Glioma SLC1A3 Expression and Tumor Microenvironment Data

A 54.0 KB Excel file from figshare, last updated in April 2026, presents data from a study on glioblastoma. The research, led by Hao Lin, integrated RNA-seq and scRNA-seq analysis to identify SLC1A3 as a key gene in tumor progression and immunosuppression. The dataset likely contains results from multi-omics re-analysis, pseudotime trajectory mapping, and in vitro validation assays.

Use Cases

• Validate SLC1A3 gene expression correlations with clinical prognosis based on TCGA cohort analysis mentioned in the description.
• Analyze tumor-endothelial cell communication networks based on the ligand-receptor axes (e.g., TNC-ITGB1, PTN-SDC3) identified in the interactome analysis.
• Investigate the transcriptional reprogramming of glioma-initiating cells based on the alternative splicing and RNA-seq data described.
• Model the impact of SLC1A3 on immune-suppressive factors like CD274 and TGFB1 using the in silico knockout results from the Geneformer foundation model.

Strengths

• Data is derived from patient-derived GIC cohorts and validated across clinical TCGA cohorts.
• Analysis integrates multiple methodologies, including RNA-seq, scRNA-seq pseudotime, and AI-driven in silico perturbation with Geneformer.
• Findings are supported by functional validation using in vitro co-culture and T cell activation assays.

Limitations

• The dataset is small at 54.0 KB, suggesting limited scope or summary-level data.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for large-scale analyses.

Provenance

Source

figshare, author Hao Lin.

Collection Method

Integrated RNA-seq and alternative splicing analysis of neural stem cells and patient-derived glioma-initiating cells, scRNA-seq pseudotime analysis, and in vitro co-culture assays.

Freshness

Last updated 2026-04-23 05:35:43; freshness should be verified.