Abstract 5249: Integrative analysis of transcriptomic, proteomic, and metabolomic data of <i>Pten</i>-knockout carcinogenic mouse prostate
Authors: Jinhui Zhang, Li Li, Sangyub Kim, LeeAnn Higgins, Yibin Deng, Christopher J. Kemp, Cheng Jiang, Junxuan Lu
Journal: Cancer Research (2017)

Abstract The prostate-specific Pten-knockout (KO) mouse carcinogenesis model is highly desirable for prostate cancer chemoprevention studies due to its close resemblance of many histopathological features of human prostate cancer including disease progression from prostatic intraepithelial neoplasia (PIN) to invasive adenocarcinomas. Here, we profiled the prostate proteome, transcriptome and aqueous metabolome of Pten-KO mice to identify reference molecular signatures that can be used for designing chemopreventive and/or therapeutic intervention and for selection of molecular biomarkers of responses to intervention. For proteomics, 4 pairs of whole prostates from Pten-KO mice (12-15 weeks of age, corresponding to high grade PIN) and their wild type littermate housed in same cages were obtained from the NCI Mouse Model Repository and analyzed by 8-plex iTRAQTM. For transcriptomic/microarray and metabolomic analyses, 3 additional matched pairs of prostate/tumor specimens at older age (22-20 weeks) were used. Proteomic and transcriptomic analyses using manual annotation methods with references from PubMed revealed top signatures that were up- and down-regulated by Pten deletion, particularly those implicated in immune function, inflammatory response, cancer, drug metabolism, cellular functions, prostate functions, and endoplasmic stress regulation. Similar to the manual annotation approach, each network analysis of 203 genes and 22 proteins (≥ 2- fold changes) by a bioinformatics software, Ingenuity Pathway Analysis (IPA) showed that inflammatory response, cellular movement, immune cell trafficking, immunological disease, and cancer were top 5 disease and biological functions in Pten-KO mice. Using references from PubMed, we manually assigned the unmapped prostate metabolites to functional categories, which included altered methionine-cysteine cycle fluxes and purine metabolites, increased nucleotide pools, cholesterol and polyamine synthesis and suppressed pools of sugar and choline derivatives, glycolysis intermediates, and purine bases. IPA network analysis of 25 metabolites (≥ 2- fold changes) revealed the biological functions related to molecular transport, amino acid metabolism, and small molecule biochemistry. In addition, we integrated transcriptomic, proteomic, and metabolomic data sets to identify latent biological relationships and to gain a comprehensive understanding of Pten-deficient prostate carcinogenesis. The integrative analysis predicted activation of inflammatory response and several central signaling nodes, such as IRF7, NF-κB, and IL-6. Collectively, the integrative analyses identify both active and latent reference molecular signatures and provide more insight into Pten-deficient prostate cancer than single omic approaches. Citation Format: Jinhui Zhang, Li Li, Sangyub Kim, LeeAnn Higgins, Yibin Deng, Christopher J. Kemp, Cheng Jiang, Junxuan Lu. Integrative analysis of transcriptomic, proteomic, and metabolomic data of Pten-knockout carcinogenic mouse prostate [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5249. doi:10.1158/1538-7445.AM2017-5249