[HTML][HTML] Molecular signatures associated with transformation and progression to breast cancer in the isogenic MCF10 model

DK Rhee, SH Park, YK Jang - Genomics, 2008 - Elsevier
DK Rhee, SH Park, YK Jang
Genomics, 2008Elsevier
Comparative microarray analyses provided insight into understanding transcript changes
during cancer progression; however, a reproducible signature underlying breast
carcinogenesis has yet to be little available. We utilized gene expression profiling to define
molecular signatures associated with transformation and cancer progression in a series of
isogenic human breast cancer cell lines including a normal, benign, noninvasive and
invasive carcinoma. Clustering analysis revealed four distinct expression patterns based on …
Comparative microarray analyses provided insight into understanding transcript changes during cancer progression; however, a reproducible signature underlying breast carcinogenesis has yet to be little available. We utilized gene expression profiling to define molecular signatures associated with transformation and cancer progression in a series of isogenic human breast cancer cell lines including a normal, benign, noninvasive and invasive carcinoma. Clustering analysis revealed four distinct expression patterns based on upregulation or downregulation patterns. These profiles proved quite useful for describing breast cancer tumorigenesis and invasiveness. Downregulation of TNFSF7, S100A4, S100A7, S100A8, and S100A9 (calcium-binding protein family), and upregulation of kallikrein-5 and thrombospondin-1 were associated with transformation and progression of breast cancer cells. Importantly, downregulation of the genes was reversed by treatment with silencing inhibitors, implying the potential roles of epigenetic inactivation in breast carcinogenesis. Exogenous expressions of S100A8 and S100A9 inhibit growth in benign and noninvasive carcinoma cells, suggesting their negative role in cell proliferation. The data presented here may facilitate the identification and functional analyses of prognostic biomarkers for breast cancer.
Elsevier