Whole Exome Sequencing For Cancer – Is There Evidence Of .

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Advances in Genomics and GeneticsDovepressopen access to scientific and medical researchReviewAdvances in Genomics and Genetics downloaded from https://www.dovepress.com/ by 137.108.70.14 on 20-Jan-2020For personal use only.Open Access Full Text ArticleWhole exome sequencing for cancer – is thereevidence of clinical utility?This article was published in the following Dove Press journal:Advances in Genomics and Genetics22 August 2014Number of times this article has been viewedAlka MalhotraSusan LevineDiane Allingham-HawkinsGenetic Test Evaluation Program,Winifred S Hayes, Inc., Lansdale,PA, USAVideo abstractPoint your SmartPhone at the code above. If you have aQR code reader the video abstract will appear. Or use:http://dvpr.es/1r47PQVCorrespondence: Alka Malhotra; DianeAllingham-HawkinsGenetic Test Evaluation Program,Winifred S Hayes, Inc., 157 South BroadStreet, Lansdale, PA 19446 USATel 1 215 855 0615Email uctionCancers are caused by the accumulation of genetic alterations that may lead to thedysfunction of regulation of cell growth, resulting in the development of tumors.1According to the American Cancer Society, it is estimated that .1.6 million individualswere diagnosed with cancer in the US in 2013 alone, with .580,000 resulting deaths.In the US, the most common new cases of cancers included breast cancer, prostatecancer, lung cancer, and colon cancer.2In the past decade, there have been significant developments in next-generationtechnologies to sequence DNA rapidly.3,4 Massively parallel sequencing not only generates data from the entire genome in a short period of time, but it also contributes tocost reduction. Whole exome sequencing (WES) involves sequencing of all codingregions (exons) in the genome. Compared with whole genome sequencing (WGS),WES facilitates handling of data and also generates higher-quality data, since it canbe performed at greater sequencing depth. The optimal sequencing depth depends on a115submit your manuscript www.dovepress.comAdvances in Genomics and Genetics 2014:4 115–128Dovepress 2014 Malhotra et al. This work is published by Dove Medical Press Limited, and licensed under Creative Commons Attribution – Non Commercial (unported, v3.0)License. The full terms of the License are available at http://creativecommons.org/licenses/by-nc/3.0/. Non-commercial uses of the work are permitted without any furtherpermission from Dove Medical Press Limited, provided the work is properly attributed. Permissions beyond the scope of the License are administered by Dove Medical Press Limited. Information onhow to request permission may be found at: doi.org/10.2147/AGG.S58809Powered by TCPDF (www.tcpdf.org)Background: In recent years, whole exome sequencing (WES), which allows detection of85% of disease-causing variants, has been used to compare tumor and normal DNA to allowthe identification of variants specific to the tumor. Genetic changes in cancer are increasinglyused for diagnosis and may guide treatment decisions. In this paper, we explore whether thereis evidence that WES improves outcomes for patients with cancer.Methods: Published evidence was evaluated using a methodology that combines the analytical validity, clinical validity, clinical utility and ethical, legal, and social implications (ACCE)model for genetic test evaluations with internationally accepted health technology assessment methodology. Conclusions were based on peer-reviewed published studies of .10 patients, with 3 studies for a given phenotype.Results: WES has been conducted most extensively (seven studies to date) in breast cancerpatients, with fewer studies of other types of cancers (eg, leukemia, prostate cancer, and ovarian cancer). Studies evaluating somatic alterations showed high intratumor and intertumor heterogeneity. In addition, both novel and previously implicated variants were identified. However, only three studies with .10 individuals have shown potential for clinical utility of WES;whereby, variants identified through WES may determine response to drug treatment.Conclusion: Despite evidence for clinical validity of WES in cancers, clinical utility is verylimited and needs to be further evaluated in large clinical studies.Keywords: next-generation sequencing, exons, evidence-based, ACCE model, health technology assessment

DovepressAdvances in Genomics and Genetics downloaded from https://www.dovepress.com/ by 137.108.70.14 on 20-Jan-2020For personal use only.Malhotra et alnumber of factors, including, but not limited to: the region(s)being sequenced; the sample source; and the algorithm usedto assemble and analyze the results. While exons representjust 1% of the genome, they account for approximately 85%of disease-causing variants, specifically for Mendelian traits;5however, the percentage for complex traits is not known.6In recent years, WES has been used to compare tumorDNA and normal DNA to identify variants specific to thetumor. WES of tumor DNA requires greater sequence depththan normal DNA to identify variants that are present intumor cells only. These analyses may provide informationabout genes with driver variants (those with an effect oncancer development) versus passenger variants (those without an effect on cancer development).7 Through identification of potentially deleterious variants, WES may provideinformation about potential new avenues for diagnosis andtreatment.While clinical exome sequencing is being offered bya number of laboratories, WES specifically for cancer iscurrently offered by two Clinical Laboratory ImprovementAmendments-certified laboratories in the US. The BaylorCollege of Medicine Medical Genetics Laboratories offersthe Cancer Exome Sequencing test,8 and Personal GenomeDiagnostics Inc., (Baltimore, MD, USA) offers the CancerComplete test.9 Using proprietary methods, PersonalGenome Diagnostics Inc. also conducts quality assessmentand evaluation of genes and pathways of interest, identifiedthrough WES.9This systematic review evaluates the available publishedevidence about the use of WES for cancer indications, withemphasis on analytical validity, clinical validity, and clinical utility.MethodsSearch strategyEvidence evaluated for this report was obtained primarilyfrom a search of the peer-reviewed literature in PubMedand Embase performed on June 3, 2013. Search termsincluded “exome” AND “sequencing” AND “cancer” AND (“diagnosis” OR “clinical” OR “utility” OR “validity”).Limits used were English language, human, and publishedsince January 1, 1996. Additional relevant citations were alsoselected from the bibliographies of retrieved references.Evidence evaluationThe evidence analysis used for this review is based on theACCE model tm) that was developed by the Centers for Disease116Powered by TCPDF (www.tcpdf.org)submit your manuscript www.dovepress.comDovepressControl and Prevention.10,11 The ACCE model takes its namefrom an abbreviation of its main components: analyticalvalidity; clinical validity; clinical utility; and ethical, legal,and social implications. The model is widely used to allow theperformance of rapid evaluations of genetic tests.12For this paper, the analytical validity is defined as theability of WES technology to measure accurately and reliablythe sequences of interest. Clinical validity is defined as theability of WES to detect or predict the associated disorderor phenotype, while clinical utility focuses on what needsto be considered when evaluating the risks and benefits ofintroducing a genetic test into routine practice, and it isbased on studies designed to investigate whether there areimprovements in health outcomes as a result of using thegenetic test in clinical practice. In this review, we focus onthese components of the ACCE model, with less emphasison the ethical, legal, and social implications.Results/evidence overviewAnalytical validityCommercial laboratories offering WES mainly use the A gilent SureSelect All Exome (Agilent Technologies,Santa Clara, CA, USA) or NimbleGen Sequence Capture(SeqCap) Human Exome (Hoffmann-La Roche Ltd, Basel,Switzerland) platforms for exome capture. The analyticalvalidity of these methods has been assessed by four studies comparing various platforms to detect variants throughWES. Three studies utilized data from healthy individualsand one study evaluated data from cancer patients; however,none of the information provided was specific to cancer. Inthe analyses, various parameters were evaluated, includingthe following: Enrichment efficiency – proportion of base pair readsfalling in the target region to the total base pair reads inany region of the genome. Genotype sensitivity – probability to accurately determinethe genotypes in the target regions. Genotype concordance – accuracy of overlap of genotypecalls between the current analysis and previously identified genotype information. Coverage – overlap with existing publicly availabledatabases with protein-coding variant information, aswell as detection percentage depending on the depth ofsequencing.Table 1 presents comparisons between the differentexome enrichment platforms, some that are currently beingused by commercial laboratories in the US. Two studieswere conducted in individuals of Asian descent,13,14 and twoAdvances in Genomics and Genetics 2014:4

Powered by TCPDF (www.tcpdf.org)SampleOne healthy Asian manwho had previousWGS data availableOne healthy Europeanindividual18 healthy Americanindividuals(eleven women;seven men)ReferenceAsan et al(2011)13Clark et al(2011)15Advances in Genomics and Genetics 2014:4Hedges et al(2011)16Agilent SureSelectaNimbleGen SeqCapbRainDance Technology(multiplex PCR-based)dAgilent SureSelect HumanAll Exon 50 MbcNimbleGen SeqCap EZExome Library v2.0bIllumina TruSeq ExomeEnrichmentcAgilent SureSelect HumanAll Exon 50 MbaNimbleGen SeqCap EzbNimbleGen SeqCap HumanExome 2.1 M ArraybPlatforms testedTable 1 Comparison of exome enrichment platformsDNA was extracted from peripheral blood leukocytesin 16 individuals and two cell lines.Variants in a common 0.8 Mb were evaluated.Exons, 5 kb flanking regions, and additionalevolutionarily conserved regions were assessed.18 individuals were divided among three platforms; inaddition, six randomly selected individuals were testedacross platforms.Sequencing was performed using ABI SOLID3 platform.Genotype data were compared with Illumina 1 MInfinium GWAS chip.DNA was extracted from peripheral bloodmononuclear cells.Sequencing was performed using IlluminaHiSeq 2000 platform.Genotype data were compared with Illumina1 M Duo SNP chip.DNA was extracted from peripheral blood.Exomes were captured in two replicates for each platform.Sequencing was performed using Illumina HiSeq2000 platform.Exome capture by the three platforms was comparedwith publicly available variant information in proteincoding genes from three databases: CCDS, refGen, andEnsemblGen.Genotype data were compared with WGS data andIllumina 1 M Infinium GWAS chip.Methodssubmit your manuscript www.dovepress.comDovepress(Continued)In most cases, results of SeqCap EZ and 2.1 M Array were similar;therefore, only one set of results is presented.SureSelect:Genotype sensitivity: 64%–85% at 20 –50 depthEnrichment efficiency: average across replicates 56.4% at.30 depthCoverage: 80.6% of publicly available data; 59% coverage at10 –50 depthGenotype concordance: .99%NimbleGen:Genotype sensitivity: 72%–91% at 20 –50 depthEnrichment efficiency:average across replicates 54.8% at.30 depthCoverage: 75.9% of publicly available data; 70%–79% coverage at10 –50 depthGenotype concordance: .99%SureSelect:Enrichment efficiency: 89.6% at 10 depthCoverage: .80% at 25 depthGenotype concordance: 99.3%SeqCap EZ:Enrichment efficiency: 96.8% at 10 depthCoverage: .80% at 25 depthGenotype concordance: 99.5%TrueSeq:Enrichment efficiency: 90.0% at 10 depthCoverage: .80% at 25 depthGenotype concordance: 99.2%SureSelect:Enrichment efficiency: average 60.8%Coverage: .90% at 10 depthGenotype concordance: average 99.8% at .20 depthSeqCap EZ:Enrichment efficiency: average 53.3%Coverage: .90% at 10 depthGenotype concordance: average 99.7% at .20 depthRainDance:Enrichment efficiency: average 52.5%Coverage: .90% at 10 depthGenotype concordance: average 98.3% at .20 depthResultsAdvances in Genomics and Genetics downloaded from https://www.dovepress.com/ by 137.108.70.14 on 20-Jan-2020For personal use only.DovepressWhole exome sequencing for cancer117

DovepressSureSelect:Coverage: 97% of sites were covered with at least one read;average number of reads was 68.9 million per sample at 45 median depth; 98.3% of CCDS variants were detectedConsistency rate (similar to genotype concordance): .99% at20 depthTrueSeq:Coverage: 97% of sites were covered with at least one read;average number of reads was 93.8 million per sample at 48 median depth; 96.5% of CCDS variants were detectedConsistency rate: .99% at 20 depthSequencing was performed using Illumina HiSeq 2000platform (Illumina samples) or GA II (Agilent samples).Exome capture by two platforms was compared withCCDS database.Comparisons were conducted within target region andoutside target region (since flanking regions are alsousually sequenced); however, only results of withintarget region are presented.Agilent SureSelect v1(n 22)Illumina TruSeq ExomeEnrichmentc (n 8)28 Chineseindividuals withbreast cancer – veryearly onset(age 22–32 years) orearly onset(38–41 years) and afirst-degree relativewith breast cancer118Powered by TCPDF (www.tcpdf.org)Guo et al(2012)14submit your manuscript www.dovepress.comDovepressNotes: Adapted with permission from Winifred S Hayes, Inc. Manufacturer details are as follows: aAgilent Technologies, Santa Clara, CA, USA; bF Hoffmann-La Roche Ltd., Basel, Switzerland; cIllumina Inc., San Diego, CA, USA; dRainDanceTechnologies, Inc., Billerica, MA, USA.Abbreviations: CCDS, Consensus Coding Sequence; GA II, Genome Analyzer II; GWAS, genome-wide association study; PCR, polymerase chain reaction; SeqCap, Sequence Capture; SNP, single nucleotide polymorphism; WGS, wholegenome sequencing.ResultsMethodsReferenceTable 1 (Continued)aPlatforms testedSampleAdvances in Genomics and Genetics downloaded from https://www.dovepress.com/ by 137.108.70.14 on 20-Jan-2020For personal use only.Malhotra et alstudies were of white individuals.15,16 For all studies, a highgenotype concordance (.98%) was estimated.13–16 However,overall coverage rates varied between studies and platforms,ranging from .80% in two studies15,16 to 59% (for AgilentSureSelect [Agilent Technologies]) in one study.13 In addition,where available, enrichment efficiency also varied amongstudies, ranging from 56.4%–89.6% for the Agilent SureSelect (Agilent Technologies) platform.13,15,16 This variationmay be explained by the different depths of coverage usedby each study.Clinical validityThe use of WES has been reported for a number of differentcancers, with a majority of studies being either case reports orhaving sample sizes , ten individuals, which is too small todraw meaningful conclusions. This section describes clinicalvalidity data obtained from at least three studies of the sameor similar cancer type, with each of the studies including .ten individuals.Breast cancerSeven studies with . ten individuals evaluated the clinicalvalidity of WES in breast cancer (summarized in Table 2). Theoverall proportion of missense variants in unrelated individuals was similar in different studies, ranging from 61.2%–65.4%.17–21 In addition, studies identified varying proportionsof variants and candidate genes depending on the subtype;for example, the tumor protein p53 (TP53) gene had a highproportion of variants in luminal B individuals (P 0.04),while the mitogen-activated protein kinase kinase kinase 1(MAP3K1) gene had a high proportion of variants in luminal A individuals (P 0.02).19 In all studies, both previouslyidentified genes – as well as those not previously detected inbreast cancer studies – were identified with a larger numberof variants than expected by chance.17,19–23Two studies were specifically conducted in families thatwere negative for the breast cancer 1, early-onset (BRCA1)gene and the breast cancer 2, early-onset (BRCA2) gene.22,23One study identified the Bloom syndrome, RecQ helicaselike (BLM) and Fanconi anemia, complementation group C(FANCC) genes with higher frequency of variants that mayhave an effect on breast cancer development;23 whereas, thesecond study identified eleven candidate genes.22Leukemia and lymphomaTable 3 presents results of WES in two types of leukemia –two studies for chronic lymphocytic leukemia (CLL)24,25 andone study for acute myeloid leukemia (AML).26 While allAdvances in Genomics and Genetics 2014:4

Powered by TCPDF (www.tcpdf.org)Population108 Mexican (n 56) and Vietnamese(n 52) patients with diverse subtypes:38 (35.2%) luminal A; 22 (20.4%)luminal B; 21 (19.4%) HER2-enriched;13 (12%) basal/basal-like; 9 (8.3%)normal-like; and 5 (4.6%) unknownOf these, data from 103 and 5 patientswere used for WES and WGS,respectively.825 patients from US with no priortreatment with chemotherapy orradiotherapy.Of these, information on 510 tumorsfrom 507 patients was used in thisstudy:* 225 (44.4%) luminal A;126 (24.9%) luminal B; 57 (11.2%)HER2-enriched; 93 (18.3%) basal-like;6 (1.2%) unknown.77 American ER patients undergoingaromatase inhibitor treatment.Of these, data from 46 and 31 patientswere used for WGS and WES,respectively.ReferenceBanerji et al(2012)17Cancer GenomeAtlas ResearchNetwork(2012)18Ellis et al(2012)19Table 2 WES in breast cancer patientsAdvances in Genomics and Genetics 2014:4Fresh frozen tumor and matched normalperipheral blood samples were used.Hybridization was performed using RocheNimbleGen Sequence Capture EZ Human ExomeLibrary v2.0 kit.cAn Illumina platforma (specific technology notspecified) was used for sequencing.Frozen tumors and matched normal controls(blood sample or normal breast tissue) were used.Hybridization was performed using AgilentSureSelect All Exome kit v2.0b or NimbleGenSeqCap Human Exome v2.0.cIllumina HiSeq 2000a was used for sequencing.Frozen breast cancer samples and normalmatched controls (peripheral blood from theMexican patients and normal breast tissue fromVietnamese patients) were used for WES.Exome was captured using a solution hybridselection method.189,980 exons across 33 Mb were sequencedusing Illumina GA II platform.aValidation of variants was performed usingthree different sequencing technologies.Methodology4,985 somatic variants were detected,with an overall rate of 1.66 variantsper Mb.Variant type:Missense: 3,153 (63.2%)Silent: 1,157 (23.2%)Nonsense: 242 (4.9%)Splice site: 97 (1.9%)Deletions: 194 (3.9%)Insertions: 110 (2.2%)Nonsilent variant rate was 1.27 per Mb.Of 494 variants tested for validation,94% were confirmed.30,626 somatic variants were detected.Variant type:Missense: 19,045 (62.2%)Silent: 6,486 (21.2%)Nonsense: 1,437 (4.7%)Splice site: 506 (1.7%)Indels: 2,302 (7.5%)Stop codon read-through: 26 (0.1%)Of the missense variants, 9,484 (49.8%)had a high probability of being deleterious.In addition, average nonsilent variant ratewas 1.49 per Mb.3,355 coding somatic variants weredetected using both WES and WGS.Of these, 1,371 were identified throughWES alone.Variant type# (of the total 3,355):Missense: 2,145 (63.9%)Nonsense: 178 (5.3%)Splice site: 69 (2.1%)Indels: 146 (4.4%)Stop codon read-through: 6 (0.2%)Of missense variants, 1,551 (72.3%) hada high probability of being deleterious.Variant rate was 1.05 per Mb.Results(Continued)Follow-up analysis of variantfrequencies identified 18 genesshowing higher number ofvariants than expected by chance(P#1.79 10-4).Follow-up analysis of variantfrequencies identified 35 genesshowing a higher number of variantsthan expected by

While clinical exome sequencing is being offered by a number of laboratories, WES specifically for cancer is currently offered by two Clinical Laboratory Improvement Amendments-certified laboratories in the US. The Baylor College of Medicine Medical Genetics Laboratories offers the Cancer Exome Sequencing test,8 and Personal Genome

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