Data Sheet 1_Histone chaperone-based stratification combined with two-sample Mendelian ran

Data from a 2026 study integrating transcriptomic and clinical data from 184 tumors and 13 normal samples in TCGA-ESCA, plus an external cohort of 119 tumors and 119 normals. The dataset, authored by Bihan Xia and shared on figshare, supports the identification of prognostic biomarkers ADORA2B and SAPCD2 in esophageal cancer using histone chaperone-based stratification and two-sample Mendelian randomization.

Use Cases

• Training prognostic models for esophageal cancer based on histone chaperone-related gene expression.
• Conducting genetic epidemiology studies using Mendelian randomization results for 26 implicated genes.
• Analyzing tumor microenvironment and immune cell deconvolution based on CIBERSORT results mentioned in the description.
• Predicting drug sensitivity (e.g., to vinorelbine, etoposide, paclitaxel) based on gene expression signatures.
• Validating clinicogenomic nomograms for 1-3 year survival prediction with AUCs of 0.67-0.75.

Strengths

• Includes data from two cohorts: TCGA-ESCA (184 tumors, 13 normals) and an external validation cohort (119 tumors, 119 normals).
• Analysis framework incorporates multiple validation steps, including RT-qPCR in paired tissues and a GWAS with 998 cases and 475,308 controls.
• Results are supported by sensitivity analyses and the Steiger directionality test for causal inference.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data may reflect bias inherent to the specific cohorts and European ancestry GWAS used.

Provenance

Source

figshare, author Bihan Xia.

Collection Method

Analysis of RNA-seq and clinical data from TCGA-ESCA and GSE53624, integrated with two-sample Mendelian randomization using eQTL instruments and an EC GWAS.

Time Range

Temporal coverage of the underlying data is not specified.

Freshness

Last updated 2026-04-13 04:31:01; freshness should be verified.

Geography

GWAS data is from European ancestry populations; spatial coverage of clinical cohorts is not specified.