{"title":"Glioma Stem Cells: GPRC5A as a Novel Predictive Biomarker and Therapeutic Target Associated with Mesenchymal and Stemness Features","authors":"Sara Sadat Aghamiri, Rada Amin","doi":"10.3390/app14188482","DOIUrl":null,"url":null,"abstract":"Glioblastoma multiforme (GBM) represents the deadliest form of brain cancer, characterized by complex interactions within its microenvironment. Despite the understanding of GBM biology, GBM remains highly resistant to any therapy. Therefore, defining innovative biomarkers in GBM can provide insights into tumor biology and potential therapeutic targets. In this study, we explored the potential of GPRC5A to serve as a pertinent biomarker for GBM. We utilized the GBM-TCGA dataset and presented the reproducible bioinformatics analysis for our results. We identified that GPRC5A expression was significantly upregulated in GBM compared to normal tissues, with higher levels correlating with poor overall survival (OS) and progression-free interval (PFI). Moreover, it was associated with key genetic mutations, particularly NF1 and PTEN mutations, and strongly correlated with the mesenchymal stem-like phenotype. GPRC5A was also predominantly associated with aggressive GBM features, including hypoxia, high extracellular matrix (ECM) environments, and extensive stromal and immune infiltrations. Its strong correlation with mesenchymal markers and hypoxic regions underscores its potential as a biomarker and therapeutic target in GBM. These findings provide valuable insights into the role of GPRC5A in GBM pathology and its potential impact as a target for GBM stratifications and treatment strategies.","PeriodicalId":8224,"journal":{"name":"Applied Sciences","volume":"26 1","pages":"8482"},"PeriodicalIF":0.0000,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/app14188482","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Mathematics","Score":null,"Total":0}
引用次数: 0
Abstract
Glioblastoma multiforme (GBM) represents the deadliest form of brain cancer, characterized by complex interactions within its microenvironment. Despite the understanding of GBM biology, GBM remains highly resistant to any therapy. Therefore, defining innovative biomarkers in GBM can provide insights into tumor biology and potential therapeutic targets. In this study, we explored the potential of GPRC5A to serve as a pertinent biomarker for GBM. We utilized the GBM-TCGA dataset and presented the reproducible bioinformatics analysis for our results. We identified that GPRC5A expression was significantly upregulated in GBM compared to normal tissues, with higher levels correlating with poor overall survival (OS) and progression-free interval (PFI). Moreover, it was associated with key genetic mutations, particularly NF1 and PTEN mutations, and strongly correlated with the mesenchymal stem-like phenotype. GPRC5A was also predominantly associated with aggressive GBM features, including hypoxia, high extracellular matrix (ECM) environments, and extensive stromal and immune infiltrations. Its strong correlation with mesenchymal markers and hypoxic regions underscores its potential as a biomarker and therapeutic target in GBM. These findings provide valuable insights into the role of GPRC5A in GBM pathology and its potential impact as a target for GBM stratifications and treatment strategies.
期刊介绍:
APPS is an international journal. APPS covers a wide spectrum of pure and applied mathematics in science and technology, promoting especially papers presented at Carpato-Balkan meetings. The Editorial Board of APPS takes a very active role in selecting and refereeing papers, ensuring the best quality of contemporary mathematics and its applications. APPS is abstracted in Zentralblatt für Mathematik. The APPS journal uses Double blind peer review.