Research Perspectives:
A Tumor initiating cell-enriched prognostic signature for HER2+:ERα- breast cancer; rationale, new features, controversies and future directions
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Abstract
Jeff C. Liu1,*, Sean E. Egan2 and Eldad Zacksenhaus1,*
1 Division of Cell & Molecular Biology, Toronto General Research Institute - University Health Network, Toronto, Canada
2 Program in Developmental and Stem Cell Biology, The Hospital for Sick Children, Toronto
Correspondence:
Jeff Liu, email:
Eldad Zacksenhaus, email:
Keywords: HER2 breast cancer; Prognostic signature; Tumor initiating cell; Cancer stem cells; Mouse models
Received: July 10, 2013 Accepted: July 24, 2013 Published: July 26, 2013
Abstract
The high intra- and inter-tumor heterogeneity of many types of cancers, including breast cancer (BC), poses great challenge to development of subtype-specific prognosis. In BC, the classification of tumors as either ERα+ (Luminal A and Luminal B), HER2+ (ERα+ or ERα-) or triple-negative (TNBC)(Basal-like, claudin-low) guides both prognostication and therapy. Indeed, prognostic signatures for ERα+ BC are being incorporated into clinical use. However, these signatures distinguish between luminal A (low risk) and Luminal B (high risk) BC; signatures that identify low/high risk patients with luminal B BC are yet to be developed. Likewise, no signature is in clinical use for HER2+ or TNBC. The major obstacles to development of robust signatures stem from diversity of BC, clonal evolution and heterogeneity within each subtype. We have recently generated a prognostic signature for HER2+:ERα- BC based on the identification of genes that were differentially expressed in a tumor-initiating cell (TIC)-enriched fraction versus non-TIC fraction from a mouse model of HER2+ BC (MMTV-Hers/Neu). Here we describe the rationale behind development of this prognosticator, and present new features of the signature, including elevated PI3K pathway activity and low TNFalpha and IFNgamma signaling in high-risk tumors. In addition, we address controversies in the field such as whether random gene expression signatures significantly associate with cancer outcome. Finally, we suggest a guideline for development of prognostic signatures and discuss future directions.
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