Hassan Ashktorab1, Hamed Azimi1, Michael L Nickerson2, Sara Bass2, Sudhir Varma3, Hassan Brim4. 1. Department of Medicine and Cancer Center, Howard University College of Medicine, Washington DC. 2. Center for Cancer Research, National Cancer Institute, Frederick, USA. 3. Hithru LLC, Silver Spring, Center for Cancer Research, National Cancer Institute, Frederick, USA. 4. Department of Pathology, Howard University College of Medicine, Washington DC.
Abstract
BACKGROUND AND AIM: Next generation sequencing (NGS) has quickly the tool of choice for genome and exome data generation. The multitude of sequencing platforms as well as the variabilities within each platform need to be assessed. In this paper we used two platforms (ION TORRENT AND ILLUMINA) to assess single nucleotides variants in colorectal cancer (CRC) specimens. METHODS: CRC specimens (n = 13) collected from 6 CRC (cancer and matched normal) patients were used to establish the mutational profile using ION TORRENT AND ILLUMINA sequencing platforms. We analyzed a set of samples from Formalin Fixed Paraffin Embedded and FF (FF) samples on both platforms to assess the effect of sample nature (FFPE vs. FF) on sequencing outcome and to evaluate the similarity/differences of SNVs across the two platforms. In addition, duplicates of FF samples were sequenced on each platform to assess variability within platform. RESULTS: The comparison of FF replicates to each other gave a concordance of 77% (± 15.3%) in Ion Torrent and 70% (± 3.7%) in Illumina. FFPE vs. FF replicates gave a concordance of 40% (± 32%) in Ion Torrent and 49% (± 19%) in Illumina. For the cross platform concordance were FFPE compared to FF (Average of 75% (± 9.8%) for FFPE samples and 67% (± 32%) for FF and 70% (± 26.8%) overall average). CONCLUSION: Our data show a significant variability within and across platforms. Also the number of detected variants depend on the nature of the specimen; FF vs. FFPE. Validation of NGS discovered mutations is a must to rule-out false positive mutants. This validation might either be performed through a second NGS platform or through Sanger sequencing.
BACKGROUND AND AIM: Next generation sequencing (NGS) has quickly the tool of choice for genome and exome data generation. The multitude of sequencing platforms as well as the variabilities within each platform need to be assessed. In this paper we used two platforms (ION TORRENT AND ILLUMINA) to assess single nucleotides variants in colorectal cancer (CRC) specimens. METHODS: CRC specimens (n = 13) collected from 6 CRC (cancer and matched normal) patients were used to establish the mutational profile using ION TORRENT AND ILLUMINA sequencing platforms. We analyzed a set of samples from Formalin Fixed Paraffin Embedded and FF (FF) samples on both platforms to assess the effect of sample nature (FFPE vs. FF) on sequencing outcome and to evaluate the similarity/differences of SNVs across the two platforms. In addition, duplicates of FF samples were sequenced on each platform to assess variability within platform. RESULTS: The comparison of FF replicates to each other gave a concordance of 77% (± 15.3%) in Ion Torrent and 70% (± 3.7%) in Illumina. FFPE vs. FF replicates gave a concordance of 40% (± 32%) in Ion Torrent and 49% (± 19%) in Illumina. For the cross platform concordance were FFPE compared to FF (Average of 75% (± 9.8%) for FFPE samples and 67% (± 32%) for FF and 70% (± 26.8%) overall average). CONCLUSION: Our data show a significant variability within and across platforms. Also the number of detected variants depend on the nature of the specimen; FF vs. FFPE. Validation of NGS discovered mutations is a must to rule-out false positive mutants. This validation might either be performed through a second NGS platform or through Sanger sequencing.
Authors: K Bodi; A G Perera; P S Adams; D Bintzler; K Dewar; D S Grove; J Kieleczawa; R H Lyons; T A Neubert; A C Noll; S Singh; R Steen; M Zianni Journal: J Biomol Tech Date: 2013-07
Authors: Xiang Chen; Pankaj Gupta; Jianmin Wang; Joy Nakitandwe; Kathryn Roberts; James D Dalton; Matthew Parker; Samir Patel; Linda Holmfeldt; Debbie Payne; John Easton; Jing Ma; Michael Rusch; Gang Wu; Aman Patel; Suzanne J Baker; Michael A Dyer; Sheila Shurtleff; Stephen Espy; Stanley Pounds; James R Downing; David W Ellison; Charles G Mullighan; Jinghui Zhang Journal: Nat Methods Date: 2015-05-04 Impact factor: 28.547
Authors: Ben Tran; Andrew M K Brown; Philippe L Bedard; Eric Winquist; Glenwood D Goss; Sebastien J Hotte; Stephen A Welch; Hal W Hirte; Tong Zhang; Lincoln D Stein; Vincent Ferretti; Stuart Watt; Wei Jiao; Karen Ng; Sangeet Ghai; Patricia Shaw; Teresa Petrocelli; Thomas J Hudson; Benjamin G Neel; Nicole Onetto; Lillian L Siu; John D McPherson; Suzanne Kamel-Reid; Janet E Dancey Journal: Int J Cancer Date: 2012-10-11 Impact factor: 7.396
Authors: Michael A Quail; Miriam Smith; Paul Coupland; Thomas D Otto; Simon R Harris; Thomas R Connor; Anna Bertoni; Harold P Swerdlow; Yong Gu Journal: BMC Genomics Date: 2012-07-24 Impact factor: 3.969
Authors: Sarah B Ng; Emily H Turner; Peggy D Robertson; Steven D Flygare; Abigail W Bigham; Choli Lee; Tristan Shaffer; Michelle Wong; Arindam Bhattacharjee; Evan E Eichler; Michael Bamshad; Deborah A Nickerson; Jay Shendure Journal: Nature Date: 2009-08-16 Impact factor: 49.962
Authors: Yuqing Li; Kenneth B Beckman; Christian Caberto; Remi Kazma; Annette Lum-Jones; Christopher A Haiman; Loïc Le Marchand; Daniel O Stram; Richa Saxena; Iona Cheng Journal: PLoS One Date: 2015-09-04 Impact factor: 3.240
Authors: Hassan Brim; Mones S Abu-Asab; Mehdi Nouraie; Jose Salazar; Jim Deleo; Hadi Razjouyan; Pooneh Mokarram; Alejandro A Schaffer; Fakhraddin Naghibhossaini; Hassan Ashktorab Journal: PLoS One Date: 2014-01-27 Impact factor: 3.240
Authors: Hassan Ashktorab; Hamed Azimi; Sudhir Varma; Edward L Lee; Adeyinka O Laiyemo; Michael L Nickerson; Hassan Brim Journal: Oncotarget Date: 2019-04-05
Authors: Aaron M Walsh; Fiona Crispie; Orla O'Sullivan; Laura Finnegan; Marcus J Claesson; Paul D Cotter Journal: Microbiome Date: 2018-03-20 Impact factor: 14.650