SLC7A11 Pan-Cancer Immunotherapy Biomarker Analysis with TNBC Validation

Pan-cancer analysis revealed SLC7A11 transcriptional expression is upregulated in over 88% of tumor types. This dataset integrates TCGA and GTEx data to analyze SLC7A11 associations with immunotherapy features and includes in vitro validation in triple-negative breast cancer cell models. It was authored by Songchen Zhao and last updated on 2026-05-19.

Use Cases

• Identify potential immunotherapy biomarkers based on SLC7A11 expression associations with tumor mutational burden and PD-L1 expression.
• Analyze gene expression correlations with immune infiltration levels across cancer types.
• Investigate miRNA regulatory networks targeting specific genes in breast cancer pathogenesis.
• Study ferroptosis resistance mechanisms based on glutathione levels and lipid peroxidation data.
• Evaluate survival outcomes in immunotherapy-treated cohorts based on biomarker expression.

Strengths

• Analysis spans multiple cancer types using TCGA and GTEx data.
• Includes experimental validation in two triple-negative breast cancer cell models (MDA-MB-231 and MDA-MB-468).
• Associations with multiple immunotherapy-related features, including tumor mutational burden, microsatellite instability, PD-L1 expression, and immune infiltration, are evaluated.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• In vitro findings require further in vivo validation as noted by the authors.

Provenance

Source

TCGA and GTEx data, plus in vitro experiments.

Collection Method

Systematic analysis of expression data, survival analyses, and experimental validation.

Freshness

Last updated 2026-05-19 05:43:46; freshness should be verified.