Validation and Implementation of a Somatic-Only Tumor Exome for Routine Clinical Application

Abstract

Next-generation sequencing–based genomic testing is standard of care for tumor workflows. However, its application across different institutions continues to be challenging given the diversity of needs and resource availability among different institutions globally. Moreover, the use of a variety of different panels, including those from a few individual genes to those involving hundreds of genes, results in a relatively skewed distribution of care for patients. It is imperative to obtain a higher level of standardization without having to be restricted to specific kits or requiring repeated validations, which are generally expensive. We show the validation and clinical implementation of the DH-CancerSeq assay, a tumor-only whole-exome–based sequencing assay with integrated informatics, while providing similar input requirements, sensitivity, and specificity to a previously validated targeted gene panel and maintaining similar turnaround times for patient care. Next-generation sequencing–based genomic testing is standard of care for tumor workflows. However, its application across different institutions continues to be challenging given the diversity of needs and resource availability among different institutions globally. Moreover, the use of a variety of different panels, including those from a few individual genes to those involving hundreds of genes, results in a relatively skewed distribution of care for patients. It is imperative to obtain a higher level of standardization without having to be restricted to specific kits or requiring repeated validations, which are generally expensive. We show the validation and clinical implementation of the DH-CancerSeq assay, a tumor-only whole-exome–based sequencing assay with integrated informatics, while providing similar input requirements, sensitivity, and specificity to a previously validated targeted gene panel and maintaining similar turnaround times for patient care. 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Toward best practice in cancer mutation detection with whole genome and whole-exome sequencing.Nat Biotechnol. 2021; 39: 1141-1150Crossref PubMed Scopus (0) Google Scholar the need for standardization across these the validation and implementation of the DH-CancerSeq assay, a somatic test with an advanced and and validation the of the this to of data in care using an in Full with medical as as also without significant with of required to be for the in the of sequencing with the availability of and a per that this the new standard for tumor and of This validation and the for the of patient samples from with variants M.M. M. S. Lindeman N.I. S. D.J. A. and for the and of variants in cancer: a of the Association for Molecular American of Clinical and College of American Mol Diagn. 2017; Full Text Full Text PDF PubMed Google L.J. Arcila M.E. C. S. J. Temple-Smolkin for validation of next-generation sequencing-based oncology a of the Association for Molecular and College of American Mol Diagn. 2017; Full Text Full Text PDF PubMed Scopus Google Scholar from the assay for this validation and These the samples with samples with different and all samples previously a sample that for controls to in control sample also run this validation samples using the on the or the to samples using the using the with the set with on the on quality and using the on the all in of to samples on the a of as the pipeline for variant and of the validation S. C. A. A. M. 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A. and for the and of variants in cancer: a of the Association for Molecular American of Clinical and College of American Mol Diagn. 2017; Full Text Full Text PDF PubMed Google Scholar using all a copy number given at of detection to for a in read distribution the with a at and and not WES sample for a selection of to and variants variant not in WES or for a given a variants in WES and not in as These to genes for calling and only genes with are as variants WES but not in gene not in WES or for a given a the from the the number of the number of genes targeted for calling to number of that as a the the and from to the specificity as A of patient previously run on and all variants in regions of and using the and number of of detection samples for are in at the level in a patient sample that a or variant with from a to not have that specific variant and on and using previously run patient samples with variants with low for input patient samples and that and at different input of and for variant and the the clinical samples and which in and copy number precision samples on at for with the resulting NGS also different and different and in on can the genomic for analysis or the number of reads that map to the human a sample with and a sample that run at both and to and four also within the and and the to be for to be for all variants and across the identified and an specificity of specificity across all (ie, genes and the of the samples in as as both and in all the somatic pipeline to and the variants at each including at the with an of assay has a of for and that a similar be for of in this assay for clinical a of using the sample in which variants that on at a also as on the WES also that WES is to variants to an input tumor of to and are patient samples that and These samples run at different input of and and the of the and for each variant across all the coverage for genes of in samples with an input of and with of the genes of a coverage of However, in from and with an input of the number of genes that the of to be that input not meet the to be as the input a input of for an of which is using and at in which genes the of for and also the input the of WES to each variant at the while also at the input a with a copy number of a with a of a with a of and each variant WES at similar and copy the covered in tumor the only that to coverage in of the of these regions in of However, among the in the regions of CDS are in of variants a and all of these not This that all variants from samples in these variant also the in the of samples run in the validation and a in the input These all variants both and not using in the tumor genes of the number of as variants with a in the validation data set and a of the number of samples and the A of these variants can be in precision analysis on the and samples with of on and in on flowcell each the similar quality metrics in the with and distribution of these data are in the variants within the precision the to each variant in each and with similar DOC and variants and within a of in the and only a of in the the sample with of that a sequencing data with its to in the the for the copy given that a of these genes in sample and that the of in other of this sample for the of clinical somatic WES the have to similar of coverage and of the and similar copy of the within the control sample including in clinical run not using for each of and each the similar quality metrics in the with and distribution of these data are in the variants within the precision the to each variant in each and with similar DOC and A of samples that covered the variant types and for the as the a level of of all and of for the of of and with those from WES for the of validation samples the variants WES from only for for this assay for and and variants and to in a of coverage in in the WES assay, with the in the at the assay of the molecular in to be in a that is in the could not that a that this variant an Association for Molecular is that on a as the and a DOC the that variants WES (ie, these variants the test This in a in from to However, of these variants at or the of and and assay on each and from the on the the of the of data this the set to and the to of within a sample to the of WES not in of the samples in which on the and variants in each of the different and in the samples and which all samples that and which a clinical variants in also at similar and read in and quality metrics of the samples to A of restricted to a of genes for clinical is the identification of germline in genes such at and similar genes for germline as and in the germline per the American College of and and these variants are at the Molecular L.J. J.A. Liu X. J.D. K.J. Morgan J.D. Tsongalis G.J. M.D. Implementation of a molecular tumor the on treatment decisions for patients at 2015; 20: PubMed Scopus (0) Google M.D. K.J. J.D. Tsongalis G.J. K. Tafe L.J. Molecular and treatment for advanced lung cancer at a of a molecular tumor Med. 2020; Google Scholar a to the Cancer is to an germline for the variant of a tumor as an with in and the of clinical somatic the with an average of per tumor types lung and breast each sample a coverage of a of variants to per D. H. S. P. J. O. N. P. P. S. J. Tafe L. P. Tsongalis G. the of exome sequencing for clinical somatic variant testing of solid Mol Diagn. 2023; Scholar WES has the of genetic alterations in solid of its of the coding of the human genome sequencing on with and biomarkers, such as microsatellite instability, and mutational signatures, could be identified reliably using the WES with gene WES for rapid of gene as new targeted therapies the burden of assay validation that use of and clinical can the implementation of WES and whole in clinical use of a informatics and clinical the burden of data analysis and of all in a care several data and among and patients with data being to a Implementation of such of data across all including clinical data and the medical and with validation of the DH-CancerSeq assay in its current is with a of which to in of the assay with the addition of several biomarkers, such as and microsatellite in for validation of that can for germline variants and obtain in with results and However, this is an We are on in and American Association for Cancer data to addition to this an to in be in future input validated for assay of and this be challenging for and This further to input of validation the of the assay, at the of validated an genes without significant genes for both and coverage clinical We to genes over the several to ensure that are to the from identification to clinical panels and genomic the standard of WES and potentially are to to cancer care. with with with with with with with with with with with with with with with with

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