Identification the immune related marker genes and transcription-factor network in ruptured cerebral aneurysms using bioinformatics analysis and machine-learning strategies

Abstract

BackgroundAs a high level of mortality and morbidity disease, ruptured cerebral aneurysms (RCA) is the most common cause of intracranial hemorrhage. MethodsThe expression profiles of GSE13353, GSE26969 were downloaded from the Gene Expression Omnibus (GEO) database to obtain differentially expressed genes (DEGs) between RCA and unruptured cerebral aneurysms (URCA). The Least Absolute Shrinkage Selection Operator (LASSO) and the SVM-RFE (SVM-RFE) analysis were used to screen the potential diagnostic genes for RCA, which were further tested in the validation cohort (GSE54083). The TRRUST database was used to predict transcription factors (TF) and the JASPAR database was used to validate the marker genes and STAT1 binding sites. Finally, the CMAP database was used to predict RCA-associated drugs for clinical transformation. ResultsA total of 120 DEGs were identified. The functional enrichment analysis revealed that NF-kappa B signaling pathway, tuberculosis, rheumatoid arthritis were enriched in the RCA group. NANS, NTRK3, OLFML2A were identified as diagnostic biomarkers of RCA. Transcription of all three marker genes is regulated by the predicted transcription factor STAT1, the CMAP database was eventually used to screen 10 most promising drugs for the treatment of RCA. ConclusionNANS, NTRK3, OLFML2A may become new candidate biomarkers of RCA, moreover, STAT1 plays an important role in the development of RCA. The mentioned immune cells may play a key role in the development and progression of RCA. MEK and MAP kinase inhibitors are the most likely drug mechanisms for RCA therapy.