Overexpressed Gαi1 exerts pro-tumorigenic activity in nasopharyngeal carcinoma.

The current study tested the expression and potential functions of Gαi1 in nasopharyngeal carcinoma (NPC). The Cancer Genome Atlas (TCGA) database results demonstrate that Gαi1 transcripts' number in NPC tissues is significantly higher than that in the normal nasal epithelial tissues. Its overexpression correlates with poor survival in certain NPC patients. Moreover, Gαi1 is significantly upregulated in NPC tissues of local primary patients and in different primary human NPC cells. Whereas its expression is relatively low in cancer-surrounding normal tissues and in primary nasal epithelial cells. Genetic silencing (via shRNA strategy) or knockout (via CRISPR-sgRNA method) of Gαi1 substantially suppressed viability, proliferation, cell cycle progression, and migration in primary NPC cells, causing significant caspase-apoptosis activation. Contrarily, ectopic Gαi1 expression exerted pro-tumorigenic activity and strengthened cell proliferation and migration in primary NPC cells. Gαi1 is important for Akt-mTOR activation in NPC cells. Akt-S6K phosphorylation was downregulated after Gαi1 shRNA or KO in primary NPC cells, but strengthened following Gαi1 overexpression. In Gαi1-silenced primary NPC cells, a S473D constitutively-active mutant Akt1 (caAkt1) restored Akt-S6K phosphorylation and ameliorated Gαi1 shRNA-induced proliferation inhibition, migration reduction and apoptosis. Bioinformatics analyses proposed zinc finger protein 384 (ZNF384) as a potential transcription factor of Gαi1. In primary NPC cells, ZNF384 shRNA or knockout (via CRISPR-sgRNA method) decreased Gαi1 mRNA and protein expression, whereas ZNF384 overexpression upregulated it. Importantly, there was an increased binding between ZNF384 protein and the Gαi1 promoter in human NPC tissues and different NPC cells. In vivo studies showed that intratumoral injection of Gαi1-shRNA-expressing adeno-associated virus (AAV) impeded subcutaneous NPC xenograft growth in nude mice. Gαi1 downregulation, Akt-mTOR inactivation, and apoptosis induction were detected in Gαi1-silenced NPC xenograft tissues. Gαi1 KO also effectively inhibited the growth of NPC xenografts in nude mice. Together, overexpressed Gαi1 exerts pro-tumorigenic activity in NPC possibly by promoting Akt-mTOR activation.

Hypoxic nasopharyngeal carcinoma-derived exosomal miR-455 increases vascular permeability by targeting ZO-1 to promote metastasis.

Nasopharyngeal carcinoma (NPC), the most frequent reason for treatment failure in head and neck tumors, has the greatest incidence of distant metastases. Increased vascular permeability facilitates metastasis. Exosomal microRNAs (miRNAs) have been implicated in the development of the premetastatic niche and are emerging as prospective biomarkers in cancer patients. We discovered that a higher level of miR-455 was connected to a larger propensity for NPC metastasis based on deep sequencing and RT-qPCR. We found that hypoxia promoted NPC exosomes release and increased miR-455 expression in a way that was hypoxia-inducible factor 1-alpha (HIF-1α) dependent. Exosomes from NPC cells with high levels of miR-455 were found to specifically target zonula occludens 1 (ZO-1), increasing the permeability of endothelial monolayers in vitro vascular permeability and transendothelial invasion experiments. Additional in vivo studies showed that zebrafish with sustained miR-455-overexpressing NPC cell xenografts displayed increased tumor cell mass throughout the body. In vivo, zebrafish vascular tight junction integrity was disrupted by exosomes produced by NPC cells with elevated miR-455 expression. Mice-bearing xenografts further supported the finding that exosomes containing miR-455 might reduce ZO-1 expression in addition to promote NPC cell growth. These findings suggest that in a hypoxic microenvironment, exosomal miR-455 released by NPC cells enhances vascular permeability and promotes metastasis by targeting ZO-1. The HIF-1α-miR-455-ZO-1 signaling pathway may be a promising predictor and potential therapeutic target for NPC with metastasis.

The pro-tumorigenic activity of p38γ overexpression in nasopharyngeal carcinoma.

It is urgent to identify and validate biomarkers for early diagnosis and efficient treatment of nasopharyngeal carcinoma (NPC). Recent studies have proposed p38 gamma (p38γ) as a cyclin-dependent kinase (CDK)-like kinase that phosphorylates retinoblastoma (Rb) to promote cyclins expression and tumorigenesis. Here the Gene Expression Profiling Interactive Analysis (GEPIA) database and results from the local NPC tissues demonstrate that p38γ is significantly upregulated in NPC tissues, correlating with poor overall survival. Furthermore, p38γ mRNA and protein expression is elevated in established NPC cell lines (CNE-1 HONE-1 and CNE-2) and primary human NPC cells, but low expression detected in human nasal epithelial cells. In established and primary NPC cells, p38γ depletion, using the shRNA strategy or the CRISPR/Cas9 gene-editing method, largely inhibited cell growth, proliferation and migration, and induced significant apoptosis activation. Contrarily, ectopic p38γ overexpression exerted opposite activity and promoted NPC cell proliferation and migration. Retinoblastoma (Rb) phosphorylation and cyclin E1/A expression were decreased in NPC cells with p38γ silencing or knockout, but increased after p38γ overexpression. Moreover, mitochondrial subcellular p38γ localization was detected in NPC cells. Significantly, p38γ depletion disrupted mitochondrial functions, causing mitochondrial depolarization, reactive oxygen species production, oxidative injury and ATP depletion in NPC cells. In vivo, intratumoral injection of adeno-associated virus-packed p38γ shRNA potently inhibited primary human NPC xenograft growth in nude mice. In p38γ shRNA virus-injected NPC xenograft tissues, p38γ expression, Rb phosphorylation, cyclin E1/A expression and ATP levels were dramatically decreased. Taken together, we conclude that p38γ overexpression is required for NPC cell growth, acting as a promising therapeutic target of NPC.

HIF-1α downregulation of miR-433-3p in adipocyte-derived exosomes contributes to NPC progression via targeting SCD1.

Resident adipocytes under a hypoxic tumor microenvironment exert an increasingly important role in cell growth, proliferation, and invasion in cancers. However, the communication between adipocytes and cancer cells during nasopharyngeal carcinoma (NPC) progression is poorly understood. Here, we demonstrate that hypoxic adipocyte-derived exosomes are key information carriers that transfer low expression of miR-433-3p into NPC cells. In addition, luciferase reporter assays detected that hypoxia inducible factor-1α (HIF-1α) induced miR-433-3p transcription through five binding sites at its promoter region. Concordantly, the low expression of miR-433-3p promoted proliferation, migration, and lipid accumulation in NPC cells via targeting stearoyl-CoA desaturase 1 (SCD1) are suggested by functional studies. Consistent with these findings, in tumor-bearing mice, NPC cells with low HIF-1α expression, high miR-433-3p expression, and low SCD1 expression were equally endowed with remarkably reduced potential of tumorigenesis. Collectively, our study highlights the critical role of the HIF-1α-miR-433-3p-SCD1 axis in NPC progression, which can serve as a mechanism-based potential therapeutic approach.

Generalized Hidden-Mapping Transductive Transfer Learning for Recognition of Epileptic Electroencephalogram Signals.

Electroencephalogram (EEG) signal identification based on intelligent models is an important means in epilepsy detection. In the recognition of epileptic EEG signals, traditional intelligent methods usually assume that the training dataset and testing dataset have the same distribution, and the data available for training are adequate. However, these two conditions cannot always be met in practice, which reduces the ability of the intelligent recognition model obtained in detecting epileptic EEG signals. To overcome this issue, an effective strategy is to introduce transfer learning in the construction of the intelligent models, where knowledge is learned from the related scenes (source domains) to enhance the performance of model trained in the current scene (target domain). Although transfer learning has been used in EEG signal identification, many existing transfer learning techniques are designed only for a specific intelligent model, which limit their applicability to other classical intelligent models. To extend the scope of application, the generalized hidden-mapping transductive learning method is proposed to realize transfer learning for several classical intelligent models, including feedforward neural networks, fuzzy systems, and kernelized linear models. These intelligent models can be trained effectively by the proposed method even though the data available are insufficient for model training, and the generalization abilities of the trained model is also enhanced by transductive learning. A number of experiments are carried out to demonstrate the effectiveness of the proposed method in epileptic EEG recognition. The results show that the method is highly competitive or superior to some existing state-of-the-art methods.

Transductive Joint-Knowledge-Transfer TSK FS for Recognition of Epileptic EEG Signals.

Intelligent recognition of electroencephalogram (EEG) signals is an important means to detect seizure. Traditional methods for recognizing epileptic EEG signals are usually based on two assumptions: 1) adequate training examples are available for model training and 2) the training set and the test set are sampled from data sets with the same distribution. Since seizures occur sporadically, training examples of seizures could be limited. Besides, the training and test sets are usually not sampled from the same distribution for generic non-patient-specific recognition of EEG signals. Hence, the two assumptions in traditional recognition methods could hardly be satisfied in practice, which results in degradation of model performance. Transfer learning is a feasible approach to tackle this issue attributed to its ability to effectively learn the knowledge from the related scenes (source domains) for model training in the current scene (target domain). Among the existing transfer learning methods for epileptic EEG recognition, transductive transfer learning fuzzy systems (TTL-FSs) exhibit distinctive advantages-the interpretability that is important for medical diagnosis and the transfer learning ability that is absent from traditional fuzzy systems. Nevertheless, the transfer learning ability of TTL-FSs is restricted to a certain extent since only the discrepancy in marginal distribution between the training data and test data is considered. In this paper, the enhanced transductive transfer learning Takagi-Sugeno-Kang fuzzy system construction method is proposed to overcome the challenge by introducing two novel transfer learning mechanisms: 1) joint knowledge is adopted to reduce the discrepancy between the two domains and 2) an iterative transfer learning procedure is introduced to enhance transfer learning ability. Extensive experiments have been carried out to evaluate the effectiveness of the proposed method in recognizing epileptic EEG signals on the Bonn and CHB-MIT EEG data sets. The results show that the method is superior to or at least competitive with some of the existing state-of-art methods under the scenario of transfer learning.

TGF-ß1 Promotes Hepatocellular Carcinoma Invasion and Metastasis via ERK Pathway-Mediated FGFR4 Expression.

BACKGROUND/AIMS: TGF-ß1 is beneficial during early liver disease but is tumor-progressive during late stages especially for hepatocellular carcinoma (HCC). Thus, exploring the underlying mechanisms may provide information about a potentially therapeutic role of TGF-ß1 in HCC. METHODS: Western blot and real-time quantitative PCR were used to quantify FGFR4 expression in HCC cell lines and a normal liver cell line. After constructing the best silencing FGFR4 expression vector, migration and invasiveness of TGF-ß1 in HCC was studied in vitro and in vivo. Western blot was used to study the mechanism of TGF-ß1 induction on FGFR4 expression with various inhibitors. RESULTS: HepG2 cell lines had the most FGFR4 expression, and data show that silencing FGFR4 suppressed cell proliferation, invasion and migration in HCC induced by TGF-ß1 in vitro and in vivo. Moreover, TGF-ß1 induced FGFR4 expression through the ERK pathway. CONCLUSION: Promoting FGFR4 expression via the ERK pathway, TGF-ß1 contributes to HCC invasion and metastasis.