Skip to main page content
Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2014 Mar 27;5:3518.
doi: 10.1038/ncomms4518.

Frequent Mutations in Chromatin-Remodelling Genes in Pulmonary Carcinoids

Affiliations
Free PMC article

Frequent Mutations in Chromatin-Remodelling Genes in Pulmonary Carcinoids

Lynnette Fernandez-Cuesta et al. Nat Commun. .
Free PMC article

Abstract

Pulmonary carcinoids are rare neuroendocrine tumours of the lung. The molecular alterations underlying the pathogenesis of these tumours have not been systematically studied so far. Here we perform gene copy number analysis (n=54), genome/exome (n=44) and transcriptome (n=69) sequencing of pulmonary carcinoids and observe frequent mutations in chromatin-remodelling genes. Covalent histone modifiers and subunits of the SWI/SNF complex are mutated in 40 and 22.2% of the cases, respectively, with MEN1, PSIP1 and ARID1A being recurrently affected. In contrast to small-cell lung cancer and large-cell neuroendocrine lung tumours, TP53 and RB1 mutations are rare events, suggesting that pulmonary carcinoids are not early progenitor lesions of the highly aggressive lung neuroendocrine tumours but arise through independent cellular mechanisms. These data also suggest that inactivation of chromatin-remodelling genes is sufficient to drive transformation in pulmonary carcinoids.

Figures

Figure 1
Figure 1
Genomic characterization of pulmonary carcinoids. (a) CIRCOS plot of the chromothripsis case. The outer ring shows chromosomes arranged end to end. Somatic copy number alterations (gains in red and losses in blue) detected by 6.0 SNP arrays are depicted in the inside ring. (b) Copy numbers and chimeric transcripts of affected chromosomes. Segmented copy number states (blue points) are shown together with raw copy number data averaged over 50 adjacent probes (grey points). To show the different levels of strength for the identified chimeric transcripts all curves are scaled according to the sequencing coverage at the fusion-point. (c) Mutation frequency detected by genome and exome sequencing in pulmonary carcinoids (PCA). Each blue dot represents the number of mutations per megabase in one pulmonary carcinoid sample. Average frequencies are also shown for adenocarcinomas (AD), squamous (SQ), and small-cell lung cancer (SCLC) base on previous studies,, (d) Comparison of context independent transversion and transition rates (an overall strand symmetry is assumed) between rates derived from molecular evolution (evol), from a previous SCLC sequencing study, and from the pulmonary carcinoids (PCA) genome and exome sequencing. All rates are scaled as such that their overall sum is one.
Figure 2
Figure 2
Significant affected genes and pathways in pulmonary carcinoids. (a) Significantly mutated genes and pathways identified by genome (n=29), exome (n=15) and transcriptome (n=69) sequencing. The percentage of pulmonary carcinoids with a specific gene or pathway mutated is noted at the right side. The q-values of the significantly mutated genes and pathways are shown in brackets (see Methods section). Samples are displayed as columns and arranged to emphasize mutually exclusive mutations. (b) Methylation levels of H3K9me3 and H3K27me3 in pulmonary carcinoids. Representative pictures of different degrees of methylation (high, intermediate, and low) for some of the samples summarized in Table 1. The mutated gene is shown in italics at the bottom right part of the correspondent picture. Wild-type samples are denoted by WT.
Figure 3
Figure 3
Expression data analysis of pulmonary carcinois based on RNAseq data. (a) Consensus Kmeans clustering, using RNAseq expression data of 50 adenocarcinomas (AD, in blue), 42 small-cell lung cancer (SCLC, in red), and 69 pulmonary carcinoids (PCA, in purple) identified 3 groups using the clustering module from GenePattern and consensus CDF, (left panel). The significance of the clustering was evaluated by using SigClust34 with a p<0.0001. Fisher's exact test35 was used to check associations between the clusters and the histological subtypes (right panel). (b) Gene Set Enrichment Analysis (GSEA) for SCLC versus PCA using RNAseq expression data. Low gene expression is indicated in blue and high expression, in red. On the right side are named the altered pathways in PCA (green) and SCLC (purple).

Similar articles

See all similar articles

Cited by 69 articles

See all "Cited by" articles

References

    1. Swarts D. R. a, Ramaekers FCS, Speel E-JM. Molecular and cellular biology of neuroendocrine lung tumors: evidence for separate biological entities. Biochim. Biophys. Acta. 2012;1826:255–271. - PubMed
    1. Peifer M, et al. Integrative genome analyses identify key somatic driver mutations of small-cell lung cancer. Nat. Genet. 2012;44:1104–1110. - PMC - PubMed
    1. Stephens PJ, et al. Massive genomic rearrangement acquired in a single catastrophic event during cancer development. Cell. 2011;144:27–40. - PMC - PubMed
    1. Imielinski M, et al. Mapping the Hallmarks of Lung Adenocarcinoma with Massively Parallel Sequencing. Cell. 2012;150:1107–1120. - PMC - PubMed
    1. Hammerman PS, et al. Comprehensive genomic characterization of squamous cell lung cancers. Nature. 2012

Publication types

MeSH terms

Feedback