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Identification of putative biomarkers for Infantile Hemangiomas and Propranolol treatment via data integration.

ABSTRACT: Infantile hemangiomas (IHs) are the most common benign tumors in early childhood. They show a distinctive mechanism of tumor growth in which a rapid proliferative phase is followed by a regression phase (involution). Propranolol is an approved treatment for IHs, but its mechanism of action remains unclear. We integrated and harmonized microRNA and mRNA transcriptome data from newly generated microarray data on IHs with publicly available data on toxicological transcriptomics from propranolol exposure, and with microRNA data from IHs and propranolol exposure. We identified subsets of putative biomarkers for proliferation and involution as well as a small set of putative biomarkers for propranolol's mechanism of action for IHs, namely EPAS1, LASP1, SLC25A23, MYO1B, and ALDH1A1. Based on our integrative data approach and confirmatory experiments, we concluded that hypoxia in IHs is regulated by EPAS1 (HIF-2?) instead of HIF-1?, and also that propranolol-induced apoptosis in endothelial cells may occur via mitochondrial stress.

SUBMITTER: Gomez-Acevedo H

PROVIDER: S-EPMC7039967 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Identification of putative biomarkers for Infantile Hemangiomas and Propranolol treatment via data integration.

Gomez-Acevedo Horacio H Dai Yuemeng Y Strub Graham G Shawber Carrie C Wu June K JK Richter Gresham T GT

Scientific reports 20200224 1

Infantile hemangiomas (IHs) are the most common benign tumors in early childhood. They show a distinctive mechanism of tumor growth in which a rapid proliferative phase is followed by a regression phase (involution). Propranolol is an approved treatment for IHs, but its mechanism of action remains unclear. We integrated and harmonized microRNA and mRNA transcriptome data from newly generated microarray data on IHs with publicly available data on toxicological transcriptomics from propranolol exp ...[more]

PMID: 32094357

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Project description:BackgroundInfantile Hemangiomas (IHs) are common benign vascular tumors of infancy that may have serious consequences. The research on diagnostic markers for IHs is scarce.MethodsThe "limma" R package was applied to identify differentially expressed genes (DEGs) in developing IHs. Plugin ClueGO in Cytoscape software performed functional enrichment of DEGs. The Search Tool for Retrieving Interacting Genes (STRING) database was utilized to construct the PPI network. The least absolute shrinkage and selection operator (LASSO) regression model and support vector machine recursive feature elimination (SVM-RFE) analysis were used to identify diagnostic genes for IHs. The receiver operating characteristic (ROC) curve evaluated diagnostic genes' discriminatory ability. Single-gene based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) was conducted by Gene Set Enrichment Analysis (GSEA). The chemicals related to the diagnostic genes were excavated by the Comparative Toxicogenomics Database (CTD). Finally, the online website Network Analyst was used to predict the transcription factors targeting the diagnostic genes.ResultsA total of 205 DEGs were singled out from IHs samples of 6-, 12-, and 24-month-old infants. These genes principally participated in vasculogenesis and development-related, endothelial cell-related biological processes. Then we mined 127 interacting proteins and created a network with 127 nodes and 251 edges. Furthermore, LASSO and SVM-RRF algorithms identified five diagnostic genes, namely, TMEM2, GUCY1A2, ISL1, WARS, and STEAP4. ROC curve analysis results indicated that the diagnostic genes had a powerful ability to distinguish IHs samples from normal samples. Next, the results of GSEA for a single gene illustrated that all five diagnostic genes inhibited the "valine, leucine, and isoleucine degradation" pathway in the development of IHs. WARS, TMEM2, and STEAP4 activated the "blood vessel development" and "vasculature development" in IHs. Subsequently, inhibitors targeting TMEM2, GUCY1A2, ISL1, and STEAP4 were mined. Finally, 14 transcription factors regulating GUCY1A2, 14 transcription factors regulating STEAP4, and 26 transcription factors regulating ISL1 were predicted.ConclusionThis study identified five diagnostic markers for IHs and further explored the mechanisms and targeting drugs, providing a basis for diagnosing and treating IHs.

Dataset Information

Identification of putative biomarkers for Infantile Hemangiomas and Propranolol treatment via data integration.

Publications

Identification of putative biomarkers for Infantile Hemangiomas and Propranolol treatment via data integration.

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