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• W152480201 abstract "In the context of personalized oncology, screening for somatic tumor mutations is crucial for prediction of an individual patient’s response to therapy. Massive parallel sequencing (MPS) has been suggested for routine diagnostics, but this technology has not been sufficiently evaluated with respect to feasibility, reliability, and cost effectiveness with routine diagnostic formalin-fixed, paraffin-embedded material. We performed ultradeep targeted semiconductor-based MPS (190 amplicons covering hotspot mutations in 46 genes) in a variety of formalin-fixed, paraffin-embedded diagnostic samples of lung adenocarcinoma tissue with known EGFR mutations (n = 28). The samples reflected the typical spectrum of tissue material for diagnostics, including small biopsies and samples with low tumor-cell content. Using MPS, we successfully sequenced all samples, with a mean read depth of 2947 reads per amplicon. High-quality sequence reads were obtained from samples containing ≥10% tumor material. In all but one sample, variant calling identified the same EGFR mutations as were detected by conventional Sanger sequencing. Moreover, we identified 43 additional mutations in 17 genes and detected amplifications in the EGFR and ERBB2 genes. MPS performance was reliable and independent of the type of material, as well as of the fixation and extraction methods, but was influenced by tumor-cell content and the degree of DNA degradation. Using sample multiplexing, focused MPS approached diagnostically acceptable cost rates. In the context of personalized oncology, screening for somatic tumor mutations is crucial for prediction of an individual patient’s response to therapy. Massive parallel sequencing (MPS) has been suggested for routine diagnostics, but this technology has not been sufficiently evaluated with respect to feasibility, reliability, and cost effectiveness with routine diagnostic formalin-fixed, paraffin-embedded material. We performed ultradeep targeted semiconductor-based MPS (190 amplicons covering hotspot mutations in 46 genes) in a variety of formalin-fixed, paraffin-embedded diagnostic samples of lung adenocarcinoma tissue with known EGFR mutations (n = 28). The samples reflected the typical spectrum of tissue material for diagnostics, including small biopsies and samples with low tumor-cell content. Using MPS, we successfully sequenced all samples, with a mean read depth of 2947 reads per amplicon. High-quality sequence reads were obtained from samples containing ≥10% tumor material. In all but one sample, variant calling identified the same EGFR mutations as were detected by conventional Sanger sequencing. Moreover, we identified 43 additional mutations in 17 genes and detected amplifications in the EGFR and ERBB2 genes. MPS performance was reliable and independent of the type of material, as well as of the fixation and extraction methods, but was influenced by tumor-cell content and the degree of DNA degradation. Using sample multiplexing, focused MPS approached diagnostically acceptable cost rates. As the era of personalization in cancer medicine approaches, clinically relevant genetic alterations are increasingly used to stratify patients for specific targeted therapeutics.1Macconaill L.E. Garraway L. Clinical implications of the cancer genome.J Clin Oncol. 2010; 28: 5219-5228Crossref PubMed Scopus (155) Google Scholar This development began with the discovery of ERBB2 (alias HER2, NEU) gene amplifications in breast cancer, which predict clinical response to trastuzumab.2Dowsett M. Procter M. McCaskill-Stevens W. de Azambuja E. Dafni U. Rueschoff J. Jordan B. Dolci S. Abramovitz M. Stoss O. Viale G. Gelber R.D. Piccart-Gebhart M. Leyland-Jones B. Disease-free survival according to degree of HER2 amplification for patients treated with adjuvant chemotherapy with or without 1 year of trastuzumab: the HERA Trial.J Clin Oncol. 2009; 27: 2962-2969Crossref PubMed Scopus (162) Google Scholar Additional examples of novel genetics-driven cancer treatment include the mandatory detection of BRAF V600E mutations before use of vemurafenib for metastatic malignant melanoma3Sosman J.A. Kim K.B. Schuchter L. Gonzalez R. Pavlick A.C. Weber J.S. McArthur G.A. Hutson T.E. Moschos S.J. Flaherty K.T. Hersey P. Kefford R. Lawrence D. Puzanov I. Lewis K.D. Amaravadi R.K. Chmielowski B. Lawrence H.J. Shyr Y. Ye F. Li J. Nolop K.B. Lee R.J. Joe A.K. Ribas A. Survival in BRAF V600-mutant advanced melanoma treated with vemurafenib.N Engl J Med. 2012; 366: 707-714Crossref PubMed Scopus (1768) Google Scholar and therapeutic targeting of EGFR in both lung cancer4Shepherd F.A. Rodrigues Pereira J. Ciuleanu T. Tan E.H. Hirsh V. Thongprasert S. Campos D. Maoleekoonpiroj S. Smylie M. Martins R. van Kooten M. Dediu M. Findlay B. Tu D. Johnston D. Bezjak A. Clark G. Santabárbara P. Seymour L. National Cancer Institute of Canada Clinical Trials GroupErlotinib in previously treated non-small-cell lung cancer.N Engl J Med. 2005; 353: 123-132Crossref PubMed Scopus (5088) Google Scholar and colorectal cancer.5Van Cutsem E. Köhne C.H. Hitre E. Zaluski J. Chang Chien C.R. Makhson A. D’Haens G. Pintér T. Lim R. Bodoky G. Roh J.K. Folprecht G. Ruff P. Stroh C. Tejpar S. Schlichting M. Nippgen J. Rougier P. Cetuximab and chemotherapy as initial treatment for metastatic colorectal cancer.N Engl J Med. 2009; 360: 1408-1417Crossref PubMed Scopus (3271) Google Scholar It is estimated that many more therapeutic approaches will become available in the near term to address the specific genetic patterns of a given tumor on a therapeutic level. This holds particularly true for lung cancer, for which additional therapeutic targets have been identified, including MET, FGFR1, PIK3CA, and DDR2.6Peifer M. Fernández-Cuesta L. Sos M.L. George J. Seidel D. Kasper L.H. et al.Integrative genome analyses identify key somatic driver mutations of small-cell lung cancer.Nat Genet. 2012; 44: 1104-1110Crossref PubMed Scopus (1001) Google Scholar, 7Hammerman P.S. Sos M.L. Ramos A.H. Xu C. Dutt A. Zhou W. et al.Mutations in the DDR2 kinase gene identify a novel therapeutic target in squamous cell lung cancer.Cancer Discov. 2011; 1: 78-89Crossref PubMed Scopus (410) Google Scholar With the recent advent of massive parallel sequencing (MPS), it is now possible to rapidly uncover genomic alterations in tumors in unprecedented detail and with relatively low cost. Data derived from recent consortium-based whole-genome and whole-exome sequencing efforts for many solid tumors have broadened our view of cancer as a complex genetic disease harboring an astounding heterogeneity.8Meyerson M. Gabriel S. Getz G. Advances in understanding cancer genomes through second-generation sequencing.Nat Rev Genet. 2010; 11: 685-696Crossref PubMed Scopus (906) Google Scholar All of these studies relied on ample amounts of fresh-frozen tissue. In routine diagnostics, however, the available material frequently consists of only small biopsies, or even single clusters of neoplastic cells. In addition, tissue available for routine molecular diagnostics is likely to consist almost exclusively of formalin-fixed, paraffin-embedded (FFPE) material.9Ross J.S. Cronin M. Whole cancer genome sequencing by next-generation methods.Am J Clin Pathol. 2011; 136: 527-539Crossref PubMed Scopus (138) Google Scholar Whole-exome or even whole-genome sequencing of FFPE material is subject to various technical constraints,10Garraway L.A. Concordance and discordance in tumor genomic profiling.J Clin Oncol. 2012; 30: 2937-2939Crossref PubMed Scopus (9) Google Scholar and, although prices have dropped dramatically, it is not yet cost effective in a routine clinical setting. Nonetheless, MPS technologies have their place in sequencing of gene panels that focus on specific hot-spot mutations in a given number of genes that are either of differential diagnostic relevance or are known to be prognosticators or response predictors for available therapeutic approaches. Such panels suffice in a routine diagnostic setting, because large-scale, whole-genome sequencing has revealed that, in a given tumor entity, only a moderate number of genes harbor mutations in >1% of the respective tumors, and of these only a few contain valuable prognostic, predictive, or differential diagnostic information. A broadened targeted approach may therefore be equally useful during routine practice as in cohort-based translational research studies. To date, only a few studies have applied MPS to routine diagnostic FFPE material, and the applications have been primarily exploratory.11Wagle N. Berger M.F. Davis M.J. Blumenstiel B. Defelice M. Pochanard P. Ducar M. Van Hummelen P. Macconaill L.E. Hahn W.C. Meyerson M. Gabriel S.B. Garraway L.A. High-throughput detection of actionable genomic alterations in clinical tumor samples by targeted, massively parallel sequencing.Cancer Discov. 2012; 2: 82-93Crossref PubMed Scopus (424) Google Scholar, 12Giulino-Roth L. Wang K. MacDonald T.Y. Mathew S. Tam Y. Cronin M.T. Palmer G. Lucena-Silva N. Pedrosa F. Pedrosa M. Teruya-Feldstein J. Bhagat G. Alobeid B. Leoncini L. Bellan C. Rogena E. Pinkney K.A. Rubin M.A. Ribeiro R.C. Yelensky R. Tam W. Stephens P.J. Cesarman E. Targeted genomic sequencing of pediatric Burkitt lymphoma identifies recurrent alterations in antiapoptotic and chromatin-remodeling genes.Blood. 2012; 120: 5181-5184Crossref PubMed Scopus (80) Google Scholar, 13Beltran H. Yelensky R. Frampton G.M. Park K. Downing S.R. Macdonald T.Y. Jarosz M. Lipson D. Tagawa S.T. Nanus D.M. Stephens P.J. Mosquera J.M. Cronin M.T. Rubin M.A. Targeted next-generation sequencing of advanced prostate cancer identifies potential therapeutic targets and disease heterogeneity.Eur Urol. 2013; 63: 920-926Abstract Full Text Full Text PDF PubMed Scopus (314) Google Scholar, 14Duncavage E.J. Magrini V. Becker N. Armstrong J.R. Demeter R.T. Wylie T. Abel H.J. Pfeifer J.D. Hybrid capture and next-generation sequencing identify viral integration sites from formalin-fixed, paraffin-embedded tissue.J Mol Diagn. 2011; 13: 325-333Abstract Full Text Full Text PDF PubMed Scopus (85) Google Scholar, 15Schweiger M.R. Kerick M. Timmermann B. Albrecht M.W. Borodina T. Parkhomchuk D. Zatloukal K. Lehrach H. Genome-wide massively parallel sequencing of formaldehyde fixed-paraffin embedded (FFPE) tumor tissues for copy-number- and mutation-analysis.PLoS One. 2009; 4: e5548Crossref PubMed Scopus (148) Google Scholar We know of no published studies that comprehensively investigated the application of MPS methods to FFPE lung cancer tissue in a routine diagnostic setting. Such a setting is of specific clinical interest, because lung cancer is the solid tumor for which multigene testing is most likely to be applied in the near future. Additionally, only limited data are available on the validity and robustness of Ion Torrent (a recently introduced semiconductor-based MPS platform16Rothberg J.M. Hinz W. Rearick T.M. Schultz J. Mileski W. Davey M. et al.An integrated semiconductor device enabling non-optical genome sequencing.Nature. 2011; 475: 348-352Crossref PubMed Scopus (1550) Google Scholar; Life Technologies, Darmstadt, Germany; Carlsbad, CA) for FFPE cancer specimens.17Beadling C. Neff T.L. Heinrich M.C. Rhodes K. Thornton M. Leamon J. Andersen M. Corless C.L. Combining highly multiplexed PCR with semiconductor-based sequencing for rapid cancer genotyping.J Mol Diagn. 2013; 15: 171-176Abstract Full Text Full Text PDF PubMed Scopus (104) Google Scholar, 18Geurts-Giele W.R. Dirkx-van der Velden A.W. Bartalits N.M. Verhoog L.C. Hanselaar W.E. Dinjens W.N. Molecular diagnostics of a single multifocal non-small cell lung cancer case using targeted next generation sequencing.Virchows Arch. 2013; 462: 249-254Crossref PubMed Scopus (20) Google Scholar, 19Hadd A.G. Houghton J. Choudhary A. Sah S. Chen L. Marko A.C. Sanford T. Buddavarapu K. Krosting J. Garmire L. Wylie D. Shinde R. Beaudenon S. Alexander E.K. Mambo E. Adai A.T. Latham G.J. Targeted, high-depth, next-generation sequencing of cancer genes in formalin-fixed, paraffin-embedded and fine-needle aspiration tumor specimens.J Mol Diagn. 2013; 15: 234-247Abstract Full Text Full Text PDF PubMed Scopus (161) Google Scholar We investigated the validity of the Ion Torrent semiconductor-based MPS system for detecting Sanger-sequenced mutations in DNA derived from FFPE lung cancer specimens with respect to different DNA extraction methods, age of the probes, sample sizes (biopsies and resections), and tumor-cell content. We also made cost and hands-on time estimates, an important cornerstone for the incorporation of MPS platforms into daily routine diagnostics. We tested the reliability and validity of an MPS amplicon sequencing approach using DNA extracted from FFPE material. Although FFPE material is the basis for routine pathological diagnostics, specimens can vary greatly with respect to tissue size (biopsy versus resection), tumor-cell content, fixation time, block age, and methods of DNA extraction. To reflect these parameters, we selected a variety of specimens (five biopsy and seven resection specimens with a tumor-cell content of ≥50% but with differing block ages; four biopsies each with <10%, 10% to 25%, and 25% to 50% tumor-cell content), including samples that were processed and embedded outside our institution. In addition, we repeated the sequencing of two samples using half the volume of amplification reagent, and we tested two samples using different extraction methods (Table 1). To test the reliability of the sequencing runs with respect to detection accuracy, five samples were run in duplicate. For all samples, the presence of EGFR gene mutations had been confirmed by Sanger sequencing.Table 1Summary of NSCLC Samples UsedSample IDSourceTumor content (%)Extraction methodConcentrationDNA (ng/μL)Library (pmol/L)VLB001Biopsy>50Qiagen2.942723VLB002Biopsy>50Qiagen1.31150VLB003Biopsy>50Qiagen3.58219VLB004Biopsy>50Qiagen1.25594VLB005Biopsy>50Qiagen1.251332VLR006Resection>50Qiagen2.91443VLR007Resection>50Qiagen2.341093VLR008Resection>50Qiagen10.6991VLR009Resection>50Qiagen9.731066VLR010Resection>50Qiagen7.7976VLR011Resection>50Qiagen2.441683VLR028Resection>50Maxwell21.41059VLB012Biopsy<10Qiagen0.22∗Samples with <10 ng input.26VLB013Biopsy<10Qiagen0.26∗Samples with <10 ng input.172VLB014Biopsy<10Qiagen0.34∗Samples with <10 ng input.509VLB015Biopsy<10Qiagen1.61∗Samples with <10 ng input.67VLB016Biopsy10−25Qiagen1.992634VLB017Biopsy10−25Qiagen1.181286VLB018Biopsy10−25Qiagen0.10∗Samples with <10 ng input.843VLB019Biopsy10−25Qiagen0.54∗Samples with <10 ng input.181VLB020Biopsy25−50Qiagen2.361081VLB021Biopsy25−50Qiagen4.941393VLB022Biopsy25−50Qiagen3.421411VLB023Biopsy25−50Maxwell4.3281VLx024†External submitter.Qiagen1.13∗Samples with <10 ng input.335VLx025†External submitter.Qiagen0.47∗Samples with <10 ng input.2049VLR008Resection>50Qiagen10.6991VLR008-2Resection>50Maxwell1.53194VLR008-3Resection>50Qiagen‡Half-volume amplicon PCR.10.61114VLR007Resection>50Qiagen2.341093VLR007-2Resection§Tumor not microdissected.unknownMaxwell66.22782Vxx026†External submitter.Qiagen11368Vxx027†External submitter.Qiagen3.54851∗ Samples with <10 ng input.† External submitter.‡ Half-volume amplicon PCR.§ Tumor not microdissected. Open table in a new tab DNA extracted from FFPE material is degraded to various degrees, which limits its usefulness for sequencing approaches using classical capture methods. However, these DNA probes are routinely used for approaches such as classical Sanger sequencing, which depend on amplification of target regions by PCR. We therefore considered an amplicon-based approach to be best for generating MPS libraries. We used an Ion AmpliSeq cancer panel (Life Technologies), that contained primers for the amplification of 190 amplicons located in known hotspot cancer regions across the human genome. The median amplicon size generated by this approach was between 80 and 100 bp, which is small enough for use with significantly degraded DNA from FFPE material. For this study, FFPE non-small cell lung cancer (NSCLC) specimens were used (n = 28). All specimens represented routine diagnostic material that had been found, in the process of diagnostic workup, to harbor EGFR mutations. The specimens were selected from the archives according to the following criteria: coming from different hospitals with differing pathology labs, representing different types of material (resection specimen, biopsies), and containing different amounts of tumor cells (Table 1). Characterization of the tissue is further detailed under Results. All cases were diagnosed or rediagnosed by two experienced pulmonary pathologists (W.W. and A.W.) according to the criteria of the World Health Organization classification of lung cancer20Travis W. Brambilla E. Müller-Hermelink H. Harris C.C. Pathology and genetics of tumours of the lung, pleura, thymus and heart. WHO Classification of Tumours. IARC Press, Lyon, France2004Google Scholar and the current International Association for the Study of Lung Cancer, American Thoracic Society, and European Respiratory Society consensus classification.21Travis W.D. Brambilla E. Noguchi M. Nicholson A.G. Geisinger K.R. Yatabe Y. et al.International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society international multidisciplinary classification of lung adenocarcinoma.J Thorac Oncol. 2011; 6: 244-285Crossref PubMed Scopus (3562) Google Scholar Tumor areas were marked on an H&E–stained slide, and corresponding tissue areas were microdissected from subsequent unstained slides. Extraction of genomic DNA was performed by proteinase K digestion and fully automated purification using either a QIAsymphony SP system (Qiagen, Hilden, Germany; Valencia, CA) or a Maxwell 16 system (Promega, Madison, WI). The DNA content was measured fluorimetrically using a Qubit dsDNA HS assay (Life Technologies) or using a quantitative real-time PCR (qPCR)–based method (RNase P detection system; Life Technologies). Use of the tissue was approved by the local ethics committee (approval no. 206/2005) in Heidelberg. For conventional EGFR exon amplification, the following primers were used in a standard PCR assay: exon 18, forward 5′-GCTGAGGTGACCCTTGTCTC-3′ and reverse 5′-ACAGCTTGCAAGGACTCTGG-3′; exon 19, forward 5′-GCTGGTAACATCCACCCAGA-3′ and reverse 5′-GAGAAAAGGTGGGCCTGAG-3′; exon 20, forward 5′-CATGTGCCCCTCCTTCTG-3′ and reverse 5′-GATCCTGGCTCCTTATCTCC-3′; and exon 21, forward 5′-CCTCACAGCAGGGTCTTCTC-3′ and reverse 5′-CCTGGTGTCAGGAAAATGCT-3′. Exons 5 to 8 of the TP53 gene were amplified using the following primers: exon 5, forward 5′-TTTCAACTCTGTCTCCTTCCTCTT-3′ and reverse 5′-AGCCCTGTCGTCTCTCCAG-3′; exon 6, forward 5′-CAGGCCTCTGATTCCTCACT-3′ and reverse 5′-CTTAACCCCTCCTCCCAGAG-3′; exon 7, forward 5′-CTTGGGCCTGTGTTATCTCC-3′ and reverse 5′-GGGTCAGAGGCAAGCAGA-3′; and exon 8, forward 5′-GCCTCTTGCTTCTCTTTTCC-3′ and reverse 5′-TAACTGCACCCTTGGTCTCC-3′. Purification of PCR products was performed with exonuclease I–shrimp alkaline phosphatase (ExoSAP) purification. Direct sequencing of the PCR amplicons was performed for both strands on an ABI 3500 genetic analyzer (Life Technologies) using a version 1.1 BigDye Terminator cycle sequencing kit and a BigDye Xterminator purification kit (Life Technologies). For this feasibility study, the multiplex PCR-based Ion AmpliSeq cancer panel was used. The panel consists of 190 primer pairs for the detection of hot-spot mutations in 46 cancer-related genes. (This panel lacks U.S. Food and Drug Administration approval for clinical use and therefore is available for research use only.) The covered amplicons are listed in Supplemental Table S1. Amplicon library preparation was performed using approximately 10 ng of DNA, as recommended by the manufacturer. In brief, the DNA was mixed with a primer pool containing all primers for generating the 190 amplicons (which comprise hot-spot mutational sites of 46 genes) and with the Ion AmpliSeq HiFi master mix and was transferred to a PCR cycler (Bio-Rad Laboratories, Munich, Germany; Hercules, CA). PCR cycling conditions were initial denaturation at 99°C for 2 minutes, followed by 21 cycles of 99°C for 15 seconds and 60°C for 4 minutes. After the end of the PCR reaction, primer end sequences were partially digested using FuPa reagent according to the manufacturer’s instructions; this step was followed by the ligation of barcoded sequencing adapters (Ion Xpress barcode adapters 1 to 16; Life Technologies). The final library was purified using AMPure XP magnetic beads (Beckman Coulter, Krefeld, Germany; Brea, CA) and was quantified using qPCR (Ion library quantitation kit; Life Technologies) on a StepOne qPCR system (Life Technologies). The individual libraries were diluted to a final concentration of 20 pmol/L, and eight libraries were pooled and processed to library amplification on Ion Sphere particles using Ion OneTouch 200-bp chemistry (Life Technologies). Unenriched libraries were quality-controlled using Ion Sphere quality control measurement on a Qubit instrument. After library enrichment (Ion OneTouch ES), the library was processed for sequencing using the Ion Torrent 200-bp sequencing chemistry; the eight barcoded libraries were loaded then onto a single 318 chip. Raw data analysis was performed using Ion Torrent Suite software version 2.2 or 3.0 (Life Technologies). The reads were aligned to the human reference sequence build 38 (hg19) using the TMAP aligner implemented in the Torrent Suite software or, alternatively, using commercial third-party software (CLC Genomics Suite, version 5.5; CLC Bio, Aarhus, Denmark; Cambridge, MA). Detection of 1-bp variants and indel polymorphisms, relative to the human reference sequence, was performed using either the Torrent Suite version 2.2 or 3.0 Variant Caller routine or the two built-in variant detection algorithms (ie, the probabilistic and the quality-based variant caller) of the CLC Genomics suite. In cases for which we re-evaluated the Sanger-based mutation calls, two experienced molecular biologists (V.E. and R.P.) reanalyzed the original Sanger trace files. For detection of gene amplifications, the number of reads of each individual amplicon in the pools was determined using the multiBamCov-Tool in the BEDTools suite.22Quinlan A.R. Hall I.M. BEDTools: a flexible suite of utilities for comparing genomic features.Bioinformatics. 2010; 26: 841-842Crossref PubMed Scopus (11683) Google Scholar For normalization, these read values were first divided by the total number of sequencing reads of the respective sample. In a second step, the normalized amplicon read depth value (NARD) was multiplied by the total number of amplicons in the pool (190 amplicons in the Ion AmpliSeq cancer panel pool): NARD = (reads amplicon x/total reads) × 190. In a third step, the median normalized amplicon read depth (MNARD) of all samples was determined as MNARD = median (NARDSample 1:NARDSample x). This value reflects the typical amplification efficiency of each individual amplicon in the pool. Amplicons were considered amplified when their normalized read depth (NARD) differed by >2 SD from the median value. The presence of EGFR gene amplifications was detected with a TaqMan copy number assay (Life Technologies) using a 105-bp probe located in exon 19 of the EGFR gene (hg19: Chr.7:55241627). In brief, 20 ng of FFPE-extracted DNA was mixed with 2× TaqMan genotyping master mix and a 1× concentration of both assay and reference probe (RNase P) in a 96-well plate. qPCR was performed on a StepOne Plus qPCR instrument (Life Technologies) with an initial 10-minute hold stage at 95°C, followed by 40 cycles of 95°C for 15 seconds and 60°C for 60 seconds. Results were analyzed using the instrument's StepOne software and the Copy Caller program (Life Technologies) Copy Caller program. The DNA concentrations of our samples ranged from 0.22 ng/μL to 10.6 ng/μL, with most of the biopsy material falling at the lower end of this concentration range, because of small sample size and/or low tumor-cell content within larger biopsy samples (Table 1). For library preparation, we used a total of 10 ng DNA, as recommended by the manufacturer. For some samples, particularly small-biopsy probes, the available DNA material was severely limited, and then <10 ng was used for library preparation. After the PCR-mediated library generation and purification, we quantified each individual library using a qPCR strategy. We measured a concentration range of the libraries between 26.48 pmol/L and 2782 pmol/L, although similar initial DNA amounts (measured fluorimetrically using the Life Technologies Qubit instrument) were used for each sample. This most likely reflected differences in DNA quality and fragmentation grade that are inherent to FFPE material. Nonetheless, because all sample libraries had a concentration greater than the recommended library concentration of 20 pmol/L, we could generate sufficient material for the subsequent sequencing runs even for those samples with low DNA quality and limited tissue amounts (Table 1). To maximize throughput and to reduce sequencing costs, we barcoded the tumor samples and pooled eight individual libraries equimolarly. This multiple-sample library was used for emulsification and enrichment with the automated Ion OneTouch technology. We performed the sequencing runs on an Ion Torrent PGM personal genome machine using 200-bp chemistry. We achieved a median chip loading density of 81.75 ± 4.35% (median, 5126,774 reads/318 chip) for the four runs performed (Supplemental Table S2). For the individual samples, we obtained an average number of 669,781 reads; two samples had much higher per-sample total reads (sample 1-126 had 1,180,000 reads and sample 38412/12 had 2,630,000 reads). The average AQ20 value (which corresponds to a predicted error rate of the aligned reads of 1%) for all 32 samples was 83.32%, reflecting an average of 40,112,050 AQ20 bases sequenced per sample. Our test cohort comprised tumor samples with different EGFR mutations, including 12 deletions or indels in exon 19, 14 single missense mutations, and two insertions within exon 20 (Table 2).Table 2Summary of Identified Mutations in the NSCLC CohortSample IDEGFR mutationAdditional mutations (NGS)SangerNGSVLB001p.K745_A750delp.K746–A749del (25%)VLB002p.L747_P753delinsS + p.A755Dp.E746–P753del (49%) + p.A755D (59%)VLB003p.L858Rp.L858R (20%)VLB004p.N771dupp.N771dup (26%)MET: p.T1010I (42%); HNF1A: p.L254 mol/L (8%)VLB005p.E746_A750delp.E746_A750del (33%)SMO: p.A327T (45%)VLR006p.746_750delinsKPp.746–750delinsKP (38%)VLR007p.S768_D770dupp.A767D (13%)†False calling due to misalignment of the three-amino-acid duplication.TP53: p.F134L (14%)VLR008p.E746_A750delp.E746_A750del (50%)TP53: p.L112P (20%); CTNNB1: p.D32N (5%)VLR009p.E746_A750delp.E746_A750del (33%)TP53: p.L194R (37%)VLR010p.L858Rp.L858R (20%)TP53: p.R273L (17%); PDGFRA: p.Y671∗ (17%)VLR011p.E746_A750delp.E746_A750del (90%)TP53: p.A276F (31%)VLR028p.E746_S752delinsVp.E746_S752delinsV (33%)VLB012p.P848Lp.L858R (5%) + p.K737E (5%) + p.L844P (4%)BRAF: p.G466E (6%) and p.G442D (7%); HRAS: p.Q70∗ (4%); KRAS: p.Q61H (9%)VLB013p.L858Rp.L858R (6%)VLB014p.L858R‡Mutation not confirmed retrospectively.TP53: p.A159P (9%); BRAF: p.G596C (5%); NRAS: p.Q61R (4%)VLB015p.D855N‡Mutation not confirmed retrospectively. + KRAS: p.G12CRB1: p.R556∗ (4%); AKT1: p.E49K (5%); TP53: p.R209K (10%); KRAS: p.G12C (6%)VLB016p.E746_A750delp.E746_A750del (10%)TP53: p.P177R (8%)VLB017p.L858Rp.L858R (13%)ATM: p.F858L (66%)VLB018p.A859Sp.A859S (18%)PIK3CA: p.E542K (13%); TP53: p.Q165∗ (39%)VLB019p.S752F‡Mutation not confirmed retrospectively.KRAS: p.G12C (11%)VLB020p.L858Rp.L858R (12%)TP53: p.E204∗ (25%)VLB021p.L858Rp.L858R (31%)TP53: p.K305∗ (20%); KIT: p.M541L (57%)VLB022p.E746_A750delp.E746_A750del (49%)TP53: p.P295S (5%); JAK3: p.V722I (37%)VLB023p.L747_T751delinsPp.L747_T751delinsP (54%)KIT: p.M541L (78%); TP53: p.C242Y (34%)VLx024p.G724S§Not covered by the NGS amplicon. + p.S768Ip.S768I (50%)TP53: p.H193L (16%)VLx025p.E746_T751delinsVp.E746_T751delinsL (22%) + p.L858R (12%)KRAS: p.G12C (9%); CTNNB1: p.S45F (4%)VLR008p.E746_A750delp.E746_A750del (50%)TP53: p.L112P (20%); CTNNB1: p.D32N (5%)VLR008-2p.E746_A750delp.E746_A750del (49%)TP53: p.L112P (22%); CTNNB1: p.D32N (4%)VLR008-3p.E746_A750delp.E746_A750del (60%)TP53: p.L112P (21%); CTNNB1: p.D32N (3%)VLR007p.S768_D770dupp.A767D (13%)†False calling due to misalignment of the three-amino-acid duplication.TP53: p.F134L (14%)VLR007-2p.S768_D770dupVxx026p.E746_T751delinsAKRAS: p.G12C (58%); TP53: p.R248L (58%)Vxx027p.G724S‡Mutation not confirmed retrospectively.KIT: p.M541L (91%); MET: p.T99I (51%); TP53: p.R196∗ (75%)† False calling due to misalignment of the three-amino-acid duplication.‡ Mutation not confirmed retrospectively.§ Not covered by the NGS amplicon. Open table in a new tab First, we compared the efficacy of the MPS approach using tissue material obtained from FFPE small biopsies or from whole-tumor resections and containing ≥50% tumor tissue. The semiconductor-based sequencing approach confirmed all precharacterized EGFR mutations obtained by Sanger sequencing, with no differences in sequence quality, amplicon coverage, or variant detection between biopsies and whole-tumor resections. The detected allele frequencies ranged between 20% and 90%, reflecting heterozygous and homozygous variants in samples containing >50% tumor tissue. In one sample (VLR007), a three–amino-acid duplication in exon 20 of the EGFR gene (p.S768_D770dup) was not detected by any of the variant callers that we used. A manual re-examination of the MPS read tracks of the sample revealed the presence of the duplication (depth of 1945 reads); however," @default.
• W152480201 created "2016-06-24" @default.
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