Bioinformatics analyses of publicly available NEPCa datasets.

Gene expression profiles are valuable resources for the identification of key players that driver disease progression. However, neuroendocrine prostate cancer (NEPCa) specimens are rare, limiting research on this aggressive disease. In this study, we generated a 12-gene signature of NEPCa and used this signature to differentiate NEPCa from prostate adenocarcinoma (AdPCa) samples in publicly available datasets. From these samples, we identified genes that were differentially expressed in NEPCa and AdPCa. Gene ontology and network analyses revealed key players in the pathogenesis of NEPCa, including E2Fs, members of MHC class II, and factors involved in neuron differentiation, neurogenesis, and stem cell signaling. In conclusion, we identified a 12-gene signature of NEPCa and found pathways that are important for the pathologic development of NEPCa.