MSCP: Mass Spectrometry-Detected Cancer Proteins from 27 Proteomics Sources

Mass Spectrometric Detected Cancer Proteins (MSCP) is an integrated database assembled from 27 large-scale cancer proteomics sources. The resource contains a unified catalog of 15,964 MS-supported human proteins, harmonized to UniProtKB-Swiss-Prot, and was created by Yuanyu Huang, last updated in May 2026.

Use Cases

• Benchmarking cancer-context protein detection against reference proteomes based on the integrated FDR-controlled catalog.
• Planning downstream assays based on cohort- and model-specific protein coverage queries.
• Enriching functional interpretation of cancer pathways using the newly identified protein set linked to GO and Reactome terms.
• Verifying protein identifications orthogonally using synthetic unique peptide patterns described in the resource.

Strengths

• Integrated data from 27 distinct large-scale cancer proteomics sources, providing broad evidence aggregation.
• Catalog of 15,964 human proteins with provenance-aware, UniProtKB-aligned harmonization.
• Identified 525 proteins newly supported by MS evidence in a cancer context, expanding known proteome coverage.

Limitations

• Dataset scale is very small (9.3 KB), suggesting it is likely a metadata summary or index rather than the full underlying protein data.
• Column-level documentation is absent; field semantics and the complete data structure must be inferred after download.
• Row count is unknown, which may limit suitability assessment for large-scale computational tasks.

Provenance

Source

27 large-scale cancer proteomics sources spanning human tumor cohorts, cancer cell lines, and patient-derived xenograft (PDX) models.

Collection Method

Protein identifications harmonized to UniProtKB-Swiss-Prot (release 2025_01) and integrated under FDR-controlled identification outputs.

Time Range

Temporal coverage of the source studies is not specified.

Freshness

Last updated 2026-05-01 14:34:49

Geography

Spatial coverage is not specified; sources likely include global research cohorts.