Application of Nonlinear Models Combined with Conventional Laboratory Indicators for the Diagnosis and Differential Diagnosis of Ovarian Cancer.

Existing biomarkers for ovarian cancer lack sensitivity and specificity. We compared the diagnostic efficacy of nonlinear machine learning and linear statistical models for diagnosing ovarian cancer using a combination of conventional laboratory indicators. We divided 901 retrospective samples into an ovarian cancer group and a control group, comprising non-ovarian malignant gynecological tumor (NOMGT), benign gynecological disease (BGD), and healthy control subgroups. Cases were randomly assigned to training and internal validation sets. Two linear (logistic regression (LR) and Fisher's linear discriminant (FLD)) and three nonlinear models (support vector machine (SVM), random forest (RF), and artificial neural network (ANN)) were constructed using 22 conventional laboratory indicators and three demographic characteristics. Model performance was compared. In an independent prospectively recruited validation set, the order of diagnostic efficiency was RF, SVM, ANN, FLD, LR, and carbohydrate antigen 125 (CA125)-only (AUC, accuracy: 0.989, 95.6%; 0.985, 94.4%; 0.974, 93.4%; 0.915, 82.1%; 0.859, 80.1%; and 0.732, 73.0%, respectively). RF maintained satisfactory classification performance for identifying different ovarian cancer stages and for discriminating it from NOMGT-, BGD-, or CA125-positive control. Nonlinear models outperformed linear models, indicating that nonlinear machine learning models can efficiently use conventional laboratory indicators for ovarian cancer diagnosis.

Interleukin-6 and Hypoxia Synergistically Promote EMT-Mediated Invasion in Epithelial Ovarian Cancer via the IL-6/STAT3/HIF-1α Feedback Loop.

Extensive peritoneal spread and capacity for distant metastasis account for the majority of mortality from epithelial ovarian cancer (EOC). Accumulating evidence shows that interleukin-6 (IL-6) promotes tumor invasion and migration in EOC, although the molecular mechanisms remain to be fully elucidated. Meanwhile, the hypoxic microenvironment has been recognized to cause metastasis by triggering epithelial-mesenchymal transition (EMT) in several types of cancers. Here, we studied the synergy between IL-6 and hypoxia in inducing EMT in two EOC cell lines, A2780 cells and SKOV3 cells. Exogenous recombination of IL-6 and autocrine production of IL-6 regulated by plasmids both induced EMT phenotype in EOC cells characterized by downregulated E-cadherin as well as upregulated expression of vimentin and EMT-related transcription factors. The combined effects of IL-6 and hypoxia were more significant than those of either one treatment on EMT. Suppression of hypoxia-inducible factor-1α (HIF-1α) before IL-6 treatment inhibited the EMT phenotype and invasion ability of EOC cells, indicating that HIF-1α occupies a key position in the regulatory pathway of EMT associated with IL-6. EMT score was found positively correlated with mRNA levels of IL-6, signal transducer and activator of transcription 3 (STAT3), and HIF-1α, respectively, in 489 ovarian samples from The Cancer Genome Atlas dataset. Next, blockade of the abovementioned molecules by chemical inhibitors reversed the alteration in the protein levels of EMT markers induced by either exogenous or endogenous IL-6. These findings indicate a positive feedback loop between IL-6 and HIF-1α, and induce and maintain EMT phenotype through STAT3 signaling, which might provide a novel rationale for prognostic prediction and therapeutic targets in EOC.

Surface structure change properties: Auto-soft bionic fibrous membrane in reducing postoperative adhesion.

Peritoneal adhesion is the most common adverse effect following abdominal surgery or inflammation. The occurrence in clinical trials has been successfully reduced using barriers. However, the shortcomings of frequently used adhesion barriers, such as rapid degradation rate of gel barrier and inadequate operation ability of solid barrier, cannot be ignored. In this study, a fibrous membrane with an ECM-like structure was prepared. The adhesion properties were reduced significantly by changing the surface structure. The fibrous membrane caused less inflammatory response and much less peripheral adhesion and intestinal obstruction compared to the casting film and the commercial film with smooth surface, though with the same components. Because of the auto-soft bionic structure and similarity in the mechanical modulus of the tissues, the fibrous membrane was more flexible when it adhered to the tissues, showed excellent effectiveness and biocompatibility. In addition to the rat and miniature pig models, a randomized, placebo-controlled, and multicenter clinical pilot study with 150 patients confirmed that because of its flexibility, biodegradability, and similarity to mechanical modulus and structure with tissues involved, the fibrous membrane served as a favorable implant for preventing post-operation adhesion.

IL-6 promotes nuclear translocation of HIF-1α to aggravate chemoresistance of ovarian cancer cells.

The inflammatory milieu in tumor modulates the resistance to the conventional antitumoral therapies. Interleukin-6 (IL-6), a pleiotropic pro-inflammatory cytokine and a crucial mediator of tumor development, has been targeted as a therapeutic strategy to overcome chemoresistance in the treatment of tumors. The protein levels and nuclear translocation of HIFs (hypoxia-inducible factors), such as HIF-1α, are linked to the drug resistance of tumor cells. However, whether IL-6 promotes the nuclear translocation of HIF-1α and the related mechanism remain to be investigated. We applied two ovarian cancer (OvCa) cell lines, A2780 cells and SKOV3 cells for the in vivo and in vitro studies. We found that IL-6 up-regulates the HIF-1α expression via the signal transducer and activator of transcription 3 (STAT3) signaling under hypoxia in either endogenous or exogenous way, and then we proved that IL-6 enhances the transcriptional activity of HIF-1α via the STAT3 signaling. Further mechanism research revealed that IL-6 promotes the nuclear translocation of HIF-1α through the STAT3 signaling under hypoxia. Proliferation assay and apoptosis assay were applied and proved that IL-6 enhances the chemoresistance of OvCa cells against cisplatin through the upregulation of HIF-1α via the STAT3 signaling in vitro. The In vivo studies confirmed the effect of IL-6 in increasing the chemoresistance of OvCa cells against cisplatin through the IL-6/STAT3/HIF-1α loop in the animal models. Our data elucidates the explicit mechanism of IL-6/STAT3/HIF-1α loop in OvCa and also provides new insights into the development of different approaches for the inflammation-induced and hypoxia-induced resistance in tumor therapies.

A Five-lncRNAs Signature-Derived Risk Score Based on TCGA and CGGA for Glioblastoma: Potential Prospects for Treatment Evaluation and Prognostic Prediction.

Accumulating studies have confirmed the crucial role of long non-coding RNAs (ncRNAs) as favorable biomarkers for cancer diagnosis, therapy, and prognosis prediction. In our recent study, we established a robust model which is based on multi-gene signature to predict the therapeutic efficacy and prognosis in glioblastoma (GBM), based on Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) databases. lncRNA-seq data of GBM from TCGA and CGGA datasets were used to identify differentially expressed genes (DEGs) compared to normal brain tissues. The DEGs were then used for survival analysis by univariate and multivariate COX regression. Then we established a risk score model, depending on the gene signature of multiple survival-associated DEGs. Subsequently, Kaplan-Meier analysis was used for estimating the prognostic and predictive role of the model. Gene set enrichment analysis (GSEA) was applied to investigate the potential pathways associated to high-risk score by the R package "cluster profile" and Wiki-pathway. And five survival associated lncRNAs of GBM were identified: LNC01545, WDR11-AS1, NDUFA6-DT, FRY-AS1, TBX5-AS1. Then the risk score model was established and shows a desirable function for predicting overall survival (OS) in the GBM patients, which means the high-risk score significantly correlated with lower OS both in TCGA and CGGA cohort. GSEA showed that the high-risk score was enriched with PI3K-Akt, VEGFA-VEGFR2, TGF-beta, Notch, T-Cell pathways. Collectively, the five-lncRNAs signature-derived risk score presented satisfactory efficacies in predicting the therapeutic efficacy and prognosis in GBM and will be significant for guiding therapeutic strategies and research direction for GBM.

Establishment of a precise novel brain trauma model in a large animal based on injury of the cerebral motor cortex.

BACKGROUND: Animal models are essential in simulating clinical diseases and facilitating relevant studies. NEW METHOD: We established a precise canine model of traumatic brain injury (TBI) based on cerebral motor cortex injury which was confirmed by neuroimaging, electrophysiology, and a series of motor function assessment methods. Twelve beagles were divided into control, sham, and model groups. The cerebral motor cortex was identified by diffusion tensor imaging (DTI), a simple marker method, and intraoperative electrophysiological measurement. Bony windows were designed by magnetic resonance imaging (MRI) scan and DTI. During the operation, canines in the control group were under general anesthesia. The canines were operated via bony window craniotomy and dura mater opening in the sham group. After opening of the bony window and dura mater, the motor cortex was impacted by a modified electronic cortical contusion impactor (eCCI) in the model group. RESULTS: Postoperative measurements revealed damage to the cerebral motor cortex and functional defects. Comparisons between preoperative and postoperative results demonstrated that the established model was successful. COMPARISON WITH EXISTING METHOD(S): Compared with conventional models, this is the first brain trauma model in large animal that was constructed based on injury to the cerebral motor cortex under the guidance of DTI, a simple marker method, and electrophysiology. CONCLUSION: The method used to establish this model can be standardized to enhance reproducibility and provide a stable and precise large animal model of TBI for clinical and basic research.

Bibliometric analysis of top 100 cited articles in nonalcoholic fatty liver disease research.

AIM: To identify and assess the research situation of top 100 cited articles in nonalcoholic fatty liver disease (NAFLD). METHODS: The global scientific research articles in the Science Citation Index-Expanded relevant to NAFLD were retrieved and listed according to their citation times from the most to the least. The 100 most frequently cited original articles were selected to systematically evaluate their bibliometric parameters including times cited, publication year, journals, subject categories, and the highly related concepts of NAFLD, which reflected the history and current situation, publication distribution of leading countries and institutes as well as the research hotspots of NAFLD. RESULTS: Top 100 cited articles in NAFLD were published from 1965 to 2015 with a citation ranging of 227 to 2151 times since publication, in which the United States was the most predominant country and Mayo Clin was the most productive institution. The majority of the top 100 cited articles were concentrated in SCI subject category of Gastroenterology and Hepatology. Hepatology and Gastroenterology is the top journal that published over half 100 top-cited articles. The significant peak of top cited articles present in the first half of the 2000s while the highest mean number of citation presents in first half of the 1980s. In addition, concepts related to pathology characteristics, epidemiology and medicalization, metabolic syndrome and its combination of symptoms including insulin resistance, biomarkers of lipid metabolism and obesity are listed as the highly related concepts. CONCLUSION: The 100 top-cited articles marked with the leading countries, institutions, journals, hotspots and development trend in NAFLD field that could provide the foundation for further investigations.

Global publication trends and research hotspots of nonalcoholic fatty liver disease: a bibliometric analysis and systematic review.

With the globally increasing prevalence, nonalcoholic fatty liver disease (NAFLD) becomes the predominant cause of chronic liver disease. A global look at the publication trends and the research hotspots of NAFLD are urgently needed to assess the situation of NAFLD research. The global scientific research in the Science Citation Index-Expanded covered articles relevant to NAFLD was retrieved and its bibliometric parameters and research hotspots of NAFLD were systematically evaluated. To sum up, 6356 articles were published in 994 different journals covering 93 SCI subject categories during 1986-2013, in which English was the most predominant language used. Starting from the late 1980s, the publication on NAFLD grew slowly and entered into a highly developing period in the 21st century, especially in the last decade. Besides hepatic steatosis, metabolic syndrome and its combination of symptoms such as obesity, insulin resistance are listed as the top frequent keywords. Bibliometric results suggest that the obviously rapid growth of the articles in recent years appears to be associated with the accelerating incidence of NAFLD and its cofactors such as metabolic syndrome. In addition, epidemiology focusing on comparing different regions and population is attracting ever-growing attention. Meantime, pathology plays an important role in NAFLD research.