenesis. The other recurring mutation was in the pseudokinase domain of JAK1 (V657F), and was identified in one other mouse that was not closely related to the proband. This mutation is orthologous to the known activating mutation V617F in human JAK2, and is identical to a recently described JAK1 pseudokinase domain mutation (V658F) found in human APL and T-ALL samples (EG Jeong et al, Clin Can Res 14: 3716, 2008). We are currently testing the functional significance of this mutation by expressing it in bone marrow cells derived from young WT vs. mCG-PR mice. In summary, unbiased whole genome sequencing of a mouse APL genome has identified a recurring mutation of JAK1 found in both human and mouse APL samples. This approach may allow us to rapidly identify progression mutations that are common to human and murine AML, and provides an important proof-of-concept that this mouse model of AML is functionally related to its human counterpart. Disclosures: No relevant conflicts of interest to declare.

Complete Sequencing and Comparison of 12 Normal Karyotype M1 AML Genomes with 12 t(15;17) Positive M3-APL Genomes

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 404-404 ◽  
Author(s):  
John S. Welch ◽  
David Larson ◽  
Li Ding ◽  
Michael D. McLellan ◽  
Tamara Lamprecht ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Somatic Mutations ◽  
Normal Karyotype ◽  
Whole Genome ◽  
Single Mutation ◽  
Cohesin Complex ◽  
Diverse Range ◽  
Recurrent Mutations ◽  
Passenger Mutations

Abstract Abstract 404 To characterize the genomic events associated with distinct subtypes of AML, we used whole genome sequencing to compare 24 tumor/normal sample pairs from patients with normal karyotype (NK) M1-AML (12 cases) and t(15;17)-positive M3-AML (12 cases). All single nucleotide variants (SNVs), small insertions and deletions (indels), and cryptic structural variants (SVs) identified by whole genome sequencing (average coverage 28x) were validated using sample-specific custom Nimblegen capture arrays, followed by Illumina sequencing; an average coverage of 972 reads per somatic variant yielded 10,597 validated somatic variants (average 421/genome). Of these somatic mutations, 308 occurred in 286 unique genes; on average, 9.4 somatic mutations per genome had translational consequences. Several important themes emerged: 1) AML genomes contain a diverse range of recurrent mutations. We assessed the 286 mutated genes for recurrency in an additional 34 NK M1-AML cases and 9 M3-AML cases. We identified 51 recurrently mutated genes, including 37 that had not previously been described in AML; on average, each genome had 3 recurrently mutated genes (M1 = 3.2; M3 = 2.8, p = 0.32). 2) Many recurring mutations cluster in mutually exclusive pathways, suggesting pathophysiologic importance. The most commonly mutated genes were: FLT3 (36%), NPM1 (25%), DNMT3A (21%), IDH1 (18%), IDH2 (10%), TET2 (10%), ASXL1 (6%), NRAS (6%), TTN (6%), and WT1 (6%). In total, 3 genes (excluding PML-RARA) were mutated exclusively in M3 cases. 22 genes were found only in M1 cases (suggestive of alternative initiating mutations which occurred in methylation, signal transduction, and cohesin complex genes). 25 genes were mutated in both M1 and M3 genomes (suggestive of common progression mutations relevant for both subtypes). A single mutation in a cell growth/signaling gene occurred in 38 of 67 cases (FLT3, NRAS, RUNX1, KIT, CACNA1E, CADM2, CSMD1); these mutations were mutually exclusive of one another, and many of them occurred in genomes with PML-RARA, suggesting that they are progression mutations. We also identified a new leukemic pathway: mutations were observed in all four genes that encode members of the cohesin complex (STAG2, SMC1A, SMC3, RAD21), which is involved in mitotic checkpoints and chromatid separation. The cohesin mutations were mutually exclusive of each other, and collectively occur in 10% of non-M3 AML patients. 3) AML genomes also contain hundreds of benign “passenger” mutations. On average 412 somatic mutations per genome were translationally silent or occurred outside of annotated genes. Both M1 and M3 cases had similar total numbers of mutations per genome, similar mutation types (which favored C>T/G>A transitions), and a similar random distribution of variants throughout the genome (which was affected neither by coding regions nor expression levels). This is consistent with our recent observations of random “passenger” mutations in hematopoietic stem cell (HSC) clones derived from normal patients (Ley et al manuscript in preparation), and suggests that most AML-associated mutations are not pathologic, but pre-existed in the HSC at the time of initial transformation. In both studies, the total number of SNVs per genome correlated positively with the age of the patient (R2 = 0.48, p = 0.001), providing a possible explanation for the increasing incidence of AML in elderly patients. 4) NK M1 and M3 AML samples are mono- or oligo-clonal. By comparing the frequency of all somatic mutations within each sample, we could identify clusters of mutations with similar frequencies (leukemic clones) and determined that the average number of clones per genome was 1.8 (M1 = 1.5; M3 = 2.2; p = 0.04). 5) t(15;17) is resolved by a non-homologous end-joining repair pathway, since nucleotide resolution of all 12 t(15;17) breakpoints revealed inconsistent micro-homologies (0 – 7 bp). Summary: These data provide a genome-wide overview of NK and t(15;17) AML and provide important new insights into AML pathogenesis. AML genomes typically contain hundreds of random, non-genic mutations, but only a handful of recurring mutated genes that are likely to be pathogenic because they cluster in mutually exclusive pathways; specific combinations of recurring mutations, as well as rare and private mutations, shape the leukemia phenotype in an individual patient, and help to explain the clinical heterogeneity of this disease. Disclosures: Westervelt: Novartis: Speakers Bureau.

scholarly journals Identification of somatic mutations in postmortem human brains by whole genome sequencing and their implications for psychiatric disorders

2018 ◽  
Vol 72 (4) ◽  
pp. 280-294 ◽  
Author(s):  
Masaki Nishioka ◽  
Miki Bundo ◽  
Junko Ueda ◽  
Fumiki Katsuoka ◽  
Yukuto Sato ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Psychiatric Disorders ◽  
Genome Sequencing ◽  
Somatic Mutations ◽  
Whole Genome ◽  
Human Brains

scholarly journals Single-cell whole-genome sequencing reveals the functional landscape of somatic mutations in B lymphocytes across the human lifespan

2019 ◽  
Author(s):  
Lei Zhang ◽  
Xiao Dong ◽  
Moonsook Lee ◽  
Alexander Y. Maslov ◽  
Tao Wang ◽  
...  
Keyword(s):  
B Cell ◽  
Whole Genome Sequencing ◽  
Single Cell ◽  
B Lymphocytes ◽  
Genome Sequencing ◽  
Somatic Mutations ◽  
Somatic Hypermutation ◽  
Whole Genome ◽  
Healthy Individuals ◽  
Human Lifespan

Introductory paragraphThe accumulation of mutations in somatic cells have been implicated as a cause of ageing since the 1950s1,2. Yet, attempts to establish a causal relationship between somatic mutations and ageing have been constrained by the lack of methods to directly identify mutational events in primary human tissues. Here we provide detailed, genome-wide mutation frequencies and spectra of human B lymphocytes from healthy individuals across the entire human lifespan, from newborns to centenarians, using a recently developed, highly accurate single-cell whole-genome sequencing method3. We found that the number of somatic mutations increases from <500 per cell in newborns to >3,000 per cell in centenarians. We discovered mutational hotspot regions, some of which, as expected, located at immunoglobulin genes associated with somatic hypermutation. B cell-specific mutation signatures were observed associated with development, ageing or somatic hypermutation (SHM). The SHM signature strongly correlated with the signature found in human chronic lymphocytic leukemia and malignant B-cell lymphomas4, indicating that even in B cells of healthy individuals the potential cancer-causing events are already present. We also identified multiple mutations in sequence features relevant to cellular function, i.e., transcribed genes and gene regulatory regions. Such mutations increased significantly during ageing, but only at approximately half the rate of the genome average, indicating selection against mutations that impact B cell function. This first full characterization of the landscape of somatic mutations in human B lymphocytes indicates that spontaneous somatic mutations accumulating with age can be deleterious and may contribute to both the increased risk for leukemia and the functional decline of B lymphocytes in the elderly.

scholarly journals Deep Whole Genome Sequencing Identifies Recurrent Genomic Alterations in Commonly-Used Breast Cancer Cell Lines and Patient Derived Xenograft Models

2021 ◽  
Author(s):  
Niantao Deng ◽  
Andre Minoche ◽  
Kate Harvey ◽  
Meng Li ◽  
Juliane Winkler ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Whole Genome Sequencing ◽  
Cell Lines ◽  
Cancer Cell ◽  
Genome Sequencing ◽  
Breast Cancer Cell ◽  
Breast Cancer Cell Lines ◽  
Whole Genome ◽  
Breast Cancers ◽  
Pdx Models

Abstract Background: Breast cancer cell lines (BCCLs) and patient-derived xenografts (PDX) are the most frequently used models in breast cancer research. Despite their widespread usage, genome sequencing of these models is incomplete, with previous studies only focusing on targeted gene panels, whole exome or shallow whole genome sequencing. Deep whole genome sequencing is the most sensitive and accurate method to detect single nucleotide variants and indels, gene copy number and structural events such as gene fusions.Results: Here we describe deep whole genome sequencing (WGS) of commonly used BCCL and PDX models using the Illumina X10 platform with an average ~ 60x coverage. We identify novel genomic alterations, including point mutations and genomic rearrangements at base-pair resolution, compared to previously available sequencing data. Through integrative analysis with publicly available functional screening data, we annotate new genomic features likely to be of biological significance. CSMD1, previously identified as a tumor suppressor gene in various cancer types, including head and neck, lung and breast cancers, has been identified with deletion in 50% of our PDX models, suggesting an important role in aggressive breast cancers. Conclusions: Our WGS data provides a comprehensive genome sequencing resource of these models.

scholarly journals Long-Term Clonal Dynamics upon Allogeneic Haematopoietic Stem Cell Transplantation Revealed Using Somatic Mutations As Clonal Tracking Marks in HSC Donor and Recipient Pairs

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 3813-3813
Author(s):  
Michael Spencer Chapman ◽  
C. Matthias Wilk ◽  
Steffen Boettcher ◽  
Larisa V. Kovtonyuk ◽  
Emily Mitchell ◽  
...  
Keyword(s):  
Stem Cell ◽  
Stem Cell Transplantation ◽  
Whole Genome Sequencing ◽  
Cell Transplantation ◽  
Genome Sequencing ◽  
Haematopoietic Stem Cell Transplantation ◽  
Somatic Mutations ◽  
Haematopoietic Stem Cell ◽  
Whole Genome

Abstract Allogeneic haematopoietic stem cell transplantation (HSCT) is a potentially curative treatment for over 40,000 patients/year in Europe and the US alone. However, substantial treatment-related mortality and morbidity, as well as risks of disease relapse give a survival rate of about 50% and leave considerable room for improvement. Despite being an established treatment for over 50 years, fundamental questions remain regarding its biology. For example, how many of the frequently &gt;100 million transplanted CD34+ cells are true haematopoietic stem cells (HSCs), determined by long-term engraftment and contribution to multi-lineage hematopoiesis (long-term engrafting HSCs [LTE-HSCs])? What are the mutational consequences for transplanted HSCs given their proliferation and potential mutagenic insults in the post-transplant period? Most recently, the discovery of clonal haematopoiesis (CH) has raised interest in the interaction between this and HSCT. Do such clones further expand during HSCT? This may potentially lead to the devastating complication of donor-cell leukemia or other CH-related risks, e.g. cardiovascular disease. Recently, some studies have addressed this using targeted sequencing panels for myeloid cancer genes. However, many clonal expansions in normal blood are not driven by mutations in such genes, with evidence suggesting that the set of potential 'driver' genes is much larger than currently recognized (Poon et al, bioRXiv 2020). Advances in HSC tracking methodologies - using naturally-occurring somatic mutations as clonal markers (Lee-Six et al, Nature 2018) - provide a powerful tool to simultaneously address these questions. Whole-genome sequencing of hundreds of single-cell derived haematopoietic stem and progenitor cell (HSPC) colonies from a single individual is used to compile a complete set of somatic mutations in each colony founder cell, and the pattern of shared mutations amongst cells used to infer their phylogeny or 'family tree'. The constant rate of mutation acquisition during post-development life allows estimation of the timing of mutation acquisition. Using phylodynamic approaches borrowed from pathogen biology, patterns of branching points can be used to infer important parameters such as the size of population 'bottlenecks' (in this context the number of LTE-HSCs), and the growth dynamics of expanded clones. We selected 7 donor/ recipient (D/ R) pairs who had undergone HSCT 9-31 years previously. For each individual (D and R), peripheral blood CD34+ HSPC-derived colonies were grown on methylcellulose medium. Whole-genome sequencing (WGS) was performed on 100-300 colonies per individual - a total of 2,278 genomes. Mutations were called using established pipelines, then filtered to remove artefacts, germline variants, and in vitro mutations leaving only somatically-acquired mutations. Phylogenies for each D/R pair were inferred, using a maximum parsimony algorithm. Mutational signatures were extracted using a hierarchical dirichlet process. D/R phylogenies were compared using metrics of phylogenetic diversity. Clonal fractions of expanded clones in D/R were compared. Approximate Bayesian computation was used to estimate numbers of LTE-HSCs. Our results reveal that HSCT engraftment is remarkably polyclonal, with thousands of transplanted HSCs (in most cases &gt;5,000) actively contributing to haematopoiesis decades after transplant. HSCs suffer little consequence in terms of their somatic mutation burden. Recipient haematopoiesis showed decreased clonal diversity compared to their donors with a mean 20% decrease of the Shannon's Diversity Index. This may partly result from increased selective pressures during HSCT. Intriguingly, several DNMT3A-driven expansions seen in donors had lower clonal fractions in recipients. Conversely, clones with &gt;1 driver mutation (e.g. DNMT3A/CHEK2) showed larger expansions in recipients compared to donors, despite originating in the donor. DNMT3A mutations frequently originated in early development - in one case occurring in utero. We demonstrate the power of applying a novel clonal tracking approach to HSCT, for the first time giving a detailed picture of the clonal dynamics of engraftment. Overall, our findings are reassuring from a safety perspective, but the different clonal composition in recipients merits further investigation to better understand the factors involved. Disclosures Manz: University of Zurich: Patents & Royalties: CD117xCD3 TEA; CDR-Life Inc: Consultancy, Current holder of stock options in a privately-held company. Campbell: Mu Genomics: Current holder of individual stocks in a privately-held company, Membership on an entity's Board of Directors or advisory committees.

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