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. 2008 Jun 27:1:28.
doi: 10.1186/1755-8794-1-28.

Pathway analysis reveals functional convergence of gene expression profiles in breast cancer

Ronglai Shen  1 , Arul M Chinnaiyan, Debashis Ghosh
Affiliations

Pathway analysis reveals functional convergence of gene expression profiles in breast cancer

Ronglai Shen et al. BMC Med Genomics. .

Abstract

Background: A recent study has shown high concordance of several breast-cancer gene signatures in predicting disease recurrence despite minimal overlap of the gene lists. It raises the question if there are common themes underlying such prediction concordance that are not apparent on the individual gene-level. We therefore studied the similarity of these gene-signatures on the basis of their functional annotations.

Results: We found the signatures did not identify the same set of genes but converged on the activation of a similar set of oncogenic and clinically-relevant pathways. A clear and consistent pattern across the four breast cancer signatures is the activation of the estrogen-signaling pathway. Other common features include BRCA1-regulated pathway, reck pathways, and insulin signaling associated with the ER-positive disease signatures, all providing possible explanations for the prediction concordance.

Conclusion: This work explains why independent breast cancer signatures that appear to perform equally well at predicting patient prognosis show minimal overlap in gene membership.

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Figures

Figure 1
Figure 1
Pair-wise functional overlap of the six breast cancer gene-signatures. 1. 70-gene profile 2. Wound response 3. Intrinsic subtype 4. Meta90 5. Recurrence score 6. Wang ER+ profile. A. The number of overlapping literature-defined oncogenic concepts (MCM) and the corresponding P-value heatmap indicating the significance of the overlap under bootstrapped null distribution. B. The number of overlapping pathway sets (MsigDB) and the corresponding P-value heatmap.
See this image and copyright information in PMC

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