Prostate cancer is a clinically and biologically heterogeneous disease. Deregulation of splice variants has been shown to contribute significantly to this complexity. High-throughput technologies such as oligonucleotide microarrays allow for the detection of transcripts that play a role in disease progression in a transcriptome-wide level. In this study, we use a publicly available dataset of normal adjacent, primary tumor, and metastatic prostate cancer samples (GSE21034) to detect differentially expressed coding and non-coding transcripts between these disease states. To achieve this, we focus on transcript-specific probe selection regions, that is, those probe sets that correspond unambiguously to a single transcript. Based on this, we are able to pinpoint at the transcript-specific level transcripts that are differentially expressed throughout prostate cancer progression. We confirm previously reported cases and find novel transcripts for which no prior implication in prostate cancer progression has been made. Furthermore, we show that transcript-specific differential expression has unique prognostic potential and provides a clinically significant source of biomarker signatures for prostate cancer risk stratification. The results presented here serve as a catalog of differentially expressed transcript-specific markers throughout prostate cancer progression that can be used as basis for further development and translation into the clinic.