Thymic Tumor Genomic Landscape from a Meta-Analysis of 729 Patients

A unified dataset of somatic mutations from 729 patients across twenty studies, created via systematic meta-analysis. The data identifies three molecular subgroups of thymic epithelial tumors with distinct biological and clinical features. The dataset was authored by Eleonora Pardini and last updated in March 2026.

Use Cases

• Classifying thymic tumor molecular subgroups based on GTF2I and TP53 mutation status.
• Analyzing mutational burden and signature differences across identified subgroups.
• Investigating convergent oncogenic hubs and signaling pathway dependencies mentioned in the results.
• Training models to predict clinical behavior (indolent vs. aggressive) from genomic alterations.

Strengths

• Integrates data from 729 patients, addressing limitations of small sample sizes mentioned in the introduction.
• Derived from a systematic meta-analysis of twenty studies, providing a unified view.
• Identifies three distinct molecular subgroups with clear biological and clinical correlates.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for specific modeling tasks.

Provenance

Source

figshare, authored by Eleonora Pardini.

Collection Method

Systematic meta-analysis integrating single-variant data from twenty published studies.

Time Range

null

Freshness

Last updated 2026-03-18 07:46:24; freshness should be verified.

Geography

null