Cancer is a clonal disease
Cancer is a clonal disease, which has acquired genetic alterations, imparting a selective advantage for survival, proliferation and invasion of the cell involved1. Most genomic alterations (point mutations, genomic rearrangements and changes in copy number2) represent rare somatic changes which are responsible for promoting tumour initiation3. The delayed discovery of commonly rearranged genes associated with solid cancers reflects the difficulty of systematically identifying rearrangements in highly re-organised cancer genomes. To date 412 genes harbouring mutations have been identified in human cancers, and these were recognised using the very labour intensive Sanger sequencing method1,4. However, more recently the development of next generation systems (whole genome sequencing) has revolutionised the approach of identifying cancer linked genes4. Numerous reasons underlie the excitement caused by the availability of such systems. Having access to disease and normal tissue samples of the same patient makes it possible to confidently comprehend the somatic changes, which are associated with cancer initiation and progression. The advanced refinement of systems biology means that the complex associations of processes which switch on and off specific genes as well as signalling pathways can be deduced directly from genomic and transcriptomic sequencing. Shah et al.5 have conducted whole genome analysis of a solid breast cancer tumour for the first time using next generation sequencing systems (NextGen). This novel technique precisely characterises all somatic changes, which may arise during the initiation and progression of individual cancers.
Evolution of the breast tumour
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In the study by Shah et al.4 an illumine sequencing based approach is employed to sequence the genome of a primary and a metastatic oestrogen receptor α positive lobular breast tumour. Shah et al. employed paired-end sequencing to locate and Sanger re-sequencing to identify single nucleotide variations (SNVs), translocations, indels, inversions, gene fusions, and copy number variations in the DNA taken from both samples5. A notable feature of this study is the integration of genomic and transcriptomic analysis, both of which are facilitated with the employment of NextGen sequencing3. Shah et al. detected 32 new non-synonymous coding somatic point mutations (in the metastatic tumour) from a total of 405 coding non-synonymous SNVs. Of these only 11 were observed in the primary tumours1.4, 5 ( 1). The primary tumour sample was derived 9 years earlier at the time of diagnosis. Shah et al. sequenced the region of DNA which harboured 30 of the 32 somatic mutations, identified in the metastatic lesion5. The authors observed varying levels of mutational heterogeneity amongst the two tumours as well as some degree of overlap4 ( 2). Out of the 32 mutations, 19 found in the metastatic tumour were not observed in the primary tumour, highlighting that considerable heterogeneity of somatic mutations arises in tumour progression4. For the remaining mutations, the digital characteristics of NextGen sequencing found 11 of the mutations to vary in their frequency within the primary tumour. Some mutations were prevalent in the primary tumour compared to the metastatic tumour, whilst others exhibited lower frequency, by as little as 1% ( 1). Targeted sequencing of 9 mutated positions across 192 breast tumours identified two tumours containing truncated versions of the HAUS3 gene2 which is responsible for efficient chromosomal segregation8. The presence of this gene is reported for the first time in human cancer by Shah et al., implying that HAUS3 may have a role in preventing tumour progression1. Shah et al. also employed fluorescence in situ hybridization (FISH) and identified 19 regions of high levels of DNA amplification. Of these, a novel amplification of the insulin receptor (INSR), was also identified for the first time1,4. These findings provide insight into the evolution of the cancer genome related to tumour progression4. However, what remains undetermined is whether these genetic alterations reflect the evolution of the cancer genome and therefore a need of further oncogenic mutations for cancer progression4,6. Another possibility for this is that they may have arisen as a result of radiotherapy and/or endocrine therapy. Shah et al. also analysed the transcriptome of the metastatic lesion utilising high-throughput sequencing for evidence of events which are capable of altering the proteome further. These events include biased allelic expression, alternative splicing and RNA editing, 5.
RNA editing events
Shah et al. identified 3,122 potential RNA editing events, of which 536 were predicted to lead to non-synonymous substitutions. Two non-synonymous editing events were found in the COG3 and SRP95, these editing events are produced by an RNA editing enzyme which is encoded by the ADAR gene. Interestingly, Shah et al. reported the up- regulation of ADAR making it one of the top 5% of all genes expressed in the tumour. This highlights an additional mechanism which when de-regulated in tumours could possibly induce genetic alteration that might impart selective proliferation or survival advantages2. Further, the heterogeneity and variation that can be induced at the genomic and transcriptomic level highlights the significance of data incorporation between the transcriptomic and proteomic analyses of cancerous tumours.
Future use of whole genome sequencing
The data gathered by Shah et al.5 highlight the importance of information integration. The application of the quantitative and digital aspects of NextGen sequencing can be employed as a means of obtaining clearer understanding of gene activation and inactivation. This would work to provide valuable perspective into the similarities and differences of associated cancers, as well as in depth understanding of how these characteristics can guide the development of targeted interventions2. Shah et al.5 emphasise the importance of sequencing technologies in highlighting genomic heterogeneity present within cancers1. Although whether these mutations were found to increase over the course of metastatic progression because of a greater ability to move away from the primary tumour site or because they were selected due to their ability of showing resistance to the adjuvant endocrine therapy and radiotherapy remains undetermined. It may be the case that the mutations do not impart any selective advantage but are instead silent passengers, which do not contribute to cancer progression1. These questions signify the difficulty of understanding the catalogue of mutations of any individual tumour made plausible by NextGen sequencing. However on the other hand, whole genome sequencing projects reveal numerous interesting matters and open new lines of further research. Observation of these mutations would require to be carried out in a targeted manner to allow identification of these rare variants. Further studies, however, are required in order to confirm the functional importance of these low abundance mutations, which may have been detected during diagnosis1. The challenge lies in the application of these findings into generating validated biomarkers, which can be employed to guide clinical decision-making1,7. Further, the reduced expense of massively parallel sequencing systems could lead to an increase of similar studies, which may involve numerous different tumour types in the future1,9.
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The presence and the frequency at which each mutation occurs in any given cancer could potentially be estimated using NextGen sequencing and it may even play a role in the outcome of the disease3. The sequencing of hundreds of cancers with integrated knowledge on their shared and differing features will be required in the near future9. The application of NextGen sequencing into innovative clinical trials will in time, increase the value of genomic application to routine cancer care7.
In conclusion, Shah et al. highlight the potential application of NextGen sequencing in identifying the forces that drive the evolution of the cancer genome responsible for tumour progression.
1. Bedard, P.L., et al. 2010. EMBO Molecular medicine. 2:3-5
2. Alderton, G.K., et al. 2009. Nature. 9:1
3. Campbell, P.J., 2008. Nature. 40:722-729
4. Li, J.B., 2009. Science. 324: 1210-1213
5. Shah, S.P., et al. 2009. Nature. 461:809-813
6. Ley, T.J., 2008. Nature. 456:66-72
7. Wood, L.D., 2007. Science. 318: 1108-1113
8. Morin, R., 2008. Biotechniques. 45:81-94
9. Strausberg, R.L., et al. 2010. British Journal of Cancer. 102: 243-248
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