Identification of critical biomarkers and immune landscape patterns in glioma based on multi-database
Abstract Purpose Glioma is the most prevalent tumor of the central nervous system. The poor clinical outcomes and limited therapeutic efficacy underscore the urgent need for early diagnosis and an optimized prognostic approach for glioma. Therefore, the aim of this study was to identify sensitive bi...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-01-01
|
| Series: | Discover Oncology |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s12672-024-01653-2 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832594624677412864 |
|---|---|
| author | Hanzhang Yuan Jingsheng Cheng Jun Xia Zeng Yang Lixin Xu |
| author_facet | Hanzhang Yuan Jingsheng Cheng Jun Xia Zeng Yang Lixin Xu |
| author_sort | Hanzhang Yuan |
| collection | DOAJ |
| description | Abstract Purpose Glioma is the most prevalent tumor of the central nervous system. The poor clinical outcomes and limited therapeutic efficacy underscore the urgent need for early diagnosis and an optimized prognostic approach for glioma. Therefore, the aim of this study was to identify sensitive biomarkers for glioma. Patients and methods Differentially expressed genes (DEGs) of glioma were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The potential biomarkers were identified using weighted gene co-expression network analysis (WGCNA) and least absolute shrinkage and selection operator (LASSO) regression. The prognostic ability of the potential biomarkers was evaluated by Cox regression and survival curve. CellMiner was used to access the correlation between the expression of potential biomarkers and anticancer drug sensitivity. We then explored the association of potential biomarkers and tumor immune infiltration by single-sample GSEA (ssGSEA) and CIBERSORT. Immune staining in glioma patient samples and cell experiments of potential biomarkers further verified their expression and function. Results Ultimately, we identified three potential biomarkers: SLC8A2, ATP2B3, and SRCIN1. These 3 genes were found significantly correlated with clinicopathological features (age, WHO grade, IDH mutation status, 1p19q codeletion status). Furthermore, the overall survival (OS), disease-specific survival (DSS), and progression-free survival (PFS) were found to be positively correlated with high expression of these 3 potential biomarkers. Besides, there was a substantial relationship between the sensitivity of anticancer drugs and these biomarkers expression. More importantly, the negative association between the 3 genes with most tumor immune cells was also established. Moreover, the decreased expression of the biomarkers was also verified in glioma patient samples. Finally, we confirmed that these 3 genes might promotes glioma proliferation and migration in vitro. Conclusion SLC8A2, ATP2B3, and SRCIN1 were identified as underlying biomarkers for glioma associated with prognosis assessments and personal immunotherapy. Graphical Abstract |
| format | Article |
| id | doaj-art-6bd1fe51d854425b8d408726207c2ae2 |
| institution | Kabale University |
| issn | 2730-6011 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Springer |
| record_format | Article |
| series | Discover Oncology |
| spelling | doaj-art-6bd1fe51d854425b8d408726207c2ae22025-01-19T12:29:11ZengSpringerDiscover Oncology2730-60112025-01-0116112210.1007/s12672-024-01653-2Identification of critical biomarkers and immune landscape patterns in glioma based on multi-databaseHanzhang Yuan0Jingsheng Cheng1Jun Xia2Zeng Yang3Lixin Xu4Department of Neurosurgery, Yueyang Central HospitalDepartment of Neurosurgery, Changde Hospital, Xiangya School of Medicine, Central South University (The First People’s Hospital of Changde City)Department of Neurosurgery, Changde Hospital, Xiangya School of Medicine, Central South University (The First People’s Hospital of Changde City)Department of Neurosurgery, Changde Hospital, Xiangya School of Medicine, Central South University (The First People’s Hospital of Changde City)Department of Neurosurgery, Changde Hospital, Xiangya School of Medicine, Central South University (The First People’s Hospital of Changde City)Abstract Purpose Glioma is the most prevalent tumor of the central nervous system. The poor clinical outcomes and limited therapeutic efficacy underscore the urgent need for early diagnosis and an optimized prognostic approach for glioma. Therefore, the aim of this study was to identify sensitive biomarkers for glioma. Patients and methods Differentially expressed genes (DEGs) of glioma were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The potential biomarkers were identified using weighted gene co-expression network analysis (WGCNA) and least absolute shrinkage and selection operator (LASSO) regression. The prognostic ability of the potential biomarkers was evaluated by Cox regression and survival curve. CellMiner was used to access the correlation between the expression of potential biomarkers and anticancer drug sensitivity. We then explored the association of potential biomarkers and tumor immune infiltration by single-sample GSEA (ssGSEA) and CIBERSORT. Immune staining in glioma patient samples and cell experiments of potential biomarkers further verified their expression and function. Results Ultimately, we identified three potential biomarkers: SLC8A2, ATP2B3, and SRCIN1. These 3 genes were found significantly correlated with clinicopathological features (age, WHO grade, IDH mutation status, 1p19q codeletion status). Furthermore, the overall survival (OS), disease-specific survival (DSS), and progression-free survival (PFS) were found to be positively correlated with high expression of these 3 potential biomarkers. Besides, there was a substantial relationship between the sensitivity of anticancer drugs and these biomarkers expression. More importantly, the negative association between the 3 genes with most tumor immune cells was also established. Moreover, the decreased expression of the biomarkers was also verified in glioma patient samples. Finally, we confirmed that these 3 genes might promotes glioma proliferation and migration in vitro. Conclusion SLC8A2, ATP2B3, and SRCIN1 were identified as underlying biomarkers for glioma associated with prognosis assessments and personal immunotherapy. Graphical Abstracthttps://doi.org/10.1007/s12672-024-01653-2GliomaBiomarkerHub genesPrognosisAnticancer agentsImmune infiltration |
| spellingShingle | Hanzhang Yuan Jingsheng Cheng Jun Xia Zeng Yang Lixin Xu Identification of critical biomarkers and immune landscape patterns in glioma based on multi-database Discover Oncology Glioma Biomarker Hub genes Prognosis Anticancer agents Immune infiltration |
| title | Identification of critical biomarkers and immune landscape patterns in glioma based on multi-database |
| title_full | Identification of critical biomarkers and immune landscape patterns in glioma based on multi-database |
| title_fullStr | Identification of critical biomarkers and immune landscape patterns in glioma based on multi-database |
| title_full_unstemmed | Identification of critical biomarkers and immune landscape patterns in glioma based on multi-database |
| title_short | Identification of critical biomarkers and immune landscape patterns in glioma based on multi-database |
| title_sort | identification of critical biomarkers and immune landscape patterns in glioma based on multi database |
| topic | Glioma Biomarker Hub genes Prognosis Anticancer agents Immune infiltration |
| url | https://doi.org/10.1007/s12672-024-01653-2 |
| work_keys_str_mv | AT hanzhangyuan identificationofcriticalbiomarkersandimmunelandscapepatternsingliomabasedonmultidatabase AT jingshengcheng identificationofcriticalbiomarkersandimmunelandscapepatternsingliomabasedonmultidatabase AT junxia identificationofcriticalbiomarkersandimmunelandscapepatternsingliomabasedonmultidatabase AT zengyang identificationofcriticalbiomarkersandimmunelandscapepatternsingliomabasedonmultidatabase AT lixinxu identificationofcriticalbiomarkersandimmunelandscapepatternsingliomabasedonmultidatabase |