This week in Nature, investigators from Wellcome Trust Sanger Institute published the fourth and fifth complete cancer genomes. Interestingly, both are cancers in which the primary mutagen is known: malignant melanoma (UV light) and small-cell lung cancer (tobacco smoke). This seems to be important, because when I looked at the number of validated somatic coding mutations in each of the first five genomes, the latest two stood out.
Granted, small-cell lung cancer and malignant melanoma differ in many ways from leukemia and breast cancer. Yet the increase of confirmed somatic coding variants in these two recent studies is striking.
Corregendum: Not the First Catalogue of Somatic Mutations
Even so, the authors’ claim that they are “providing the first comprehensive catalogue of somatic mutations from an individual cancer” seems unjustified. Perhaps this is based on the idea that AML1 and LBC1 focused on coding variants only. Yet I point out that in AML2 we evaluated 282 noncoding somatic mutations and confirmed over 50. In the melanoma study, only 470 of the 33,345 newly found somatic mutations were sent through validation, and the method for selecting these was not made clear. At best, the “first comprehensive” claim is a semantic one; at worst, it’s just wrong.
That said, these are still landmark studies. Even with the emergence of next-generation sequencing, completing a cancer genome is a marvelous achievement. It requires substantial financial resources and technical expertise; we certainly knew that WTSI had these. But guiding the data through analysis and forming a cohesive story out of it is the real challenge. It requires persistence, intellect, and scientific rigor, but most of all it requires strong leadership. I congratulate our friends across the pond for showing that they have what it takes.
Illumina’s Fourth, ABI SOLiD’s First Cancer Genome
The melanoma study, like the first three cancer genomes, applied high-throughput sequencing on the Illumina platform (2 x 75bp, in this case). In contrast, the SCLC study is the first cancer genome to be sequenced on a different platform – ABI SOLiD. While the read lengths for SOLiD were not impressive (2×25 bp), the specificity was – 77 of 79 (97%) of somatic coding SNVs and 333 of 354 (94%) randomly chosen genome-wide variants tested confirmed by PCR and traditional sequencing.
Unfortunately, SOLiD also comes with a sensitivity cost. Only 22 of 29 previously identified SNVs (77%) were called. Indels were a real problem – neither of the two previously known coding indels were detected, and the validation rate for predicted somatic indels was 25%.
Mutational Signatures Implicate UV Light and Tobacco
Intriguingly, in both studies the authors identified distinct mutational signatures of exposure to the long-suspected environmental risk factor – ultraviolet radiation (in malignant skin cancer) and tobacco smoke’s “cocktail of carcinogens” (in lung cancer). The substantial number of mutations in each genome made it possible to characterize these signatures with unprecedented statistical power.
The strength of both studies is the insight into the molecular mechanisms of DNA damage, repair, and mutation that could be inferred from such a powerful dataset. In melanoma, the most prevalent mutations were C->T and G->A transitions; the mutational spectrum and sequence context indicate that most of these are attributable to ultraviolet-light-induced DNA damage. In lung cancer, G->T transversions were the commonest substitution; these mutations have previously been linked to polycyclic aromatic hydrocarbons and acrolein in tobacco smoke.
Don’t Smoke. Wear Sunscreen.
Cancer, like many common, complex diseases, has many risk factors that come from the environment as well as from one’s DNA. Here, for perhaps the first time, we get a picture of the significant mutational burden associated with two lifestyle choices. Smoking is an obvious one – avoiding it dramatically decreases one’s risk of cancer and a host of other diseases. Now science can offer another definitive piece of advice. Everybody’s free, as Baz Luhrmann puts it, to wear sunscreen.
References
Pleasance ED, Cheetham RK, Stephens PJ, McBride DJ, Humphray SJ, Greenman CD, Varela I, Lin ML, Ordóñez GR, Bignell GR, Ye K, Alipaz J, Bauer MJ, Beare D, Butler A, Carter RJ, Chen L, Cox AJ, Edkins S, Kokko-Gonzales PI, Gormley NA, Grocock RJ, Haudenschild CD, Hims MM, James T, Jia M, Kingsbury Z, Leroy C, Marshall J, Menzies A, Mudie LJ, Ning Z, Royce T, Schulz-Trieglaff OB, Spiridou A, Stebbings LA, Szajkowski L, Teague J, Williamson D, Chin L, Ross MT, Campbell PJ, Bentley DR, Futreal PA, & Stratton MR (2009). A comprehensive catalogue of somatic mutations from a human cancer genome. Nature PMID: 20016485
Pleasance ED, Stephens PJ, O’Meara S, McBride DJ, Meynert A, Jones D, Lin ML, Beare D, Lau KW, Greenman C, Varela I, Nik-Zainal S, Davies HR, Ordoñez GR, Mudie LJ, Latimer C, Edkins S, Stebbings L, Chen L, Jia M, Leroy C, Marshall J, Menzies A, Butler A, Teague JW, Mangion J, Sun YA, McLaughlin SF, Peckham HE, Tsung EF, Costa GL, Lee CC, Minna JD, Gazdar A, Birney E, Rhodes MD, McKernan KJ, Stratton MR, Futreal PA, & Campbell PJ (2009). A small-cell lung cancer genome with complex signatures of tobacco exposure. Nature PMID: 20016488
chris shaffer says
Perhaps you could comment on the various possibilities as to why the increase in the number of validated somatic coding mutations. At first blush I wonder if this is simply reflecting the improvements in the sequencing protocols which leads to more coverage per unit effort/cost which leads to higher detection rates. Or perhaps the validation process has improved so you get more validations per unit effort/cost. Alternatively this observation could indeed be a reflection of real cancer/mutational differences in the samples. Your thoughts?
Dan Koboldt says
Chris,
This is an excellent question that I’d considered discussing in my original post. In general, I don’t believe that sequencing technology advances can account for the differences in mutations found across the five cancer genomes. Although the first (AML1) utilized only shorter single-end reads (36 bp), the genome was extensively characterized before and after our Nature paper – using traditional sequencing, and later using paired-end Illumina libraries – and I’m very confident that we’re not missing many coding mutations. AML2, the breast cancer genome, and Sanger’s melanoma study were all done on the same platform, Illumina 2×75. Every study ends up at around 40x haploid coverage per tumor. I doubt the costs were the same, but the endpoint coverage seems comparable.
Unless I’m mistaken, validation was essentially identical in all five studies – PCR and 3730 resequencing in normal and tumor DNA.
Are there somatic coding mutations that we’re missing? A few, almost certainly. Regions refractory to accurate short read alignment (during discovery) and/or primer design (during validation) are likely to have hidden a handful of coding mutations. However, I think that these issues are likely to have a similar effect on all short-read technologies. As reads get longer, and as third-generation sequencing technologies (e.g. PacBio, with >1kb reads) come to market, this problem may go away.
Finally, all sequencing questions aside, the number of somatic coding mutations seems consistent with my limited knowledge of the mutational profile of each cancer. AML was a challenge because we knew there were fewer genetic changes compared to many other cancers. Breast cancer was probably somewhere in the middle. I’d guess that small-cell lung cancer and melanoma were expected to harbor more mutations, because they’re associated with exposure to known mutagens.
henry furneaux says
One wonders if the somatic mutation spectrum (nature of mutation and propensity of the affected pathway ) obtained by this will be sufficient to identify the causative mutagen. If so , this may be a boon to investigators trying to discover the relevant mutagen in the analysis of environmental cancers of unknown origin.