Mutational Signatures in Cancer


A cancer carries thousands of somatic mutations, most of which provide no selective advantage to clones which acquire them. Much research is focussed on the few driver mutations that do confer such an advantage; how such mutations enable cancer development and whether they can be targeted as cancer therapies.  However, the recent reduction in cost of large scale sequencing (either whole exome or whole genome sequencing), has allowed mutational information to be used in a different way.  The study of mutational signatures can provide information about the mutagens to which a patient has been exposed to over a lifetime, any DNA repair mechanisms malfunctioning within the tumour, and potential therapeutic agents to which the tumour may be sensitive (Helleday, Eshtad et al. 2014).

Following large scale sequencing, signatures are generated by categorising base pair substitutions into 6 categories (C.G→A.T, C.G→G.C, C.G→T.A, T.A→A.T, T.A→C.G, T.A→G.C) and also taking into account the bases on each side of the substituted base. This gives 96 possibilities and each of these can be scored, giving an image such as that below.  This is a signature common in colorectal cancers, and is a product of defects in the mismatch repair (MMR) pathway.

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Figure 1. An example of a mutational signature from a MMR defective tumour. Taken from http://cancer.sanger.ac.uk/cosmic/signatures

Sequencing can also provide information about other types of mutation.  Indels, which are insertions or deletions can be quantified, together with their average size.  This provides further information about the damage/repair environment within the tumour.  For example, indels between 4 and approximately 50 bases, surrounded by mircohomology can be indicative of tumours relying on non-homologous end joining due to a defect in homologous recombination (HR).  Information about gross chromosomal rearrangements, such as tandem duplications, translocations and karyotypic variations can be integrated with base substitution information.  This can be viewed in a circos plot.  Below are examples of these plots from a tumour defective in homologous recombination (A) with large numbers of rearrangements and another defective in MMR (B) with large numbers of substitutions.

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Figure 2. Circos plots of tumours with different repair defects.  A is HR defective and B is MMR defective.  Adapted from (Davies, Morganella et al. 2017).

So what is the value of studying these mutational signatures? Since they give a historical perspective on the damage accrued by the genome, they can be used to monitor historical exposure to various agents.  For example, the presence of a particular mutational signature associated with exposure to Aristolochic acids (present in traditional medicines) has been identified to be present in a large number hepatocellular carcinomas in Asia (Ng, Poon et al. 2017). This in turn can inform policy on the availability of such agents.

Additionally study of mutational signatures allows the improved targeting of therapies. HR defective tumours present a distinct mutational signature and such tumours are generally sensitive to PARP inhibitors. MMR defective tumours carry a high mutational load and respond well to immune checkpoint inhibitors such as anti-PD-1 antibodies (Le, Durham et al. 2017). Although colorectal tumours are routinely examined for MMR status to allow specific treatment, MMR defective tumours in other cancer types are likely missed. A recent study showed that a small percentage of breast cancers carry MMR defects without germline mutation in MMR genes (Davies, Morganella et al. 2017). These tumours may respond well to immune checkpoint blockade. Therefore, the classification of tumours by mutational signatures could provide a broader but more highly targeted use for several existing therapies. Although currently these are only identified in a research setting, the falling cost of sequencing may allow such characterisation to be part of the process in treatment of cancer patients.

Blog written by Jess Hudson

References:

Davies, H., S. Morganella, C. A. Purdie, S. J. Jang, E. Borgen, H. Russnes, D. Glodzik, X. Zou, A. Viari, A. L. Richardson, A. L. Borresen-Dale, A. Thompson, J. E. Eyfjord, G. Kong, M. R. Stratton and S. Nik-Zainal (2017). “Whole-Genome Sequencing Reveals Breast Cancers with Mismatch Repair Deficiency.” Cancer Res 77(18): 4755-4762.

Helleday, T., S. Eshtad and S. Nik-Zainal (2014). “Mechanisms underlying mutational signatures in human cancers.” Nat Rev Genet 15(9): 585-598.

Le, D. T., J. N. Durham, K. N. Smith, H. Wang, B. R. Bartlett, L. K. Aulakh, S. Lu, H. Kemberling, C. Wilt, B. S. Luber, F. Wong, N. S. Azad, A. A. Rucki, D. Laheru, R. Donehower, A. Zaheer, G. A. Fisher, T. S. Crocenzi, J. J. Lee, T. F. Greten, A. G. Duffy, K. K. Ciombor, A. D. Eyring, B. H. Lam, A. Joe, S. P. Kang, M. Holdhoff, L. Danilova, L. Cope, C. Meyer, S. Zhou, R. M. Goldberg, D. K. Armstrong, K. M. Bever, A. N. Fader, J. Taube, F. Housseau, D. Spetzler, N. Xiao, D. M. Pardoll, N. Papadopoulos, K. W. Kinzler, J. R. Eshleman, B. Vogelstein, R. A. Anders and L. A. Diaz, Jr. (2017). “Mismatch repair deficiency predicts response of solid tumors to PD-1 blockade.” Science 357(6349): 409-413.

Ng, A. W. T., S. L. Poon, M. N. Huang, J. Q. Lim, A. Boot, W. Yu, Y. Suzuki, S. Thangaraju, C. C. Y. Ng, P. Tan, S. T. Pang, H. Y. Huang, M. C. Yu, P. H. Lee, S. Y. Hsieh, A. Y. Chang, B. T. Teh and S. G. Rozen (2017). “Aristolochic acids and their derivatives are widely implicated in liver cancers in Taiwan and throughout Asia.” Sci Transl Med 9(412).

 

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