Comprehensive evaluation and validation of targeted next-generation sequencing performance in two clinical laboratories

Mendez,Pedro; Dang,Jennifer; Kim,James  Wansoo; Lee,Sharon; Yoon,Jun-Hee; Kim,Thomas; Sailey,Charles  J.; Jablons,David  M.; Kim,Il-Jin

doi:10.3892/ijo.2016.3497

Comprehensive evaluation and validation of targeted next-generation sequencing performance in two clinical laboratories

Authors:
- Pedro Mendez
- Jennifer Dang
- James Wansoo Kim
- Sharon Lee
- Jun-Hee Yoon
- Thomas Kim
- Charles J. Sailey
- David M. Jablons
- Il-Jin Kim
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Affiliations: Thoracic Oncology Laboratory, Department of Surgery, University of California San Francisco, San Francisco, CA 94115, USA, CureSeq Inc., Brisbane, CA 94005, USA
Published online on: April 25, 2016 https://doi.org/10.3892/ijo.2016.3497
Pages: 235-242

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Abstract

Next-generation sequencing (NGS) has led to breakthroughs for genetic and genomic analyses and personalized medicine approaches for many diseases. More and more clinical laboratories are using NGS as a genetic screening tool for providing mutation information that is used to select the best treatment regimens for cancer patients. However, several obstacles prevent the routine implementation of NGS technology into the clinical molecular diagnosis setting: the sophisticated sample preparation process, high cost, time-consuming data analyses, as well as the reproducibility and accuracy of interpretation. To systematically evaluate the performance and quality of targeted NGS cancer panel analyses in clinical laboratories, we performed three different tests: i) laboratory-to-laboratory accuracy test, ii) intra-laboratory precision validation, and iii) limit of detection test, using formalin-fixed, paraffin-embedded cancer tissue specimens, cell lines and mutation positive DNA. A laboratory-to-laboratory accuracy test performed using 51 samples showed 100% sensitivity and 99.97% specificity. For the intra-laboratory precision test, 100% reproducibility was observed. For the limit of detection test, KRAS mutations from samples diluted from 70 to 2% of mutant allele frequencies were detected correctly. We believe that the present study demonstrated the feasibility of clinical implementation of a targeted NGS cancer panel analysis for personalized medicine.

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1	Cancer Genome Atlas Research Network. Comprehensive molecular profiling of lung adenocarcinoma. Nature. 511:543–550. 2014. View Article : Google Scholar : PubMed/NCBI
2	George J, Lim JS, Jang SJ, Cun Y, Ozretić L, Kong G, Leenders F, Lu X, Fernández-Cuesta L, Bosco G, et al: Comprehensive genomic profiles of small cell lung cancer. Nature. 524:47–53. 2015. View Article : Google Scholar : PubMed/NCBI
3	Govindan R, Ding L, Griffith M, Subramanian J, Dees ND, Kanchi KL, Maher CA, Fulton R, Fulton L, Wallis J, et al: Genomic landscape of non-small cell lung cancer in smokers and never-smokers. Cell. 150:1121–1134. 2012. View Article : Google Scholar : PubMed/NCBI
4	Hammerman PS, Lawrence MS, Voet D, Jing R, Cibulskis K, Sivachenko A, Stojanov P, McKenna A, Lander ES, Gabriel S, et al; Cancer Genome Atlas Research Network. Comprehensive genomic characterization of squamous cell lung cancers. Nature. 489:519–525. 2012. View Article : Google Scholar
5	Network TCGA; Cancer Genome Atlas Network. Comprehensive molecular characterization of human colon and rectal cancer. Nature. 487:330–337. 2012. View Article : Google Scholar : PubMed/NCBI
6	Cancer Genome Atlas Network. Comprehensive molecular portraits of human breast tumours. Nature. 490:61–70. 2012. View Article : Google Scholar : PubMed/NCBI
7	Abstract G and Brief I; Cancer Genome Atlas Research Network. The Molecular Taxonomy of Primary Prostate Cancer. Cell. 163:1011–1025. 2015. View Article : Google Scholar
8	Cancer Genome Atlas Research Network. Comprehensive molecular characterization of urothelial bladder carcinoma. Nature. 507:315–322. 2014. View Article : Google Scholar : PubMed/NCBI
9	Hodis E, Watson IR, Kryukov GV, Arold ST, Imielinski M, Theurillat JP, Nickerson E, Auclair D, Li L, Place C, et al: A landscape of driver mutations in melanoma. Cell. 150:251–263. 2012. View Article : Google Scholar : PubMed/NCBI
10	Bass AJ, Thorsson V, Shmulevich I, Reynolds SM, Miller M, Bernard B, Hinoue T, Laird PW, Curtis C, Shen H, Weisenberger DJ, et al; Cancer Genome Atlas Research Network. Comprehensive molecular characterization of gastric adenocarcinoma. Nature. 513:202–209. 2014. View Article : Google Scholar :
11	Andersson AK, Ma J, Wang J, Chen X, Gedman AL, Dang J, Nakitandwe J, Holmfeldt L, Parker M, Easton J, et al; St. Jude Children's Research Hospital-Washington University Pediatric Cancer Genome Project. The landscape of somatic mutations in infant MLL-rearranged acute lymphoblastic leukemias. Nat Genet. 47:330–337. 2015. View Article : Google Scholar : PubMed/NCBI
12	Brennan CWW, Verhaak RGWGW, McKenna A, Campos B, Noushmehr H, Salama SR, Zheng S, Chakravarty D, Sanborn JZ, Berman SH, et al: The somatic genomic landscape of glioblastoma. Cell. 155:462–477. 2013. View Article : Google Scholar : PubMed/NCBI
13	Cancer Genome Atlas Research Network. Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia. N Engl J Med. 368:2059–2074. 2013. View Article : Google Scholar : PubMed/NCBI
14	Cancer T and Atlas G; Cancer Genome Atlas Research Network. Integrated genomic analyses of ovarian carcinoma. Nature. 474:609–615. 2011. View Article : Google Scholar
15	Chan-On W, Nairismägi M-L, Ong CK, Lim WK, Dima S, Pairojkul C, Lim KH, McPherson JR, Cutcutache I, Heng HL, et al: Exome sequencing identifies distinct mutational patterns in liver fluke-related and non-infection-related bile duct cancers. Nat Genet. 45:1474–1478. 2013. View Article : Google Scholar : PubMed/NCBI
16	Chen K, Yang D, Li X, Sun B, Song F, Cao W, Brat DJ, Gao Z, Li H, Liang H, et al: Mutational landscape of gastric adenocarcinoma in Chinese: Implications for prognosis and therapy. Proc Natl Acad Sci USA. 112:1107–1112. 2015. View Article : Google Scholar : PubMed/NCBI
17	Johnson BE, Mazor T, Hong C, Barnes M, Aihara K, McLean CY, Fouse SD, Yamamoto S, Ueda H, Tatsuno K, et al: Mutational analysis reveals the origin and therapy-driven evolution of recurrent glioma. Science. 343:189–193. 2014. View Article : Google Scholar :
18	Jones DTW, Jäger N, Kool M, Zichner T, Hutter B, Sultan M, Cho YJ, Pugh TJ, Hovestadt V, Stütz AM, et al: Dissecting the genomic complexity underlying medulloblastoma. Nature. 488:100–105. 2012. View Article : Google Scholar : PubMed/NCBI
19	Lawrence MS, Sougnez C, Lichtenstein L, Cibulskis K, Lander E, Gabriel SB, Getz G, Ally A, Balasundaram M, Birol I, et al; Cancer Genome Atlas Network. Comprehensive genomic characterization of head and neck squamous cell carcinomas. Nature. 517:576–582. 2015. View Article : Google Scholar
20	Li M, Zhang Z, Li X, Ye J, Wu X, Tan Z, Liu C, Shen B, Wang XA, Wu W, et al: Whole-exome and targeted gene sequencing of gallbladder carcinoma identifies recurrent mutations in the ErbB pathway. Nat Genet. 46:872–876. 2014. View Article : Google Scholar : PubMed/NCBI
21	Lin DC, Hao JJ, Nagata Y, Xu L, Shang L, Meng X, Sato Y, Okuno Y, Varela AM, Ding LW, et al: Genomic and molecular characterization of esophageal squamous cell carcinoma. Nat Genet. 46:467–473. 2014. View Article : Google Scholar : PubMed/NCBI
22	Lohr JG, Stojanov P, Carter SL, Cruz-Gordillo P, Lawrence MS, Auclair D, Sougnez C, Knoechel B, Gould J, Saksena G, et al; Multiple Myeloma Research Consortium. Widespread genetic heterogeneity in multiple myeloma: Implications for targeted therapy. Cancer Cell. 25:91–101. 2014. View Article : Google Scholar : PubMed/NCBI
23	Creighton CJ, Morgan M, Gunaratne PH, Wheeler DA, Gibbs RA, Gordon Robertson A, Chu A, Beroukhim R, Cibulskis K, Signoretti S, et al; Cancer Genome Atlas Research Network. Comprehensive molecular characterization of clear cell renal cell carcinoma. Nature. 499:43–49. 2013. View Article : Google Scholar
24	Tirode F, Surdez D, Ma X, Parker M, Le Deley MC, Bahrami A, Zhang Z, Lapouble E, Grossetête-Lalami S, Rusch M, et al; St. Jude Children's Research Hospital-Washington University Pediatric Cancer Genome Project and the International Cancer Genome Consortium. Genomic landscape of Ewing sarcoma defines an aggressive subtype with co-association of STAG2 and TP53 mutations. Cancer Discov. 4:1342–1353. 2014. View Article : Google Scholar : PubMed/NCBI
25	Carrick DM, Mehaffey MG, Sachs MC, Altekruse S, Camalier C, Chuaqui R, Cozen W, Das B, Hernandez BY, Lih CJ, et al: Robustness of next generation sequencing on older formalin-fixed paraffin-embedded tissue. PLoS One. 10:e01273532015. View Article : Google Scholar : PubMed/NCBI
26	Fujita S, Masago K, Takeshita J, Okuda C, Otsuka K, Hata A, Kaji R, Katakami N and Hirata Y: Validation of an ion torrent sequencing platform for the detection of gene mutations in biopsy specimens from patients with non-small-cell lung cancer. PLoS One. 10:e01302192015. View Article : Google Scholar : PubMed/NCBI
27	Newman AM, Bratman SV, To J, Wynne JF, Eclov NC, Modlin LA, Liu CL, Neal JW, Wakelee HA, Merritt RE, et al: An ultrasensitive method for quantitating circulating tumor DNA with broad patient coverage. Nat Med. 20:548–554. 2014. View Article : Google Scholar : PubMed/NCBI
28	Dawson SJ, Tsui DWY, Murtaza M, Biggs H, Rueda OM, Chin SF, Dunning MJ, Gale D, Forshew T, Mahler-Araujo B, et al: Analysis of circulating tumor DNA to monitor metastatic breast cancer. N Engl J Med. 368:1199–1209. 2013. View Article : Google Scholar : PubMed/NCBI