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Mapping the hallmarks of lung adenocarcinoma with massively parallel sequencing.

ABSTRACT: Lung adenocarcinoma, the most common subtype of non-small cell lung cancer, is responsible for more than 500,000 deaths per year worldwide. Here, we report exome and genome sequences of 183 lung adenocarcinoma tumor/normal DNA pairs. These analyses revealed a mean exonic somatic mutation rate of 12.0 events/megabase and identified the majority of genes previously reported as significantly mutated in lung adenocarcinoma. In addition, we identified statistically recurrent somatic mutations in the splicing factor gene U2AF1 and truncating mutations affecting RBM10 and ARID1A. Analysis of nucleotide context-specific mutation signatures grouped the sample set into distinct clusters that correlated with smoking history and alterations of reported lung adenocarcinoma genes. Whole-genome sequence analysis revealed frequent structural rearrangements, including in-frame exonic alterations within EGFR and SIK2 kinases. The candidate genes identified in this study are attractive targets for biological characterization and therapeutic targeting of lung adenocarcinoma.

SUBMITTER: Imielinski M

PROVIDER: S-EPMC3557932 | biostudies-literature | 2012 Sep

REPOSITORIES: biostudies-literature

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Mapping the hallmarks of lung adenocarcinoma with massively parallel sequencing.

Imielinski Marcin M Berger Alice H AH Hammerman Peter S PS Hernandez Bryan B Pugh Trevor J TJ Hodis Eran E Cho Jeonghee J Suh James J Capelletti Marzia M Sivachenko Andrey A Sougnez Carrie C Auclair Daniel D Lawrence Michael S MS Stojanov Petar P Cibulskis Kristian K Choi Kyusam K de Waal Luc L Sharifnia Tanaz T Brooks Angela A Greulich Heidi H Banerji Shantanu S Zander Thomas T Seidel Danila D Leenders Frauke F Ansén Sascha S Ludwig Corinna C Engel-Riedel Walburga W Stoelben Erich E Wolf Jürgen J Goparju Chandra C Thompson Kristin K Winckler Wendy W Kwiatkowski David D Johnson Bruce E BE Jänne Pasi A PA Miller Vincent A VA Pao William W Travis William D WD Pass Harvey I HI Gabriel Stacey B SB Lander Eric S ES Thomas Roman K RK Garraway Levi A LA Getz Gad G Meyerson Matthew M

Cell 20120901 6

Lung adenocarcinoma, the most common subtype of non-small cell lung cancer, is responsible for more than 500,000 deaths per year worldwide. Here, we report exome and genome sequences of 183 lung adenocarcinoma tumor/normal DNA pairs. These analyses revealed a mean exonic somatic mutation rate of 12.0 events/megabase and identified the majority of genes previously reported as significantly mutated in lung adenocarcinoma. In addition, we identified statistically recurrent somatic mutations in the ...[more]

PMID: 22980975

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Project description:BackgroundMassively parallel sequencing offers an enormous potential for expression profiling, in particular for interspecific comparisons. Currently, different platforms for massively parallel sequencing are available, which differ in read length and sequencing costs. The 454-technology offers the highest read length. The other sequencing technologies are more cost effective, on the expense of shorter reads. Reliable expression profiling by massively parallel sequencing depends crucially on the accuracy to which the reads could be mapped to the corresponding genes.Methodology/principal findingsWe performed an in silico analysis to evaluate whether incorrect mapping of the sequence reads results in a biased expression pattern. A comparison of six available mapping software tools indicated a considerable heterogeneity in mapping speed and accuracy. Independently of the software used to map the reads, we found that for compact genomes both short (35 bp, 50 bp) and long sequence reads (100 bp) result in an almost unbiased expression pattern. In contrast, for species with a larger genome containing more gene families and repetitive DNA, shorter reads (35-50 bp) produced a considerable bias in gene expression. In humans, about 10% of the genes had fewer than 50% of the sequence reads correctly mapped. Sequence polymorphism up to 9% had almost no effect on the mapping accuracy of 100 bp reads. For 35 bp reads up to 3% sequence divergence did not affect the mapping accuracy strongly. The effect of indels on the mapping efficiency strongly depends on the mapping software.Conclusions/significanceIn complex genomes, expression profiling by massively parallel sequencing could introduce a considerable bias due to incorrectly mapped sequence reads if the read length is short. Nevertheless, this bias could be accounted for if the genomic sequence is known. Furthermore, sequence polymorphisms and indels also affect the mapping accuracy and may cause a biased gene expression measurement. The choice of the mapping software is highly critical and the reliability depends on the presence/absence of indels and the divergence between reads and the reference genome. Overall, we found SSAHA2 and CLC to produce the most reliable mapping results.

Dataset Information

Mapping the hallmarks of lung adenocarcinoma with massively parallel sequencing.

Publications

Mapping the hallmarks of lung adenocarcinoma with massively parallel sequencing.

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