Most cancer genomes are genomically unstable. Genomic instability (GI) accumulates through genomic aberrations at several levels, from single nucleotide changes (point mutations), large structural changes (losses, gains and translocations) of chromosome fragments, to gains and losses of whole chromosomes (aneuploidy). GI is now considered a distinct cancer hallmark .
Recent large-scale whole-genome sequencing efforts by The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and others have identified high GI rates across multiple cancer types including breast, lung, gastric and colorectal. An important realisation that has come out from these studies is that GI is a major causal factor for cancer genesis and progression in several solid cancers. For example, limited amounts of GI in normal and pre-cancerous tissues can predispose to sporadic cancers during the lifetimes of individuals . GI promotes intratumoural heterogeneity by facilitating ‘clonal inventions’ in tumours, thus enabling adaptation of tumours to (micro)environmental stress. GI confers inherent and acquired resistance to therapies, and thus posses significant prognostic and therapeutic challenges.
However, most genomically unstable cancer genomes display apparently random accumulation of genomic aberrations at elevated rates. Consequently, to understand the causal nature of GI, it is crucial to answer some important questions: (i) how do we identify and track these dynamically accumulating aberrations?; (ii) how do we distinguish the causal (driver) aberrations from the background (passenger) ones?; and (iii) do these causal aberrations point to internal or external processes that give rise to these aberrations and which are thus responsible for tumorigenesis and tumour progression. In other words, can we make derive order from this apparent chaos of GI.
A few months ago, Cancer Research UK (CRUK) set out seven ‘biggest challenges‘ in cancer research, and among these is (challenge number 3): Can we prevent cancers by studying the ‘scars’ that carcinogens leave in our DNA?
What this CRUK challenge means is as follows. The apparently random accumulation of genomic aberrations in cancer genomes in fact constitutes the “genomic history” the genomes. Each such aberration constitutes a ‘scar’ left by a ‘scarring process’ accumulated during this evolutionary history of the genome. Consequently, by careful analysis of these scars, it is possible to effectively reconstruct the evolutionary history of the cancer genome , and more importantly it is possible to identify distinct mutational processes that give rise to these scars .
These scarring mutational processes could be endogenous — i.e., internal cellular processes — e.g. aberrant DNA-damage repair mechanisms — or their products — e.g. reactive oxygen species and aldehydes — that are capable of damaging the DNA; or exogenous — i.e., external carcinogenic agents capable of damaging the DNA, for example, tobacco smoke and UV radiation. Each such mutational process produces a characteristic scar based on the manner in which the DNA is changed or damaged. Consequently, scars represent the footprints of these mutational processes, and by studying them it is possible to point to specific mutational processes, which if overcome or totally avoided may help to prevent cancers.
A series of studies [3-8] based on analysis of whole-genome sequences from a large number of cancers, set out to characterise genomic scars and map these scars to likely mutational processes in cancers. For example,  defined scars by looking for six kinds of base substitutions — C>A, C>G, C>T, T>A, T>C and T>G — within three-nucleotide windows, thus adding sequence context (one base on each side) to each mutation, to produce 96 possible mutation combinations. By mapping these combinations onto ~7000 cancer genomes covering 30 different cancer types, the study revealed 21 distinct mutational signatures (Figure 1). Each of these signatures could be associated to distinct endogenous or exogenous mutational processes — for example, signature 4 found mostly in lung cancers associated strongly with tobacco smoke, whereas signature 7 found mostly in melanoma associated strongly with UV radiations. Among the endogenous processes were aberrant DNA-damage repair mechanisms arising from BRCA1/2 mutations, which associated with signature 3 found mostly in breast, ovarian and pancreatic cancers.
Another study  identified aristolochic acid found in several herbal remedies as a carcinogen that gave rise a characteristic AA-UTUC mutational signature: AT to TA transversions at the sequence motif A[C|T]AGG, located primarily on nontranscribed strands.
We  and others  further corroborated these with observations from breast and ovarian cancer genomes. In particular, we  were able to associate frequent chromosomal breaks, amplifications, deletions and translocations (referred to as chromosomal instability) with aberrant double-strand break (DSB) repair mechanisms arising due to mutations or losses in DSB repair genes.
Basing on these findings, some of the important questions and challenges research in cancer will look to address in the future include: How can we employ these signatures to further understand the causal processes underlying cancer genesis and development; for better diagnosis; for more accurate prediction of patient responses to therapies; for the design and development of future therapies; and most importantly for the prevention of cancer itself?
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 Forsberg LA, Rasi C et al. Signatures of post-zygotic structural genetic aberrations in the cells of histologically normal breast tissue that can predispose to sporadic breast cancer. Genome Research 2015, 25: 1521-1535.
 Nik-Zainal S, van Loo P et al. The life history of 21 breast cancers. Cell 2012, 149(5):994-1007.
 Alexandrov LB, Nik-Zainal S et al. Signatures of mutational processes in human cancer. Nature 2013, 500, 415–421.
 Poon SL, Pang ST et al. Genome-wide mutational signatures of aristolochic acid and its application as a screening tool. Science Translational Medicine 2013, 5:197.
 Chan-On W, Nairismägi ML et al. Exome sequencing identifies distinct mutational patterns in liver fluke-related and non-infection-related bile duct cancers. Nature Genetics 2013, 45(12):1474-8.
 Liu C, Srihari S et al. Personalised pathway analysis reveals association between DNA repair pathway dysregulation and chromosomal instability in sporadic breast cancer. Molecular Oncology 2015, doi:10.1016/j.molonc.2015.09.007.
 Vollan HKM, Rueda OM et al. A tumor DNA complex aberration index is an independent predictor of survival in breast and ovarian cancer. Molecular Oncology 2015, 9:115–127.