BACKGROUND: Despite widespread interest in next-generation sequencing (NGS), the adoption of personalized clinical genomics and mutation profiling of cancer specimens is lagging, in part because of technical limitations. Tumors are genetically heterogeneous and often contain normal/stromal cells, features that lead to low-abundance somatic mutations that generate ambiguous results or reside below NGS detection limits, thus hindering the clinical sensitivity/specificity standards of mutation calling. We applied COLD-PCR (coamplification at lower denaturation temperature PCR), a PCR methodology that selectively enriches variants, to improve the detection of unknown mutations before NGS-based amplicon resequencing. METHODS: We used both COLD-PCR and conventional PCR (for comparison) to amplify serially diluted mutation-containing cell-line DNA diluted into wild-type DNA, as well as DNA from lung adenocarcinoma and colorectal cancer samples. After amplification of TP53 (tumor protein p53), KRAS (v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog), IDH1 [isocitrate dehydrogenase 1 (NADP(+)), soluble], and EGFR (epidermal growth factor receptor) gene regions, PCR products were pooled for library preparation, bar-coded, and sequenced on the Illumina HiSeq 2000. RESULTS: In agreement with recent findings, sequencing errors by conventional targeted-amplicon approaches dictated a mutation-detection limit of approximately 1%-2%. Conversely, COLD-PCR amplicons enriched mutations above the error-related noise, enabling reliable identification of mutation abundances of approximately 0.04%. Sequencing depth was not a large factor in the identification of COLD-PCR-enriched mutations. For the clinical samples, several missense mutations were not called with conventional amplicons, yet they were clearly detectable with COLD-PCR amplicons. Tumor heterogeneity for the TP53 gene was apparent. CONCLUSIONS: As cancer care shifts toward personalized intervention based on each patient's unique genetic abnormalities and tumor genome, we anticipate that COLD-PCR combined with NGS will elucidate the role of mutations in tumor progression, enabling NGS-based analysis of diverse clinical specimens within clinical practice.
BACKGROUND: Despite widespread interest in next-generation sequencing (NGS), the adoption of personalized clinical genomics and mutation profiling of cancer specimens is lagging, in part because of technical limitations. Tumors are genetically heterogeneous and often contain normal/stromal cells, features that lead to low-abundance somatic mutations that generate ambiguous results or reside below NGS detection limits, thus hindering the clinical sensitivity/specificity standards of mutation calling. We applied COLD-PCR (coamplification at lower denaturation temperature PCR), a PCR methodology that selectively enriches variants, to improve the detection of unknown mutations before NGS-based amplicon resequencing. METHODS: We used both COLD-PCR and conventional PCR (for comparison) to amplify serially diluted mutation-containing cell-line DNA diluted into wild-type DNA, as well as DNA from lung adenocarcinoma and colorectal cancer samples. After amplification of TP53 (tumor protein p53), KRAS (v-Ki-ras2 Kirsten ratsarcoma viral oncogene homolog), IDH1 [isocitrate dehydrogenase 1 (NADP(+)), soluble], and EGFR (epidermal growth factor receptor) gene regions, PCR products were pooled for library preparation, bar-coded, and sequenced on the Illumina HiSeq 2000. RESULTS: In agreement with recent findings, sequencing errors by conventional targeted-amplicon approaches dictated a mutation-detection limit of approximately 1%-2%. Conversely, COLD-PCR amplicons enriched mutations above the error-related noise, enabling reliable identification of mutation abundances of approximately 0.04%. Sequencing depth was not a large factor in the identification of COLD-PCR-enriched mutations. For the clinical samples, several missense mutations were not called with conventional amplicons, yet they were clearly detectable with COLD-PCR amplicons. Tumor heterogeneity for the TP53 gene was apparent. CONCLUSIONS: As cancer care shifts toward personalized intervention based on each patient's unique genetic abnormalities and tumor genome, we anticipate that COLD-PCR combined with NGS will elucidate the role of mutations in tumor progression, enabling NGS-based analysis of diverse clinical specimens within clinical practice.
Authors: Magali Olivier; Ros Eeles; Monica Hollstein; Mohammed A Khan; Curtis C Harris; Pierre Hainaut Journal: Hum Mutat Date: 2002-06 Impact factor: 4.878
Authors: Tobias Sjöblom; Siân Jones; Laura D Wood; D Williams Parsons; Jimmy Lin; Thomas D Barber; Diana Mandelker; Rebecca J Leary; Janine Ptak; Natalie Silliman; Steve Szabo; Phillip Buckhaults; Christopher Farrell; Paul Meeh; Sanford D Markowitz; Joseph Willis; Dawn Dawson; James K V Willson; Adi F Gazdar; James Hartigan; Leo Wu; Changsheng Liu; Giovanni Parmigiani; Ben Ho Park; Kurtis E Bachman; Nickolas Papadopoulos; Bert Vogelstein; Kenneth W Kinzler; Victor E Velculescu Journal: Science Date: 2006-09-07 Impact factor: 47.728
Authors: Jeffrey A Engelman; Toru Mukohara; Kreshnik Zejnullahu; Eugene Lifshits; Ana M Borrás; Christopher-Michael Gale; George N Naumov; Beow Y Yeap; Emily Jarrell; Jason Sun; Sean Tracy; Xiaojun Zhao; John V Heymach; Bruce E Johnson; Lewis C Cantley; Pasi A Jänne Journal: J Clin Invest Date: 2006-08-10 Impact factor: 14.808
Authors: Frank Diehl; Kerstin Schmidt; Michael A Choti; Katharine Romans; Steven Goodman; Meng Li; Katherine Thornton; Nishant Agrawal; Lori Sokoll; Steve A Szabo; Kenneth W Kinzler; Bert Vogelstein; Luis A Diaz Journal: Nat Med Date: 2007-07-31 Impact factor: 53.440
Authors: Christina I Zito; David Riches; Julia Kolmakova; Jan Simons; Michael Egholm; David F Stern Journal: Genes Chromosomes Cancer Date: 2008-07 Impact factor: 5.006
Authors: Michael A Quail; Iwanka Kozarewa; Frances Smith; Aylwyn Scally; Philip J Stephens; Richard Durbin; Harold Swerdlow; Daniel J Turner Journal: Nat Methods Date: 2008-12 Impact factor: 28.547
Authors: Joseph B Hiatt; Colin C Pritchard; Stephen J Salipante; Brian J O'Roak; Jay Shendure Journal: Genome Res Date: 2013-02-04 Impact factor: 9.043
Authors: Chen Song; Elena Castellanos-Rizaldos; Rafael Bejar; Benjamin L Ebert; G Mike Makrigiorgos Journal: Clin Chem Date: 2015-10-02 Impact factor: 8.327
Authors: Elena Castellanos-Rizaldos; Katherine Richardson; Rui Lin; Grant Wu; Mike G Makrigiorgos Journal: Clin Chem Date: 2014-10-08 Impact factor: 8.327
Authors: K Perez; R Walsh; K Brilliant; L Noble; E Yakirevich; V Breese; C Jackson; D Chatterjee; V Pricolo; L Roth; N Shah; T Cataldo; H Safran; D Hixson; P Quesenberry Journal: Exp Mol Pathol Date: 2013-03-22 Impact factor: 3.362
Authors: D M Murphy; R Bejar; K Stevenson; D Neuberg; Y Shi; C Cubrich; K Richardson; P Eastlake; G Garcia-Manero; H Kantarjian; B L Ebert; G Mike Makrigiorgos Journal: Leukemia Date: 2013-05-27 Impact factor: 11.528
Authors: Ioannis Ladas; Mariana Fitarelli-Kiehl; Chen Song; Viktor A Adalsteinsson; Heather A Parsons; Nancy U Lin; Nikhil Wagle; G Mike Makrigiorgos Journal: Clin Chem Date: 2017-07-05 Impact factor: 8.327