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Comparative Study
. 2006 Jan 11:7:3.
doi: 10.1186/1471-2164-7-3.

Structural and functional properties of genes involved in human cancer

Simon J Furney  1 , Desmond G Higgins, Christos A Ouzounis, Núria López-Bigas
Affiliations
Comparative Study

Structural and functional properties of genes involved in human cancer

Simon J Furney et al. BMC Genomics. .

Abstract

Background: One of the main goals of cancer genetics is to identify the causative elements at the molecular level leading to cancer.

Results: We have conducted an analysis of a set of genes known to be involved in cancer in order to unveil their unique features that can assist towards the identification of new candidate cancer genes.

Conclusion: We have detected key patterns in this group of genes in terms of the molecular function or the biological process in which they are involved as well as sequence properties. Based on these features we have developed an accurate Bayesian classification model with which human genes have been scored for their likelihood of involvement in cancer.

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Figures

Figure 1
Figure 1
(a) Distribution of conservation score of proteins involved in cancer (red line) and all human proteins (blue line) against their closest homologue in M. musculus, R. norvegicus, G. gallus and between Paralogues. The conservation score gives an estimation of the mutation rate that the protein has been subjected to during evolution that is independent of the length of the protein. (b) Protein length, calculated as number of amino acids, and gene length distribution of cancer proteins (red) and all human proteins (blue).
Figure 2
Figure 2
Number of genes involved in cancer with each Molecular function (a) or Biological process (b) GO assignments (red) and number of genes expected in a same size random group of genes from the human genome (blue) (the P-value for the χ2 test is 1.5e-30 for the Molecular function and 3.5e-36 for the Biological process GO assignments). Note that one gene can have multiple GO assignments. χ2 values for each cell are represented with a colour-coded scale. Colours towards red signify over-representation and those towards blue signify under-representation of cancer genes with a particular GO assignment. Green signifies equal representation of both sets in a category.
Figure 3
Figure 3
ROC curve for the prediction of cancer genes. The 45° diagonal of the ROC space represents a random guess situation. The performance of the model at 0.5 and 0.7 cut-off probability scores are shown with dashed lines.
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