Data Sheet 1_A pan-cancer atlas of metabolic regulatory circuitries integrating multi-omic

463,433 significant associations were identified across 33 tumor types, yielding 24,796 metabolic regulatory circuitries. This atlas was constructed by Higor Almeida Cordeiro Nogueira using the OncoMetabolismGPS framework, integrating transcriptomic, epigenomic, genomic, proteomic, phenotypic, immunological, and clinical data. The resource was last updated on 2026-05-26.

Use Cases

• Identify metabolic regulatory modules linked to specific tumor phenotypes based on integrated multi-omic signatures.
• Investigate context-dependent metabolic vulnerabilities in cancer based on divergent and convergent regulatory circuitries.
• Prioritize candidate diagnostic markers based on associations between metabolic programs and clinical outcomes.
• Analyze the relationship between tumor stemness, transcript isoform variation, and immune microenvironment states.

Strengths

• Integrates data across 33 tumor types, providing broad cancer coverage.
• Identified 463,433 significant associations and 24,796 regulatory circuitries, indicating a detailed analytical scope.
• Framework integrates seven distinct data types: transcriptomic, epigenomic, genomic, proteomic, phenotypic, immunological, and clinical.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is provided as a 3.7 MB DOCX file, which may require format conversion for computational analysis.

Provenance

Source

figshare

Collection Method

Constructed using the OncoMetabolismGPS multi-omic analytical framework.

Freshness

Last updated 2026-05-26 04:41:12; freshness should be verified.