Anti-ESR1 monoclonal antibody, clone FS604

During female mammal reproductive tract development, epithelial cells of the lower Mullerian duct are committed to become stratified squamous epithelium of the vagina and ectocervix, when the expression of Delta Np63 transcription factor is induced by mesenchymal cells. The absence of Delta Np63 expression leads to adenosis, the putative precursor of vaginal adenocarcinoma. Our previous studies with genetically engineered mouse models have established that fibroblast growth factor (FGF)/mitogen-activated protein kinase (MAPK), bone morphogenetic protein (BMP)/SMAD, and activin A/runt-related transcription factor 1 (RUNX1) signaling pathways are independently required for Delta Np63 expression in Mullerian duct epithelium (MDE). Here, we report that sine oculis homeobox homolog 1 (SIX1) plays a critical role in the activation of Delta Np63 locus in MDE as a downstream transcription factor of mesenchymal signals. In the developing mouse reproductive tract, SIX1 expression was restricted to MDE within the future cervix and vagina. SIX1 expression was totally absent in SMAD4 null MDE and was reduced in RUNX1 null and FGFR2 null MDE, indicating that SIX1 is under the control of vaginal mesenchymal factors: BMP4, activin A and FGF7/10. Furthermore,Six1,Runx1, andSmad4gene-dose-dependently activated Delta Np63 expression in MDE within the vaginal fornix. Using a mouse model of diethylstilbestrol (DES)-associated vaginal adenosis, we found DES action through epithelial estrogen receptor alpha (ESR1) inhibits activation of Delta Np63 locus in MDE by transcriptionally repressing SIX1 and RUNX1 in the vaginal fornix.

Background Platinum resistance is an important cause of clinical recurrence and death for ovarian cancer. This study tries to systematically explore the molecular mechanisms for platinum resistance in ovarian cancer and identify regulatory genes and pathways via text mining and other methods. Methods Genes in abstracts of associated literatures were identified. Gene ontology and protein-protein interaction (PPI) network analysis were performed. Then co-occurrence between genes and ovarian cancer subtypes were carried out followed by cluster analysis. Results Genes with highest frequencies are mostly involved in DNA repair, apoptosis, metal transport and drug detoxification, which are closely related to platinum resistance. Gene ontology analysis confirms this result. Some proteins such as TP53, HSP90, ESR1, AKT1, BRCA1, EGFR and CTNNB1 work as hub nodes in PPI network. According to cluster analysis, specific genes were highlighted in each subtype of ovarian cancer, indicating that various subtypes may have different resistance mechanisms respectively. Conclusions Platinum resistance in ovarian cancer involves complicated signaling pathways and different subtypes may have specific mechanisms. Text mining, combined with other bio-information methods, is an effective way for systematic analysis.