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Broad, Hybrid Capture–Based Next-Generation Sequencing Identifies Actionable Genomic Alterations in Lung Adenocarcinomas Otherwise Negative for Such Alterations by Other Genomic Testing Approaches
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Abstract
PURPOSE: Broad, hybrid capture-based next-generation sequencing (NGS), as a clinical test, uses less tissue to identify more clinically relevant genomic alterations compared with profiling with multiple non-NGS tests. We set out to determine the frequency of such genomic alterations via this approach in tumors in which previous extensive non-NGS testing had not yielded a targetable driver alteration. EXPERIMENTAL DESIGN: We enrolled patients with lung adenocarcinoma with a ≤ 15 pack-year smoking history whose tumors previously tested "negative" for alterations in 11 genes (mutations in EGFR, ERBB2, KRAS, NRAS, BRAF, MAP2K1, PIK3CA, and AKT1 and fusions involving ALK, ROS1, and RET) via multiple non-NGS methods. We performed hybridization capture of the coding exons of 287 cancer-related genes and 47 introns of 19 frequently rearranged genes and sequenced these to deep, uniform coverage. RESULTS: Actionable genomic alterations with a targeted agent based on NCCN guidelines were identified in 26% [8 of 31: EGFR G719A, BRAF V600E, SOCS5-ALK, HIP1-ALK, CD74-ROS1, KIF5B-RET (n = 2), CCDC6-RET]. Seven of these patients either received or are candidates for targeted therapy. Comprehensive genomic profiling using this method also identified a genomic alteration with a targeted agent available on a clinical trial in an additional 39% (12 of 31). CONCLUSIONS: Broad, hybrid capture-based NGS identified actionable genomic alterations in 65% [95% confidence interval (CI), 48%-82%] of tumors from never or light smokers with lung cancers deemed without targetable genomic alterations by earlier extensive non-NGS testing. These findings support first-line profiling of lung adenocarcinomas using this approach as a more comprehensive and efficient strategy compared with non-NGS testing. See related commentary by McCutcheon and Giaccone, p. 3584.
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“Digital polymerase chain reaction assays have been developed with high sensitivity and specificity for detection of variants in ctDNA (24, 27), however, these approaches are typically limited to hotspot mutations in a few genes, and cannot interrogate the full spectrum of mutations that may emerge in the setting of acquired resistance during targeted therapy (28).”
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Lynch, T. J., Bell, D. W., Sordella, R., Gurubhagavatula, S., Okimoto, R. A., Brannigan, B. W., Harris, P. L., Haserlat, S. M., Supko, J. G., Haluska, F. G., et al. (2004) · New England Journal of Medicine · doi:10.1056/nejmoa040938 · Cited by 11,486
EGFR Mutations in Lung Cancer: Correlation with Clinical Response to Gefitinib Therapy
Paez, J. G., Jänne, P. A., Lee, J. C., Tracy, S., Greulich, H., Gabriel, S., Herman, P., Kaye, F. J., Lindeman, N., Boggon, T. J., et al. (2004) · Science · doi:10.1126/science.1099314 · Cited by 9,368
Gefitinib or Carboplatin–Paclitaxel in Pulmonary Adenocarcinoma
Mok, T. S., Wu, Y.-L., Thongprasert, S., Yang, C.-H., Chu, D.-T., Saijo, N., Sunpaweravong, P., Han, B., Margono, B., Ichinose, Y., et al. (2009) · New England Journal of Medicine · doi:10.1056/nejmoa0810699 · Cited by 8,261
Rosell, R., Carcereny, E., Gervais, R., Vergnenegre, A., Massuti, B., Felip, E., Palmero, R., Garcia-Gomez, R., Pallares, C., Sanchez, J. M., et al. (2012) · The Lancet Oncology · doi:10.1016/s1470-2045(11)70393-x · Cited by 5,489
Mutational heterogeneity in cancer and the search for new cancer-associated genes
Lawrence, M. S., Stojanov, P., Polak, P., Kryukov, G. V., Cibulskis, K., Sivachenko, A., Carter, S. L., Stewart, C., Mermel, C. H., Roberts, S. A., et al. (2013) · Nature · doi:10.1038/nature12213 · Cited by 5,461
Identification of the transforming EML4–ALK fusion gene in non-small-cell lung cancer
Soda, M., Choi, Y. L., Enomoto, M., Takada, S., Yamashita, Y., Ishikawa, S., Fujiwara, S.-I., Watanabe, H., Kurashina, K., Hatanaka, H., et al. (2007) · Nature · doi:10.1038/nature05945 · Cited by 5,439
Next-generation DNA sequencing
Shendure, J., & Ji, H. (2008) · Nature Biotechnology · doi:10.1038/nbt1486 · Cited by 4,509
Mutational landscape and significance across 12 major cancer types
Kandoth, C., McLellan, M. D., Vandin, F., Ye, K., Niu, B., Lu, C., Xie, M., Zhang, Q., McMichael, J. F., Wyczalkowski, M. A., et al. (2013) · Nature · doi:10.1038/nature12634 · Cited by 4,419
Pao, W., Miller, V., Zakowski, M., Doherty, J., Politi, K., Sarkaria, I., Singh, B., Heelan, R., Rusch, V., Fulton, L., et al. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0405220101 · Cited by 4,338
Self-citationCrizotinib versus Chemotherapy in Advanced ALK -Positive Lung Cancer
Shaw, A. T., Kim, D.-W., Nakagawa, K., Seto, T., Crinó, L., Ahn, M.-J., De Pas, T., Besse, B., Solomon, B. J., Blackhall, F., et al. (2013) · New England Journal of Medicine · doi:10.1056/nejmoa1214886 · Cited by 3,381
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Research works printed but not linked: 4
- Camidge, 2014, Efficacy and safety of crizotinib in patients with advanced c-MET-amplified non-small cell lung cancer (NSCLC), J Clin Oncol, 32, 5s, 10.1200/jco.2014.32.15_suppl.8001 · DOI
- Ali, 2014, Identifying ALK rearrangements that are not detected by FISH with targeted next-generation sequencing of lung carcinoma, J Clin Oncol, 32, 5s, 10.1200/jco.2014.32.15_suppl.8049 · DOI
- Planchard, 2013, Interim results of phase II study BRF113928 of dabrafenib in BRAF V600E mutation–positive non-small cell lung cancer (NSCLC) patients, J Clin Oncol, 31
- Cheng, MSK-IMPACT: A hybridization capture-based next generation sequencing clinical assay for solid tumor molecular oncology, J Mol Diagn
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Institutional implementation of clinical tumor profiling on an unselected cancer population
Sholl, L. M., Do, K., Shivdasani, P., Cerami, E., Dubuc, A. M., Kuo, F. C., Garcia, E. P., Jia, Y., Davineni, P., Abo, R. P., et al. (2016) · JCI Insight · doi:10.1172/jci.insight.87062 · Cited by 450
Thompson, J. C., Yee, S. S., Troxel, A. B., Savitch, S. L., Fan, R., Balli, D., Lieberman, D. B., Morrissette, J. D., Evans, T. L., Bauml, J., et al. (2016) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-16-1231 · Cited by 325
“Digital PCR assays have been developed with high sensitivity and specificity for detection of variants in ctDNA (24, 27); however, these approaches are typically limited to hotspot mutations in a few genes, and cannot interrogate the full spectrum of mutations that may emerge in the setting of acquired resistance duri…”
BackgroundScientific Advances in Lung Cancer 2015
Tsao, A. S., Scagliotti, G. V., Bunn, P. A., Carbone, D. P., Warren, G. W., Bai, C., de Koning, H. J., Yousaf-Khan, A. U., McWilliams, A., Tsao, M. S., et al. (2016) · Journal of Thoracic Oncology · doi:10.1016/j.jtho.2016.03.012 · Cited by 284
Metadata
- Authors
- Drilon, A., Wang, L., Arcila, M. E., Balasubramanian, S., Greenbowe, J. R., Ross, J. S., Stephens, P., Lipson, D., Miller, V. A., Kris, M. G., Ladanyi, M., & Rizvi, N. A.
- Affiliations
- Memorial Sloan Kettering Cancer Center (US)
- Foundation Medicine (United States) (US)
- Corresponding author
- Drilon, Alexander
- ORCID
- Venue
- Clinical Cancer Research
- Published
- 2015-08-13
- Volume
- 21
- Issue
- 16
- Pages
- 3631-3639
- ISSN
- 1078-0432 (ISSN-L)
- 1557-3265
- PMC
- PMC4917003
- OpenAlex
- W2146448515
- Cited by
- 274
- References
- 31
- Citations by year
- 2026: 4 · 2025: 13 · 2024: 19 · 2023: 24 · 2022: 23 · 2021: 28 · 2020: 23 · 2019: 24 · 2018: 39 · 2017: 27 · 2016: 28 · 2015: 21
- FWCI
- 30.32
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Clinical Cancer Research (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Cancer Institute (P01CA129243, NIH P01 CA129243, P30CA008748)
- Topics
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Treatments and Mutations
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Diagnosis and Treatment
- Keywords
- lung adenocarcinoma, actionable genomic alterations, comprehensive genomic profiling, BRAF V600E mutation, ALK fusion, ROS1 rearrangement, RET fusion, KIF5B-RET, CCDC6-RET, targeted therapy, driver mutations, EGFR, KRAS, BRAF, PIK3CA, AKT1, anaplastic lymphoma kinase, ROS1, RET
- MeSH terms
- Adenocarcinoma of Lung, Adenocarcinoma, Adult, Aged, Base Sequence, Exons, Female, Humans, Introns, Lung Neoplasms, Male, Middle Aged, Mutation, Neoplasm Proteins, Gene Rearrangement, Genome, Human, Sequence Analysis, DNA, Genomics, Molecular Targeted Therapy, High-Throughput Nucleotide Sequencing
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