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Integrated proteomic and transcriptomic profiling of mouse lung development and Nmyc target genes.

ABSTRACT: Although microarray analysis has provided information regarding the dynamics of gene expression during development of the mouse lung, no extensive correlations have been made to the levels of corresponding protein products. Here, we present a global survey of protein expression during mouse lung organogenesis from embryonic day E13.5 until adulthood using gel-free two-dimensional liquid chromatography coupled to shotgun tandem mass spectrometry (MudPIT). Mathematical modeling of the proteomic profiles with parallel DNA microarray data identified large groups of gene products with statistically significant correlation or divergence in coregulation of protein and transcript levels during lung development. We also present an integrative analysis of mRNA and protein expression in Nmyc loss- and gain-of-function mutants. This revealed a set of 90 positively and negatively regulated putative target genes. These targets are evidence that Nmyc is a regulator of genes involved in mRNA processing and a repressor of the imprinted gene Igf2r in the developing lung.

SUBMITTER: Cox B

PROVIDER: S-EPMC2673710 | biostudies-literature | 2007

REPOSITORIES: biostudies-literature

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Integrated proteomic and transcriptomic profiling of mouse lung development and Nmyc target genes.

Cox Brian B Kislinger Thomas T Wigle Dennis A DA Kannan Anitha A Brown Kevin K Okubo Tadashi T Hogan Brigid B Jurisica Igor I Frey Brendan B Rossant Janet J Emili Andrew A

Molecular systems biology 20070508

Although microarray analysis has provided information regarding the dynamics of gene expression during development of the mouse lung, no extensive correlations have been made to the levels of corresponding protein products. Here, we present a global survey of protein expression during mouse lung organogenesis from embryonic day E13.5 until adulthood using gel-free two-dimensional liquid chromatography coupled to shotgun tandem mass spectrometry (MudPIT). Mathematical modeling of the proteomic pr ...[more]

PMID: 17486137

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Project description:Pancreatic cancer (PC) has a dismal prognosis despite advancing scientific and technological knowledge. The exploration of novel genes is critical to improving current therapeutic measures. This research is aimed at selecting hub genes that can act as candidate therapeutic target genes and as prognostic biomarkers in PC. Gene expression profiles of datasets GSE101448, GSE15471, and GSE62452 were extracted from the GEO database. The "limma" package was performed to select differentially expressed genes (DEGs) between PC and normal tissue samples in each dataset. Robust rank aggregation (RRA) algorithm was conducted to integrate multiple expression profiles and identify robust DEGs. GO analysis and KEGG analysis were conducted to identify the functional correlation of the DEGs. The CIBERSORT algorithm was conducted to estimate the immune cell composition of each tissue sample. STRING and Cytoscape were used to establish the protein-protein interaction (PPI) network. The cytoHubba plugin in Cytoscape was performed to identify hub genes. Survival analysis based on hub gene expression was performed with clinical information from TCGA database. 566 robust DEGs (338 upregulated genes and 226 downregulated genes) were identified. Tumor tissue had a higher infiltration of resting dendritic cells and tumor-associated macrophages (TAM), including M0, M1, and M2 macrophages, while infiltration levels of B memory cells, plasma cells, T cells CD8, T follicular helper cells, and NK cells in normal tissue were relatively higher. GO terms and KEGG pathway analysis results revealed enrichment in tumor-associated pathways, including the extracellular matrix organization, cell-substrate adhesion cytokine-cytokine receptor interaction, calcium signaling pathway, and glycine, serine, and threonine metabolism, to name a few. Finally, FN1, MSLN, PLAU, and VCAN were selected as hub genes. High expression of FN1, MSLN, PLAU, and VCAN in PC significantly correlated with poor prognosis. Integrated transcriptomic analysis was used to provide new insights into PC pathogenesis. FN1, MSLN, PLAU, and VCAN may be considered as novel biomarkers of PC.

Project description:BackgroundThe 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.MethodsFor 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.ResultsAt 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.ConclusionsOur 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.

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Integrated proteomic and transcriptomic profiling of mouse lung development and Nmyc target genes.

Publications

Integrated proteomic and transcriptomic profiling of mouse lung development and Nmyc target genes.

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