ABSTRACT
Ovarian carcinomas (OCs) represent a heterogeneous group of neoplasms consisting of several entities with pathogenesis, molecular profiles, multiple risk factors, and outcomes. OC has been regarded as the most lethal cancer among women all around the world. There are at least five main types of OCs classified by the fifth edition of the World Health Organization of tumors: high-/low-grade serous carcinoma, mucinous carcinoma, clear cell carcinoma, and endometrioid carcinoma. With the improved knowledge of genome-wide association study (GWAS) and expression quantitative trait locus (eQTL) analyses, the knowledge of genomic landscape of complex diseases has been uncovered in large measure. Moreover, pathway analyses also play an important role in exploring the underlying mechanism of complex diseases by providing curated pathway models and information about molecular dynamics and cellular processes. To investigate OCs deeper, we introduced a novel disease susceptible gene prediction method, XGBG, which could be used in identifying OC-related genes based on different omics data and deep learning methods. We first employed the graph convolutional network (GCN) to reconstruct the gene features based on both gene feature and network topological structure. Then, a boosting method is utilized to predict OC susceptible genes. As a result, our model achieved a high AUC of 0.7541 and an AUPR of 0.8051, which indicates the effectiveness of the XGPG. Based on the newly predicted OC susceptible genes, we gathered and researched related literatures to provide strong support to the results, which may help in understanding the pathogenesis and mechanisms of the disease.
ABSTRACT
OBJECTIVE: To observe the effects of collagen-coating, epidermal growth factor (EGF), Bromodeoxyuridine (BrdU) on growth and function of neonatal ventricular cardiomyocytes in transcatheter closure device patches in vitro. METHODS: Neonatal ventricular cardiomyocytes were cultured with transcatheter closure device patches (1 cm x 2 cm) coated with or without collagen and treated with 10% FBS (control), EGF (20 ng/ml), BrdU (0.1 mmol/L), respectively. In vitro ventricular cardiomyocytes growth and function as well as IGF-I content were determined. RESULTS: (1) The beginning time of ventricular cardiomyocytes beating on patches was similar in collagen-coated and uncoated patches treated with PBS, EGF or BrdU, respectively (P > 0.05). The cell beating time was significantly earlier in Brdu group than in PBS and EGF groups (all P < 0.05). (2) Time of cultured cell covering on patches was significantly earlier in coated patches than those uncoated patches in PBS, EGF and BrdU treated groups (all P < 0.05). The ventricular cardiomyocytes covering time on patches was significantly earlier in EGF group than that in PBS and BrdU groups (all P < 0.05). (3) Ventricular cardiomyocytes types survived on patches included endothelial cells, fibroblasts and myocytes. The highest content of endothelial cells was evidenced in EGF group and the highest content of fibroblasts was found in Brdu group. Myocytes content was similar between PBS and BrdU groups (P > 0.05) and significantly higher than that in EGF group (all P < 0.05). (4) IGF-I peaked at the seventh culture day in all groups (all P < 0.01). CONCLUSIONS: Ventricular cardiomyocytes covering on patches could be enhanced by collagen coating. EGF could promote endothelial cells growth while Brdu could stimulate fibroblasts growth on patches.