Table 1_A pan-cancer atlas of metabolic regulatory circuitries integrating multi-omic, imm

A pan-cancer atlas integrating transcriptomic, epigenomic, genomic, proteomic, phenotypic, immunological, and clinical data across 33 tumor types. The dataset, created by Higor Almeida Cordeiro Nogueira and last updated in May 2026, contains 463,433 significant associations aggregated into 24,796 metabolic regulatory circuitries. It was constructed using the OncoMetabolismGPS analytical framework to link metabolic programs to tumor phenotypes and immune states.

Use Cases

• Identifying convergent or divergent metabolic regulatory patterns based on the described circuitries and their associations with tumor phenotypes.
• Prioritizing candidate diagnostic markers based on regulatory circuitries linked to clinical outcomes mentioned in the description.
• Analyzing context-dependent metabolic vulnerabilities in cancer based on the multi-layered regulatory architecture described.
• Investigating the role of transcript isoform–level variation and tumor stemness in metabolic regulation, as highlighted in the results.

Strengths

• Integrates data across 33 tumor types, covering a broad cancer spectrum.
• Contains 463,433 significant associations and 24,796 defined regulatory circuitries, providing a structured resource.
• Built using a defined multi-omic analytical framework (OncoMetabolismGPS) integrating seven data dimensions.

Limitations

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

Provenance

Source

figshare

Collection Method

Constructed using the OncoMetabolismGPS analytical framework integrating multi-omic data.

Freshness

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