mRNA–miRNA bipartite network reconstruction to predict prognostic module biomarkers in colorectal cancer stage differentiation

Abstract

Biomarker detection is one of the most important and challenging problems in cancer studies. Recently, non-coding RNA based biomarkers such as miRNA expression levels have been used for early diagnosis of many cancer types. In this study, a systems biology approach was used to detect novel miRNA based biomarkers for CRC diagnosis in early stages. The mRNA expression data from three CRC stages (Low-grade Intraepithelial Neoplasia (LIN), High-grade Intraepithelial Neoplasia (HIN) and Adenocarcinoma) were used to reconstruct co-expression networks. The networks were clustered to extract co-expression modules and detected low preserved modules among CRC stages. Then, the experimentally validated mRNA-miRNA interaction data were applied to reconstruct three mRNA-miRNA bipartite networks. Twenty miRNAs with the highest degree (hub miRNAs) were selected in each bipartite network to reconstruct three bipartite subnetworks for further analysis. The analysis of these hub miRNAs in the bipartite subnetworks revealed 30 distinct important miRNAs as prognostic markers in CRC stages. There are two novel CRC related miRNAs (hsa-miR-190a-3p and hsa-miR-1277-5p) in these 30 hub miRNAs that have not been previously reported in CRC. Furthermore, a drug-gene interaction network was reconstructed to detect potential candidate drugs for CRC treatment. Our analysis shows that the hub miRNAs in the mRNA-miRNA bipartite network are very essential in CRC progression and should be investigated precisely in future studies. In addition, there are many important target genes in the results that may be critical in CRC progression and can be analyzed as therapeutic targets in future research.

Identification of biomarkers in common chronic lung diseases by co-expression networks and drug-target interactions analysis

“…According to the study by Horvath and Dong (Horvath and Dong 2008), the signed weighted gene co-expression network (WGCN) was firstly constructed considering biweight midcorrelation (Song et al 2012) between the disease-specific DEGs (Huang et al 2017;Chen et al 2017;Motieghader et al 2017). Next, the modules were identified.…”

Circ2Disease: a manually curated database of experimentally validated circRNAs in human disease

“…The miRNA set analysis using TAM tool 37 demonstrated that hsa-miR-20a-5p was significantly enriched in immune system, HIV latency, cell proliferation, angiogenesis and apoptosis. This makes it as an attractive candidate potentially involved in cell signaling and disease 1 . Thus, we searched hsa-miR-20a-5p in circRNA-miRNA-gene network in Circ2Disease.…”

“…Circular RNA (circRNA) is a type of RNA molecule which forms a covalently closed continuous loop by back-splicing or lariat 1 . Although circRNA was discovered decades ago, it was initially perceived as RNA splicing errors 2 .…”

Synthetic Repurposing of Drugs in Hypertension: a Datamining Method Based on Association Rules and a Novel Discrete Algorithm

“…iii) Graph and network theory-based researches: these approaches represents communication among the biological components through a graph or a network [24]. For this purpose, graph algorithms are applied to the generated system [25,26], and hidden interactions are detected [27]. Although these techniques are confronted with minimal validity challenges and produce significant results, they are not applicable to most drug repurposing cases because biological elements follow the hypergraph theory [28,29].…”