Functional genomics has helped us identify a catalog of genetic and epigenetic alterations that may be exploited as potential therapeutic targets and biomarkers of response. New treatment combinations targeting ER and such oncogenic signaling pathways which block the crosstalk between these pathways have been proven effective in preclinical models. Results of recent clinical studies suggest that subsets of patients benefit from the combination of

inhibitor targeting certain oncogenic signaling pathway with endocrine 查找更多 therapy. Especially, inhibition of the m TOR signaling pathway, a key component implicated in mediating multiple signaling cascades, offers a promising approach to restore sensitivity to endocrine therapy in breast cancer. We systematically reviewed important publications cited in Pub Med, recent abstracts from ASCO annual meetings CDK抑制剂 and San Antonio Breast Cancer

Symposium, and relevant trials registered at Clinical Trials.gov. We present the molecular mechanisms contributing to endocrine resistance, in particular focusing on the biological rationale for the clinical development of novel targeted agents in endocrine resistant breast cancer. We summarize clinical trials utilizing novel strategies to overcome therapeutic

resistance, highlighting the need to better identify the appropriate patients 确认细节 whose diseases are most likely to benefit from these specific strategies.
By using a combined method of density functional theory(DFT), molecular mechanics(MM2) and statistics for two-dimensional(2D), as well as the comparative molecular field analysis(Co MFA) and comparative molecular similarity index analysis(Co MSIA) methods for three-dimensional(3D), theoretical studies on 2D/3D quantitative structure-activity relationships(QSAR) of 22 novel compounds of [1,2,4]triazolo[1,5-a] pyridinylpyridines acting as PI3 K inhibitors against the human colon carcinoma cell line(HCT-116) have been performed. Both the 2D- and 3D-QSAR models established from the random 18 compounds in training set show significant statistical quality and satisfactory predictive ability(R2 = 0.821, q2 = 0.773 for 2D-QSAR, R2 = 0.966, q2 = 0.668 for Co MFA, R2 = 0.979, q2 = 0.