The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Targeted Next-Generation Sequencing Panel (ThyroSeq) for Detection of Mutations in Thyroid Cancer
Open accessAbstract
OBJECTIVES: Next-generation sequencing (NGS) allows for high-throughput sequencing analysis of large regions of the human genome. We explored the use of targeted NGS for simultaneous testing for multiple mutations in thyroid cancer. DESIGN: A custom panel (ThyroSeq) was designed to target 12 cancer genes with 284 mutational hot spots. Sequencing was performed to analyze DNA from 228 thyroid neoplastic and nonneoplastic samples including 105 frozen, 72 formalin-fixed, and 51 fine-needle aspiration samples representing all major types of thyroid cancer. RESULTS: Only 5-10 ng of input DNA was sufficient for successful analysis of 99.6% of samples. The analytical accuracy for mutation detection was 100% with the sensitivity of 3%-5% of mutant allele. ThyroSeq DNA assay identified mutations in 19 of 27 of classic papillary thyroid carcinomas (PTCs) (70%), 25 of 30 follicular variant PTCs (83%), 14 of 18 conventional (78%) and 7 of 18 oncocytic follicular carcinomas (39%), 3 of 10 poorly differentiated carcinomas (30%), 20 of 27 anaplastic (ATCs) (74%), and 11 of 15 medullary thyroid carcinomas (73%). In contrast, 5 of 83 benign nodules (6%) were positive for mutations. Most tumors had a single mutation, whereas several ATCs and PTCs demonstrated two or three mutations. The most common mutations detected were BRAF and RAS followed by PIK3CA, TP53, TSHR, PTEN, GNAS, CTNNB1, and RET. The BRAF mutant allele frequency was 18%-48% in PTCs and was lower in ATCs. CONCLUSIONS: The ThyroSeq NGS panel allows simultaneous testing for multiple mutations with high accuracy and sensitivity, requires a small amount of DNA and can be performed in a variety of thyroid tissue and fine-needle aspiration samples, and provides quantitative assessment of mutant alleles. Using this approach, the point mutations were detected in 30%-83% of specific types of thyroid cancer and in only 6% of benign thyroid nodules and were shown to be present in the majority of cells within the cancer nodule.
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A method and server for predicting damaging missense mutations.
Adzhubei, I. A., Schmidt, S., Peshkin, L., Ramensky, V. E., Gerasimova, A., Bork, P., Kondrashov, A. S., & Sunyaev, S. R. (2010) · Nature Methods · doi:10.1038/nmeth0410-248 · Cited by 13,194
Sequencing technologies – the next generation
Metzker, M. L. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2626 · Cited by 7,066
Cited by
Haugen, B. R., Alexander, E. K., Bible, K. C., Doherty, G. M., Mandel, S. J., Nikiforov, Y. E., Pacini, F., Randolph, G. W., Sawka, A. M., Schlumberger, M., et al. (2016) · Thyroid® · doi:10.1089/thy.2015.0020 · Cited by 16,535
Self-citationMemorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT)
Cheng, D. T., Mitchell, T. N., Zehir, A., Shah, R. H., Benayed, R., Syed, A., Chandramohan, R., Liu, Z. Y., Won, H. H., Scott, S. N., et al. (2015) · The Journal of Molecular Diagnostics · doi:10.1016/j.jmoldx.2014.12.006 · Cited by 2,119
Singhi, A. D., McGrath, K., Brand, R. E., Khalid, A., Zeh, H. J., Chennat, J. S., Fasanella, K. E., Papachristou, G. I., Slivka, A., Bartlett, D. L., et al. (2018) · Gut · doi:10.1136/gutjnl-2016-313586 · Cited by 405
Self-citationShonka, D. C., Ho, A., Chintakuntlawar, A. V., Geiger, J. L., Park, J. C., Seetharamu, N., Jasim, S., Abdelhamid Ahmed, A. H., Bible, K. C., Brose, M. S., et al. (2022) · Head & Neck · doi:10.1002/hed.27025 · Cited by 117
Self-citationArtificial intelligence defines protein-based classification of thyroid nodules
Sun, Y., Selvarajan, S., Zang, Z., Liu, W., Zhu, Y., Zhang, H., Chen, W., Chen, H., Li, L., Cai, X., et al. (2022) · Cell Discovery · doi:10.1038/s41421-022-00442-x · Cited by 73
Metadata
- Authors
- Nikiforova, M. N., Wald, A. I., Roy, S., Durso, M. B., & Nikiforov, Y. E.
- Venue
- The Journal of Clinical Endocrinology & Metabolism
- Publisher
- The Endocrine Society
- Published
- 2013-11
- Volume
- 98
- Issue
- 11
- Pages
- E1852-E1860
- ISSN
- 0021-972X (ISSN-L)
- 1945-7197
- OpenAlex
- W2136507932
- Cited by
- 485
- References
- 2
- FWCI
- 37.74
- Type
- journal article
- Language
- en
- Open access
- bronze
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