Identification of a 3-Gene Prognostic Index for Papillary Thyroid Carcinoma.

The accurate determination of the risk of cancer recurrence is a critical unmet need in managing thyroid cancer (TC). Although numerous studies have successfully demonstrated the use of high throughput molecular diagnostics in TC prediction, it has not been successfully applied in routine clinical use, particularly in Chinese patients. In our study, we objective to screen for characteristic genes specific to PTC and establish an accurate model for diagnosis and prognostic evaluation of PTC. We screen the differentially expressed genes by Python 3.6 in The Cancer Genome Atlas (TCGA) database. We discovered a three-gene signature Gap junction protein beta 4 (GJB4), Ripply transcriptional repressor 3 (RIPPLY3), and Adrenoceptor alpha 1B (ADRA1B) that had a statistically significant difference. Then we used Gene Expression Omnibus (GEO) database to establish a diagnostic and prognostic model to verify the three-gene signature. For experimental validation, immunohistochemistry in tissue microarrays showed that thyroid samples' proteins expressed by this three-gene are differentially expressed. Our protocol discovered a robust three-gene signature that can distinguish prognosis, which will have daily clinical application.

Prioritizing Susceptible Genes for Thyroid Cancer Based on Gene Interaction Network.

Thyroid cancer ranks second in the incidence rate of endocrine malignant cancer. Thyroid cancer is usually asymptomatic at the initial stage, which makes patients easily miss the early treatment time. Combining genetic testing with imaging can greatly improve the diagnostic efficiency of thyroid cancer. Researchers have discovered many genes related to thyroid cancer. However, the effects of these genes on thyroid cancer are different. We hypothesize that there is a stronger interaction between the core genes that cause thyroid cancer. Based on this hypothesis, we constructed an interaction network of thyroid cancer-related genes. We traversed the network through random walks, and sorted thyroid cancer-related genes through ADNN which is fusion of Adaboost and deep neural network (DNN). In addition, we discovered more thyroid cancer-related genes by ADNN. In order to verify the accuracy of ADNN, we conducted a fivefold cross-validation. ADNN achieved AUC of 0.85 and AUPR of 0.81, which are more accurate than other methods.

R-Smad signaling-mediated VEGF expression coordinately regulates endothelial cell differentiation of rat mesenchymal stem cells.

A low-efficiency yield hinders the use of stem cells as a source of endothelial cells (ECs) for therapeutic vascularization, and the diversity of the transforming growth factor-ß (TGF-ß) superfamily has undermined understanding the effects of its potent vascularization-inducing. Herein, we studied the role of the TGF-ß superfamily in EC differentiation of rat bone marrow mesenchymal stem cells (MSCs) induced by Smad2/3 and Smad1/5/8 signaling. MSCs that had been sorted by flow cytometry as CD31-negative were cultured for 14 days in medium supplemented with vascular endothelial growth factor (VEGF) and basic fibroblast growth factor (bFGF) as the control. The Smad2/3 pathway was activated by TGF-ß1 and Smad1/5/8 by bone morphogenetic proteins (BMPs). In the early phase in the Smad2/3-activated group, there were 10% CD31-positive cells, which was significantly higher than in the control group. A low Smad1/5/8 phosphorylation level after BMP4 activation doubled the number of CD31-positive cells, while a higher phosphorylation level after BMP9 activation showed no effect. A Smad2/3 inhibitor initially blocked differentiation but later promoted it, while a Smad1/5/8 inhibitor reversed the induction observed with BMPs. Moreover, the positive effects of R-Smad on differentiation were weakened by the VEGF neutralizing antibody, and a Smad3 inhibitor decreased VEGF expression and blocked differentiation in both the early and late phases. In conclusion, differentiation of ECs from MSCs via Smad2/3 signaling is stage dependent. Activation, particularly by Smad3, significantly promotes differentiation at an early phase but later is suppressive. A low Smad1/5/8 phosphorylation level has a positive effect, and R-Smad effects are partly mediated by VEGF.

[Fabrication of tissue engineered vein containing valve scaffolds].

OBJECTIVE: To fabricate porous biodegradable tissue engineered vein containing valve scaffolds. METHODS: Based on the self-made cast, the tissue engineered vein containing valve scaffolds was fabricated by injection molding plus thermally induced phase separation. Poly (lactic-co-glycolic acid) (PLGA, LA/GA mole ratio 75:25) was used as matrices. Morphological structures and biocompatibility of scaffolds were tested. Cell seeding on scaffold was performed and the mechanic characteristics of cellular constructs evaluated. RESULTS: The scaffold had an inner diameter of 9 mm with a wall thickness of 0.9 mm and the thickness of valves was (0.32 ± 0.04) mm. Scanning electron microscopic (SEM) micrographs showed regular ladder-like porous structures and the average pore size and porosity of scaffolds were 10 - 20 µm and 90%. The PLGA scaffolds were biocompatible. The cellular constructs were tested in vitro, and the valve leaflets were functionally capable of opening and closing when stimulated. CONCLUSION: Based on the self-made cast, the tissue engineered vein containing valve scaffolds can be fabricated by injection molding plus thermally induced phase separation. Further researches are warranted.