Understanding the evolution of the drug-resistant state in prostate cancer is particularly challenging given the long natural history of this cancer, its wide range of clinical aggressiveness, and the variability of treatment responses observed among patients. Genomic studies of rapid autopsies have provided critical insights into mechanisms of clonal evolution, treatment resistance, and the contribution of inter- and intrapatient heterogeneity.
In a recent study, Drake et al. delve deeper by studying the phosphoproteomes of castration-resistant prostate cancer samples obtained at rapid autopsy to understand the diversity of activated signaling pathways underlying the lethal form of this disease. The researchers used network-based computational approaches, integrated differential phosphorylation of protein kinases with transcriptome data, and analysis of master regulators and identified several potentially targetable signaling proteins. Although transcriptomic regulators were often consistent (and may even converge) across patients, protein kinase activities varied between patients, potentially contributing to clinical differences.
This study opens several new and exciting questions for further exploration, including: When does activation of these potential upstream events occur? What is their driving role and relationship to androgen signaling, and are they associated with specific genomic subclasses in prostate cancer? These findings also provide a foundation for the design of future studies aimed to target or co-target these networks using clinically relevant models. Overall, this study provides insights and strategies to explore the biology of the prostate cancer lethal phenotype and highlights the feasibility of using clinical tissues to identify phosphoproteomic biomarkers that may improve future patient selection for new and emerging targeted therapies.
J. M. Drake et al., Phosphoproteome integration reveals patient-specific networks in prostate cancer. Cell 166, 1041–1054 (2016). [Abstract]
- Copyright © 2016, American Association for the Advancement of Science