Proteomic and transcriptomic profiling of Pten gene-knockout mouse model of prostate cancer

Background: The prostate-specific phosphatase and tensin homolog deleted on chromosome 10 (Pten) gene-conditional knockout (KO) mouse carcinogenesis model is highly desirable for studies of prostate cancer biology and chemoprevention due to its close resemblance of primary molecular defect and many histopathological features of human prostate cancer including androgen response and disease progression from prostatic intraepithelial neoplasia to invasive adenocarcinoma. Here, we profiled the proteome and transcriptome of the Pten-KO mouse prostate tumors for global macromolecular expression alterations for signaling changes and biomarker signatures. Methods: For proteomics, four pairs of whole prostates from tissue-specific conditional knockout Pten-KO mice (12-15 weeks of age) and their respective wild-type littermates housed in the same cages were analyzed by 8-plex isobaric tags for relative and absolute quantitation iTRAQ. For microarray transcriptomic analysis, three additional matched pairs of prostate/tumor specimens from respective mice at 20 to 22 weeks of age were used. Real-time quantitative reverse transcription-polymerase chain reaction was used to verify the trends of protein and RNA expression changes. Gene Set Enrichment Analysis and Ingenuity Pathway Analysis were carried out for bioinformatic characterizations of pathways and networks. Results: At the macromolecular level, proteomic and transcriptomic analyses complement and cross-validate to reveal overexpression signatures including inflammation and immune alterations, in particular, neutrophil/myeloid lineage suppressor cell features, chromatin/histones, ion and nutrient transporters, and select glutathione peroxidases and transferases in Pten-KO prostate tumors. Suppressed expression patterns in the Pten-KO prostate tumors included glandular differentiation such as secretory proteins and androgen receptor targets, smooth muscle features, and endoplasmic reticulum stress proteins. Bioinformatic analyses identified immune and inflammation responses as the most profound macromolecular landscape changes, and the predicted key nodal activities through Akt, nuclear factor-kappaB, and P53 in the Pten-KO prostate tumor. Comparison with other genetically modified mouse prostate carcinogenesis models revealed notable molecular distinctions, especially the dominance of immune and inflammation features in the Pten-KO prostate tumors. Conclusions: Our work identified prominent macromolecular signatures and key nodal molecules that help to illuminate the patho- and immunobiology of Pten-loss driven prostate cancer and can facilitate the choice of biomarkers for chemoprevention and interception studies in this clinically relevant mouse prostate cancer model.