Abstract
BackgroundRecently, erdafitinib (Balversa), the first targeted therapy drug for genetic alteration, was approved to metastatic urothelial carcinoma. Cancer genomics research has been greatly encouraged. Currently, a large number of gene regulatory networks between different states have been constructed, which can reveal the difference states of genes. However, they have not been applied to the subtypes of Muscle-invasive bladder cancer (MIBC).ResultsIn this paper, we propose a method that construct gene regulatory networks under different molecular subtypes of MIBC, and analyse the regulatory differences between different molecular subtypes. Through differential expression analysis and the differential network analysis of the top 100 differential genes in the network, we find that SERPINI1, NOTUM, FGFR1 and other genes have significant differences in expression and regulatory relationship between MIBC subtypes.ConclusionsFurthermore, pathway enrichment analysis and differential network analysis demonstrate that Neuroactive ligand-receptor interaction and Cytokine-cytokine receptor interaction are significantly enriched pathways, and the genes contained in them are significant diversity in the subtypes of bladder cancer.
Highlights
Erdafitinib (Balversa), the first targeted therapy drug for genetic alteration, was approved to metastatic urothelial carcinoma
Gene regulatory network is a kind of biological network that expresses complex regulatory relationships between genes,and is meaningful in medical diagnosis, treatment, and drug design [1]
A gene regulatory network model with the known real expression data is established to be well consistent with the real data, so as to the potential regulatory relationship can be inferred
Summary
Erdafitinib (Balversa), the first targeted therapy drug for genetic alteration, was approved to metastatic urothelial carcinoma. A large number of gene regulatory networks between different states have been constructed, which can reveal the difference states of genes. They have not been applied to the subtypes of Muscle-invasive bladder cancer (MIBC). Gaussian Graphical Models (GGMs) are widely used in estimating GRNs [2] It assumes that the gene expression measurements follow a multivariate. The precision matrix or inverse covariance matrix can reflect the conditional dependence between genes. This method belongs to the “reverse engineering” problem of gene regulatory network. Reverse engineering is one of the important methods for constructing gene regulatory networks
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