A Second Generation, Multiple Myeloma-Specific, Targeted Sequencing Platform for Detecting Translocations, Copy Number Alterations, and Single Nucleotide Variants

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 4207-4207
Author(s):  
Brian S White ◽  
Irena Lanc ◽  
Daniel Auclair ◽  
Robert Fulton ◽  
Mark A Fiala ◽  
...  

Abstract Background: Multiple myeloma (MM) is a hematologic cancer characterized by a diversity of genetic lesions-translocations, copy number alterations (CNAs), and single nucleotide variants (SNVs). The prognostic value of translocations and of CNAs has been well established. Determining the clinical significance of SNVs, which are recurrently mutated at much lower frequencies, and how this significance is impacted by translocations and CNAs requires additional, large-scale correlative studies. Such studies can be facilitated by cost-effective targeted sequencing approaches. Hence, we designed a single-platform targeted sequencing approach capable of detecting all three variant types. Methods: We designed oligonucleotide probes complementary to the coding regions of 467 genes and to the IgH and MYC loci, allowing a probe to closely match at most 5 regions within the genome. Genes were selected if they were expressed in an independent RNA-seq MM data set and harbored germline SNP-filtered variants that: (1) occurred with frequency >3%, (2) were clustered in hotspots, (3) occurred in recurrently mutated "cancer genes" (as annotated in COSMIC or MutSig), or (4) occurred in genes involved in DNA repair and/or B-cell biology. IgH and MYC tiling was unbiased (with respect to annotated features within the loci) and spanned from 50 kilobasepairs (kbps) upstream of both regions to 50 kbps downstream of IgH and 100 kbps downstream of MYC. Results: We performed targeted sequencing of 96 CD138-enriched samples derived from MM patients, as well as matched peripheral blood leukocyte normal controls. Sequencing depth (mean 107X) was commensurate with that of available exome sequencing data from these samples (mean 71X). Samples harbored a mean of 25 non-silent variants, including those in known MM-associated genes: NRAS (24%), KRAS (22%), FAM46C (17%), TP53 (10%), DIS3 (8%), and BRAF (3%). Variants detected by both platforms showed a strong correlation (r^2 = 0.8). The capture array detected activating, oncogenic variants in NRAS Q61K (n=3 patients) and KRAS G12C/D/R/V (n=5) that were not detected in exome data. Additionally, we found non-silent, capture-specific variants in MTOR (3%) and in two transcription-related genes that have been previously implicated in cancer: ZFHX4 (5%) and CHD3 (5%). To assess the potential role of deep subclonal variants and our ability to detect them, we performed additional sequencing (mean 565X) on six of the tumor/normal pairs. This revealed 14 manually-reviewed, non-silent variants that were not detected by the initial targeted sequencing. These had a mean variant allele frequency of 2.8% and included mutations in DNMT3A and FAM46C. At least one of these 14 variants occurred in five of the six re-sequenced samples. This highlights the importance of this additional depth, which will be used in future studies. Our approach successfully detected CNAs near expected frequencies, including hyperdiploidy (52%), del(13) (43%), and gain of 1q (35%). Similarly, it inferred IgH translocations at expected frequencies: t(4;14) (14%), t(6;14) (3%), t(11;14) (15%), and t(14;20) (1%). As expected, translocations occur predominantly within the IgH constant region, but also frequently 5' (i.e., telomeric) of the IGHM switch region, and occasionally within the V and D regions. We detected MYC -associated translocations, whose frequencies have been the subject of debate, at 10% (n=9 patients), with five involving IgH, three having both partners in or near MYC, and one having both types. Finally, our platform detected novel IgH translocations with partners near DERL3 (n=2), MYCN (n=1), and FLT3 (n=1). Additional evidence suggests that DERL3 and MYCN may be targets of IgH-induced overexpression: of 84 RNA-seq patient samples, six exhibited outlying expression of DERL3, including one sample in which we detected the translocation in corresponding DNA, and one exhibited outlying expression of MYCN. Conclusion: Our MM-specific targeted sequencing strategy is capable of detecting deeply subclonal SNVs, in addition to CNAs and IgH and MYC translocations. Though additional validation is required, particularly with respect to translocation detection, we anticipate that such technology will soon enable clinical testing on a single sequencing platform. Disclosures Vij: Celgene, Onyx, Takeda, Novartis, BMS, Sanofi, Janssen, Merck: Consultancy; Takeda, Onyx: Research Funding.

2020 ◽  
Vol 144 (12) ◽  
pp. 1535-1546
Author(s):  
Kyung Park ◽  
Hung Tran ◽  
Kenneth W. Eng ◽  
Sinan Ramazanoglu ◽  
Rebecca M. Marrero Rolon ◽  
...  

Context.— An increasing number of molecular laboratories are implementing next-generation sequencing platforms to identify clinically actionable and relevant genomic alterations for precision oncology. Objective.— To describe the validation studies as per New York State–Department of Health (NYS-DOH) guidelines for the Oncomine Comprehensive Panel v2, which was originally tailored to the National Cancer Institute Molecular Analysis for Therapy Choice (NCI-MATCH) trial. Design.— Accuracy, precision, and reproducibility were investigated by using 130 DNA and 18 RNA samples from cytology cell blocks; formalin-fixed, paraffin-embedded tissues; and frozen samples. Analytic sensitivity and specificity were tested by using ATCC and HapMap cell lines. Results.— High accuracy and precision/reproducibility were observed for single nucleotide variants and insertion/deletions. We also share our experience in the detection of gene fusions and copy number alterations from an amplicon-based sequencing platform. After sequencing analysis, variant annotation and report generation were performed by using the institutional knowledgebase. Conclusions.— This study serves as an example for validating a comprehensive targeted next-generation sequencing assay with both DNASeq and RNASeq components for NYS-DOH.


2021 ◽  
Author(s):  
Ryunosuke Saiki ◽  
Yukihide Momozawa ◽  
Yasuhito Nannya ◽  
Masahiro M Nakagawa ◽  
Yotaro Ochi ◽  
...  

AbstractImplicated in the development of hematological malignancies (HM) and cardiovascular mortality, clonal hematopoiesis (CH) in apparently healthy individuals has been investigated by detecting either single-nucleotide variants and indels (SNVs/indels) or copy number alterations (CNAs), but not both. Here by combining targeted sequencing of 23 CH-related genes and array-based CNA detection of blood-derived DNA, we have delineated the landscape of CH-related SNVs/indels and CNAs in a general population of 11,234 individuals, including 672 with subsequent HM development. Both CH-related lesions significantly co-occurred, which combined, affected blood count, hypertension, and the mortality from HM and cardiovascular diseases depending on the total number of both lesions, highlighting the importance of detecting both lesions in the evaluation of CH.


2018 ◽  
Author(s):  
Riccardo Panero ◽  
Maddalena Arigoni ◽  
Martina Olivero ◽  
Francesca Cordero ◽  
Alessandro Weisz ◽  
...  

AbstractBackgroundRNA-seq represents an attractive methodology for the detection of functional genomic variants because it allows the integration of variant frequency and their expression. However, although specific statistic frameworks have been designed to detect SNVs/INDELS/gene fusions in RNA-seq data, very little has been done to understand the effect of library preparation protocols on transcript variant detection in RNA-seq data.ResultsHere, we compared RNA-seq results obtained on short reads sequencing platform with two protocols: one based on polyA+ RNA selection protocol (POLYA) and the other based on exonic regions capturing protocol (ACCESS). Our data indicate that ACCESS detects 10% more coding SNV/INDELs with respect to POLYA, making this protocol more suitable for this goal. Furthermore, ACCESS requires less reads for coding SNV detection with respect to POLYA. On the other hand, if the analysis aims at identifying SNV/INDELs also in the 5’and 3’ UTRs, POLYA is definitively the preferred method. No particular advantage comes from the usage of ACCESS or POLYA in the detection of fusion transcripts.ConclusionData show that a careful selection of the “wet” protocol adds specific features that cannot be obtained with bioinformatics alone.


Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 580-580
Author(s):  
Laura Schuettpelz ◽  
Daniel C. Link ◽  
Dong Shen ◽  
Matthew J. Walter ◽  
Daniel C Koboldt ◽  
...  

Abstract Abstract 580 Therapy-related acute myeloid leukemia/myelodysplasia (t-AML/t-MDS) accounts for 10–20% of all cases of AML, and its incidence is rising. Treatment options are limited and the prognosis very poor, highlighting the need for new therapies in t-AML/t-MDS. However, the genetic mutations contributing to transformation in t-AML/t-MDS are largely unknown, limiting the development of novel targeted therapeutics. Our group previously reported the sequence of the first two cancer genomes, both in patients with de novo AML (Nature 456:66, 2008; NEJM 361:1058, 2009). Herein, we report the sequence of the cancer genome of a patient with t-AML. The patient presented with early-onset breast, then ovarian cancer (age <40), and was treated with surgery, radiation and combination chemotherapy (cytoxan, etoposide, adriamycin, carboplatinum and taxol). Clinical sequencing of BRCA1 and BRCA2 revealed no mutations. Four years later, recurrence of her ovarian cancer was detected and she again was treated with chemotherapy. Two months after completing this chemotherapy, she presented with t-AML and respiratory failure, and she died 8 days after presentation. Typical of t-AML, the karyotype of this leukemia was complex, with -7, del(5q), and several marker chromosomes that could not be resolved with standard cytogenetic analysis. Bone marrow and a skin biopsy were obtained after informed consent and analyzed in the following ways: 1) whole genome sequencing of leukemic bone marrow and skin DNA on the Illumina platform using paired end reads with an average read length of 75 bp; 2) SNP genotyping on the Affymetrix 6.0 array (on leukemic and skin DNA) to detect copy number alterations and uniparental disomy; 3) RNA expression profiling using the Affymetrix Exon 1.0 array; 4) spectral karyotyping. For the leukemic sample, a total of 115 Gb of sequence was obtained (28.7X haploid coverage). Based on SNP genotyping, >96% of heterozygous SNPs were detected. Similar data were obtained for the skin sample. A total of 27 validated somatic single nucleotide variants or indels were detected in coding sequences. None of these mutations have been previously reported in de novo AML. Eight novel chromosomal translocations were identified and the breakpoints defined. One translocation, t(3;4)(q27.3;p15.32), resulted in the production of an in frame fusion transcript of DGKG (diacylglycerol kinase gamma) with BST1 (bone marrow cell stromal antigen 1). Studies are underway to characterize the effect of this fusion gene on hematopoietic cell growth and differentiation. In addition to -7 and del(5q), somatic copy number alterations on chromosome 3 and 12 were identified. There is controversy whether haploinsufficiency of genes on chromosomes 7 and 5q is sufficient to contribute to transformation, or whether further mutations lead to loss of heterozygosity of one or more genes in these regions. In the present case, careful review of the sequence and array data revealed no ‘homozygous' somatic single nucleotide variants, indels, or copy number alterations of coding genes on the remaining copy of chromosome 5 or 7. The patient's clinical presentation strongly suggested genetic cancer susceptibility. Analysis of the skin genome of this patient identified a heterozygous deletion of exons 7–9 of TP53, likely contributing to the early onset of her breast cancer; a uniparental disomy event resulted in the deletion being homozygous in the leukemia sample. Interestingly, the mutant TP53 allele is expressed, and it is predicted to produce a truncated p53 protein lacking most of its DNA binding domain. Functional studies of the mutant p53 protein are underway. Of note, based on a detailed family history and genotyping of the patient's mother, we suspect that the TP53 deletion occurred spontaneously. Ongoing whole genome sequencing studies in a large number of t-AML samples should identify novel somatic mutations and germline variants that contribute to t-AML. Disclosures: No relevant conflicts of interest to declare.


2018 ◽  
Author(s):  
S Abujudeh ◽  
SS Zeki ◽  
MCV van Lanschot ◽  
M Pusung ◽  
JMJ Weaver ◽  
...  

AbstractLarge-scale cancer genome studies suggest that tumors are driven by somatic copy number alterations (SCNAs) or single-nucleotide variants (SNVs). Due to the low-cost, the clinical use of genomics assays is biased towards targeted gene panels, which identify SNVs. There is a need for a comparably low-cost and simple assay for high-resolution SCNA profiling. Here we present our method, conliga, which infers SCNA profiles from a low-cost and simple assay.


2021 ◽  
Author(s):  
Ryunosuke Saiki ◽  
Yukihide Momozawa ◽  
Yasuhito Nannya ◽  
Masahiro M. Nakagawa ◽  
Yotaro Ochi ◽  
...  

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 4442-4442
Author(s):  
Alexander Höllein ◽  
Sven O. Twardziok ◽  
Wencke Walter ◽  
Stephan Hutter ◽  
Jesús María Hernández ◽  
...  

Abstract Background: The diagnosis and risk stratification of multiple myeloma (MM) is based on clinical and cytogenetic tests. Magnetic CD138 enrichment followed by interphase FISH is the gold standard to identify prognostic translocations and copy number alterations. Gene expression (GEP) studies show that MM might consist of various subgroups with distinct clinical outcomes (Zhan et al., Blood 2006). Whole genome sequencing (WGS) and targeted sequencing studies have further shed light onto recurrent mutations in MM and clinical implications are being derived (Lohr et al., Cancer Cell 2014). We set up a single workflow to analyze MM by WGS and RNA-Seq to evaluate whether this diagnostic workup is superior to conventional diagnostic testing. Methods: The cohort comprised 211 patients (pts) diagnosed with MM at our institution from 2011 to 2017. For all pts FISH and WGS was performed on CD138 enriched cells. For WGS 150bp paired-end sequences where generated on Illumina HiseqX and NovaSeq 6000 (Illumina, San Diego, CA). A mixture genomic DNA from multiple anonymous donors was used as normal controls. To remove potential germline variants, each variant was queried against the gnomAD database, variants with global population frequencies >1% where excluded. 47 genes recurrently mutated in MM were selected for evaluation (Kortüm et. al., Blood 2016). Copy number alterations (CNAs) were called using GATK4 and structural variations (SVs) were called using MANTA accounting for missing matched-normal samples. For transcriptome analysis total RNA was sequenced and the resulting estimated gene counts were pre-processed and normalized, applying trimmed mean of M-values normalization method. Results: WGS allowed us to detect 98/102 (96%) translocations that had previously been identified by FISH. Specifically we confirmed 24/24 of t(4;14), 6/7 of t(6;14), 11/12 of t(8;14), 51/53 of t(11;14) and 6/6 of t(14;16) cases by WGS. Moreover, by conventional FISH 12 pts had an IGH (n=4) or MYC (n=8) translocation with an unknown partner chromosome. We identified all 12 translocations by WGS. By WGS we also identified 679/740 (92 %) copy number alterations (CNA) detected by FISH. In detail these were 100/103 del(13q), 17/21 del(17p), 10/10 del(1p) and 79/87 +1q. Concordance rates for trisomies 3, 5, 9, 11, 15 and 19 were 80/91, 75/87, 92/97, 87/97, 53/55 and 86/92, respectively. Zhan et al. defined 7 MM subgroups (CD-1, CD-2, HY, MF, MS, LB, PR) based on GEP. 4 groups (CD-1/CD-2, MF, MS) were genetically defined by recurrent translocations and 1 by hyperploidy (HY). They used 700 probes to separate the groups of which 400 transcripts were recovered in our RNA-Seq analysis (GEPSeq). Supervised clustering grouped all 211 pts at the following frequencies: CD-1 (5%), CD-2 (25%), HY (30%), MF (5%), MS (11%), LB (14%), (PR 10%). 56/62 (90%) of pts that were allocated to CD-1/CD-2 had the characteristic translocation (t(11;14) or t(6;14)), while 23/24 (92%) of pts and 5/10 (50%) pts in GEPSeq group MS and MF had the respective t(4;14) or t(14;16). GEP allocates pts with hyperdiploidy to group HY and 51/63 (81%) pts in HY had a hyperdiploid karyotype by FISH. We specifically queried the WGS data for patients with discrepant FISH and GEPSeq results: WGS identified hyperdiploidy in 10/12 patients that were allocated to HY and could not be assigned by FISH due to insufficient material for complete testing, resulting in a 97% final concordance of GEPSeq and karyotype. One patient in group MS without FISH data for t(4;14) could be confirmed by WGS as harbouring the translocation (concordance 100%). Interestingly in 5/5 patients that were allocated to the MF group by GEPSeq 2 had an IGH-MYC or IGH-MYCN rearrangement respectively and 2 had another IGH rearrangement involving chromosome 8q. By WGS the most frequently mutated (mut) genes were KRAS (26%), NRAS (23 %), TP53 (8%), BRAF (4%) and ATM (2%), which is in line with published data (Lohr 2014). NRASmut was significantly associated with GEPSeq groups CD-2 and HY (p=0.001) and ATMmut with MF, MS and PR (p=0.047). Conclusion: RNA-Seq and WGS prove highly valuable in differentiating genetically distinct MM subgroups. The simultaneous analysis of gene mutations might have future implications for study design and selecting treatment options. A single workflow based on WGS and RNA-Seq provides a comprehensive genetic analysis in MM, is feasible and might substitute conventional diagnostic testing in the near future. Disclosures Höllein: MLL Munich Leukemia Laboratory: Employment. Twardziok:MLL Munich Leukemia Laboratory: Employment. Walter:MLL Munich Leukemia Laboratory: Employment. Hutter:MLL Munich Leukemia Laboratory: Employment. Hernández:MLL Munich Leukemia Laboratory: Employment. Meggendorfer:MLL Munich Leukemia Laboratory: Employment. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.


2021 ◽  
Vol 11 (1) ◽  
pp. 33
Author(s):  
Nayoung Han ◽  
Jung Mi Oh ◽  
In-Wha Kim

For predicting phenotypes and executing precision medicine, combination analysis of single nucleotide variants (SNVs) genotyping with copy number variations (CNVs) is required. The aim of this study was to discover SNVs or common copy CNVs and examine the combined frequencies of SNVs and CNVs in pharmacogenes using the Korean genome and epidemiology study (KoGES), a consortium project. The genotypes (N = 72,299) and CNV data (N = 1000) were provided by the Korean National Institute of Health, Korea Centers for Disease Control and Prevention. The allele frequencies of SNVs, CNVs, and combined SNVs with CNVs were calculated and haplotype analysis was performed. CYP2D6 rs1065852 (c.100C>T, p.P34S) was the most common variant allele (48.23%). A total of 8454 haplotype blocks in 18 pharmacogenes were estimated. DMD ranked the highest in frequency for gene gain (64.52%), while TPMT ranked the highest in frequency for gene loss (51.80%). Copy number gain of CYP4F2 was observed in 22 subjects; 13 of those subjects were carriers with CYP4F2*3 gain. In the case of TPMT, approximately one-half of the participants (N = 308) had loss of the TPMT*1*1 diplotype. The frequencies of SNVs and CNVs in pharmacogenes were determined using the Korean cohort-based genome-wide association study.


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