Search

Chromosomal microarray testing is indicated for patients with diagnoses including unexplained developmental delay or intellectual disability, autism spectrum disorders, and multiple congenital anomalies. The short multiply aggregated sequence homologies (SMASH) genomic assay is a novel next-generation sequencing technology that performs copy number analysis at resolution similar to high-coverage whole genome sequencing but requires far less capacity. We benchmarked the performance of SMASH on a panel of genomic DNAs containing known copy number variants (CNVs). SMASH was able to detect pathogenic copy number variants of ≥10 kb in 77 of 77 samples. No pathogenic events were seen in 32 of 32 controls, indicating 100% sensitivity and specificity for detecting pathogenic CNVs >10 kb. Repeatability (interassay precision) and reproducibility (intra-assay precision) were assessed with 13 samples and showed perfect concordance. We also established that SMASH had a limit of detection of 20% for detection of large mosaic CNVs. Finally, we analyzed seven blinded specimens by SMASH analysis and successfully identified all pathogenic events. These results establish the efficacy of the SMASH genomic assay as a clinical test for the detection of pathogenic copy number variants at a resolution comparable to chromosomal microarray analysis., (Copyright © 2020 Association for Molecular Pathology and American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.)

Clinical whole-genome sequencing (WGS) offers clear diagnostic benefits for patients with rare disease. However, there are barriers to its widespread adoption, including a lack of standards for clinical practice. The Medical Genome Initiative consortium was formed to provide practical guidance and support the development of standards for the use of clinical WGS.

To test the performance of a new sequencing platform, develop an updated somatic calling pipeline and establish a reference for future benchmarking experiments, we performed whole-genome sequencing of 3 common cancer cell lines (COLO-829, HCC-1143 and HCC-1187) along with their matched normal cell lines to great sequencing depths (up to 278x coverage) on both Illumina HiSeqX and NovaSeq sequencing instruments. Somatic calling was generally consistent between the two platforms despite minor differences at the read level. We designed and implemented a novel pipeline for the analysis of tumor-normal samples, using multiple variant callers. We show that coupled with a high-confidence filtering strategy, the use of combination of tools improves the accuracy of somatic variant calling. We also demonstrate the utility of the dataset by creating an artificial purity ladder to evaluate the somatic pipeline and benchmark methods for estimating purity and ploidy from tumor-normal pairs. The data and results of the pipeline are made accessible to the cancer genomics community.

Background: Prompted by the revolution in high-throughput sequencing and its potential impact for treating cancer patients, we initiated a clinical research study to compare the ability of different sequencing assays and analysis methods to analyze glioblastoma tumors and generate real-time potential treatment options for physicians., Methods: A consortium of seven institutions in New York City enrolled 30 patients with glioblastoma and performed tumor whole genome sequencing (WGS) and RNA sequencing (RNA-seq; collectively WGS/RNA-seq); 20 of these patients were also analyzed with independent targeted panel sequencing. We also compared results of expert manual annotations with those from an automated annotation system, Watson Genomic Analysis (WGA), to assess the reliability and time required to identify potentially relevant pharmacologic interventions., Results: WGS/RNAseq identified more potentially actionable clinical results than targeted panels in 90% of cases, with an average of 16-fold more unique potentially actionable variants identified per individual; 84 clinically actionable calls were made using WGS/RNA-seq that were not identified by panels. Expert annotation and WGA had good agreement on identifying variants [mean sensitivity = 0.71, SD = 0.18 and positive predictive value (PPV) = 0.80, SD = 0.20] and drug targets when the same variants were called (mean sensitivity = 0.74, SD = 0.34 and PPV = 0.79, SD = 0.23) across patients. Clinicians used the information to modify their treatment plan 10% of the time., Conclusion: These results present the first comprehensive comparison of technical and machine augmented analysis of targeted panel and WGS/RNA-seq to identify potential cancer treatments.

We developed and validated a clinical whole-genome and transcriptome sequencing (WGTS) assay that provides a comprehensive genomic profile of a patient's tumor. The ability to fully capture the mappable genome with sufficient sequencing coverage to precisely call DNA somatic single nucleotide variants, insertions/deletions, copy number variants, structural variants, and RNA gene fusions was analyzed. New York State's Department of Health next-generation DNA sequencing guidelines were expanded for establishing performance validation applicable to whole-genome and transcriptome sequencing. Whole-genome sequencing laboratory protocols were validated for the Illumina HiSeq X Ten platform and RNA sequencing for Illumina HiSeq2500 platform for fresh or frozen and formalin-fixed, paraffin-embedded tumor samples. Various bioinformatics tools were also tested, and CIs for sensitivity and specificity thresholds in calling clinically significant somatic aberrations were determined. The validation was performed on a set of 125 tumor normal pairs. RNA sequencing was performed to call fusions and to confirm the DNA variants or exonic alterations. Here, we present our results and WGTS standards for variant allele frequency, reproducibility, analytical sensitivity, and present limit of detection analysis for single nucleotide variant calling, copy number identification, and structural variants. We show that The New York Genome Center WGTS clinical assay can provide a comprehensive patient variant discovery approach suitable for directed oncologic therapeutic applications., (Copyright © 2018 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.)

Next-generation DNA sequencing (NGS) technologies are currently being applied in both research and clinical settings for the understanding and management of disease. The goal is to use high-throughput sequencing to identify specific variants that drive tumorigenesis within each individual's tumor genomic profile. The significance of copy number and structural variants in glioblastoma makes it essential to broaden the search beyond oncogenic single nucleotide variants toward whole genome profiles of genetic aberrations that may contribute to disease progression. The heterogeneity of glioblastoma and its variability of cancer driver mutations necessitate a more robust examination of a patient's tumor genome. Here, we present patient whole genome sequencing (WGS) information to identify oncogenic structural variants that may contribute to glioblastoma pathogenesis. We provide WGS protocols and bioinformatics approaches to identify copy number and structural variations in 41 glioblastoma patient samples. We present how WGS can identify structural diversity within glioblastoma samples. We specifically show how to apply current bioinformatics tools to detect EGFR variants and other structural aberrations from DNA whole genome sequencing and how to validate those variants within the laboratory. These comprehensive WGS protocols can provide additional information directing more precise therapeutic options in the treatment of glioblastoma.