STAT1 and IL-7 as Diagnostic Biomarkers for Ovarian Cancer Subtypes

Transcriptome RNA-seq data for High-Grade and Low-Grade Serous Ovarian Carcinoma from GEO datasets GSE27651 and GSE126132. The dataset was created by Zhuna Wu and last updated on 2026-04-14. It includes results of differential expression analysis, immune cell infiltration estimates, and validation data from independent cohorts.

Use Cases

• Train a binary classifier to distinguish HGSOC from LGSOC based on STAT1 and IL-7 expression levels.
• Analyze correlations between gene expression and tumor-infiltrating immune cell fractions using the CIBERSORT algorithm results.
• Validate potential diagnostic biomarkers for ovarian cancer in independent transcriptomic cohorts.
• Investigate the JAK-STAT and cytokine-cytokine receptor interaction pathways in serous ovarian cancer.

Strengths

• Validation performed in an independent merged cohort of 55 HGSOC and 13 LGSOC samples.
• Biomarker performance quantified with AUC values (e.g., 0.908 for STAT1 in train group).
• Findings supported by immunohistochemistry (IHC) validation showing significant protein expression differences (P < 0.05).

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The clinical utility of the biomarkers requires prospective validation, as noted in the conclusion.

Provenance

Source

GEO database (GSE27651, GSE126132, with validation from GSE14001, GSE73168, GSE146965).

Collection Method

Transcriptome RNA-seq data analysis, differential expression, LASSO and mSVM-RFE feature selection.

Freshness

Last updated 2026-04-14 04:15:01; freshness should be verified.