The mutation spectrum revealed by paired genome sequences from a lung cancer patient

Abstract

Lung cancer is the leading cause of cancer-related mortality worldwide, with non-small-cell lung carcinomas in smokers being the predominant form of the disease. Although previous studies have identified important common somatic mutations in lung cancers, they have primarily focused on a limited set of genes and have thus provided a constrained view of the mutational spectrum. Recent cancer sequencing efforts have used next-generation sequencing technologies to provide a genome-wide view of mutations in leukaemia, breast cancer and cancer cell lines. Here we present the complete sequences of a primary lung tumour (60x coverage) and adjacent normal tissue (46x). Comparing the two genomes, we identify a wide variety of somatic variations, including >50,000 high-confidence single nucleotide variants. We validated 530 somatic single nucleotide variants in this tumour, including one in the KRAS proto-oncogene and 391 others in coding regions, as well as 43 large-scale structural variations. These constitute a large set of new somatic mutations and yield an estimated 17.7 per megabase genome-wide somatic mutation rate. Notably, we observe a distinct pattern of selection against mutations within expressed genes compared to non-expressed genes and in promoter regions up to 5 kilobases upstream of all protein-coding genes. Furthermore, we observe a higher rate of amino acid-changing mutations in kinase genes. We present a comprehensive view of somatic alterations in a single lung tumour, and provide the first evidence, to our knowledge, of distinct selective pressures present within the tumour environment.

DNA replication timing and selection shape the landscape of nucleotide variation in cancer genomes

“…We wondered whether the association between SNV frequency in genic regions and replication timing was a spurious correlation driven by transcription level, as transcription-coupled repairs are known to influence somatic SNV frequencies in cancer cells 3,4 . Consistent with these previous observations, SNV frequency in functionally neutral intronic regions decreased with increasing transcription level.…”

“…Using next-generation DNA sequencing technologies, somatic mutations have been mapped for hundreds of cancer genomes [1][2][3][4][5][6][7][8][9][10] , with thousands more under way 11 . How such alterations influence the tumorigenesis is not completely understood.…”

“…On the other hand, for small-scale mutations, it is straightforward to delineate the two; the underlying mutation rate can be directly inferred from the observed mutation frequency in functionally neutral, or nearly neutral, regions. Of small-scale mutations, single-nucleotide variation is one of the most abundant, functionally important source of evolution [1][2][3][4][5][6][7][8][9][10]13,19,20 .…”

Optimized filtering reduces the error rate in detecting genomic variants by short-read sequencing

“…For instance, >500 somatic SNVs in a lung cancer tumor were validated using mass spectrometry 5 , whereas other studies resequenced hundreds of SNVs using Sanger sequencing [6][7][8] . An important drawback of such validation experiments is that they rapidly become as expensive and time-consuming as the wholegenome sequencing experiment itself.…”

Targeted next generation sequencing of clinically significant gene mutations and translocations in leukemia

“…[5][6][7][8][9] These studies have uncovered new prognostic markers in AML such as DNMT3A and IDH1, illustrating the importance of next generation sequencing in the research/discovery setting. In the clinical laboratory, however, such mutations are generally identified by more conventional methods such as PCR (and variants thereof), Sanger sequencing, and fluorescent in-situ hybridization (FISH).…”