The description of the “chromothripsis” phenomenon has initiated a vital discussion about clustered genomic aberration events and their role in cancer development [52, 55, 56]. While chromothripsis senso stricto has been characterized as a type of focally clustered genomic aberrations generated in a one time cellular event and being limited to a defined set of copy number states , other operational definitions have been employed based on clustered aberrations [7, 16, 23, 45, 55, 57]. It seems likely that some of the previous discussions of “chromothripsis” referred to a number of underlying event types, all resulting in localized genome fragmentation and re-assembly events. For instance, DNA double strand break and end-joining-mediated repair may result in a restricted number of copy number levels, whereas aberrant replication based mechanisms will lead to a more diverse set of copy number aberrations [45, 55]. Here, we introduce the term “chromothripsis-like patterns” (CTLP) when referring to clustered genomic events, to accommodate both common labelling and presumed biological variability of clustered genomic copy number aberrations.
At this time, due to the lack of sufficiently large number of cancer data sets from whole-genome sequencing analyses, a meta-analysis of “strict” chromothripsis cases is not feasible. We have followed a pragmatic approach to quantify the occurrence of CTLP from genomic array data sets. In our algorithm, we implemented the two most significant features shared by different operational chromothripsis definitions, namely copy number status changes and breakpoints clustering, which can be well measured by array based technologies. Previous studies provided various algorithms to detect “chromothripsis” events [9, 15, 58]. However, besides its application to an extensive data set, the specific advantage of our method presented here is its ability to detect regions of shattering with limited influence from the varying sizes of affected chromosomes. Since the step length of our scanning window is 5 Mb, theoretically the detected CTLP regions are within an accuracy of ±5 Mb. Note that the performance of this algorithm may be influenced by poor quality arrays, especially those with highly scattered and unevenly distributed probe signal intensities.
In this study, we identified 918 CTLP-containing genome profiles, based on an analysis of copy number aberration patterns from 22,347 oncogenomic arrays and representing 132 cancer types. Despite the inherent limitations of such a meta-analysis approach, we were able to provide several new insights regarding the distribution of clustered genomic copy number aberrations and to produce a comprehensive estimate of CTLP incidence in a large range of cancer entities.
In our analysis, CTLP exhibited an uneven distribution along tumor genomes, with disease related local enrichment. These “CTLP dense” chromosomal regions may reveal associations between disease related cancer associated genes and molecular mechanisms behind genome shattering events. This potential correlation is exemplified by the prevalence of mutant TP53 in “chromothriptic” Li-Fraumeni syndrome associated Sonic-Hedgehog medulloblastomas . As the extent of CTLP related deletions of the TP53 locus indicates, CTLP related gene dosage changes may predispose to double-hit effects on specific tumor suppressors. In contrast, we found regional enrichment for CTLP with pre-dominant copy number gains on chromosomes 8, 11 and 12. In the initial study, chromosome 8 shattering was found in a small cell lung cancer cell line . This event contained the MYC oncogene, which had be shown to be amplified in 10-20% of small cell lung cancers . Moreover, strong overexpression of MYC involved in a “chromothripsis” region was also detected in a neuroblastoma sample . In a study of colorectal tumors, chromosomes 8 and 11 were involved in concurrent pulverization events with generation of fusion genes, involving e.g. SAPS3 and ZFP91. In a study on hepatocellular carcinoma, CCND1 amplification was embedded within a “chromothriptic” event on chromosome 11 . Therefore, the overall uneven distribution of CTLP may point to specific driver mutations that contribute to CTLP generation, and/or to a class of cancer promoting mutations based on regional genome shattering events.
When comparing cancer types, we observed a high CTLP prevalence in a limited set of entities, particularly among soft tissue tumors. This finding supports and improves upon a previous prediction of particularly high “chromothripsis” rate in bone tumors . Also, the uneven distribution of CTLP is a strong indicator for a disease related selection of specific genomic aberrations, supporting their involvement in the oncogenetic process.
In the initial study, the authors stated that chromothripsis could be a one-off cataclysmic event that generates multiple concurrent mutations and rearrangements . However, the role of chromothripsis in terms of “shortcut” to cancer genome generation is still elusive. We note that additional and complex non-CTLP genome re-arrangements exist in the majority of CTLP samples. The number and uneven distribution of affected chromosomes in CTLP supports the biological heterogeneity of cancer samples with CTLP containing genome profiles. Furthermore, the normalized spatial distribution of shattered chromosomal regions, as well as the observed significant overlap between telomere and pulverized regions is supportive of breakage-fusion-bridge cycles as one of the mechanisms acting in a subset of samples. Further efforts are needed to investigate the temporal order of chromothripsis and non-chromothripsis events in complex samples, and to substantiate the existence of a dichotomy between “one-off” chromothripsis and other classes of localized genome shattering events, all resulting in clustered genomic copy number aberrations.
In our associated clinical data, CTLP were related to more advanced tumor stages and overall worse prognosis when compared to non-CTLP cases. One possible explanation is that the numerous concurrent genetic alterations induced by genome shattering events disturb a large number of genes and contribute to more aggressive tumor phenotypes. By themselves, these observations do not differentiate whether CTLP arise as a early events promoting aggressive tumor behavior with fast growth rates and reduced response rates to therapeutic interventions; or whether this observation relates to underlying primary mutations predisposing to genomic instability, aggressive clinical behavior and CTLP as a resulting epiphenomenon. Interestingly, the high rate of TP53 involvement by itself would support both possibilities for this gene, i.e. chromothripsis as result of TP53 mutation as well as chromothriptic events with TP53 locus involvement promoting an aggressive clinical behavior.
From Table 1 we may notice that the array based technologies are, in general, less sensitive than whole-genome sequencing data for calling chromothripsis-like events. This is partly due to the very limited ability of most array platforms to detect balanced genomic aberrations, such as inversions and translocation events. In the future, the accumulation of large-scale sequencing data should be able to provide further insights into localise genome shattering events.