ArticleFrontiers in neurology2022
SAA1 Expression as a Potential Prognostic Marker of the Tumor Microenvironment in Glioblastoma.
Article in Frontiers in neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 13 citations in OpenAlex.
- Identification of immune-related gene signature for predicting prognosis of glioblastoma patients.Translational cancer research · 2026Article
- GLIO-Select: Machine Learning-Based Feature Selection and Weighting of Tissue and Serum Proteomic and Metabolomic Data Uncovers Sex Differences in Glioblastoma.International journal of molecular sciences · 2025Article
- TAF7 directly targets SAA1 to enhance triple-negative breast cancer metastasis via phosphorylating E-cadherin and N-cadherin.iScience · 2025Article
- The prognostic relevance of a gene expression signature in MRI-defined highly vascularized glioblastoma.Heliyon · 2024Article
- Identification of a risk model for prognostic and therapeutic prediction in renal cell carcinoma based on infiltrating M0 cells.Scientific reports · 2024Article
- Necroptosis-related lncRNAs: establishment of a gene module and distinction between the cold and hot tumors in glioma.Frontiers in oncology · 2023Article
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5 authors at 2 institutions in 1 country.
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Abstract
Background: Glioblastoma (GBM) is the most common primary brain malignant tumor, and patients with GBM have a poor prognosis. The tumor microenvironment (TME) is connected to tumorigenesis and prognosis. However, the TME-related genes and therapeutic targets in GBM are yet to be identified. Thus, the presented study aimed to identify TME-related biomarkers in GBM and develop a novel target for the treatment of the disease. Methods: ESTIMATE computational methods were utilized to estimate the amounts of stromal and immune components in 697 patients with glioma from the Cancer Genome Atlas database. Then, the protein-protein interaction network and univariate Cox regression analyzed the differentially expressed genes. Serum amyloid A1 (SAA1) was determined to be a predictive factor. SAA1 expression was statistically significant in GBM compared to the normal samples and other glioma subtypes and negatively associated with survival. Independent prognostic analysis identified SAA1 as a TME-related prognostic factor. Furthermore, Western blot analysis showed that SAA1 is upregulated in GBM, which was confirmed by the external validation in the Chinese Glioma Genome Atlas. The gene set enrichment analysis in GBM revealed enrichment of immune-related activities in the SAA1 high-expression group, while mitosis and cell cycle were enriched in the low-expression group. CIBERSORT analysis of the tumor-infiltrating immune cell proportion revealed that M2 macrophages, neutrophils, activated mast cells, resting mast cells, and regulatory T cells were correlated with SAA1 expression. Finally, immune checkpoint genes, tumor mutation burden, and drug sensitivity were also analyzed between the high- and low-expression groups. Conclusion: SAA1 could be a distinctive gene between GBM and other subtype gliomas, and thus a novel biomarker for estimating the survival and TME status. The altered expression level shifts the primary function of SAA1 from cell cycle and mitosis to immune activity. High expression of SAA1 is associated with poor survival and upregulates the expression of LAIR1 and TNFSF14, thereby deeming it as the drug sensitivity indicator for XAV939, TGX-221, and lapatinib in GBM immune therapy.
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