Prostate cancer (PCa) is a major public health issue in industrialized countries, mainly because of patients’ relapse by castration-refractory disease after androgen ablation. PCa progresses through a series of clinical states characterized by the extent of the disease, the hormonal status (castration-sensitive or castration-resistant) and the presence or absence of metastases. Progression to castration-resistant prostate cancer (CRPCa) involves several mechanisms such as ligand-independent androgen receptor activation and adaptive up-regulation of anti-apoptotic genes. CRPCa is highly aggressive and incurable, jeopardizing the patient’s quality of life and lifespan. Identifying the molecular events responsible for the progression to CRPCa is essential to avoid its development and design specific therapies. Despite the existing treatment guidelines for PCa and novel clinical trials for CRPCa, major challenges still remain for identifying specific CRPCa biomarkers and therapeutic targets for effective tailored therapy design for these patients. In this context, molecular profiling of human PCa may importantly contribute to the identification of new disease-specific biomarkers in order to improve PCa early diagnosis, prognosis and disease course and to predict strategies that help develop novel therapies. System-wide approaches such as transcriptomics and proteomics are nowadays applied to monitor molecular variations at the cellular level. Proteomics approaches offer a great potential for the discovery of novel biomarkers and the identification of new therapeutic agents by accurate quantification of proteins. Several studies have been published in the past where different proteomics approaches were used to identify PCa proteome. In the present study we analyzed the PCa proteome from several PCa cell lines representing different hormonal status of the disease to identify potential biomarkers differentially expressed in CRPCa.