The National Lung Matrix Trial of personalized therapy in lung cancer.
Bayes Theorem
Carcinoma, Non-Small-Cell Lung
/ etiology
Clinical Protocols
Clinical Trials as Topic
Cohort Studies
Genetic Markers
Genotype
High-Throughput Nucleotide Sequencing
Humans
Lung Neoplasms
/ etiology
Molecular Targeted Therapy
Oncogenes
/ genetics
Patient Selection
Precision Medicine
Smoke
/ adverse effects
Smoking
/ genetics
Triage
Journal
Nature
ISSN: 1476-4687
Titre abrégé: Nature
Pays: England
ID NLM: 0410462
Informations de publication
Date de publication:
07 2020
07 2020
Historique:
received:
28
01
2020
accepted:
08
06
2020
pubmed:
17
7
2020
medline:
21
10
2020
entrez:
17
7
2020
Statut:
ppublish
Résumé
The majority of targeted therapies for non-small-cell lung cancer (NSCLC) are directed against oncogenic drivers that are more prevalent in patients with light exposure to tobacco smoke
Identifiants
pubmed: 32669708
doi: 10.1038/s41586-020-2481-8
pii: 10.1038/s41586-020-2481-8
pmc: PMC7116732
mid: EMS114936
doi:
Substances chimiques
Genetic Markers
0
Smoke
0
Types de publication
Clinical Trial, Phase II
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
807-812Subventions
Organisme : Medical Research Council
ID : FC001169
Pays : United Kingdom
Organisme : Cancer Research UK
ID : FC001169
Pays : United Kingdom
Organisme : Cancer Research UK
ID : 12820
Pays : United Kingdom
Organisme : Cancer Research UK
ID : A22209
Pays : United Kingdom
Organisme : Wellcome Trust
ID : FC001169
Pays : United Kingdom
Organisme : Cancer Research UK
ID : A19363
Pays : United Kingdom
Commentaires et corrections
Type : CommentIn
Type : CommentIn
Type : CommentIn
Type : ErratumIn
Références
Lynch, T. J. et al. Activating mutations in the epidermal growth factor receptor underlying responsiveness of non-small-cell lung cancer to gefitinib. N. Engl. J. Med. 350, 2129–2139 (2004).
doi: 10.1056/NEJMoa040938
Bergethon, K. et al. ROS1 rearrangements define a unique molecular class of lung cancers. J. Clin. Oncol. 30, 863–870 (2012).
doi: 10.1200/JCO.2011.35.6345
Kwak, E. L. et al. Anaplastic lymphoma kinase inhibition in non-small-cell lung cancer. N. Engl. J. Med. 363, 1693–1703 (2010).
doi: 10.1056/NEJMoa1006448
Carr, T. H. et al. Defining actionable mutations for oncology therapeutic development. Nat. Rev. Cancer 16, 319–329 (2016).
doi: 10.1038/nrc.2016.35
Berry, S. M., Carlin, B. P., Lee, J. J. & Muller, P. Bayesian Adaptive Methods for Clinical Trials (CRC, 2010).
Eisenhauer, E. A. et al. New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur. J. Cancer 45, 228–247 (2009).
doi: 10.1016/j.ejca.2008.10.026
The Cancer Genome Atlas Research Network. Comprehensive molecular profiling of lung adenocarcinoma. Nature 511, 543–550 (2014).
doi: 10.1038/nature13385
The Cancer Genome Atlas Research Network. Comprehensive genomic characterization of squamous cell lung cancers. Nature 489, 519–525 (2012).
doi: 10.1038/nature11404
Koselugo (selumetinib) approved in US for paediatric patients with neurofibromatosis type 1 plexiform neurofibromas. https://www.astrazeneca.com/media-centre/press-releases/2020/koselugo-selumetinib-approved-in-us-for-paediatric-patients-with-neurofibromatosis-type-1-plexiform-neurofibromas.html (AstraZeneca, 2020).
Schmid, P. et al. Capivasertib plus paclitaxel versus placebo plus paclitaxel as first-line therapy for metastatic triple-negative breast cancer: the PAKT trial. J. Clin. Oncol. 38, 423–433 (2020).
doi: 10.1200/JCO.19.00368
Jamal-Hanjani, M. et al. Tracking the evolution of non-small-cell lung cancer. N. Engl. J. Med. 376, 2109–2121 (2017).
doi: 10.1056/NEJMoa1616288
de Bruin, E. C. et al. Spatial and temporal diversity in genomic instability processes defines lung cancer evolution. Science 346, 251–256 (2014).
doi: 10.1126/science.1253462
Kim, I. A., Lee, J. S., Kim, H. J., Kim, W. S. & Lee, K. Y. Cumulative smoking dose affects the clinical outcomes of EGFR-mutated lung adenocarcinoma patients treated with EGFR-TKIs: a retrospective study. BMC Cancer 18, 768 (2018).
doi: 10.1186/s12885-018-4691-0
Offin, M. et al. Tumor mutation burden and efficacy of EGFR-tyrosine kinase inhibitors in patients with EGFR-mutant lung cancers. Clin. Cancer Res. 25, 1063–1069 (2019).
doi: 10.1158/1078-0432.CCR-18-1102
McFadden, D. G. et al. Mutational landscape of EGFR-, MYC-, and Kras-driven genetically engineered mouse models of lung adenocarcinoma. Proc. Natl Acad. Sci. USA 113, E6409–E6417 (2016).
doi: 10.1073/pnas.1613601113
Westcott, P. M. et al. The mutational landscapes of genetic and chemical models of Kras-driven lung cancer. Nature 517, 489–492 (2015).
doi: 10.1038/nature13898
Liao, R. G. et al. Inhibitor-sensitive FGFR2 and FGFR3 mutations in lung squamous cell carcinoma. Cancer Res. 73, 5195–5205 (2013).
doi: 10.1158/0008-5472.CAN-12-3950
Castiglione, R. et al. Comparison of the genomic background of MET-altered carcinomas of the lung: biological differences and analogies. Mod. Pathol. 32, 627–638 (2019).
doi: 10.1038/s41379-018-0182-8
Gautschi, O. et al. Targeting RET in patients with RET-rearranged lung cancers: results from the global, multicenter RET registry. J. Clin. Oncol. 35, 1403–1410 (2017).
doi: 10.1200/JCO.2016.70.9352
Subbiah, V. et al. Precision targeted therapy with BLU-667 for RET-driven cancers. Cancer Discov. 8, 836–849 (2018).
doi: 10.1158/2159-8290.CD-18-0338
Morgan, P. et al. Can the flow of medicines be improved? Fundamental pharmacokinetic and pharmacological principles toward improving phase II survival. Drug Discov. Today 17, 419–424 (2012).
doi: 10.1016/j.drudis.2011.12.020
Basu, B. et al. First-in-human pharmacokinetic and pharmacodynamic study of the dual m-TORC 1/2 inhibitor AZD2014. Clin. Cancer Res. 21, 3412–3419 (2015).
doi: 10.1158/1078-0432.CCR-14-2422
Rothwell, D. G. et al. Utility of ctDNA to support patient selection for early phase clinical trials: the TARGET study. Nat. Med. 25, 738–743 (2019).
doi: 10.1038/s41591-019-0380-z
Pengelly, R. J. et al. A SNP profiling panel for sample tracking in whole-exome sequencing studies. Genome Med. 5, 89 (2013).
doi: 10.1186/gm492
Kim, S. et al. Strelka2: fast and accurate calling of germline and somatic variants. Nat. Methods 15, 591–594 (2018).
doi: 10.1038/s41592-018-0051-x
Chen, X. et al. Manta: rapid detection of structural variants and indels for germline and cancer sequencing applications. Bioinformatics 32, 1220–1222 (2016).
Thall, P. F., Wooten, L. H. & Tannir, N. M. Monitoring event times in early phase clinical trials: some practical issues. Clin. Trials 2, 467–478 (2005).
doi: 10.1191/1740774505cn121oa
Van Loo, P. et al. Allele-specific copy number analysis of tumors. Proc. Natl Acad. Sci. USA 107, 16910–16915 (2010).
doi: 10.1073/pnas.1009843107
Bailey, M. H. et al. Comprehensive characterization of cancer driver genes and mutations. Cell 173, 371–385.e18 (2018).
doi: 10.1016/j.cell.2018.02.060
Wang, K. et al. PennCNV: an integrated hidden Markov model designed for high-resolution copy number variation detection in whole-genome SNP genotyping data. Genome Res. 17, 1665–1674 (2007).
Cheng, J. et al. Single-cell copy number variation detection. Genome Biol. 12, R80 (2011).
Abbosh, C. et al. Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution. Nature 545, 446–451 (2017).