Clinical Validation of Whole Genome Sequencing for Cancer Diagnostics
2021; Elsevier BV; Volume: 23; Issue: 7 Linguagem: Inglês
10.1016/j.jmoldx.2021.04.011
ISSN1943-7811
AutoresPaul Roepman, Ewart de Bruijn, Stef van Lieshout, Lieke Schoenmaker, Mirjam C. Boelens, Hendrikus J. Dubbink, Willemina R.R. Geurts-Giele, Floris H. Groenendijk, Manon M. H. Huibers, Mariëtte E.G. Kranendonk, Margaretha G.M. Roemer, Kris G. Samsom, Marloes Steehouwer, Wendy W.J. de Leng, Alexander Hoischen, Bauke Ylstra, Kim Monkhorst, Jacobus J. M. van der Hoeven, Edwin Cuppen,
Tópico(s)Genomics and Rare Diseases
ResumoWhole genome sequencing (WGS) using fresh-frozen tissue and matched blood samples from cancer patients may become the most complete genetic tumor test. With the increasing availability of small biopsies and the need to screen more number of biomarkers, the use of a single all-inclusive test is preferable over multiple consecutive assays. To meet high-quality diagnostics standards, we optimized and clinically validated WGS sample and data processing procedures, resulting in a technical success rate of 95.6% for fresh-frozen samples with sufficient (≥20%) tumor content. Independent validation of identified biomarkers against commonly used diagnostic assays showed a high sensitivity (recall; 98.5%) and precision (positive predictive value; 97.8%) for detection of somatic single-nucleotide variants and insertions and deletions (across 22 genes), and high concordance for detection of gene amplification (97.0%; EGFR and MET) as well as somatic complete loss (100%; CDKN2A/p16). Gene fusion analysis showed a concordance of 91.3% between DNA-based WGS and an orthogonal RNA-based gene fusion assay. Microsatellite (in)stability assessment showed a sensitivity of 100% with a precision of 94%, and virus detection (human papillomavirus), an accuracy of 100% compared with standard testing. In conclusion, whole genome sequencing has a >95% sensitivity and precision compared with routinely used DNA techniques in diagnostics, and all relevant mutation types can be detected reliably in a single assay. Whole genome sequencing (WGS) using fresh-frozen tissue and matched blood samples from cancer patients may become the most complete genetic tumor test. With the increasing availability of small biopsies and the need to screen more number of biomarkers, the use of a single all-inclusive test is preferable over multiple consecutive assays. To meet high-quality diagnostics standards, we optimized and clinically validated WGS sample and data processing procedures, resulting in a technical success rate of 95.6% for fresh-frozen samples with sufficient (≥20%) tumor content. Independent validation of identified biomarkers against commonly used diagnostic assays showed a high sensitivity (recall; 98.5%) and precision (positive predictive value; 97.8%) for detection of somatic single-nucleotide variants and insertions and deletions (across 22 genes), and high concordance for detection of gene amplification (97.0%; EGFR and MET) as well as somatic complete loss (100%; CDKN2A/p16). Gene fusion analysis showed a concordance of 91.3% between DNA-based WGS and an orthogonal RNA-based gene fusion assay. Microsatellite (in)stability assessment showed a sensitivity of 100% with a precision of 94%, and virus detection (human papillomavirus), an accuracy of 100% compared with standard testing. In conclusion, whole genome sequencing has a >95% sensitivity and precision compared with routinely used DNA techniques in diagnostics, and all relevant mutation types can be detected reliably in a single assay. Needs and complexity in molecular cancer diagnostics are rapidly increasing, driven by a growing number of targeted drugs and developments toward more personalized treatments.1Hyman D.M. Taylor B.S. Baselga J. Implementing genome-driven oncology.Cell. 2017; 168: 584-599Abstract Full Text Full Text PDF PubMed Scopus (250) Google Scholar,2Mosele F. Remon J. Mateo J. Westphalen C.B. Barlesi F. Lolkema M.P. Normanno N. Scarpa A. Robson M. Meric-Bernstam F. Wagle N. Stenzinger A. Bonastre J. Bayle A. Michiels S. Bièche I. Rouleau E. Jezdic S. Douillard J.-Y. Reis-Filho J. Dienstmann R. André F. Recommendations for the use of next-generation sequencing (NGS) for patients with metastatic cancers: a report from the ESMO Precision Medicine Working Group.Ann Oncol. 2020; 31: 1491-1505Abstract Full Text Full Text PDF PubMed Scopus (119) Google Scholar Simultaneously, advances in next-generation DNA sequencing technology have greatly enhanced the capability of cancer genome analyses, thereby rapidly progressing diagnostic approaches from small targeted panels to large panels and exome sequencing. Currently, whole genome sequencing (WGS) using tissue and matched blood samples from patients with (metastatic) cancer3Weinstein J.N. Collisson E.A. Mills G.B. Mills Shaw K.R. Ozenberger B.A. Ellrott K. Shmulevich I. Sander C. Stuart J.M. The Cancer Genome Atlas Research NetworkThe Cancer Genome Atlas Pan-Cancer analysis project.Nat Genet. 2013; 45: 1113-1120Crossref PubMed Scopus (3280) Google Scholar is getting in reach as the most complete genetic tumor diagnostics test. In the context of the Dutch national Center for Personalized Cancer Treatment (CPCT) clinical study (NCT01855477; https://clinicaltrials.gov/ct2/show/NCT01855477, last accessed May 21, 2021), Hartwig Medical Foundation has established a national WGS facility, including robust sampling procedure and logistics in >45 (of the 87) hospitals located across the Netherlands for the centralized analysis of tumor biopsies by WGS. Since the start in 2016, >5000 tumors and matched control samples have been analyzed by WGS, of which the first cohort of 2500 patients has been extensively characterized and described.4Priestley P. Baber J. Lolkema M.P. Steeghs N. de Bruijn E. Shale C. Duyvesteyn K. Haidari S. van Hoeck A. Onstenk W. Roepman P. Voda M. Bloemendal H.J. Tjan-Heijnen V.C.G. van Herpen C.M.L. Labots M. Witteveen P.O. Smit E.F. Sleijfer S. Voest E.E. Cuppen E. Pan-cancer whole-genome analyses of metastatic solid tumours.Nature. 2019; 575: 210-216Crossref PubMed Scopus (210) Google Scholar Originally, this clinical study aimed to analyze data for biomarker discovery, but with growing clinical demands for more extensive and broader DNA analysis for patient stratification toward targeted treatments,5Manolio T.A. Rowley R. Williams M.S. Roden D. Ginsburg G.S. Bult C. Chisholm R.L. Deverka P.A. McLeod H.L. Mensah G.A. Relling M.V. Rodriguez L.L. Tamburro C. Green E.D. Opportunities, resources, and techniques for implementing genomics in clinical care.Lancet. 2019; 394: 511-520Abstract Full Text Full Text PDF PubMed Scopus (26) Google Scholar the scope of WGS is now entering routine diagnostic usage. As part of this development, the required amount of tumor tissue for as well as the turn-around time of the WGS procedure were decreased, together with implementation of more extensive quality control metrics and independent validation required for accreditation. Currently, there is an ongoing trend toward the availability of only small biopsies, especially for advanced stage cancer where metastatic lesions are sampled using core needle biopsies, with at the same time a growing need to screen for an increasing number of biomarkers. For future proof and efficient molecular diagnostics, the use of a single all-inclusive test is preferred over multiple consecutive assays that, together, often take more time, require more tissue, and provide a far less complete profile of the molecular characteristics. To meet the high-quality diagnostics standards, we have optimized and clinically validated the performance of the WGS workflow on fresh-frozen tumor samples, both technically as well as bioinformatically, as these are highly interconnected in determining the precision (positive predictive value) and sensitivity (recall) of the test. The validation efforts include current standard-of-care biomarkers (oncogenic hotspots, inactivating mutations in tumor suppressor genes), but also broader analyses of gene fusions and other genomic rearrangements as well as emerging genome-wide or complex biomarkers, like tumor mutational burden estimation, microsatellite instability (MSI),6Huang M.N. McPherson J.R. Cutcutache I. Teh B.T. Tan P. Rozen S.G. MSIseq: software for assessing microsatellite instability from catalogs of somatic mutations.Sci Rep. 2015; 5: 13321Crossref PubMed Scopus (66) Google Scholar and homologous repair deficiency (HRD) signatures.7Davies H. Glodzik D. Morganella S. Yates L.R. Staaf J. Zou X. Ramakrishna M. Martin S. Boyault S. Sieuwerts A.M. Simpson P.T. King T.A. Raine K. Eyfjord J.E. Kong G. Borg Å. Birney E. Stunnenberg H.G. van de Vijver M.J. Børresen-Dale A.-L. Martens J.W.M. Span P.N. Lakhani S.R. Vincent-Salomon A. Sotiriou C. Tutt A. Thompson A.M. Van Laere S. Richardson A.L. Viari A. Campbell P.J. Stratton M.R. Nik-Zainal S. HRDetect is a predictor of BRCA1 and BRCA2 deficiency based on mutational signatures.Nat Med. 2017; 23: 517-525Crossref PubMed Scopus (369) Google Scholar,8Nguyen L. Martens J.W.M. Van Hoeck A. Cuppen E. Pan-cancer landscape of homologous recombination deficiency.Nat Commun. 2020; 11: 5584Crossref PubMed Scopus (42) Google Scholar More important, an open-source and data-driven filtering and reporting strategy has been put into place to reduce the wealth of information into a diagnostically manageable size and to provide an overview of all clinically relevant DNA aberrations. Herein, we show that WGS has an overall >95% sensitivity (recall) and precision (positive predictive value) compared with other routinely used tests and that all relevant mutation types can be readily and reliably detected in a single assay. Although WGS required minimal quantity of input material and can be applied pan-cancer, the tumor purity was a limiting factor (requiring >20% tumor cells) as well as the availability of fresh-frozen tumor material, which were prerequisites for high-quality results, as described herein. Together, WGS has now matured from a research technology into an International Organization for Standardization (ISO) accredited test that is ready to be used for clinical decision making. For this study, samples were used from patients that were included as part of the Center for Personalized Cancer Treatment (CPCT) (NCT01855477), the Drug Rediscovery Protocol (DRUP) (NCT02925234; https://clinicaltrials.gov/ct2/show/NCT02925234, last accessed May 21, 2021), and the Whole genome sequencing Implementation in standard Diagnostics for Every cancer patient (WIDE) (NL68609.031.18; https://www.toetsingonline.nl/to/ccmo_search.nsf/fABRpop?readform&unids7E4B29996099EEEAC12585A5001611EB, last accessed May 21, 2021) clinical studies, which were approved by the medical ethical committees of the University Medical Center Utrecht and the Netherlands Cancer Institute. All patients have consented to the reuse of their pseudonymized data for research aimed at improving cancer care. Whole genome sequencing (WGS) was performed under ISO-17025 accreditation at the Hartwig Medical Foundation laboratory (Amsterdam, the Netherlands). The WGS test used DNA extracted from fresh-frozen or frozen archived tumor tissue (primary or metastatic) and from matching blood samples (reference). DNA extraction is performed on the QIAsymphony (Qiagen, Hilden, Germany) following standard reagents and protocols: 1 mL of blood was used for DNA isolation using the QIAsymphony DSP DNA Midi kit (Qiagen). The QIAsymphony DSP DNA Mini kit was used for tissue DNA isolation. Next, 50 to 200 ng DNA was fragmented by sonication on the Covaris LE220 Focused ultrasonicator (Covaris, Brighton, UK; median fragment size, 450 bp) for TruSeq Nano DNA Library (Illumina, San Diego, CA) preparation, including PCR amplification (eight cycles). All procedures were automated on the Beckman Coulter Biomek 4000 and Biomek i7 liquid handling robots (Beckman Coulter, Brea, CA). The Illumina HiSeqX and NovaSeq6000 platforms were used for sequencing tumor (approximately 90×) and blood (approximately 30×) genomes. No minimal threshold was applied regarding the mean coverage but instead the Gbase sequencing output for the tumor and blood samples had to be >300 and >100 Gb, respectively, to be eligible for downstream diagnostic analysis. Additional data quality criteria were as follows: read mapping percentage, >95%; reference genome-wide coverage 10×, >90%; reference genome-wide coverage 20×, >70%; tumor genome-wide 30× coverage, >80%; and tumor genome-wide 60× coverage, >65%. WGS analysis required tumor samples with sufficient tumor cell percentage (≥20%). Prescreening of eligible tumor samples was performed by manual pathologic tumor cell percentage (pTCP) scoring of hematoxylin and eosin–stained sections, cut from the same frozen biopsy [following standard formalin-fixed, paraffin-embedded (FFPE) protocol] that was used for DNA isolation (to minimize the potential effect of tumor heterogeneity). In addition, molecular-based tumor cell purity (mTCP) was determined based on the WGS data (see Bioinformatics) for optimal analysis and interpretation of the DNA results. The mTCP was also determined after shallow whole-genome sequencing (8× to 15× coverage depth) to be able to identify tumors with a potential discrepancy in pTCP and mTCP before continuing with deep sequencing (approximately 90× to 110×). This also allowed prescreening tumors for which no (reliable) pathologic assessment was available. Only cases with an mTCP of ≥20% were considered eligible for diagnostics analysis. Sequencing data were analyzed with an in-house developed open-source software-based pipeline. Reliable variant calling by sequencing techniques (especially WGS) depends on a complex, often Bayesian, approach, including read quality, variant allele frequency, sequence depth, and tumor purity and ploidy. A schematic overview of all of the used tools is provided in Supplemental Figure S1. Sequencing read alignment of matching tumor and blood reference samples was performed using the Burrows-Wheeler Aligner version 0.7.17. Somatic variant calling [single-nucleotide variants (SNVs), multinucleotide variants, and insertions and deletions (indels)] between the tumor reference pair was performed using STRELKA version 1.0.14 (https://github.com/Illumina/strelka, last accessed May 21, 2021), with which indels up to 50 bp could reliably be identified.9Kim S. Scheffler K. Halpern A.L. Bekritsky M.A. Noh E. Källberg M. Chen X. Kim Y. Beyter D. Krusche P. Saunders C.T. Strelka2: fast and accurate calling of germline and somatic variants.Nat Methods. 2018; 15: 591-594Crossref PubMed Scopus (283) Google Scholar Larger insertions and deletions (≥50 bp) were detected using the tool GRIDSS version 2.8.3 (https://github.com/PapenfussLab/gridss, last accessed May 21, 2021) as being structural variants. GRIDSS is a structural variant detection tool including a genome-wide break-end assembler and a somatic structural variation caller, and is able to detect genomic break junctions.10Cameron D.L. Schröder J. Penington J.S. Do H. Molania R. Dobrovic A. Speed T.P. Papenfuss A.T. GRIDSS: sensitive and specific genomic rearrangement detection using positional de Bruijn graph assembly.Genome Res. 2017; 27: 2050-2060Crossref PubMed Scopus (89) Google Scholar Variant and gene ploidy aspects were assessed using the AMBER tool version 3.3 (https://github.com/hartwigmedical/hmftools/tree/master/amber, last accessed May 21, 2021), which determined allele copy numbers of heterozygous germline variants in the tumor samples. In combination with COBALT version 1.7 (https://github.com/hartwigmedical/hmftools/tree/master/count-bam-lines, last accessed May 21, 2021), which determined read depth ratios and copy numbers of the supplied tumor and reference data, information was gathered concerning the local copy number and ploidy for bins of approximately 1 kb across the tumor genome. In addition, a sex check was performed using the COBALT output based on the observed sex chromosome pattern. Output from the AMBER (bi-allele frequencies), COBALT (read depth ratios), STREKLA (somatic variants), and GRIDSS (structural variants) was combined in the tool PURPLE version 2.43 (Supplemental Figure S1) that was designed specifically for WGS data. PURPLE was able to estimate the purity (mTCP) and copy number profile of a tumor sample by searching for the best genome-wide purity/ploidy fit with the input data. The tool provided tumor purity corrected variant allele frequencies (VAFs) and allele-specific copy numbers that could be used for detection of loss of heterozygosity.11Cameron D.L. Baber J. Shale C. Papenfuss A.T. Valle-Inclan J.E. Besselink N. Cuppen E. Priestley P. GRIDSS, PURPLE, LINX: Unscrambling the tumor genome via integrated analysis of structural variation and copy number.bioRxiv. 2020; 781013Google Scholar More important, tumor purity correction allowed for reliable identification of somatic complete loss of a gene [eg, loss of heterozygosity of BRCA1 and deep (bi-allelic) deletions of CDKN2A]. Downstream interpretation of structural variants and the calling and annotation of gene fusions were performed using LINX version 1.7 (https://github.com/hartwigmedical/hmftools/tree/master/sv-linx, last accessed May 21, 2021). This tool was able to group together the individual structural variant calls into distinct events, predicted the local structure of the derivative chromosome, and properly classified and annotated events for their functional impact.11Cameron D.L. Baber J. Shale C. Papenfuss A.T. Valle-Inclan J.E. Besselink N. Cuppen E. Priestley P. GRIDSS, PURPLE, LINX: Unscrambling the tumor genome via integrated analysis of structural variation and copy number.bioRxiv. 2020; 781013Google Scholar Genome-wide mutational characteristics were determined, including the tumor's mutational load (ML; defined as the total number of somatic missense variants across the whole genome of the tumor) and the tumor mutational burden (TMB; defined as the number of all somatic variants per genome Mb). MSI was assessed using the method described by the MSISeq tool.6Huang M.N. McPherson J.R. Cutcutache I. Teh B.T. Tan P. Rozen S.G. MSIseq: software for assessing microsatellite instability from catalogs of somatic mutations.Sci Rep. 2015; 5: 13321Crossref PubMed Scopus (66) Google Scholar In brief, the number of indels was calculated per million bases and occurring in homopolymers of five or more bases or dinucleotide, trinucleotide, and tetranucleotide sequences of repeat count four or more. Samples with a score >4 were classified as MSI. Homologous recombination DNA repair deficiency was assessed using the previously described CHORD tool version 60.02_1.03.8Nguyen L. Martens J.W.M. Van Hoeck A. Cuppen E. Pan-cancer landscape of homologous recombination deficiency.Nat Commun. 2020; 11: 5584Crossref PubMed Scopus (42) Google Scholar The CHORD tool is random forest classifier of HRD and was able to distinguish between BRCA1 and BRCA2-type HRD phenotypes. The main discriminants for HRD were the numbers of deletes with microhomology and the number of large duplications with length between 1 and 100 kb. CHORD achieved a maximum F1 score (approximately 0.88) for predicting HRD with a cutoff of 0.5, and samples above this cutoff were classified as HRD.8Nguyen L. Martens J.W.M. Van Hoeck A. Cuppen E. Pan-cancer landscape of homologous recombination deficiency.Nat Commun. 2020; 11: 5584Crossref PubMed Scopus (42) Google Scholar Furthermore, the presence of viral DNA was detected using VIRUSBreakend (GRIDSS subtool) that identified viral integrations anywhere in the host genome using a single breakend-based strategy followed by taxonomic classification of the detected viral DNA.12Cameron D.L. Jacobs N. Roepman P. Priestley P. Cuppen E. Papenfuss A.T. VIRUSBreakend: Viral Integration Recognition Using Single Breakends.Bioinformatics. 2021; btab343Crossref PubMed Google Scholar All code and scripts used for analysis of the WGS data are open source and available at GitHub (https://github.com/hartwigmedical, last accessed February 15, 2021). The raw and analyzed WGS data used in this article are available for validation and cancer research purposes through a standardized controlled data access procedure (https://www.hartwigmedicalfoundation.nl/applying-for-data, last accessed February 15, 2021). Independent validation was performed for all to-be-reported types of clinically relevant DNA aberrations, including mutations (SNVs, multinucleotide variants, and indels) with specific focus on BRAF, gene amplification (ERBB2 and MET as examples) and complete loss of genes (CDKN2A, BRCA1, and BRCA2), microsatellite (in)stability, gene fusions, and viral infection [human papillomavirus (HPV) as example]. WGS results were retrospectively compared against (as far as possible) routine diagnostic assays performed independently in ISO15189-accredited pathology laboratories. If a clinical assay was not available for the validation purpose, a custom research-use-only test was performed. The following independently performed validation experiments were performed. An overview of the used tumor samples and tumor types for each validation experiment is available as Supplemental Table S1. A custom-designed (research-use-only) single-molecule molecular inversion probe (smMIP) sequencing panel was designed for independent confirmation of variants detected by WGS. The smMIP panel sequencing was designed and processed similar to previous reports (Radboudumc, Nijmegen, the Netherlands).13Eijkelenboom A. Kamping E.J. Kastner-van Raaij A.W. Hendriks-Cornelissen S.J. Neveling K. Kuiper R.P. Hoischen A. Nelen M.R. Ligtenberg M.J.L. Tops B.B.J. Reliable next-generation sequencing of formalin-fixed, paraffin-embedded tissue using single molecule tags.J Mol Diagn. 2016; 18: 851-863Abstract Full Text Full Text PDF PubMed Scopus (65) Google Scholar,14Acuna-Hidalgo R. Sengul H. Steehouwer M. van de Vorst M. Vermeulen S.H. Kiemeney L.A.L.M. Veltman J.A. Gilissen C. Hoischen A. Ultra-sensitive sequencing identifies high prevalence of clonal hematopoiesis-associated mutations throughout adult life.Am J Hum Genet. 2017; 101: 50-64Abstract Full Text Full Text PDF PubMed Scopus (100) Google Scholar In total, 415 smMIPs (covering 1.4 kbp) were designed to test 192 randomly selected variants (165 SNVs and 27 indels) that were detected by WGS across 29 tumor samples. smMIP validation was performed using the same isolated DNA as was used for WGS, and analyzed by JSI SeqPilot version 5.1.0 (JSI Medical Systems, Ettenheim, Germany). Orthogonal clinical validation of variant detection was performed using 48 samples and compared against a custom-made Oncomine next-generation sequencing (NGS) gene panel (Thermo Scientific, Waltham, MA), processed independently (double blind) in a routine pathology laboratory under ISO15189 accreditation (Erasmus MC, Rotterdam, the Netherlands).15Pruis M.A. Geurts-Giele W.R.R. Von der TJH Meijssen I.C. Dinjens W.N.M. Aerts J.G.J.V. Dingemans A.M.C. Lolkema M.P. Paats M.S. Dubbink H.J. Highly accurate DNA-based detection and treatment results of MET exon 14 skipping mutations in lung cancer.Lung Cancer. 2020; 140: 46-54Abstract Full Text Full Text PDF PubMed Scopus (20) Google Scholar The custom Oncomine assay covered 25.2 kb exonic regions across 40 genes [design (version 5.1) available in supplementary data of the article by Pruis et al15Pruis M.A. Geurts-Giele W.R.R. Von der TJH Meijssen I.C. Dinjens W.N.M. Aerts J.G.J.V. Dingemans A.M.C. Lolkema M.P. Paats M.S. Dubbink H.J. Highly accurate DNA-based detection and treatment results of MET exon 14 skipping mutations in lung cancer.Lung Cancer. 2020; 140: 46-54Abstract Full Text Full Text PDF PubMed Scopus (20) Google Scholar] and was performed using the same isolated DNA as was used for WGS, thereby ruling out potential tumor heterogeneity. JSI SeqPilot version 5.2.0 was used for analysis, and a formal clinical report was generated. In addition, for 10 samples, a comparison was made between the WGS-based ML assessment and the Oncomine Tumor Mutational Load assay (Thermo Scientific). WGS-based copy number assessment was validated against fluorescent in situ hybridization (FISH) using COLO829 and a cohort of diagnostic tumor samples. For COLO829, a comparison was made for the ploidy of chromosomes 9, 13, 16, 18, and 9p24 (CD274/PDCD1LG2), and 2q23 (ALK) (Amsterdam UMC, Amsterdam, the Netherlands). Chromosome enumeration probes (CEPs) for the centromeric region of chromosome 9, 13, 16, and CEP9, CEP13, CEP16, and CEP18 were used, as well as locus-specific break-apart probes for 2p23 (ALK) fusion (Vysis, Abbott, IL) and 9p24 (CD274/PDCD1LG2) fusion (Leica Biosystems, Wetzlar, Germany). Slides were visualized on a Leica DM5500 fluorescence microscope (Leica Biosystems), and for each marker, 100 cells per slide were scored for the percentages of cells with respective numbers of chromosomes (signals) counted. Diagnostic ERBB2 copy number readout was validated using 16 tumor samples and using Her2/neu FISH analysis at an independent routine pathology laboratory (University Medical Center Utrecht). Fresh-frozen sections for FISH analysis were from the same biopsy used for WGS or from a matching second biopsy obtained at the same moment. FISH scoring was performed according to guidelines.16Wolff A.C. Elizabeth Hale Hammond M. Allison K.H. Harvey B.E. Mangu P.B. Bartlett J.M.S. Bilous M. Ellis I.O. Fitzgibbons P. Hanna W. Jenkins R.B. Press M.F. Spears P.A. Vance G.H. Viale G. McShane L.M. Dowsett M. Human epidermal growth factor receptor 2 testing in breast cancer: American Society of Clinical Oncology/College of American Pathologists Clinical Practice Guideline focused update.J Clin Oncol. 2018; 36: 2105-2122Crossref PubMed Scopus (515) Google Scholar For fresh-frozen samples, new sections were fixed using overnight incubation with formalin. Subsequently, routine FFPE FISH protocol was used, excluding the xylene deparaffinization step. Slides were used for probe hybridization (LPS001; Cytocell, Cambridge, UK), scanned using the Leica DM6000 scanner, and analyzed with Cytovision software (Leica Biosystems). A formal clinical report was generated that was compared with the WGS results, for which the absolute copy numbers detected by WGS were compared with the absolute copy numbers detected by FISH. In addition to ERBB2, WGS-based MET copy number readouts were investigated for samples classified as positive for MET amplification based on routine chromogenic dual in situ hybridization on matching FFPE biopsies. Routine MET amplification status was assessed using the MET DNP and Chromosome 7 DIG probes (Ventana, Tuscan, AZ) on sections (5 μm thick; SuperFrost slide; Thermo Scientific), according to the manufacturer's instructions. Samples were classified as positive for MET/CEP7 ratio >2.2. Detection of complete loss of genes by WGS was validated using CDKN2A in which the WGS data were compared against p16 protein expression. CDKN2A/p16 was assessed by immunohistochemistry (IHC) on sections (3 μm thick) of matching FFPE tumor samples, using the monoclonal primary antibody E6H4 (Ventana). Validation of gene fusion detection by WGS was performed against RNA-based Anchored Multiplex PCR NGS assay (Archer FusionPlex Solid Tumor; ArcherDx, Boulder, CO). Twenty-four samples were selected on the basis of the WGS results to include multiple fusion genes. Matching RNA (200 ng), isolated from the same tissue as the DNA that was used for WGS, was analyzed according to routine pathologic procedures (ISO15189 certified; Erasmus MC). A formal clinical report was generated and compared with the WGS results. For a set of 50 tumor samples, the microsatellite status was validated using the MSI analysis system (Promega, Madison, WI) and performed at a routine pathology laboratory (Erasmus MC)17van Lier M.G.F. Wagner A. van Leerdam M.E. Biermann K. Kuipers E.J. Steyerberg E.W. Dubbink H.J. Dinjens W.N.M. A review on the molecular diagnostics of Lynch syndrome: a central role for the pathology laboratory.J Cell Mol Med. 2010; 14: 181-197Crossref PubMed Scopus (53) Google Scholar and using the same isolated DNA that was used for WGS. These fluorescent multiplex PCR assays analyzed five nearly monomorphic mononucleotide microsatellite loci (BAT-25, BAT-26, NR-21, NR-24, and MONO-27). Matching tumor and blood samples were analyzed for accurate detection. Both the number of positive loci as well as binary classification of MSI and microsatellite stable were reported. Additional MSI-positive cases (n = 10) were included in the validation based on routine mis-match repair (MMR) IHC status (mlh1, pms2, msh2, and msh6) and/or MLH1 methylation status (MS-MLPA kit; MRC-Holland, Amsterdam, the Netherlands). WGS-based detection of presence of high-risk HPV and/or Epstein-Barr virus (EBV) DNA was compared against routine pathologic testing (Netherlands Cancer Institute) using the QIAscreen HPV PCR Test (Qiagen) for HPV and EBV-encoded RNA (EBER) IHC for detection of presence of EBV in the tumor (both according to standard protocols). If available, results of routine testing for HPV and/or EBV were used for comparison with WGS. If not available, HPV status was determined retrospectively using an aliquot of the DNA (20 ng) that was used for WGS. In addition to the orthogonal clinical validation experiments that are described in the next paragraphs, the analytical performance of WGS was continuously monitored using a genome-in-a-bottle mix-in sample (tumor, 30% NA12878; normal, 100% NA24385) for which all DNA aberrations were known. The accuracy of genome-in-a-bottle genome-wide variant detection (SNVs and short indels) by WGS was high and stable across different runs and using multiple sequencers (in a time period of 8 months) with a precision of 0.998 (range, 0.994 to 0.998) and a sensitivity (recall) of 0.989 (range, 0.973 to 0.990) (Table 1). F-scores (combining the precision and recall of the test) for variant detection exceeded the preset 0.98 lower limit for high-quality sequencing data (median, 0.993; range, 0.985 to 0.994). Direct comparison of all genome-wide somatic base calls (COLO829) between HiSeq and NovaSeq runs indicated a concordant result for 99.99953% of the bases. All discordant bases (1445 of approximately 3.1 billion) were located outside protein coding regions
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