Sai Krishna A.V.S. , Swati Sinha , Manchanahalli R. Satyanarayana Rao , Sainitin Donakonda
{"title":"PTEN 状态对多形性胶质母细胞瘤的影响:胶质细胞类型特异性研究确定了独特的预后标志物。","authors":"Sai Krishna A.V.S. , Swati Sinha , Manchanahalli R. Satyanarayana Rao , Sainitin Donakonda","doi":"10.1016/j.compbiomed.2024.109395","DOIUrl":null,"url":null,"abstract":"<div><div>Glioblastoma multiforme (GBM) is the most invasive form of brain tumor, accounting for 5 % of the cases per 100,000 people in various countries. The phosphatase and tensin homolog deleted from chromosome 10 (PTEN) is a well-known tumor suppressor, and its alteration leads to a deleterious effect on GBM progression. The molecular mechanism of tumorigenesis in glial cell types, driven by PTEN status, is yet to be elucidated. In this study, we analyzed publicly available single-cell transcriptome profiles of PTEN wild-type (WT) and NULL GBM patients. We compared them with normal brain data to uncover many unique gene sets influenced by PTEN status. The co-expression network analysis of differentially expressed genes (DEGs) between normal brain and PTEN (WT and NULL) identified highly interconnected genes. The weighted gene co-expression network analysis (WGCNA), based on the DESeq2 algorithm, identified glial cell-type-specific modules in PTEN status-dependent bulk RNA expression profiles. We overlapped network module gene sets from single-cell and bulk transcriptome profiles, and shared genes were considered for further analysis. The hallmark pathway enrichment analysis of the genes unique to PTEN-WT and NULL revealed various tumor growth-related pathways across the glial cell types. Further characterization of PTEN-WT and PTEN-NULL networks belonging to the single-cell and bulk RNA datasets revealed that PTEN status influences the network modules in astrocytes, microglia, and oligodendrocyte precursor cells. An integrated influence value algorithm identified hub genes for each glial cell type. The prognostic analysis identified clinically relevant hub genes specific to the cell type in PTEN-WT: <em>GLIPR2</em> (astrocytes), <em>CFH</em>, <em>IL32</em>, <em>MXRA5</em> (microglia), and PTEN-NULL: <em>ID1</em> (astrocytes) and <em>LAT2</em> (microglia). Our glial cell type-level transcriptome analysis unearthed unique molecular pathways and prognostic markers in PTEN status-dependent GBM patients.</div></div>","PeriodicalId":10578,"journal":{"name":"Computers in biology and medicine","volume":"184 ","pages":"Article 109395"},"PeriodicalIF":7.0000,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The impact of PTEN status on glioblastoma multiforme: A glial cell type-specific study identifies unique prognostic markers\",\"authors\":\"Sai Krishna A.V.S. , Swati Sinha , Manchanahalli R. Satyanarayana Rao , Sainitin Donakonda\",\"doi\":\"10.1016/j.compbiomed.2024.109395\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Glioblastoma multiforme (GBM) is the most invasive form of brain tumor, accounting for 5 % of the cases per 100,000 people in various countries. The phosphatase and tensin homolog deleted from chromosome 10 (PTEN) is a well-known tumor suppressor, and its alteration leads to a deleterious effect on GBM progression. The molecular mechanism of tumorigenesis in glial cell types, driven by PTEN status, is yet to be elucidated. In this study, we analyzed publicly available single-cell transcriptome profiles of PTEN wild-type (WT) and NULL GBM patients. We compared them with normal brain data to uncover many unique gene sets influenced by PTEN status. The co-expression network analysis of differentially expressed genes (DEGs) between normal brain and PTEN (WT and NULL) identified highly interconnected genes. The weighted gene co-expression network analysis (WGCNA), based on the DESeq2 algorithm, identified glial cell-type-specific modules in PTEN status-dependent bulk RNA expression profiles. We overlapped network module gene sets from single-cell and bulk transcriptome profiles, and shared genes were considered for further analysis. The hallmark pathway enrichment analysis of the genes unique to PTEN-WT and NULL revealed various tumor growth-related pathways across the glial cell types. Further characterization of PTEN-WT and PTEN-NULL networks belonging to the single-cell and bulk RNA datasets revealed that PTEN status influences the network modules in astrocytes, microglia, and oligodendrocyte precursor cells. An integrated influence value algorithm identified hub genes for each glial cell type. The prognostic analysis identified clinically relevant hub genes specific to the cell type in PTEN-WT: <em>GLIPR2</em> (astrocytes), <em>CFH</em>, <em>IL32</em>, <em>MXRA5</em> (microglia), and PTEN-NULL: <em>ID1</em> (astrocytes) and <em>LAT2</em> (microglia). Our glial cell type-level transcriptome analysis unearthed unique molecular pathways and prognostic markers in PTEN status-dependent GBM patients.</div></div>\",\"PeriodicalId\":10578,\"journal\":{\"name\":\"Computers in biology and medicine\",\"volume\":\"184 \",\"pages\":\"Article 109395\"},\"PeriodicalIF\":7.0000,\"publicationDate\":\"2024-11-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers in biology and medicine\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S001048252401480X\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers in biology and medicine","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S001048252401480X","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOLOGY","Score":null,"Total":0}
The impact of PTEN status on glioblastoma multiforme: A glial cell type-specific study identifies unique prognostic markers
Glioblastoma multiforme (GBM) is the most invasive form of brain tumor, accounting for 5 % of the cases per 100,000 people in various countries. The phosphatase and tensin homolog deleted from chromosome 10 (PTEN) is a well-known tumor suppressor, and its alteration leads to a deleterious effect on GBM progression. The molecular mechanism of tumorigenesis in glial cell types, driven by PTEN status, is yet to be elucidated. In this study, we analyzed publicly available single-cell transcriptome profiles of PTEN wild-type (WT) and NULL GBM patients. We compared them with normal brain data to uncover many unique gene sets influenced by PTEN status. The co-expression network analysis of differentially expressed genes (DEGs) between normal brain and PTEN (WT and NULL) identified highly interconnected genes. The weighted gene co-expression network analysis (WGCNA), based on the DESeq2 algorithm, identified glial cell-type-specific modules in PTEN status-dependent bulk RNA expression profiles. We overlapped network module gene sets from single-cell and bulk transcriptome profiles, and shared genes were considered for further analysis. The hallmark pathway enrichment analysis of the genes unique to PTEN-WT and NULL revealed various tumor growth-related pathways across the glial cell types. Further characterization of PTEN-WT and PTEN-NULL networks belonging to the single-cell and bulk RNA datasets revealed that PTEN status influences the network modules in astrocytes, microglia, and oligodendrocyte precursor cells. An integrated influence value algorithm identified hub genes for each glial cell type. The prognostic analysis identified clinically relevant hub genes specific to the cell type in PTEN-WT: GLIPR2 (astrocytes), CFH, IL32, MXRA5 (microglia), and PTEN-NULL: ID1 (astrocytes) and LAT2 (microglia). Our glial cell type-level transcriptome analysis unearthed unique molecular pathways and prognostic markers in PTEN status-dependent GBM patients.
期刊介绍:
Computers in Biology and Medicine is an international forum for sharing groundbreaking advancements in the use of computers in bioscience and medicine. This journal serves as a medium for communicating essential research, instruction, ideas, and information regarding the rapidly evolving field of computer applications in these domains. By encouraging the exchange of knowledge, we aim to facilitate progress and innovation in the utilization of computers in biology and medicine.