Phosphoproteome Integration Reveals Patient-Specific Networks in Prostate Cancer

Abstract

SUMMARY We used clinical tissue from lethal metastatic castration resistant prostate cancer (CRPC) patients obtained at rapid autopsy to evaluate diverse genomic, transcriptomic, and phosphoproteomic datasets for pathway analysis. Using Tied Diffusion through Interacting Events (TieDIE), we integrated differentially expressed master transcriptional regulators, functionally mutated genes, and differentially activated kinases in CRPC tissues to synthesize a robust signaling network consisting of druggable kinase pathways. Using MSigDB hallmark gene sets, six major signaling pathways with phosphorylation of several key residues were significantly enriched in CRPC tumors after incorporation of phosphoproteomic data. Individual autopsy profiles developed using these hallmarks revealed clinically relevant pathway information potentially suitable for patient stratification and targeted therapies in late stage prostate cancer. Here we describe phosphorylation-based cancer hallmarks using integrated personalized signatures (pCHIPS) that sheds light on the diversity of activated signaling pathways in metastatic CRPC while providing an integrative, pathway-based reference for drug prioritization in individual patients.

Phosphotyrosine-based-phosphoproteomics scaled-down to biopsy level for analysis of individual tumor biology and treatment selection

“…On this latter point, kinase-substrate analysis (KSEA) [34] and integrated personalized signatures (pCHIPS) [35] have recently been proposed for kinase pathway activity or drug prioritization, but these methods have not been validated for single clinical samples. Antibody-based protein arrays may provide a more high-throughput alternative phosphoproteomics approach and have shown potential for the identification of treatment targets [36] and patient stratification [37].…”

Precision Oncology: The Road Ahead

“…The proteome represents the ideal readout to define a cell’s functional state in response to internal or external perturbations, and proteogenomic analysis is being integrated in large-scale characterization efforts of the TCGA [195–197]. This integration has the power to nominate driver genes from large chromosomal deletions or amplifications and can identify new driver clusters that are not easily found in transcriptomics signatures [195, 196, 198]. Although TCGA analysis has long included antibody-based phosphoprotein analyses, the comprehensive proteomic characterization based on mass spectrometry increases the breadth of phosphoproteomics data and importantly, allows for the identification of post-translational modifications beyond phosphorylation [199].…”

Complementing genomics and transcriptomics: Phosphoproteomics illuminates systems biology in prostate cancer

“…We observed that the AKT/mTOR/MAPK signaling pathway was significantly enriched in the integrated analysis but only marginally enriched when phosphoproteomic data were excluded. Proteins involved in other cancer hallmarks, including cell cycle pathway, DNA repair pathway, and nuclear receptor pathway, were also enriched when we included the phosphoproteomic input 5 . These results provide compelling evidence for inclusion of the phosphoproteome in the identification of potential therapeutic targets in metastatic CRPC.…”

“…This pathway-based method expands upon heat diffusion strategies, such as the HotNet algorithm, 8 to integrate information from several different sources. We employed TieDIE to integrate our phosphoproteomic data with genomic data, transcriptomic data, and a priori knowledge from pathway databases 5 and generated a cohort-level scaffold network for mCRPC. Importantly, integration of the phosphoproteomic data enhanced, and in some cases validated, the pathway networks provided by genomic or transcriptional analyses.…”