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A signature inferred from Drosophila mitotic genes predicts survival of breast cancer patients.

Damasco C, Lembo A, Somma MP, Gatti M, Di Cunto F, Provero P - PLoS ONE (2011)

Bottom Line: We thus constructed a gene expression signature (the DM signature) using the human orthologues of 108 Drosophila melanogaster genes required for either the maintenance of chromosome integrity (36 genes) or mitotic division (72 genes).For most genes of the DM signature, an increased expression is negatively correlated with patient survival.The genes that provide the highest contribution to the predictive power of the DM signature are those involved in cytokinesis.

View Article: PubMed Central - PubMed

Affiliation: Molecular Biotechnology Center and Department of Genetics, Biology and Biochemistry, University of Turin, Turin, Italy.

ABSTRACT

Introduction: The classification of breast cancer patients into risk groups provides a powerful tool for the identification of patients who will benefit from aggressive systemic therapy. The analysis of microarray data has generated several gene expression signatures that improve diagnosis and allow risk assessment. There is also evidence that cell proliferation-related genes have a high predictive power within these signatures.

Methods: We thus constructed a gene expression signature (the DM signature) using the human orthologues of 108 Drosophila melanogaster genes required for either the maintenance of chromosome integrity (36 genes) or mitotic division (72 genes).

Results: The DM signature has minimal overlap with the extant signatures and is highly predictive of survival in 5 large breast cancer datasets. In addition, we show that the DM signature outperforms many widely used breast cancer signatures in predictive power, and performs comparably to other proliferation-based signatures. For most genes of the DM signature, an increased expression is negatively correlated with patient survival. The genes that provide the highest contribution to the predictive power of the DM signature are those involved in cytokinesis.

Conclusion: This finding highlights cytokinesis as an important marker in breast cancer prognosis and as a possible target for antimitotic therapies.

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Related in: MedlinePlus

Predictive power of the DM signature.Kaplan-Meier analysis using the DM signature shows significant                            differences in survival of patients from five independents breast cancer                            datasets.
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pone-0014737-g001: Predictive power of the DM signature.Kaplan-Meier analysis using the DM signature shows significant differences in survival of patients from five independents breast cancer datasets.

Mentions: Although most of these gene expression data were generated using the same microarray platform, and could in principle be merged in a single dataset as recently described [13], we evaluated the DM signature on the individual datasets. We chose this approach because the robustness of a gene signature on independent datasets is an important criterion for validation of its predictive power. In our prognostic power analysis, we used relapse-free survival times when available, or overall survival times otherwise. Because three genes of the DM signature (H3F3A, PPAN-P2RY11 and KIF4) were not represented in the Affymetrix platform, we performed our analyses on 105 genes. For each dataset, patients were divided into two groups based on the expression profiles of the genes in the DM signature using hierarchical clustering. Differences in survival probability between the two groups were then evaluated with a standard log-rank test on Kaplan-Meier curves. Figure 1 shows that the differences in survival are statistically significant for all datasets considered.


A signature inferred from Drosophila mitotic genes predicts survival of breast cancer patients.

Damasco C, Lembo A, Somma MP, Gatti M, Di Cunto F, Provero P - PLoS ONE (2011)

Predictive power of the DM signature.Kaplan-Meier analysis using the DM signature shows significant                            differences in survival of patients from five independents breast cancer                            datasets.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3046113&req=5

pone-0014737-g001: Predictive power of the DM signature.Kaplan-Meier analysis using the DM signature shows significant differences in survival of patients from five independents breast cancer datasets.
Mentions: Although most of these gene expression data were generated using the same microarray platform, and could in principle be merged in a single dataset as recently described [13], we evaluated the DM signature on the individual datasets. We chose this approach because the robustness of a gene signature on independent datasets is an important criterion for validation of its predictive power. In our prognostic power analysis, we used relapse-free survival times when available, or overall survival times otherwise. Because three genes of the DM signature (H3F3A, PPAN-P2RY11 and KIF4) were not represented in the Affymetrix platform, we performed our analyses on 105 genes. For each dataset, patients were divided into two groups based on the expression profiles of the genes in the DM signature using hierarchical clustering. Differences in survival probability between the two groups were then evaluated with a standard log-rank test on Kaplan-Meier curves. Figure 1 shows that the differences in survival are statistically significant for all datasets considered.

Bottom Line: We thus constructed a gene expression signature (the DM signature) using the human orthologues of 108 Drosophila melanogaster genes required for either the maintenance of chromosome integrity (36 genes) or mitotic division (72 genes).For most genes of the DM signature, an increased expression is negatively correlated with patient survival.The genes that provide the highest contribution to the predictive power of the DM signature are those involved in cytokinesis.

View Article: PubMed Central - PubMed

Affiliation: Molecular Biotechnology Center and Department of Genetics, Biology and Biochemistry, University of Turin, Turin, Italy.

ABSTRACT

Introduction: The classification of breast cancer patients into risk groups provides a powerful tool for the identification of patients who will benefit from aggressive systemic therapy. The analysis of microarray data has generated several gene expression signatures that improve diagnosis and allow risk assessment. There is also evidence that cell proliferation-related genes have a high predictive power within these signatures.

Methods: We thus constructed a gene expression signature (the DM signature) using the human orthologues of 108 Drosophila melanogaster genes required for either the maintenance of chromosome integrity (36 genes) or mitotic division (72 genes).

Results: The DM signature has minimal overlap with the extant signatures and is highly predictive of survival in 5 large breast cancer datasets. In addition, we show that the DM signature outperforms many widely used breast cancer signatures in predictive power, and performs comparably to other proliferation-based signatures. For most genes of the DM signature, an increased expression is negatively correlated with patient survival. The genes that provide the highest contribution to the predictive power of the DM signature are those involved in cytokinesis.

Conclusion: This finding highlights cytokinesis as an important marker in breast cancer prognosis and as a possible target for antimitotic therapies.

Show MeSH
Related in: MedlinePlus