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      Performance comparison of two commercial human whole-exome capture systems on formalin-fixed paraffin-embedded lung adenocarcinoma samples

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          Abstract

          Background

          Next Generation Sequencing (NGS) has become a valuable tool for molecular landscape characterization of cancer genomes, leading to a better understanding of tumor onset and progression, and opening new avenues in translational oncology. Formalin-fixed paraffin-embedded (FFPE) tissue is the method of choice for storage of clinical samples, however low quality of FFPE genomic DNA (gDNA) can limit its use for downstream applications.

          Methods

          To investigate the FFPE specimen suitability for NGS analysis and to establish the performance of two solution-based exome capture technologies, we compared the whole-exome sequencing (WES) data of gDNA extracted from 5 fresh frozen (FF) and 5 matched FFPE lung adenocarcinoma tissues using: SeqCap EZ Human Exome v.3.0 (Roche NimbleGen) and SureSelect XT Human All Exon v.5 (Agilent Technologies).

          Results

          Sequencing metrics on Illumina HiSeq were optimal for both exome systems and comparable among FFPE and FF samples, with a slight increase of PCR duplicates in FFPE, mainly in Roche NimbleGen libraries. Comparison of single nucleotide variants (SNVs) between FFPE-FF pairs reached overlapping values >90 % in both systems. Both WES showed high concordance with target re-sequencing data by Ion PGM™ in 22 lung-cancer genes, regardless the source of samples. Exon coverage of 623 cancer-related genes revealed high coverage efficiency of both kits, proposing WES as a valid alternative to target re-sequencing.

          Conclusions

          High-quality and reliable data can be successfully obtained from WES of FFPE samples starting from a relatively low amount of input gDNA, suggesting the inclusion of NGS-based tests into clinical contest. In conclusion, our analysis suggests that the WES approach could be extended to a translational research context as well as to the clinic (e.g. to study rare malignancies), where the simultaneous analysis of the whole coding region of the genome may help in the detection of cancer-linked variants.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12885-016-2720-4) contains supplementary material, which is available to authorized users.

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          Most cited references29

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          The genomic landscapes of human breast and colorectal cancers.

          Human cancer is caused by the accumulation of mutations in oncogenes and tumor suppressor genes. To catalog the genetic changes that occur during tumorigenesis, we isolated DNA from 11 breast and 11 colorectal tumors and determined the sequences of the genes in the Reference Sequence database in these samples. Based on analysis of exons representing 20,857 transcripts from 18,191 genes, we conclude that the genomic landscapes of breast and colorectal cancers are composed of a handful of commonly mutated gene "mountains" and a much larger number of gene "hills" that are mutated at low frequency. We describe statistical and bioinformatic tools that may help identify mutations with a role in tumorigenesis. These results have implications for understanding the nature and heterogeneity of human cancers and for using personal genomics for tumor diagnosis and therapy.
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            Diverse somatic mutation patterns and pathway alterations in human cancers.

            The systematic characterization of somatic mutations in cancer genomes is essential for understanding the disease and for developing targeted therapeutics. Here we report the identification of 2,576 somatic mutations across approximately 1,800 megabases of DNA representing 1,507 coding genes from 441 tumours comprising breast, lung, ovarian and prostate cancer types and subtypes. We found that mutation rates and the sets of mutated genes varied substantially across tumour types and subtypes. Statistical analysis identified 77 significantly mutated genes including protein kinases, G-protein-coupled receptors such as GRM8, BAI3, AGTRL1 (also called APLNR) and LPHN3, and other druggable targets. Integrated analysis of somatic mutations and copy number alterations identified another 35 significantly altered genes including GNAS, indicating an expanded role for galpha subunits in multiple cancer types. Furthermore, our experimental analyses demonstrate the functional roles of mutant GNAO1 (a Galpha subunit) and mutant MAP2K4 (a member of the JNK signalling pathway) in oncogenesis. Our study provides an overview of the mutational spectra across major human cancers and identifies several potential therapeutic targets.
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              Whole-exome sequencing and clinical interpretation of FFPE tumor samples to guide precision cancer medicine

              Translating whole exome sequencing (WES) for prospective clinical use may impact the care of cancer patients; however, multiple innovations are necessary for clinical implementation. These include: (1) rapid and robust WES from formalin-fixed paraffin embedded (FFPE) tumor tissue, (2) analytical output similar to data from frozen samples, and (3) clinical interpretation of WES data for prospective use. Here, we describe a prospective clinical WES platform for archival FFPE tumor samples. The platform employs computational methods for effective clinical analysis and interpretation of WES data. When applied retrospectively to 511 exomes, the interpretative framework revealed a “long tail” of somatic alterations in clinically important genes. Prospective application of this approach identified clinically relevant alterations in 15/16 patients. In one patient, previously undetected findings guided clinical trial enrollment leading to an objective clinical response. Overall, this methodology may inform the widespread implementation of precision cancer medicine.
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                Author and article information

                Contributors
                bonfiglio.silvia@hsr.it
                irene.vanni@hsanmartino.it
                rossella.valeria@hsr.it
                anna.truini@email.it
                lazarevic.dejan@hsr.it
                mariagiovanna.dalbello@hsanmartino.it
                angela.alama@hsanmartino.it
                marco.mora@hsanmartino.it
                ery80x@yahoo.it
                carlo.genova1985@gmail.com
                cittaro.davide@hsr.it
                francesco.grossi@hsanmartino.it
                simona.coco@hsanmartino.it
                Journal
                BMC Cancer
                BMC Cancer
                BMC Cancer
                BioMed Central (London )
                1471-2407
                30 August 2016
                30 August 2016
                2016
                : 16
                : 1
                : 692
                Affiliations
                [1 ]Centre for Translational Genomics and Bioinformatics, San Raffaele Scientific Institute, Via Olgettina 58, Milan, 20132 Italy
                [2 ]Lung Cancer Unit, IRCCS AOU San Martino - IST National Cancer Research Institute, L.go R. Benzi 10, Genoa, 16132 Italy
                [3 ]Department of Internal Medicine and Medical Specialties (DIMI), University of Genoa, Italy, IRCCS AOU San Martino - IST National Cancer Research Institute, L.go R. Benzi 10, Genoa, 16132 Italy
                [4 ]Department of Pathology, IRCCS AOU San Martino - IST National Cancer Research Institute, L.go R. Benzi 10, Genoa, 16132 Italy
                Author information
                http://orcid.org/0000-0002-5296-4325
                Article
                2720
                10.1186/s12885-016-2720-4
                5004269
                27578032
                0e6f19f4-2626-4602-97bc-efc55e67dd94
                © The Author(s). 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 1 June 2016
                : 11 August 2016
                Funding
                Funded by: Italian Ministry of Health
                Award ID: GR 2011-12; 02350922
                Award Recipient :
                Funded by: Banca Carige Italia
                Award ID: 2013.0277-12
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2016

                Oncology & Radiotherapy
                exome sequencing,ffpe,quality control,solution-based capture,cancer-related genes,lung adenocarcinoma

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