Cancer of the prostate (CaP) is the most common malignancy diagnosed in men in the Western society. During the last years, prostate specific antigen (PSA) has been used as a biomarker for CaP, although a high PSA value is not specific for CaP. Thus, there is an urgent need for new and improved diagnostic markers for CaP. In this thesis, the aim was to find a miRNA signature for diagnosis of CaP and to elucidate if differences in behavior between transition zone and peripheral zone tumors are reflected in miRNA expression. One of the major findings is anexpression signature based on nine miRNAs that with high accuracy (85%) could classify normal and malignant tissues from the transition zone of the prostate. The results furthermore show that the major differences in miRNA expression are found between normal and malignant tissues, rather than between the different zones. In addition, tumors arising in the peripheral zone have fewer changes in miRNA expression compared to tumors in the transition zone, indicating that the peripheral zone is more prone to tumor development compared to the transition zone of the prostate. A crucial step in pre-processing of expression data, in order to differentiate true biological changes, is the normalization step. Therefore, an additional aim of this thesis was to compare different normalization methods for qPCR array data in miRNA expression experiments. The results show that data-driven methods based on quantile normalization performs the best. The results also show that in smaller miRNA expression studies, only investigating a few miRNAs, RNU24 is the most suitable endogenous control gene for normalization. Taken together, the results in this thesis show the importance of miRNAs and the possibility of their future use as biomarkers in the field of prostate cancer.