Prostate cancer (PCa) is one of the leading types of cancer in men. Although the diagnosis of this disease is currently quite effective, there is still a need to search for noninvasive diagnostic and monitoring methods. Consequently, identifying the mechanisms underlying the development and progression of PCa is crucial. It has been confirmed that the hallmarks of PCa include changes in metabolism, particularly that of fatty acids. Therefore, the application of lipidomics with an accurate histopathological assessment can provide the necessary information and reveal the metabolites that are characteristic of the disease. The use of formalin-fixed, paraffin-embedded (FFPE) tissue samples as an alternative matrix in retrospective research makes this approach highly innovative. The main goal of this study was to perform an untargeted lipidomic analysis of FFPE PCa tissue samples (n = 52) using gas chromatography coupled with mass spectrometry (GC-MS), in comparison to controls (n = 50). To our knowledge, this study is the first to simultaneously conduct a metabolic analysis and histopathological assessment. In the latter, the samples were evaluated based on Gleason grading score and pTNM stage. The obtained results were evaluated by univariate (Student’s t-test or Mann-Whitney U-test) as well as multivariate statistical analysis (principal component analysis, partial least squares-discriminant analysis, variable importance into projection, and selectivity ratio) in order to select the metabolites with the most discriminative power. Additionally, the correlation between the level of metabolites and pathological characteristics was determined. The results of the analyses confirmed the changes in the lipid metabolism pathway in PCa. It can be assumed that PCa is linked with elevated de novo biosynthesis of steroid hormone-related fatty acids and beta-oxidation of fatty acids. An increased level of three fatty acids, namely 9-octadecanoic acid, 9,12-octadecadienoic acid, and 5, 8, 1,14-eicosatetraenoic acid, was observed in the PCa samples. These fatty acids were assigned as metabolites with the best discriminative power for the two tested groups. In practice, these compounds could be considered as specific biochemical factors that may be implemented in the diagnosis of PCa, but their significance should be validated on a more extensive set of samples. Undoubtedly, these results are valuable as they provide important information on prostate cancerogenesis in the context of a metabolic switch.