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pmid:30522449
Different mutational characteristics of the subsets of EGFR-tyrosine kinase inhibitor sensitizing mutation-positive lung adenocarcinoma.
Eun Young Kim · Arum Kim · Gaeun Lee · Hangsuck Lee · Yoon Soo Chang
BMC cancer · 2018 doi:10.1186/s12885-018-5116-9
Paper
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Experiment
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Data
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Analysis
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Execution
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Complete file
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In parallel, publicly available data of 47 TCGA-LUAD cases with mEGFR (LUAD cohort) were extracted from the GDC data portal and analyzed by non-negative matrix factorization using the Maftools package.\nRESULTS: In the study cohort, the C > A transversions accounted for 12.9% of all single nucleotide variations (SNVs), comprising the second smallest proportion among SNVs. The E19del-subgroup had a significantly lower mutational burden with significantly higher Ti/Tv ratio than the SNV-subgroup, which includes cases with L858R and other EGFR-TKI sensitizing SNVs. (P = 0.0326 and 0.0002, respectively, Mann-Whitney U test). In the LUAD cohort, the mutational burden was substantially lower than in other TCGA cancer cohorts, and the frequency of C > A transversions was 30.3%, occupying the second frequency. The E19del-subgroup had a lower mutational burden overall and a higher Ti/Tv ratio than the SNV-subgroup (P = 0.0497 and P = 0.0055, respectively, Mann-Whitney U test). Smoking-related signature 4 was observed only in the L858R-subgroup, while ignature 30 and 5 was observed in both groups.\nCONCLUSIONS: Lung adenocarcinoma with mEGFR(+) has a lower mutational burden and does not show a characteristic mutation pattern influenced by smoking. E19del and L858R, which are representative subtypes of mEGFR(+) lung adenocarcinoma, differ in terms of mutational spectrum, as the E19del-subgroup has a lower mutation burden and a higher Ti/Tv ratio than the SNV-subgroup. These findings could help explain the differences in the responses to EGFR-TKIs and in the clinical courses between the two lung adenocarcinoma subgroups.", "claims": [{"id": "claim-method", "statement": "The mutation patterns found in cancers are analyzed by non-negative matrix factorization (NMF), and compared to 30 types of mutational signatures [8].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:30522449", "locator": "sections[4] \"Statistics\" paragraph 2", "quote": "The mutation patterns found in cancers are analyzed by non-negative matrix factorization (NMF), and compared to 30 types of mutational signatures [8]."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All reagents used in this study are commercially available from the listed companies. 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