Comprehensive molecular profiling of lung adenocarcinoma - PubMed (original) (raw)

. 2014 Jul 31;511(7511):543-50.

doi: 10.1038/nature13385. Epub 2014 Jul 9.

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Comprehensive molecular profiling of lung adenocarcinoma

Cancer Genome Atlas Research Network. Nature. 2014.

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Abstract

Adenocarcinoma of the lung is the leading cause of cancer death worldwide. Here we report molecular profiling of 230 resected lung adenocarcinomas using messenger RNA, microRNA and DNA sequencing integrated with copy number, methylation and proteomic analyses. High rates of somatic mutation were seen (mean 8.9 mutations per megabase). Eighteen genes were statistically significantly mutated, including RIT1 activating mutations and newly described loss-of-function MGA mutations which are mutually exclusive with focal MYC amplification. EGFR mutations were more frequent in female patients, whereas mutations in RBM10 were more common in males. Aberrations in NF1, MET, ERBB2 and RIT1 occurred in 13% of cases and were enriched in samples otherwise lacking an activated oncogene, suggesting a driver role for these events in certain tumours. DNA and mRNA sequence from the same tumour highlighted splicing alterations driven by somatic genomic changes, including exon 14 skipping in MET mRNA in 4% of cases. MAPK and PI(3)K pathway activity, when measured at the protein level, was explained by known mutations in only a fraction of cases, suggesting additional, unexplained mechanisms of pathway activation. These data establish a foundation for classification and further investigations of lung adenocarcinoma molecular pathogenesis.

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Figures

Figure 1

Figure 1. Somatic mutations in lung adenocarcinoma

a, Co-mutation plot from whole exome sequencing of 230 lung adenocarcinomas. Data from TCGA samples were combined with previously published data for statistical analysis. Co-mutation plot for all samples used in the statistical analysis (n =412) can be found in Supplementary Fig. 2. Significant genes with a corrected P value less than 0.025 were identified using the MutSig2CV algorithm and are ranked in order of decreasing prevalence. b, c, The differential patterns of mutation between samples classified as transversion high and transversion low samples (b) or male and female patients (c) are shown for all samples used in the statistical analysis (n =412). Stars indicate statistical significance using the Fisher’s exact test (black stars: q <0.05, grey stars: P <0.05) and are adjacent to the sample set with the higher percentage of mutated samples.

Figure 2

Figure 2. Aberrant RNA transcripts in lung adenocarcinoma associated with somatic DNA translocation or mutation

a, Normalized exon level RNA expression across fusion gene partners. Grey boxes around genes mark the regions that are removed as a consequence of the fusion. Junction points of the fusion events are also listed in Supplementary Table 9. Exon numbers refer to reference transcripts listed in Supplementary Table 9. b, MET exon 14 skipping observed in the presence of exon 14 splice site mutation (ss mut), splice site deletion (ss del) or a Y1003* mutation. A total of 22 samples had insufficient coverage around exon 14 for quantification. The percentage skipping is (total expression minus exon 14 expression)/total expression. c, Significant differences in the frequency of 129 alternative splicing events in mRNA from tumours with U2AF1 S34F tumours compared to U2AF1 WT tumours (q value <0.05). Consistent with the function of U2AF1 in 3′ splice site recognition, most splicing differences involved cassette exon and alternative 3′ splice site events (chi-squared test, P <0.001).

Figure 3

Figure 3. Identification of novel candidate driver genes

a, GISTIC analysis of focal amplifications in oncogene-negative (n =87) and oncogene-positive (n =143) TCGA samples identifies focal gains of MET and ERBB2 that are specific to the oncogene-negative set (purple). b, TP53, KEAP1, NF1 and RIT1 mutations are significantly enriched in samples otherwise lacking oncogene mutations (adjusted P <0.05 by Fisher’s exact test). c, Co-mutation plot of variants of known significance within the RTK/RAS/RAF pathway in lung adenocarcinoma. Not shown are the 63 tumours lacking an identifiable driver lesion. Only canonical driver events, as defined in Supplementary Fig. 9, and proposed driver events, are shown; hence not every alteration found is displayed. d, New candidate driver oncogenes (blue: 13% of cases) and known somatically activated drivers events (red: 63%) that activate the RTK/RAS/RAF pathway can be found in the majority of the 230 lung adenocarcinomas.

Figure 4

Figure 4. Pathway alterations in lung adenocarcinoma

a, Somatic alterations involving key pathway components for RTK signalling, mTOR signalling, oxidative stress response, proliferation and cell cycle progression, nucleosome remodelling, histone methylation, and RNA splicing/processing. b, c, Proteomic analysis by RPPA (n =181) P values by two-sided _t_-test. Box plots represent 5%, 25%, 75%, median, and 95%. PP, proximal proliferative; TRU, terminal respiratory unit; PI, proximal inflammatory. c, mTOR signalling may be activated, by either Akt (for example, via PI(3)K) or inactivation of AMPK (for example, via STK11 loss). Tumours were separated into three main groups: those with PI(3)K-AKT activation, through either PIK3CA activating mutation or unknown mechanism (high p-AKT); those with LKB1-AMPK inactivation, through either STK11 mutation or unknown mechanism with low levels of LKB1 and p-AMPK; and those showing none of the above features.

Figure 5

Figure 5. Integrative analysis

a–c, Integrating unsupervised analyses of 230 lung adenocarcinomas reveals significant interactions between molecular subtypes. Tumours are displayed as columns, grouped by mRNA expression subtypes (a), DNA methylation subtypes (b), and integrated subtypes by iCluster analysis (c). All displayed features are significantly associated with subtypes depicted. The CIMP phenotype is defined by the most variable CpG island and promoter probes.

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