Rabbit Anti-Human RELA (Phospho-Ser529) polyclonal antibody

Carboxyl terminus of Hsc-70-interacting protein (CHIP), as U-box-type ubiquitin ligase, connects the chaperone and proteasome systems and plays a pivotal role in maintaining protein homeostasis in the cytoplasm. CHIP induces the ubiquitination and degradation of diverse oncogenic substrate proteins and therefore involves in the progression of tumorigenesis. In this study, the CHIP expression was examined in different human breast cancer cell lines and a group of breast cancer tissues. We found, for the first time, that CHIP expression was correlated with the molecular subtyping of breast cancer. CHIP was least expressed in the base-like subtype of breast cancer, which are triple-negative breast cancer (TNBC) breast cancer predominantly. Accordingly, CHIP expression was evidently decreased in the TNBC MDA-MB-231 breast cancer cell line. Enforced induction of CHIP in the MDA-MB-231 cells exerted no obvious influences on cellular growth and cell cycle. The apoptotic and proliferation cells in hCHIP cells were both reduced compared to the ctrl cells. The mRNA and protein expressions of the anti-apoptotic Bcl-2 and Bcl-xL were markedly increased in the hCHIP cells compared to that of the ctrl cells. The expression of RelA was significantly reduced in the nuclear extract in hCHIP cells compared to that in the ctrl cells. The protein expressions of IKK beta were markedly decreased in the hCHIP cells compared to the ctrl cells. The reduced cellular proliferation was largely due to the attenuated IKK beta-p65/NF-kappa B activity. Meanwhile, the invasion ability but not the migration ability was diminished when CHIP was overexpressed in the MDA-MB-231 cells. The activity of MMP2 but not MMP9 was significantly decreased in the hCHIP cells compared to the ctrl cells. Taken together, these observations here provide functional evidence for CHIP behaved as a tumor suppressor in the TNBC breast cancer cells. CHIP influenced diverse biological aspects of the MDA-MB-231 breast cancer cells. Importantly, CHIP expression is a useful indicator of the molecular subtyping of breast cancer.

Background Traditional Chinese medicine (TCM) encompasses numerous herbal formulas which play critical therapeutic roles through "multi-components, multi-targets and multi-pathways" mechanisms. Exploring the interaction among these mechanisms can certainly help to depict the core therapeutic function of herbal formulas. Xiaoyao decoction (XYD) is one of the most well-known traditional Chinese medicine formulas which has been widely applied to treat various diseases. In this study, taking XYD as an example, we proposed a network pharmacology-based method to identify the main therapeutic targets of this herbal concoctions. Methods Chemical data of XYD were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP), Traditional Chinese Medicines Integrated Database (TCMID) and Compound Reference Database (CRD) and screened oral bioavailability attributes from SwissADME using Veber's filter. Targets of sample chemicals were identified using the online tool similarity ensemble approach (SEA), and pathways were enriched using STRING database. On the basis of targets-pathways interactions from the enrichment, a "targets-pathways-targets" (TPT) network was constructed. In the TPT network, the importance of each target was calculated by the declining value of network efficiency, which represents the influential strength of a specific set-off target on the whole network. Network-based predictive results were statistically validated with existing experimental evidence. Results The TPT network was comprised of 279 nodes and 6549 edges. The declining value of network efficiency of the sample targets was significantly correlated with their involvement frequency in existing studies of XYD using Spearman's test (p < 0.001). The top 10% of candidate targets, such as AKT1, PIK3R1, NFKB1 and RELA, etc., were chosen as XYD's main therapeutic targets, which further show pharmacological functions synergistically through 11 main pathways. These pathways are responsible for endocrine, nutritional or metabolic diseases, neoplasms and diseases of the nervous system, etc. Conclusions The network pharmacology-based approach in the present study shows promising potential for identifying the main therapeutic targets from TCM formulas. This study provides valuable information for TCM researchers and clinicians for better understanding the main therapeutic targets and therapeutic roles of herbal decoctions in clinical settings.