Abstract
Abstract Background: Co-expression modules in cancer are cohesive groups of genes with highly correlated expression patterns, presumably regulating phenotypes important in carcinogenesis, metastasis, or response to treatment. With the growing database of gene expression data, it is now possible to deduce co-expression modules active in breast cancer subpopulations. Methods: We assembled 74 breast-cancer related gene expression datasets containing ∼5,500 samples altogether. Per dataset, we identified genes with bimodal expression analyzed using mixture-model clustering to ultimately find gene groups that are consistently co-regulated across multiple datasets. Functional and pathway enrichment of modules was assessed using DAVID and g:profiler software tools. Associations between module expression and patient outcome, chemotherapy response, clinical variables, epithelial vs. stromal expression, intrinsic subtype and other published signatures were assessed using standard statistical methods. Results: Our meta-analysis identified 11 modules ranging in size from ∼5-200 genes. As expected, there were modules representing estrogen signaling, cell proliferation, and ERBB2 signaling that correlate with intrinsic subtype and receptor status. In addition, we found modules associated with immune signaling, development, histone modification, and the ECM. The immune modules were highly correlated to previously published Tcell/Bcell, STAT1, and IFN immune signatures. In multivariate analysis, the combination of a downregulated Tcell/Bcell immune module and an upregulated proliferation module associated with recurrence, suggesting that cancers with a high proliferation rate in the absence of an activated immune system are prone to recur. This association was especially strong in TN and basal cancers. Comparing modules associated with response to chemotherapy to those associated with the prognosis of untreated patients, the most common pattern was that of a module associating with good prognosis or a good response to chemotherapy (but not both). For instance, high expression of the estrogen module associates with a good prognosis but a poor response to chemotherapy, whereas upregulation of the proliferation module associates with a poor prognosis but a good response to chemotherapy. Another pattern we observed, of a biomarker that associates with good prognosis without chemotherapy and a good response to chemotherapy, was found in the T/B cell immune modules. Conclusion: Co-expression modules provide a high-level functional view of breast cancer that complements the ‘cancer hallmarks’. These results suggest that in some high-immune patients, the same host processes contributing to an excellent response to chemotherapy might preclude its necessity, and support a treatment strategy boosting anti-tumoral immunity in low-immunity patients with highly proliferating tumors. Citation Format: Denise M. Wolf, Christina Yau, Aaron Boudreau, Laura Esserman, Laura Van ‘t Veer, Marc Lenburg. Co-expression modules as hallmarks of breast cancer survival and response. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 5221. doi:10.1158/1538-7445.AM2013-5221
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