Cancer Biomarker Correlations with Drug Response and Adjusted P-Values

A dataset by Ginte Kutkaite containing cancer-type-specific correlations between the expression of candidate biomarkers SLFN11, ERBB2, IVL, BID, SPRY4, NES, and MAOB and drug response. The data is available as an 8.7 MB XLSX file, last updated on May 11, 2026, and is shared under a CC-BY-4.0 license.

Use Cases

• Identifying potential biomarkers for drug sensitivity based on gene expression correlations.
• Validating candidate genes like SLFN11 and ERBB2 as predictors of therapeutic response.
• Performing meta-analysis across cancer types using correlation data with adjusted p-values.

Strengths

• Includes adjusted p-values for statistical rigor.
• Focuses on seven specific candidate biomarkers (SLFN11, ERBB2, IVL, BID, SPRY4, NES, MAOB).
• Provides cancer-type-specific analysis.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The 8.7 MB file size suggests a relatively small dataset.

Provenance

Source

figshare

Freshness

Last updated 2026-05-11 17:32:58; freshness should be verified.