Estrogen receptor β (ERβ) plays critical roles in thyroid cancer progression. However, its role in thyroid cancer stem cell maintenance remains elusive. Here, we report that ERβ is overexpressed in papillary thyroid cancer stem cells (PTCSCs), whereas ablation of ERβ decreases stemness-related factors expression, diminishes ALDH+ cell populations, and suppresses sphere formation ability and tumor growth. Screening estrogen-responsive lncRNAs in PTC spheroid cells, we find that lncRNA-H19 is highly expressed in PTCSCs and PTC tissue specimens, which is correlated with poor overall survival. Mechanistically, estradiol (E2) significantly promotes H19 transcription via ERβ and elevates H19 expression. Silencing of H19 inhibits E2-induced sphere formation ability. Furthermore, H19 acting as a competitive endogenous RNA sequesters miRNA-3126-5p to reciprocally release ERβ expression. ERβ depletion reverses H19-induced stem-like properties upon E2 treatment. Appropriately, ERβ is upregulated in PTC tissue specimens. Notably, aspirin attenuates E2-induced cancer stem-like traits through decreasing both H19 and ERβ expression. Collectively, our findings reveal that ERβ-H19 positive feedback loop has a compelling role in PTCSC maintenance under E2 treatment and provides a potential therapeutic targeting strategy for PTC.

Mitochondria-associated membranes (MAM) are a well-recognized contact link between the mitochondria and endoplasmic reticulum that affects mitochondrial biology and vascular smooth muscle cells (VSMCs) proliferation via the regulation of mitochondrial Ca2+(Ca2+m) influx. Nogo-B receptor (NgBR) plays a vital role in proliferation, epithelial-mesenchymal transition, and chemoresistance of some tumors. Recent studies have revealed that downregulation of NgBR, which stimulates the proliferation of VSMCs, but the underlying mechanism remains unclear. Here, we investigated the role of NgBR in MAM and VSMC proliferation. We analyzed the expression of NgBR in pulmonary arteries using a rat model of hypoxic pulmonary hypertension (HPH), in which rats were subjected to normoxic recovery after hypoxia. VSMCs exposed to hypoxia and renormoxia were used to assess the alterations in NgBR expression in vitro. The effect of NgBR downregulation and overexpression on VSMC proliferation was explored. The results revealed that NgBR expression was negatively related with VSMCs proliferation. Then, MAM formation and the phosphorylation of inositol 1,4,5-trisphosphate receptor type 3 (IP3R3) was detected. We found that knockdown of NgBR resulted in MAM disruption and augmented the phosphorylation of IP3R3 through pAkt, accompanied by mitochondrial dysfunction including decreased Ca2+m, respiration and mitochondrial superoxide, increased mitochondrial membrane potential and HIF-1α nuclear localization, which were determined by confocal microscopy and Seahorse XF-96 analyzer. By contrast, NgBR overexpression attenuated IP3R3 phosphorylation and HIF-1α nuclear localization under hypoxia. These results reveal that dysregulation of NgBR promotes VSMC proliferation via MAM disruption and increased IP3R3 phosphorylation, which contribute to the decrease of Ca2+m and mitochondrial impairment.

During the past decades, there have been continuous attempts in the prediction of metabolism mediated by cytochrome P450s (CYP450s) 3A4, 2D6, and 2C9. However, it has indeed remained a huge challenge to accurately predict the metabolism of xenobiotics mediated by these enzymes. To address this issue, microsomal metabolic reaction system (MMRS)-a novel concept, which integrates information about site of metabolism (SOM) and enzyme-was introduced. By incorporating the use of multiple feature selection (FS) techniques (ChiSquared (CHI), InfoGain (IG), GainRatio (GR), Relief) and hybrid classification procedures (Kstar, Bayes (BN), K-nearest neighbours (IBK), C4.5 decision tree (J48), RandomForest (RF), Support vector machines (SVM), AdaBoostM1, Bagging), metabolism prediction models were established based on metabolism data released by Sheridan et al. Four major biotransformations, including aliphatic C-hydroxylation, aromatic C-hydroxylation, N-dealkylation and O-dealkylation, were involved. For validation, the overall accuracies of all four biotransformations exceeded 0.95. For receiver operating characteristic (ROC) analysis, each of these models gave a significant area under curve (AUC) value >0.98. In addition, an external test was performed based on dataset published previously. As a result, 87.7% of the potential SOMs were correctly identified by our four models. In summary, four MMRS-based models were established, which can be used to predict the metabolism mediated by CYP3A4, 2D6, and 2C9 with high accuracy.