Integration of Technical, Bioinformatic, and Variant Assessment Approaches in the Validation of a Targeted Next-Generation Sequencing Panel for Myeloid Malignancies

Context.— Detection of variants in hematologic malignancies is increasingly important because of a growing number of variants impacting diagnosis, prognosis, and treatment response, and as potential therapeutic targets. The use of next-generation sequencing technologies to detect variants in hematologic malignancies in a clinical diagnostic laboratory setting allows for efficient identification of routinely tested markers in multiple genes simultaneously, as well as the identification of novel and rare variants in other clinically relevant genes. Objective.— To apply a systematic approach to evaluate and validate a commercially available next-generation sequencing panel (TruSight Myeloid Sequencing Panel, Illumina, San Diego, California) targeting 54 genes. In this manuscript, we focused on the parameters that were used to evaluate assay performance characteristics. Data Sources.— Analytical validation was performed using samples containing known variants that had been identified previously. Cases were selected from different disease types, with variants in a range of genes. Panel performance characteristics were assessed and genomic regions requiring additional analysis or wet-bench approaches identified. Conclusions.— We validated the performance characteristics of a myeloid next-generation sequencing panel for detection of variants. The TruSight Myeloid Sequencing Panel covers more than 95% of target regions with depth greater than 500×. However, because of unique variant types such as large insertions or deletions or genomic regions of high GC content, variants in CEBPA, FLT3, and CALR required supplementation with non–next-generation sequencing assays or with informatics approaches to address deficiencies in performance. The use of multiple bioinformatics approaches (2 variant callers and informatics scripts) allows for maximizing calling of true positives, while identifying limitations in using either method alone.

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The efficacy of targeted next-generation sequencing for detection of clinically actionable mutations in cancer.

Journal of Clinical Oncology ◽

10.1200/jco.2012.30.15_suppl.10598 ◽

2012 ◽

Vol 30 (15_suppl) ◽

pp. 10598-10598

Author(s):

Yu-Ye Wen ◽

Erica Fang ◽

Yanchun Li ◽

Condie Edwin Carmack ◽

Marilyn M. Li

Keyword(s):

Next Generation Sequencing ◽

Sanger Sequencing ◽

Cancer Gene ◽

Cancer Genes ◽

Next Generation ◽

Clinical Diagnostic Laboratory ◽

Kras Mutations ◽

Diagnostic Laboratory ◽

Turn Around Time ◽

Generation Sequencing

10598 Background: The emergence of next-generation sequencing (NGS) technologies has significantly accelerated the identification of cancer-causing mutations and the development of personalized cancer care. However, the clinical application of these technologies to detect cancer gene mutations has been extremely limited due to the long turn around time, the high cost, and large amount of input DNA required by existing NGS-based tests. Methods: We have assessed the performance of a novel NGS technology that merges multiplex PCR with ion semiconductor sequencing (AmpliSeq, Life Technologies, Inc.) in our clinical diagnostic laboratory. The test interrogates 739 common mutations in 46 cancer genes including many clinically actionable mutations concurrently. First, we studied 12 tumor samples including 4 archived FFPE, 4 blood/bone marrow, and 4 cell line samples with known mutations to evaluate the sensitivity and specificity of the test. We then studied 34 de-identified, archived FFPE tumor samples of unknown genotype to further evaluate the efficacy of the test. Results: We successfully identified all known mutations previously detected by Pyposequencing or Sanger sequencing technologies. Multiple serial dilution studies showed that the test could detect mutations at frequencies as low as 5% with 99% confidence. For the samples of unknown genotype, we detected 23 COSMIC mutations in 16 samples including HRAS, BRAF, MET, TP53 mutations in lung cancer, KRAS, PIK3CA, TP53, APC, BRAF, ERBB2 mutations in colon cancer, TP53 and KRAS mutations in breast cancer, and KIT and PDGFRA mutations in GIST. Analysis of the variant call data showed that a minimum of 100X coverage is required in order to detect mutations at 10% frequency or above; a minimum 300K final library reads are necessary in order to minimize/eliminate amplicon dropout. Conclusions: The targeted NGS test can effectively detect cancer gene mutation with input DNA as low as a few nanograms, turn around time can be as short as two days, and can significantly lower cost compared to traditional Sanger sequencing. Our experience demonstrates that this technology holds great potential for clinical use, including diagnostic and therapeutic applications.

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An enhanced method for targeted next generation sequencing copy number variant detection using ExomeDepth

Wellcome Open Research ◽

10.12688/wellcomeopenres.11548.1 ◽

2017 ◽

Vol 2 ◽

pp. 49

Author(s):

Andrew Parrish ◽

Richard Caswell ◽

Garan Jones ◽

Christopher M. Watson ◽

Laura A. Crinnion ◽

...

Keyword(s):

Next Generation Sequencing ◽

Copy Number ◽

Gc Content ◽

Read Depth ◽

Next Generation ◽

Clinical Diagnostic Laboratory ◽

Targeted Next Generation Sequencing ◽

Clinical Diagnostic ◽

Depth Analysis ◽

Generation Sequencing

Copy number variants (CNV) are a major cause of disease, with over 30,000 reported in the DECIPHER database. To use read depth data from targeted Next Generation Sequencing (NGS) panels to identify CNVs with the highest degree of sensitivity, it is necessary to account for biases inherent in the data. GC content and ambiguous mapping due to repetitive sequence elements and pseudogenes are the principal components of technical variability. In addition, the algorithms used favour the detection of multi-exon CNVs, and rely on suitably matched normal dosage samples for comparison. We developed a calling strategy that subdivides target intervals, and uses pools of historical control samples to overcome these limitations in a clinical diagnostic laboratory. We compared our enhanced strategy with an unmodified pipeline using the R software package ExomeDepth, using a cohort of 109 heterozygous CNVs (91 deletions, 18 duplications in 26 genes), including 25 single exon CNVs. The unmodified pipeline detected 104/109 CNVs, giving a sensitivity of 89.62% to 98.49% at the 95% confidence interval. The detection of all 109 CNVs by our enhanced method demonstrates 95% confidence the sensitivity is ≥96.67%, allowing NGS read depth analysis to be used for CNV detection in a clinical diagnostic setting.

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Unbiased machine learning methods to predict the limitations of variant calling in homologous genomic regions using next-generation sequencing

Molecular Genetics and Metabolism ◽

10.1016/s1096-7192(21)00467-4 ◽

2021 ◽

Vol 132 ◽

pp. S250-S252

Author(s):

Feng Li ◽

Rohan Gnanaolivu ◽

Noemi Vidal-Folch ◽

Neiladri Saha ◽

Nipun Mistry ◽

...

Keyword(s):

Machine Learning ◽

Next Generation Sequencing ◽

Variant Calling ◽

Next Generation ◽

Learning Methods ◽

Machine Learning Methods ◽

Genomic Regions ◽

Generation Sequencing

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Applications of next-generation sequencing in hematologic malignancies

Human Immunology ◽

10.1016/j.humimm.2021.02.006 ◽

2021 ◽

Author(s):

Lori A. Ramkissoon ◽

Nathan D. Montgomery

Keyword(s):

Next Generation Sequencing ◽

Hematologic Malignancies ◽

Next Generation ◽

Generation Sequencing

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Next-Generation Sequencing Studies: Optimal Design and Analysis, Missing Heritability and Rare Variants

Current Epidemiology Reports ◽

10.1007/s40471-014-0022-4 ◽

2014 ◽

Vol 1 (4) ◽

pp. 213-219 ◽

Cited By ~ 2

Author(s):

Paul Marjoram ◽

Duncan C. Thomas

Keyword(s):

Next Generation Sequencing ◽

Optimal Design ◽

Rare Variants ◽

Next Generation ◽

Missing Heritability ◽

Sequencing Studies ◽

Generation Sequencing

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Clinical Application of Metagenomic Next-Generation Sequencing in Patients with Hematologic Malignancies Suffering from Sepsis

Microorganisms ◽

10.3390/microorganisms9112309 ◽

2021 ◽

Vol 9 (11) ◽

pp. 2309

Author(s):

Wang-Da Liu ◽

Ting-Yu Yen ◽

Po-Yo Liu ◽

Un-In Wu ◽

Prerana Bhan ◽

...

Keyword(s):

Next Generation Sequencing ◽

Hematologic Malignancies ◽

Blood Cultures ◽

Diagnostic Methods ◽

Next Generation ◽

Viral Loads ◽

A Prospective Study ◽

Positive Results ◽

Serology Testing ◽

Generation Sequencing

Background: Sepsis remains a common but fatal complication among patients with immune suppression. We aimed to investigate the performance of metagenomic next-generation sequencing (mNGS) compared with standard microbiological diagnostics in patients with hematologic malignancies. Methods: We performed a prospective study from June 2019 to December 2019. Adult patients with hematologic malignancies and a clinical diagnosis of sepsis were enrolled. Conventional diagnostic methods included blood cultures, serum galactomannan for Aspergillus, cryptococcal antigen and cytomegalovirus (CMV) viral loads. Blood samples for mNGS were collected within 24 h after hypotension developed. Results: Of 24 patients enrolled, mNGS and conventional diagnostic methods (blood cultures, serology testing and virus RT-PCR) reached comparable positive results in 9 cases. Of ten patients, mNGS was able to identify additional pathogens compared with conventional methods; most of the pathogens were virus. Conclusion: Our results show that mNGS may serve as adjunctive diagnostic tool for the identification of pathogens of hematologic patients with clinically sepsis.

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Identification of Genetic Hereditary Predisposition to Hematologic Malignancies By Clinical Next-Generation Sequencing

Blood ◽

10.1182/blood.v126.23.3854.3854 ◽

2015 ◽

Vol 126 (23) ◽

pp. 3854-3854 ◽

Cited By ~ 2

Author(s):

Amy E Knight Johnson ◽

Lucia Guidugli ◽

Kelly Arndt ◽

Gorka Alkorta-Aranburu ◽

Viswateja Nelakuditi ◽

...

Keyword(s):

Next Generation Sequencing ◽

Sanger Sequencing ◽

Family Members ◽

Hematologic Malignancies ◽

Dyskeratosis Congenita ◽

Molecular Diagnostic ◽

Next Generation ◽

Hereditary Predisposition ◽

Ngs Data ◽

Generation Sequencing

Abstract Introduction: Myelodysplastic syndrome (MDS) and acute leukemia (AL) are a clinically diverse and genetically heterogeneous group of hematologic malignancies. Familial forms of MDS/AL have been increasingly recognized in recent years, and can occur as a primary event or secondary to genetic syndromes, such as inherited bone marrow failure syndromes (IBMFS). It is critical to confirm a genetic diagnosis in patients with hereditary predisposition to hematologic malignancies in order to provide prognostic information and cancer risk assessment, and to aid in identification of at-risk or affected family members. In addition, a molecular diagnosis can help tailor medical management including informing the selection of family members for allogeneic stem cell transplantation donors. Until recently, clinical testing options for this diverse group of hematologic malignancy predisposition genes were limited to the evaluation of single genes by Sanger sequencing, which is a time consuming and expensive process. To improve the diagnosis of hereditary predisposition to hematologic malignancies, our CLIA-licensed laboratory has recently developed Next-Generation Sequencing (NGS) panel-based testing for these genes. Methods: Thirty six patients with personal and/or family history of aplastic anemia, MDS or AL were referred for clinical diagnostic testing. DNA from the referred patients was obtained from cultured skin fibroblasts or peripheral blood and was utilized for preparing libraries with the SureSelectXT Enrichment System. Libraries were sequenced on an Illumina MiSeq instrument and the NGS data was analyzed with a custom bioinformatic pipeline, targeting a panel of 76 genes associated with IBMFS and/or familial MDS/AL. Results: Pathogenic and highly likely pathogenic variants were identified in 7 out of 36 patients analyzed, providing a positive molecular diagnostic rate of 20%. Overall, 6 out of the 7 pathogenic changes identified were novel. In 2 unrelated patients with MDS, heterozygous pathogenic sequence changes were identified in the GATA2 gene. Heterozygous pathogenic changes in the following autosomal dominant genes were each identified in a single patient: RPS26 (Diamond-Blackfan anemia 10), RUNX1 (familial platelet disorder with propensity to myeloid malignancy), TERT (dyskeratosis congenita 4) and TINF2 (dyskeratosis congenita 3). In addition, one novel heterozygous sequence change (c.826+5_826+9del, p.?) in the Fanconi anemia associated gene FANCA was identified. . The RNA analysis demonstrated this variant causes skipping of exon 9 and results in a premature stop codon in exon 10. Further review of the NGS data provided evidence of an additional large heterozygous multi-exon deletion in FANCA in the same patient. This large deletion was confirmed using array-CGH (comparative genomic hybridization). Conclusions: This study demonstrates the effectiveness of using NGS technology to identify patients with a hereditary predisposition to hematologic malignancies. As many of the genes associated with hereditary predisposition to hematologic malignancies have similar or overlapping clinical presentations, analysis of a diverse panel of genes is an efficient and cost-effective approach to molecular diagnostics for these disorders. Unlike Sanger sequencing, NGS technology also has the potential to identify large exonic deletions and duplications. In addition, RNA splicing assay has proven to be helpful in clarifying the pathogenicity of variants suspected to affect splicing. This approach will also allow for identification of a molecular defect in patients who may have atypical presentation of disease. Disclosures No relevant conflicts of interest to declare.

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