SOD2 acetylation on lysine 68 promotes stem cell reprogramming in breast cancer.

Mitochondrial superoxide dismutase (SOD2) suppresses tumor initiation but promotes invasion and dissemination of tumor cells at later stages of the disease. The mechanism of this functional switch remains poorly defined. Our results indicate that as SOD2 expression increases acetylation of lysine 68 ensues. Acetylated SOD2 promotes hypoxic signaling via increased mitochondrial reactive oxygen species (mtROS). mtROS, in turn, stabilize hypoxia-induced factor 2α (HIF2α), a transcription factor upstream of "stemness" genes such as Oct4, Sox2, and Nanog. In this sense, our findings indicate that SOD2K68Ac and mtROS are linked to stemness reprogramming in breast cancer cells via HIF2α signaling. Based on these findings we propose that, as tumors evolve, the accumulation of SOD2K68Ac turns on a mitochondrial pathway to stemness that depends on HIF2α and may be relevant for the progression of breast cancer toward poor outcomes.

An integrated bioinformatics approach identifies elevated cyclin E2 expression and E2F activity as distinct features of tamoxifen resistant breast tumors.

Approximately half of estrogen receptor (ER) positive breast tumors will fail to respond to endocrine therapy. Here we used an integrative bioinformatics approach to analyze three gene expression profiling data sets from breast tumors in an attempt to uncover underlying mechanisms contributing to the development of resistance and potential therapeutic strategies to counteract these mechanisms. Genes that are differentially expressed in tamoxifen resistant vs. sensitive breast tumors were identified from three different publically available microarray datasets. These differentially expressed (DE) genes were analyzed using gene function and gene set enrichment and examined in intrinsic subtypes of breast tumors. The Connectivity Map analysis was utilized to link gene expression profiles of tamoxifen resistant tumors to small molecules and validation studies were carried out in a tamoxifen resistant cell line. Despite little overlap in genes that are differentially expressed in tamoxifen resistant vs. sensitive tumors, a high degree of functional similarity was observed among the three datasets. Tamoxifen resistant tumors displayed enriched expression of genes related to cell cycle and proliferation, as well as elevated activity of E2F transcription factors, and were highly correlated with a Luminal intrinsic subtype. A number of small molecules, including phenothiazines, were found that induced a gene signature in breast cancer cell lines opposite to that found in tamoxifen resistant vs. sensitive tumors and the ability of phenothiazines to down-regulate cyclin E2 and inhibit proliferation of tamoxifen resistant breast cancer cells was validated. Our findings demonstrate that an integrated bioinformatics approach to analyze gene expression profiles from multiple breast tumor datasets can identify important biological pathways and potentially novel therapeutic options for tamoxifen-resistant breast cancers.