Targeted, high-depth, next-generation sequencing of cancer genes in formalin-fixed, paraffin-embedded and fine-needle aspiration tumor specimens.

Implementation of highly sophisticated technologies, such as next-generation sequencing (NGS), into routine clinical practice requires compatibility with common tumor biopsy types, such as formalin-fixed, paraffin-embedded (FFPE) and fine-needle aspiration specimens, and validation metrics for platforms, controls, and data analysis pipelines. In this study, a two-step PCR enrichment workflow was used to assess 540 known cancer-relevant variants in 16 oncogenes for high-depth sequencing in tumor samples on either mature (Illumina GAIIx) or emerging (Ion Torrent PGM) NGS platforms. The results revealed that the background noise of variant detection was elevated approximately twofold in FFPE compared with cell line DNA. Bioinformatic algorithms were optimized to accommodate this background. Variant calls from 38 residual clinical colorectal cancer FFPE specimens and 10 thyroid fine-needle aspiration specimens were compared across multiple cancer genes, resulting in an accuracy of 96.1% (95% CI, 96.1% to 99.3%) compared with Sanger sequencing, and 99.6% (95% CI, 97.9% to 99.9%) compared with an alternative method with an analytical sensitivity of 1% mutation detection. A total of 45 of 48 samples were concordant between NGS platforms across all matched regions, with the three discordant calls each represented at <10% of reads. Consequently, NGS of targeted oncogenes in real-life tumor specimens using distinct platforms addresses unmet needs for unbiased and highly sensitive mutation detection and can accelerate both basic and clinical cancer research.

[1]  M. Hegde,et al.  Assessment of target enrichment platforms using massively parallel sequencing for the mutation detection for congenital muscular dystrophy. , 2012, The Journal of molecular diagnostics : JMD.

[2]  Ralf Herwig,et al.  Targeted high throughput sequencing in clinical cancer Settings: formaldehyde fixed-paraffin embedded (FFPE) tumor tissues, input amount and tumor heterogeneity , 2011, BMC Medical Genomics.

[3]  M. Bar‐eli,et al.  Analysis of N-RAS exon-1 mutations in myelodysplastic syndromes by polymerase chain reaction and direct sequencing. , 1989, Blood.

[4]  P. Savelkoul,et al.  Comparative analysis of four methods to extract DNA from paraffin-embedded tissues: effect on downstream molecular applications , 2010, BMC Research Notes.

[5]  Emily H Turner,et al.  Target-enrichment strategies for next-generation sequencing , 2010, Nature Methods.

[6]  F. Cianchi,et al.  The use of COLD-PCR and high-resolution melting analysis improves the limit of detection of KRAS and BRAF mutations in colorectal cancer. , 2010, The Journal of molecular diagnostics : JMD.

[7]  J. Rothberg,et al.  Prospective Genomic Characterization of the German Enterohemorrhagic Escherichia coli O104:H4 Outbreak by Rapid Next Generation Sequencing Technology , 2011, PloS one.

[8]  Jon R. Armstrong,et al.  Hybrid capture and next-generation sequencing identify viral integration sites from formalin-fixed, paraffin-embedded tissue. , 2011, The Journal of molecular diagnostics : JMD.

[9]  S. Collins,et al.  Rare occurrence of N-ras point mutations in Philadelphia chromosome positive chronic myeloid leukemia. , 1989, Blood.

[10]  Kikuya Kato,et al.  Intratumor heterogeneity of epidermal growth factor receptor mutations in lung cancer and its correlation to the response to gefitinib , 2008, Cancer science.

[11]  Renzo Boldorini,et al.  Increased Detection Sensitivity for KRAS Mutations Enhances the Prediction of Anti-EGFR Monoclonal Antibody Resistance in Metastatic Colorectal Cancer , 2011, Clinical Cancer Research.

[12]  Richard Durbin,et al.  Sequence analysis Fast and accurate short read alignment with Burrows – Wheeler transform , 2009 .

[13]  T. Dallman,et al.  Performance comparison of benchtop high-throughput sequencing platforms , 2012, Nature Biotechnology.

[14]  Thomas LaFramboise,et al.  Sensitive mutation detection in heterogeneous cancer specimens by massively parallel picoliter reactor sequencing , 2006, Nature Medicine.

[15]  M. Mazumdar,et al.  Intra- and Inter-Tumor Heterogeneity of BRAFV600EMutations in Primary and Metastatic Melanoma , 2012, PloS one.

[16]  Steven J. M. Jones,et al.  Evolution of an adenocarcinoma in response to selection by targeted kinase inhibitors , 2010, Genome Biology.

[17]  Jin Li,et al.  Ice-COLD-PCR enables rapid amplification and robust enrichment for low-abundance unknown DNA mutations , 2010, Nucleic Acids Res..

[18]  H. Scott,et al.  Sensitive detection of BCR-ABL1 mutations in patients with chronic myeloid leukemia after imatinib resistance is predictive of outcome during subsequent therapy. , 2011, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[19]  Olivier Harismendy,et al.  Detection of low prevalence somatic mutations in solid tumors with ultra-deep targeted sequencing , 2011, Genome Biology.

[20]  Sung-Liang Yu,et al.  Pretreatment epidermal growth factor receptor (EGFR) T790M mutation predicts shorter EGFR tyrosine kinase inhibitor response duration in patients with non-small-cell lung cancer. , 2012, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[21]  M. DePristo,et al.  A framework for variation discovery and genotyping using next-generation DNA sequencing data , 2011, Nature Genetics.

[22]  Bernard P. Puc,et al.  An integrated semiconductor device enabling non-optical genome sequencing , 2011, Nature.

[23]  P. Nowell.  Mechanisms of tumor progression. , 1986, Cancer research.

[24]  E. Boczko,et al.  An Analysis of Quantitative PCR Reliability Through Replicates Using the C Method. , 2010, Journal of biomedical science and engineering.

[25]  M. Metzker.  Sequencing technologies — the next generation , 2010, Nature Reviews Genetics.

[26]  Yuri E Nikiforov,et al.  Molecular diagnostics and predictors in thyroid cancer. , 2009, Thyroid : official journal of the American Thyroid Association.

[27]  N. Rosenfeld,et al.  Noninvasive Identification and Monitoring of Cancer Mutations by Targeted Deep Sequencing of Plasma DNA , 2012, Science Translational Medicine.

[28]  A. Kohlmann,et al.  The Interlaboratory RObustness of Next-generation sequencing (IRON) study: a deep sequencing investigation of TET2, CBL and KRAS mutations by an international consortium involving 10 laboratories , 2011, Leukemia.

[29]  P. A. Futreal,et al.  Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. , 2012, The New England journal of medicine.

[30]  Kathleen M Murphy,et al.  Comparison of Sanger sequencing, pyrosequencing, and melting curve analysis for the detection of KRAS mutations: diagnostic and clinical implications. , 2010, The Journal of molecular diagnostics : JMD.

[31]  K. Bloom,et al.  Sensitive multiplex detection of KRAS codons 12 and 13 mutations in paraffin-embedded tissue specimens , 2010, Journal of Clinical Pathology.

[32]  Sabine Tejpar,et al.  Effects of KRAS, BRAF, NRAS, and PIK3CA mutations on the efficacy of cetuximab plus chemotherapy in chemotherapy-refractory metastatic colorectal cancer: a retrospective consortium analysis. , 2010, The Lancet. Oncology.

[33]  Debyani Chakravarty,et al.  Intratumoral heterogeneity of receptor tyrosine kinases EGFR and PDGFRA amplification in glioblastoma defines subpopulations with distinct growth factor response , 2012, Proceedings of the National Academy of Sciences.

[34]  Mingming Jia,et al.  COSMIC (the Catalogue of Somatic Mutations in Cancer): a resource to investigate acquired mutations in human cancer , 2009, Nucleic Acids Res..

[35]  Torsten Seemann,et al.  Evolution of Multidrug Resistance during Staphylococcus aureus Infection Involves Mutation of the Essential Two Component Regulator WalKR , 2011, PLoS pathogens.

[36]  P. Nederlof,et al.  A multiplex PCR predictor for aCGH success of FFPE samples , 2005, British Journal of Cancer.

[37]  Nikhil Wagle,et al.  High-throughput detection of actionable genomic alterations in clinical tumor samples by targeted, massively parallel sequencing. , 2012, Cancer discovery.

[38]  Daniel N. Frank,et al.  BARCRAWL and BARTAB: software tools for the design and implementation of barcoded primers for highly multiplexed DNA sequencing , 2009, BMC Bioinformatics.

[39]  Yi-long Wu,et al.  Relative abundance of EGFR mutations predicts benefit from gefitinib treatment for advanced non-small-cell lung cancer. , 2011, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[40]  Keith L. Ligon,et al.  Profiling Critical Cancer Gene Mutations in Clinical Tumor Samples , 2009, PloS one.