ssMutPA: single-sample mutation-based pathway analysis approach for cancer precision medicine.

Area of Science:

• Oncology
• Bioinformatics
• Computational Biology

Background:

• Single-sample pathway enrichment analysis is vital for identifying cancer subtypes and biomarkers in precision medicine.
• Current methods primarily focus on gene expression, overlooking the critical role of somatic mutations in cancer development.

Purpose of the Study:

• To develop a novel single-sample mutation-based pathway analysis approach (ssMutPA).
• To infer individualized pathway activities by integrating somatic mutation data and protein-protein interaction networks.
• To complement existing gene expression-focused pathway analysis methods for precision medicine.

Main Methods:

• ssMutPA evaluates gene effects from mutations using local and global weighted strategies based on network topology.
• It calculates a single-sample mutation-based pathway enrichment score (ssMutPES) for each pathway.
• The approach integrates somatic mutation data with protein-protein interaction networks.

Main Results:

• ssMutPA was applied to 33 cancer cohorts from The Cancer Genome Atlas, revealing patient stratification with distinct prognoses.
• Characteristic pathways identified showed significant overlap across cancers, suggesting potential as prognosis biomarkers.
• Application to melanoma cohorts identified patient subgroups likely to benefit from immunotherapy.

Conclusions:

• ssMutPA successfully infers mutation-based individualized pathway activity profiles.
• The method complements existing gene expression-based analyses, enhancing precision medicine development.
• The ssMutPA tool is publicly available for research use.