The Major Prognostic Features of Nuclear Receptor NR5A2 in Infiltrating Ductal Breast Carcinomas.

Background. Gene expression profiles of 181 breast cancer samples were analyzed to identify prognostic features of nuclear receptors NR5A1 and NR5A2 based upon their associated transcriptional networks. Methods. A supervised network analysis approach was used to build the NR5A-mediated transcriptional regulatory network. Other bioinformatic tools and statistical methods were utilized to confirm and extend results from the network analysis methodology. Results. NR5A2 expression is a negative factor in breast cancer prognosis in both ER(-) and ER(-)/ER(+) mixed cohorts. The clinical and cohort significance of NR5A2-mediated transcriptional activities indicates that it may have a significant role in attenuating grade development and cancer related signal transduction pathways. NR5A2 signature that conditions poor prognosis was identified based upon results from 15 distinct probes. Alternatively, the expression of NR5A1 predicts favorable prognosis when concurrent NR5A2 expression is low. A favorable signature of eight transcription factors mediated by NR5A1 was also identified. Conclusions. Correlation of poor prognosis and NR5A2 activity is identified by NR5A2-mediated 15-gene signature. NR5A2 may be a potential drug target for treating a subset of breast cancer tumors across breast cancer subtypes, especially ER(-) breast tumors. The favorable prognostic feature of NR5A1 is predicted by NR5A1-mediated 8-gene signature.

Correction to: Prognostic Features of Signal Transducer and Activator of Transcription 3 in an ER(+) Breast Cancer Model System.

[This corrects the article on p. 21 in vol. 13, PMID: 24526833.].

Prognostic features of signal transducer and activator of transcription 3 in an ER(+) breast cancer model system.

The aberrantly expressed signal transducer and activator of transcription 3 (STAT3) predicts poor prognosis, primarily in estrogen receptor positive (ER(+)) breast cancers. Activated STAT3 is overexpressed in luminal A subtype cells. The mechanisms contributing to the prognosis and/or subtype relevant features of STAT3 in ER(+) breast cancers are through multiple interacting regulatory pathways, including STAT3-MYC, STAT3-ERα, and STAT3-MYC-ERα interactions, as well as the direct action of activated STAT3. These data predict malignant events, treatment responses and a novel enhancer of tamoxifen resistance. The inferred crosstalk between ERα and STAT3 in regulating their shared target gene-METAP2 is partially validated in the luminal B breast cancer cell line-MCF7. Taken together, we identify a poor prognosis relevant gene set within the STAT3 network and a robust one in a subset of patients. VEGFA, ABL1, LYN, IGF2R and STAT3 are suggested therapeutic targets for further study based upon the degree of differential expression in our model.