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At present, scientists have performed numerous studies investigating the morbidity of renal cell carcinoma (RCC) in the genetic and microRNA (miRNA) fields, obtaining a substantial amount of knowledge. However, the experimentally validated data of genes, miRNA and transcription factors (TFs) cannot be found in a unified form, which makes it challenging to decipher the regulatory mechanisms. In the present study, the genes, miRNAs and TFs involved in RCC are regarded as elements in the regulatory network, and the present study therefore focuses on the association between each entity. Three regulatory networks were constructed hierarchically to indicate the regulatory association between the genes, miRNAs and TFs clearly, including the differentially expressed, associated and global networks. All the elements were macroscopically investigated in these networks, instead of only investigating one or several of them. The present study not only compared and analyzed the similarities and the differences between the three networks, but also systematically expounded the pathogenesis of RCC and supplied theoretical foundations for future gene therapy investigations. Following the construction of the three networks, certain important pathways were highlighted. The upstream and downstream element table of differentially expressed genes and miRNAs was listed, in which self-adaption associations and circle-regulations were identified. In future studies, the identified genes and miRNAs should be granted more attention.

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To date, scientists have obtained a substantial amount of knowledge with regard to genes and microRNAs (miRNAs) in pancreatic cancer (PC). However, deciphering the regulatory mechanism of these genes and miRNAs remains difficult. In the present study, three regulatory networks consisting of a differentially-expressed network, a related network and a global network, were constructed in order to identify the mechanisms and certain key miRNA and gene pathways in PC. The interactions between transcription factors (TFs) and miRNAs, miRNAs and target genes and an miRNA and its host gene were investigated. The present study compared and analyzed the similarities and differences between the three networks in order to distinguish the key pathways. Certain pathways involving the differentially-expressed genes and miRNAs demonstrated specific features. TP53 and hsa-miR-125b were observed to form a self-adaptation association. A further 16 significant differentially-expressed miRNAs were obtained and it was observed that an miRNA and its host gene exhibit specific features in PC, for example, hsa-miR-196a-1 and its host gene, HOXB7, form a self-adaptation association. The differentially-expressed network partially illuminated the mechanism of PC. The present study provides comprehensive data that is associated with PC and may aid future studies in obtaining pertinent data results with regards to PC. In the future, an improved understanding of PC may be obtained through an increased knowledge of the occurrence, mechanism, improvement, metastasis and treatment of the disease.

Through years of effort, researchers have made notable progress in gene and microRNA fields about retinoblastoma morbidity. However, experimentally validated data for genes, microRNAs (miRNAs) and transcription factors (TFs) can only be found in a scattered form, which makes it difficult to conclude the relationship between genes and retinoblastoma systematically. In this study, we regarded genes, miRNAs and TFs as elements in the regulatory network and focused on the relationship between pairs of examples. In this way, we paid attention to all the elements macroscopically, instead of only researching one or several. To show regulatory relationships over genes, miRNAs and TFs clearly, we constructed 3 regulatory networks hierarchically, including a differentially expressed network, a related network and a global network, for analysis of similarities and comparison of differences. After construction of the three networks, important pathways were highlighted. We constructed an upstream and downstream element table of differentially expressed genes and miRNAs, in which we found self-adaption relations and circle-regulation. Our study systematically assessed factors in the pathogenesis of retinoblastoma and provided theoretical foundations for gene therapy researchers. In future studies, especial attention should be paid to the highlighted genes and miRNAs.

Abstract. Bladder cancer (BC) is the fifth most common malignancy occurring worldwide and a significant cause of cancer-related morbidity and mortality. Although BC is a serious health issue, studies available concerning the relationship of genes, microRNAs (miRNAs) and their host genes has been lacking. In the present study, we assessed experimentally validated data from various sources that reported the effect of miRNA on various diseases, miRNA targeting of mRNAs, and combined these data with initial transcription factor (TF) binding site predictions within miRNA promoter regions. Topology networks obtained in this study included the differentially expressed, BC-associated and global networks. The three networks may be used to assess the effect of miRNAs and their regulation in human BC. By comparing and analyzing the similarities and differences among the three networks, key nodes with the largest potential of affecting the behavior of a particular network were identified. The results also showed potentially substantially influential miRNAs and TFs, which revealed subnetworks demonstrating the mechanisms involved as well as regulatory miRNA network motifs in human BC. Regulatory pathways regarding differentially expressed elements, such as genes and miRNAs, demonstrate self-adapting associations including, self-adapting associations and feedback loops in genes MYC, TP53, PTEN and 10 differentially expressed miRNAs. The differentially expressed network partially identified the BC mechanism. miRNA-targeted human BC genes were also enriched in highly relevant pathways, cell cycle regulation and apoptosis. The present study systematically delineated the pathogenesis of BC and provided theoretical foundations for gene therapy investigators to focu attention on key genes and miRNAs in future studies.

Over recent years, genes and microRNA (miRNA/miR) have been considered as key biological factors in human carcinogenesis. During cancer development, genes may act as multiple identities, including target genes of miRNA, transcription factors and host genes. The present study concentrated on the regulatory networks consisting of the biological factors involved in cervical cancer in order to investigate their features and affect on this specific pathology. Numerous raw data was collected and organized into purposeful structures, and adaptive procedures were defined for application to the prepared data. The networks were therefore built with the factors as basic components according to their interacting associations. The networks were constructed at three levels of interdependency, including a differentially-expressed network, a related network and a global network. Comparisons and analyses were made at a systematic level rather than from an isolated gene or miRNA. Critical hubs were extracted in the core networks and notable features were discussed, including self-adaption feedback regulation. The present study expounds the pathogenesis from a novel point of view and is proposed to provide inspiration for further investigation and therapy.

Abstract. To date, numerous studies have suggested that microRNAs (miRNAs) and genes play key roles in osteosarcoma (OS); however, the majority of these studies have been conducted with a specific focus on either the genes or the miRNAs, which has made the regulatory mechanisms of OS difficult to decipher. The aim of the present study was to systematically investigate the elements [genes, miRNAs and transcription factors (TFs)] associated with the morbidity of OS and to explore the associations among these elements, instead of focusing on one or several elements. The scattered data were collected from existing studies of OS, and three regulatory networks (abnormally expressed, related and global) were constructed to explore OS at a macroscopic level. The abnormally expressed network showed the numerous incorrect data linkages that are present when OS emerges, making it useful as a map of the faults in OS. In theory, the correction of these errors could lead to the prevention and even cure of the disease. Unlike studies in which cancer networks have been formed based purely on gene data, the present study focused on genes and miRNAs, as well as the associations among them, to form the regulatory networks of OS. The constructed regulatory networks were shown to contain numerous self-adaptation associations, which may aid in the analysis of the pathogenesis of OS. By comparing and analyzing the similarities and differences, a number of important pathways were highlighted. A notable finding was the predicted TFs obtained by the P-Match method, which could be used to further study the pathogenesis of OS. In the present study, the mechanism of OS has been systematically analyzed and a theoretical foundation for the mechanism has been provided, which may assist the development of gene therapy targeting OS.