Please note that we have stopped the regular imports of Gene Expression Omnibus (GEO) data into ArrayExpress. This may not be the latest version of this experiment.
E-GEOD-32641 - Major functional transcriptome of an inferred center regulator of an ER(-) breast cancer model system
Released on 25 September 2012, last updated on 4 May 2014
We aimed to find clinically relevant gene activities ruled by the signal transducer and activator of transcription 3 (STAT3) proteins in an ER(-) breast cancer population via network approach. STAT3 is negatively associated with both lymph nodal category and stage. MYC is a component of STAT3 network. MYC and STAT3 may co-regulate gene expressions for Warburg effect, stem cell like phenotype, cell proliferation and angiogenesis. We identified a STAT3 network in silico showing its ability in predicting its target gene expressions primarily for specific tumor subtype, tumor progression, treatment options and prognostic features. The aberrant expressions of MYC and STAT3 are enriched in triple negatives (TN). They promote histological grade, vascularity, metastasis and tumor anti-apoptotic activities. VEGFA, STAT3, FOXM1 and METAP2 are druggable targets. High levels of METAP2, MMP7, IGF2 and IGF2R are unfavorable prognostic factors. STAT3 is an inferred center regulator at early cancer development predominantly in TN. 91 specimens of primary infiltrating ductal carcinoma of breast (IDC) included triple negatives(48/91), ERBB2+(29/91),ER(-)PR(+)HER(-)(5/91), ER(-)PR(+)HER(+)(6/91) and ER(-) but HER(?)(3/91). Five specimens for metaplastic carcinoma of breast (MCB) were included. Seven non-tumor samples were surgically taken from breast tissue adjacent to some of 91 ER(-) IDC breast tumors as a control in this study.
transcription profiling by array
Chiung-Nien Chen, Fon-Jou Hsieh, Hsiao-Lin Hwa, King-Jen Chang, Li-Yu D Liu, Li-Yun Chang, Shiu-Feng Huang, Wen-Hung Kuo, Yi-Shing Lin
Major Functional Transcriptome of an Inferred Center Regulator of an ER(-) Breast Cancer Model System. Liu LY, Chang LY, Kuo WH, Hwa HL, Lin YS, Huang SF, Chen CN, Chang KJ, Hsieh FJ. , PMID:22553414