PatientProfiler: building patient-specific signaling models from proteogenomic data.

ABSTRACT: Deciphering patient-specific mechanisms of cancer cell reprogramming remains a crucial challenge in systems oncology, as it is key to improving patient diagnosis and treatment. For this reason, comprehensive and patient-specific multi-omic characterization of tumor specimens has become increasingly common in clinical practice. Here, we developed PatientProfiler, a computational workflow that integrates proteogenomic data with curated causal interaction networks to generate mechanistic models of signal transduction for individual patients. PatientProfiler allows multi-omic data analysis and standardization, generation of patient-specific mechanistic models of signal transduction, and extraction of network-based prognostic biomarkers. We successfully benchmarked the tool on proteogenomic and

SUBMITTER: Lombardi V 

PROVIDER: S-EPMC12672659 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature