Comprehensive translocation and clonality detection in lymphoproliferative disorders by next-generation sequencing.
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ABSTRACT:
SUBMITTER: Wren D
PROVIDER: S-EPMC5286955 | biostudies-literature | 2017 Feb
REPOSITORIES: biostudies-literature
Publications
Comprehensive translocation and clonality detection in lymphoproliferative disorders by next-generation sequencing.
Wren Dörte D Walker Brian A BA Brüggemann Monika M Catherwood Mark A MA Pott Christiane C Stamatopoulos Kostas K Langerak Anton W AW Gonzalez David D
Haematologica 20161020 2
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Project description:Clonality analysis in classic Hodgkin lymphoma (cHL) is of added value for correctly diagnosing patients with atypical presentation or histology reminiscent of T cell lymphoma, and for establishing the clonal relationship in patients with recurrent disease. However, such analysis has been hampered by the sparsity of malignant Hodgkin and Reed-Sternberg (HRS) cells in a background of reactive immune cells. Recently, the EuroClonality-NGS Working Group developed a novel next-generation sequencing (NGS)-based assay and bioinformatics platform (ARResT/Interrogate) to detect immunoglobulin (IG) gene rearrangements for clonality testing in B-cell lymphoproliferations. Here, we demonstrate the improved performance of IG-NGS compared to conventional BIOMED-2/EuroClonality analysis to detect clonal gene rearrangements in 16 well-characterized primary cHL cases within the IG heavy chain (IGH) and kappa light chain (IGK) loci. This was most obvious in formalin-fixed paraffin-embedded (FFPE) tissue specimens, where three times more clonal cases were detected with IG-NGS (9 cases) compared to BIOMED-2 (3 cases). In total, almost four times more clonal rearrangements were detected in FFPE with IG-NGS (N = 23) as compared to BIOMED-2/EuroClonality (N = 6) as judged on identical IGH and IGK targets. The same clonal rearrangements were also identified in paired fresh frozen cHL samples. To validate the neoplastic origin of the detected clonotypes, IG-NGS clonality analysis was performed on isolated HRS cells, demonstrating identical clonotypes as detected in cHL whole-tissue specimens. Interestingly, IG-NGS and HRS single-cell analysis after DEPArray™ digital sorting revealed rearrangement patterns and copy number variation profiles indicating clonal diversity and intratumoral heterogeneity in cHL. Our data demonstrate improved performance of NGS-based detection of IG gene rearrangements in cHL whole-tissue specimens, providing a sensitive molecular diagnostic assay for clonality assessment in Hodgkin lymphoma.
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Project description:Balanced chromosome rearrangements (BCRs) can cause genetic diseases by disrupting or inactivating specific genes, and the characterisation of breakpoints in disease-associated BCRs has been instrumental in the molecular elucidation of a wide variety of genetic disorders. However, mapping chromosome breakpoints using traditional methods, such as in situ hybridization with fluorescent dye-labeled bacterial artificial chromosome clones (BAC-FISH), is rather laborious and time consuming. In addition, the resolution of BAC-FISH is often insufficient to unequivocally identify the disrupted gene. To overcome these limitations, we have performed shotgun sequencing of flow-sorted derivative chromosomes using ânext generationâ (Solexa/Illumina) multiplex sequencing-by-synthesis technology. As shown here for three different disease-associated BCRs, the coverage attained by this platform is sufficient to bridge the breakpoints by PCR amplification, and this procedure allows to determine their exact nucleotide positions within few weeks. Its implementation will greatly facilitate large-scale breakpoint mapping and gene finding in patients with disease-associated balanced translocations. Array CGH was performed in three carriers of balanced translocations to exclude DNA copy number changes.
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Project description:Next-generation sequencing (NGS)-based measurable residual disease (MRD) monitoring in post-treatment settings can be crucial for relapse risk stratification in patients with B-cell and plasma cell neoplasms. Prior studies have focused on validation of various technical aspects of the MRD assays, but more studies are warranted to establish the performance characteristics and enable standardization and broad utilization in routine clinical practice. Here, the authors describe an NGS-based IGH MRD quantification assay, incorporating a spike-in calibrator for monitoring B-cell and plasma cell neoplasms based on their unique IGH rearrangement status. Comparison of MRD status (positive or undetectable) by NGS and flow cytometry (FC) assays showed high concordance (91%, 471/519 cases) and overall good linear correlation in MRD quantitation, particularly for chronic lymphocytic leukemia and B-lymphoblastic leukemia/lymphoma (R = 0.85). Quantitative correlation was lower for plasma cell neoplasms, where underestimation by FC is a known limitation. No significant effects on sequencing efficiency by the spike-in calibrator were observed, with excellent inter- and intra-assay reproducibility within the authors' laboratory, and in comparison to an external laboratory, using the same assay and protocols. Assays performed both at internal and external laboratories showed highly concordant MRD detection (100%) and quantitation (R = 0.97). Overall, this NGS-based MRD assay showed highly reproducible results with quantitation that correlated well with FC MRD assessment, particularly for B-cell neoplasms.
| S-EPMC10918645 | biostudies-literature
Project description:Next-generation DNA sequencing promises to revolutionize clinical medicine and basic research. However, while this technology has the capacity to generate hundreds of billions of nucleotides of DNA sequence in a single experiment, the error rate of ~1% results in hundreds of millions of sequencing mistakes. These scattered errors can be tolerated in some applications but become extremely problematic when "deep sequencing" genetically heterogeneous mixtures, such as tumors or mixed microbial populations. To overcome limitations in sequencing accuracy, we have developed a method termed Duplex Sequencing. This approach greatly reduces errors by independently tagging and sequencing each of the two strands of a DNA duplex. As the two strands are complementary, true mutations are found at the same position in both strands. In contrast, PCR or sequencing errors result in mutations in only one strand and can thus be discounted as technical error. We determine that Duplex Sequencing has a theoretical background error rate of less than one artifactual mutation per billion nucleotides sequenced. In addition, we establish that detection of mutations present in only one of the two strands of duplex DNA can be used to identify sites of DNA damage. We apply the method to directly assess the frequency and pattern of random mutations in mitochondrial DNA from human cells.
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Project description:NGPS is a method for de-novo, full-length protein sequencing in high throughput. The method is based on cleavage of the protein at semi-random sites by microwave-assisted acid hydrolysis (MAAH), enrichment of LC-MS/MS amenable peptides from the hydrolysate by solid-phase-extraction, LC-MS/MS analysis, de-novo long peptide tag sequencing of resulting peptides and assembly of peptide tags into consensus contigs.
2017-04-03 | PXD003804 | Pride
Project description:IntroductionThe molecular diagnosis of mitochondrial disorders is complicated by phenotypic variability, genetic heterogeneity, and the complexity of mitochondrial heteroplasmy. Next-generation sequencing (NGS) of the mitochondrial genome in combination with a targeted panel of nuclear genes associated with mitochondrial disease provides the highest likelihood of obtaining a comprehensive molecular diagnosis. To assess the clinical utility of this approach, we describe the results from a retrospective review of patients having dual genome panel testing for mitochondrial disease.MethodsDual genome panel testing by NGS was performed on a cohort of 1,509 unrelated affected individuals with suspected mitochondrial disorders. This test included 163 nuclear genes associated with mitochondrial diseases and the entire mitochondrial genome. A retrospective review was performed to evaluate diagnostic yield, disease-gene contributions, and heteroplasmy levels of pathogenic/likely pathogenic (P/LP) mitochondrial DNA (mtDNA) variants.ResultsThe overall diagnostic yield was 14.6%, with 7.7% from the nuclear genome and 6.9% from the mtDNA genome. P/LP variants in nuclear genes were enriched in both well-established genes (e.g., POLG) and more recently described genes (e.g., FBXL4), highlighting the importance of keeping the panel design updated.ConclusionVariants in nuclear and mitochondrial genomes equally contributed to a 14.6% diagnostic yield in this patient cohort. Dual genome NGS testing provides a comprehensive framework for diagnosing mitochondrial disorders, offering clinical utility that can be considered as first-tier approach compared to single genome testing. Characterizing disease-causing genes, variants, and mtDNA heteroplasmy enhances understanding of mitochondrial disorders. Testing alternative tissues can further increase diagnostic yield.
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Project description:Tumors are characterized by properties of genetic instability, heterogeneity, and significant oligoclonality. Elucidating this intratumoral heterogeneity is challenging but important. In this study, we propose a framework, BubbleTree, to characterize the tumor clonality using next generation sequencing (NGS) data. BubbleTree simultaneously elucidates the complexity of a tumor biopsy, estimating cancerous cell purity, tumor ploidy, allele-specific copy number, and clonality and represents this in an intuitive graph. We further developed a three-step heuristic method to automate the interpretation of the BubbleTree graph, using a divide-and-conquer strategy. In this study, we demonstrated the performance of BubbleTree with comparisons to similar commonly used tools such as THetA2, ABSOLUTE, AbsCN-seq and ASCAT, using both simulated and patient-derived data. BubbleTree outperformed these tools, particularly in identifying tumor subclonal populations and polyploidy. We further demonstrated BubbleTree's utility in tracking clonality changes from patients' primary to metastatic tumor and dating somatic single nucleotide and copy number variants along the tumor clonal evolution. Overall, the BubbleTree graph and corresponding model is a powerful approach to provide a comprehensive spectrum of the heterogeneous tumor karyotype in human tumors. BubbleTree is R-based and freely available to the research community (https://www.bioconductor.org/packages/release/bioc/html/BubbleTree.html).
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