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Updated: May 11, 2026

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
Published on: October 3, 2025
Systems analysis of the NCI-60 cancer cell lines by alignment of protein pathway activation modules with "-OMIC" data
Giulia Federici1, Xi Gao, Janusz Slawek
1Department of Hematology, Istituto Superiore di Sanità, Rome, Italy.
Abstract:
The NCI-60 cell line set is likely the most molecularly profiled set of human tumor cell lines in the world. However, a critical missing component of previous analyses has been the inability to place the massive amounts of "-omic" data in the context of functional protein signaling networks, which often contain many of the drug targets for new targeted therapeutics. We used reverse-phase protein array (RPPA) analysis to measure the activation/phosphorylation state of 135 proteins, with a total analysis of nearly 200 key protein isoforms involved in cell proliferation, survival, migration, adhesion, etc., in all 60 cell lines. We aggregated the signaling data into biochemical modules of interconnected kinase substrates for 6 key cancer signaling pathways: AKT, mTOR, EGF receptor (EGFR), insulin-like growth factor-1 receptor (IGF-1R), integrin, and apoptosis signaling. The net activation state of these protein network modules was correlated to available individual protein, phosphoprotein, mutational, metabolomic, miRNA, transcriptional, and drug sensitivity data. Pathway activation mapping identified reproducible and distinct signaling cohorts that transcended organ-type distinctions. Direct correlations with the protein network modules involved largely protein phosphorylation data but we also identified direct correlations of signaling networks with metabolites, miRNA, and DNA data. The integration of protein activation measurements into biochemically interconnected modules provided a novel means to align the functional protein architecture with multiple "-omic" data sets and therapeutic response correlations. This approach may provide a deeper understanding of how cellular biochemistry defines therapeutic response. Such "-omic" portraits could inform rational anticancer agent screenings and drive personalized therapeutic approaches.
Insights
This study maps protein signaling networks in NCI-60 cancer cell lines using reverse-phase protein arrays (RPPA). It integrates omics data to reveal distinct signaling cohorts and inform personalized cancer therapies.
Area of Science:
- Cancer research
- Molecular biology
- Systems biology
Background:
- The NCI-60 cell line set is extensively molecularly profiled.
- Previous analyses lacked integration of omics data with functional protein signaling networks.
- Protein signaling pathways are crucial for targeted therapeutic development.
Purpose of the Study:
- To integrate diverse omics data with functional protein signaling networks in the NCI-60 cell lines.
- To map protein activation states within key cancer signaling pathways.
- To correlate signaling network activity with other molecular data and drug sensitivity.
Main Methods:
- Utilized reverse-phase protein array (RPPA) to measure activation/phosphorylation of 135 proteins (nearly 200 isoforms).
- Aggregated signaling data into biochemical modules for 6 key cancer pathways (AKT, mTOR, EGFR, IGF-1R, integrin, apoptosis).
- Correlated protein network module activation with omics data (mutational, metabolomic, miRNA, transcriptional) and drug sensitivity.
Main Results:
- Identified reproducible and distinct signaling cohorts across cell lines, independent of organ type.
- Established direct correlations between signaling networks and metabolites, miRNA, and DNA data, in addition to phosphorylation data.
- Demonstrated that integrated protein activation measurements align functional protein architecture with omics datasets and therapeutic response.
Conclusions:
- The integration of protein activation into biochemical modules offers a novel approach to understanding cancer signaling.
- This systems biology approach provides a deeper insight into how cellular biochemistry dictates therapeutic response.
- These "omic" portraits can guide anticancer agent screening and advance personalized therapeutic strategies.
