ABSTRACT
Patients with Her2-positive breast cancer exhibit de novo resistance or develop acquired resistance in less than one year after Her2 targeting treatment, but the mechanism is not fully elucidated. Compensatory pathways such as the IGF-1R/IRS-1 pathway, are activated, leading to aberrant enhanced PI3K/Akt/mTOR pathway activity to attenuate the efficacy of trastuzumab. Cullin7 could participate in the degradation of IRS-1 in a mTOR/S6K dependent manner. Whether Cullin7 participates in trastuzumab resistance needs to be further investigated. Here, we reveals that Cullin7 is overexpressed in trastuzumab-resistant Her2 positive breast cancer cells. Knockdown of Cullin7 reduces degradation of Ser phosphorylation of IRS-1, attenuates activation of the PI3K/AKT pathway, and partly restores trastuzumab sensitivity in trastuzumab-resistant Her2 positive breast cancer cells. IGFBP-3 expression is decreased in trastuzumab-resistant Her2 positive breast cancer cells, which leads to release of the Wnt signaling pathway inhibition and an increase in Cullin7 expression, as mediated by TCF7L2. Overexpression of Cullin7 in Her2-amplified breast cancer tissues has clinical implications because it positively correlates with shorter disease-free survival (DFS) and inadequate response to trastuzumab. Thus, our results suggest a critical role for Cullin7 in response to trastuzumab, which has significant implications for selection of the optimal therapeutic strategy for Her2 positive breast cancers.
Subject(s)
Breast Neoplasms/pathology , Cullin Proteins/genetics , Drug Resistance, Neoplasm , Insulin Receptor Substrate Proteins/metabolism , Insulin-Like Growth Factor Binding Protein 3/genetics , Receptor, ErbB-2/genetics , Animals , Breast Neoplasms/genetics , Cell Line, Tumor , Cell Survival , Down-Regulation , Female , Gene Amplification , Humans , Insulin Receptor Substrate Proteins/chemistry , Mice , Neoplasm Transplantation , Phosphatidylinositol 3-Kinases/metabolism , Proteolysis , Proto-Oncogene Proteins c-akt/metabolism , TrastuzumabABSTRACT
This study calculated the spectrum entropy (SE), approximate entropy (ApEn), and Lem-Ziv complexity (LZC) of sleeping EEG signals of eight healthy adults. The statistical results show that all the three nonlinear features can clearly reflect sleeping stage. Among them, the SE is easy to calculate and traces varying sleeping periods fairly and consistently, while the ApEn performs even better but is relatively complicated. The LZC is also simple but loses information details in its preprocessing of original measurement data, which consequently down grades its consistency. Based on a tradeoff of efficiency and efficacy, we consider the SE would be a good feature for real-time tracing sleep stages. Some conclusions are reported based on this study.
