Introduction Prostate cancer (PC) is the most frequently diagnosed cancer among men and the second leading cause of male cancer-related deaths worldwide. The poor prognosis of PC is largely due to late diagnosis of the disease when it has progressed to advanced stages marked by androgen-independence. We construe that these direly needed advances are limited by our poor understanding of early events in the progression of PC and that would thus represent ideal targets for early intervention. To begin to fill this void, we interrogated molecular ‘oncophenotypes’ that embody the transition of PC from an androgen-dependent (AD) to –independent (AI) state. Material and methods We have previously established AD and AI murine PC cell lines, PLum-AD and PLum-AI, respectively, which recapitulate primary and progressive PC morphologically and genetically. We statistically surveyed global gene expression in these cell lines by microarray analysis. Differential profiles were functionally interrogated by pathways, gene set enrichment and topological gene-gene network analyses – features built in the commercially available software Ingenuity Pathways Analysis. Results and discussions Gene expression analysis of PLum-AD and PLum-AI transcriptomes (n=3 each), revealed 723 differentially expressed genes (392 upregulated and 331 downregulated) in PLum-AI compared with PLum-AD cells. Gene set analysis demonstrated enrichment of biological functions and pathways in PLum-AI cells that are central to tumour aggressiveness including epithelial-to-mesenchymal transition (EMT), cell migration, and cell invasion. Further analysis demonstrated that the p38 mitogen activated protein kinase (MAPK) was predicted to be significantly activated in the PLum-AI cells. Conversely, gene sets that previously showed to be associated with favourable response to the p38 inhibitor SB203580 were attenuated in the PLum-AI cells, suggesting that these aggressive cells may be therapeutically vulnerable to p38 inhibition. Network analysis also alluded to activation of other signalling networks particularly those associated with enhanced EMT, inflammation and immune function/response. Conclusion Our pilot genome-wide gene expression analysis of a murine model of PC progression identified molecular oncophenotypes (e.g. inflammation and EMT) that denote this progression and that comprise high-potential targets (e.g. p38) for early treatment of PC. Efforts are underway to functionally assess the potential roles of these genes as therapeutic targets for PC progression.