Trends in Genetics
Volume 24, Issue 9, September 2008, Pages 427-430
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Genome Analysis
Low duplicability and network fragility of cancer genes

https://doi.org/10.1016/j.tig.2008.06.003Get rights and content

We identified genomic and network properties of ∼600 genes mutated in different cancer types. These genes tend not to duplicate but, unlike most human singletons, they encode central hubs of highly interconnected modules within the protein–protein interaction network (PIN). We find that cancer genes are fragile components of the human gene repertoire, sensitive to dosage modification. Furthermore, other nodes of the human PIN with similar properties are rare and probably enriched in candidate cancer genes.

Section snippets

Functional heterogeneity of genes mutated in cancer

Recent systematic and unbiased screenings of cancer genomes revealed a significant number of functionally heterogeneous genes to be mutated in tumors 1, 2, 3, 4. These studies described each tumor as a distinct disease with specific, and partly unrelated, genetic determinants. However, high heterogeneity does not necessarily imply that these genes lack common properties. Modifications of cancer genes, although functionally different, lead to the same outcome: uncontrolled cell proliferation.

Genes mutated in cancer duplicate less than other human genes

We measured gene duplicability by aligning the corresponding protein sequences directly to the human genome (see Supplementary Section 1.1 and Figure S1). We defined as ‘duplicates’ all additional genomic matches covering at least 60% of the query length. This threshold of coverage allowed us to detect duplicates that were at least 70% identical to more than one half of the query sequence (Figure S2). A gene was considered a ‘singleton’ if the corresponding protein matched only to one genomic

Cancer proteins are central hubs of interconnected modules of the human protein–protein interaction network

We derived the human protein–protein interaction network (PIN) from the Human Protein Reference Database (HPRD), which consists of a manually curated collection of in vivo, in vitro and high-throughput data [13]. After removing self-interactions, we obtained a graph composed of 9264 nodes (proteins) and 34 564 edges (protein–protein interactions). It contains information on 304 cancer and 154 CAN-proteins and has the features of a scale-free network [14] (see Supplementary Section 2). Although

Biological implications of systems-level properties of cancer genes

Our analysis showed that genes mutated in cancer are characterized by systems-level properties independent of their molecular function. They are significantly enriched in a special group of human singletons encoding proteins in central positions of highly interconnected clusters of the human PIN. These properties suggest an intrinsic fragility of cancer genes toward perturbations: gene dosage modifications of highly interconnected hubs (but, arguably, also sequence mutations) are likely to

Identification of novel candidate cancer genes

Only a small proportion of the human PIN is composed of highly clustered hubs that, unlike most human hubs, are preferentially encoded by singletons (Supplementary Section 5). This is consistent with the hypothesis that such positions constitute general weak points for the system, probably sensitive to dosage effect. Resembling the same system-level properties of cancer genes, they are likely to bear novel candidate cancer genes. We therefore focused on 101 singleton genes encoding highly

Concluding remarks

Our analysis provided evidence for the existence of shared properties of human genes involved in cancer that can explain their role in terms of system perturbations rather than modifications of single components. This finding offers a novel paradigm to interpret the heterogeneous mutational landscape of cancer genomes. It also provides the starting platform for measuring the actual effects of each gene modification on network stability. Future efforts in this direction will help not only to

Acknowledgements

The authors thank Lars Jensen (EMBL-Heidelberg) for the list of gene-associated abstracts and Giovanni D’Ario (IFOM) and Lara Lusa (Istituto Tumori, Milan) for help with statistics. This work was supported by an AIRC Start-Up grant to F.D.C.

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