Analysis the role of VEGFA and COL۴A۱ in signaling pathways associated with Glioblastoma progression: Unraveling LncRNA-miRNA axis as high potential biomarkers
- سال انتشار: 1403
- محل انتشار: دومین کنگره بین المللی کنسرژنومیکس
- کد COI اختصاصی: ICGCS02_037
- زبان مقاله: انگلیسی
- تعداد مشاهده: 155
نویسندگان
Department of Cellular and Molecular Biology, Najafabad Branch, Islamic Azad University, Isfahan, Iran
Department of Cellular and Molecular Biology, Najafabad Branch, Islamic Azad University, Isfahan, Iran
Zist Fanavari Novin Biotechnology Institute, Isfahan, Iran
چکیده
Glioblastoma (GBM), recognized as the most malignant variant of brain cancer, manipulates the intricate interactions between neurons and glial cells to establish a microenvironment conducive to its proliferation while simultaneously undermining the homeostatic excitability of neural networks, thereby obstructing endeavors aimed at attaining sustained clinical remission. Biomarkers, including microRNAs, have the potential to identify the manifestation of this invasive pathology, as well as to aid in the formulation of therapeutic strategies. Method: By using Gene expression omnibus (GEO) database, Three gene expression datasets (GSE۱۰۸۴۷۶, GSE۵۰۱۶۱ and GSE۴۲۹۰) and a miRNA expression dataset (GSE۶۵۶۲۶) and a lncRNA expression dataset (GSE۱۰۰۶۷۵) were selected and downloaded. Three gene expression datasets merged and differentially expressed genes (DEGs) and differentially miRNAs (DEMs) were extracted with R studio. The obtained DEGs were placed in ENRICHR database and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis to extract the signaling pathways related Glioblastoma(GBM). Obtained genes from Signaling pathways were used to extract hub genes via STRING database. MirWALK database was used to identify miRNA interaction and miRNA expression dataset (GSE۶۵۶۲۶) was used as a validation. lncRRIsearch database used to examined lncRNA interactions and lncRNA dataset (GSE۱۰۰۶۷۵) was used as validation. Survival analysis were performed using GEPIA۲ database. Result: A total of ۲۵۶ differentially expressed genes (DEGs) were identified from ۳۹۶ samples, with ۵۲ upregulated and ۲۰۴ downregulated (adj.p-value< ۰> ۱.۵). The ۵۲ upregulated genes were analyzed using ENRICHR and KEGG, revealing three significant signaling pathways (adj.p-value< ۰.۰۵): Relaxin signaling pathway, Focal Adhesion, and PI۳K-Akt signaling pathway. Common genes among these pathways were further analyzed using STRING, identifying six hub genes: VEGFA, COL۱A۲, COL۳A۱, COL۴A۱, COL۴A۲, and FLNA. Among these, VEGFA and COL۴A۱ were determined to be the most influential. Subsequently, VEGFA and COL۴A۱ were analyzed using miRWALK to identify the most relevant miRNAs, resulting in the identification of hsa-miR-۸۷۴-۵p (Energy=-۲۵.۸, position:۳'UTR) and hsa-miR-۴۳۰۶ (Energy= -۲۰.۳, position: ۳'UTR). Validation using differentially expressed miRNAs (DEMs) from GSE۶۵۶۲۶ confirmed these miRNAs. NEAT۱ (Energy= -۷۷۶.۸۹) was identified as a significant lncRNA interacting with VEGFA. Survival analysis indicated that VEGFA and COL۴A۱ had an impact on high expression groups, although the analysis showed no significant impact between high and low expression groups. Conclusion: This study unraveled VEGFA and COL۴A۱ as the main hub genes involved in Relaxin signaling pathway, Focal adhesion, PI۳K-Akt signaling pathways. Moreover further investigation into miRNA interaction revealed hsa-miR-۸۷۴-۵p and has-miR-۴۳۰۶ as significant regulators. NEAT۱ identified as crucial lncRNA interacting with VEGFA. Although survival analysis indicated that the high expression of these two genes had insignificant impact, actually high expression group reduces overall survival. Findings provide robust foundation for future researches into the molecular mechanisms underlying these pathways and potential therapeutic biomarkers.کلیدواژه ها
Glioblastoma, Biomarkers, Systems biology, Bioinformatics, Signaling pathwaysمقالات مرتبط جدید
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