Integrating differential expression, co-expression and gene network analysis for the identification of common genes associated with tumor angiogenesis deregulation

• Published in: Journal of biomedical informatics 2023-08, Vol.144, p.104421-104421, Article 104421
• Main Authors: Monterde, Beatriz, Rojano, Elena, Córdoba-Caballero, José, Seoane, Pedro, Perkins, James R., Medina, Miguel Ángel, Ranea, Juan A.G.
• Format: Article
• Language: English
• Subjects: Angiogenesis; Gene network analysis; Integrative analysis; RNA-seq; Tumor angiogenesis deregulation
• ISSN: 1532-0464; 1532-0480
• DOI: 10.1016/j.jbi.2023.104421

Angiogenesis is essential for tumor growth and cancer metastasis. Identifying the molecular pathways involved in this process is the first step in the rational design of new therapeutic strategies to improve cancer treatment. In recent years, RNA-seq data analysis has helped to determine the genetic and molecular factors associated with different types of cancer. In this work we performed integrative analysis using RNA-seq data from human umbilical vein endothelial cells (HUVEC) and patients with angiogenesis-dependent diseases to find genes that serve as potential candidates to improve the prognosis of tumor angiogenesis deregulation and understand how this process is orchestrated at the genetic and molecular level. We downloaded four RNA-seq datasets (including cellular models of tumor angiogenesis and ischaemic heart disease) from the Sequence Read Archive. Our integrative analysis includes a first step to determine differentially and co-expressed genes. For this, we used the ExpHunter Suite, an R package that performs differential expression, co-expression and functional analysis of RNA-seq data. We used both differentially and co-expressed genes to explore the human gene interaction network and determine which genes were found in the different datasets that may be key for the angiogenesis deregulation. Finally, we performed drug repositioning analysis to find potential targets related to angiogenesis inhibition. We found that that among the transcriptional alterations identified, SEMA3D and IL33 genes are deregulated in all datasets. Microenvironment remodeling, cell cycle, lipid metabolism and vesicular transport are the main molecular pathways affected. In addition to this, interacting genes are involved in intracellular signaling pathways, especially in immune system and semaphorins, respiratory electron transport and fatty acid metabolism. The methodology presented here can be used for finding common transcriptional alterations in other genetically-based diseases. [Display omitted] •Integrative analysis to identify common genes for pathogenic processes.•Using RNA-seq and gene network data to analyse deregulated angiogenesis.•Identification of SEMA3D and IL33 in all datasets with integrative analysis.•The methodology can be used to analyse other diseases and pathological processes.