Unlocking the power of cross-species genomic analyses: identification of evolutionarily conserved breast cancer networks and validation of preclinical models
ABSTRACT The application of high-throughput genomic technologies has revealed that individual breast tumors display a variety of molecular features that require more personalized approaches to treatment. Several recent studies have demonstrated that a cross-species analytic approach provides a powerful means to filter through genetic complexity by identifying evolutionarily conserved genetic networks that are fundamental to the oncogenic process. Mouse-human tumor comparisons will provide insights into cellular origins of tumor subtypes, define interactive oncogenetic networks, identify potential novel therapeutic targets, and further validate as well as guide the selection of genetically engineered mouse models for preclinical testing.
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ABSTRACT: Predicting molecular responses in human by extrapolating results from model organisms requires a precise understanding of the architecture and regulation of biological mechanisms across species. Here, we present a large-scale comparative analysis of organ and tissue transcriptomes involving the three mammalian species human, mouse and rat. To this end, we created a unique, highly standardized compendium of tissue expression. Representative tissue specific datasets were aggregated from more than 33,900 Affymetrix expression microarrays. For each organism, we created two expression datasets covering over 55 distinct tissue types with curated data from two independent microarray platforms. Principal component analysis (PCA) revealed that the tissue-specific architecture of transcriptomes is highly conserved between human, mouse and rat. Moreover, tissues with related biological function clustered tightly together, even if the underlying data originated from different labs and experimental settings. Overall, the expression variance caused by tissue type was approximately 10 times higher than the variance caused by perturbations or diseases, except for a subset of cancers and chemicals. Pairs of gene orthologs exhibited higher expression correlation between mouse and rat than with human. Finally, we show evidence that tissue expression profiles, if combined with sequence similarity, can improve the correct assignment of functionally related homologs across species. The results demonstrate that tissue-specific regulation is the main determinant of transcriptome composition and is highly conserved across mammalian species.BMC Genomics 10/2013; 14(1):716. DOI:10.1186/1471-2164-14-716 · 4.04 Impact Factor
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ABSTRACT: Human prostate cancer (PCa) is known to harbor recurrent genomic aberrations consisting of chromosomal losses, gains, rearrangements and mutations that involve oncogenes and tumor suppressors. Genetically engineered mouse (GEM) models have been constructed to assess the causal role of these putative oncogenic events and provide molecular insight into disease pathogenesis. While GEM models generally initiate neoplasia by manipulating a single gene, expression profiles of GEM tumors typically comprise hundreds of transcript alterations. It is unclear whether these transcriptional changes represent the pleiotropic effects of single oncogenes, and/or cooperating genomic or epigenomic events. Therefore, it was determined if structural chromosomal alterations occur in GEM models of PCa and whether the changes are concordant with human carcinomas. Whole genome array-based comparative genomic hybridization (CGH) was used to identify somatic chromosomal copy number aberrations (SCNAs) in the widely used TRAMP, Hi-Myc, Pten-null and LADY GEM models. Interestingly, very few SCNAs were identified and the genomic architecture of Hi-Myc, Pten-null and LADY tumors were essentially identical to the germline. TRAMP neuroendocrine carcinomas contained SCNAs, which comprised three recurrent aberrations including a single copy loss of chromosome 19 (encoding Pten). In contrast, cell lines derived from the TRAMP, Hi-Myc, and Pten-null tumors were notable for numerous SCNAs that included copy gains of chromosome 15 (encoding Myc) and losses of chromosome 11 (encoding p53). Implications: Chromosomal alterations are not a prerequisite for tumor formation in GEM prostate cancer models and cooperating events do not naturally occur by mechanisms that recapitulate changes in genomic integrity as observed in human prostate cancer.Molecular Cancer Research 10/2014; 13(2). DOI:10.1158/1541-7786.MCR-14-0262 · 4.50 Impact Factor
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ABSTRACT: IntroductionAlthough aberrant tyrosine kinase signaling characterizes particular breast cancer subtypes, a global analysis of tyrosine phosphorylation in mouse models of breast cancer has not been undertaken. This may identify conserved oncogenic pathways and potential therapeutic targets.Methods We applied an immunoaffinity/mass spectrometry workflow to three mouse models; murine stem cell virus (MSCV)-Neu, expressing truncated Neu, the rat orthologue of human epidermal growth factor receptor 2, Her2 (HER2); mouse mammary tumour virus (MMTV)- polyoma virus middle-T-antigen (PyMT) (PyMT); and the p53 -/- transplant model (p53). Pathways and protein-protein interaction networks were identified by bioinformatics. Molecular mechanisms underpinning differences in tyrosine phosphorylation were characterized by Western blotting and array comparative genomic hybridization. The functional role of Mesenchymal epithelial transition factor (Met) in a subset of p53-null tumours was interrogated using a selective tyrosine kinase inhibitor (TKI), small interfering (si)RNA-mediated knockdown and cell proliferation assays.ResultsThe three models could be distinguished based on tyrosine phosphorylation signatures and signaling networks. HER2 tumours exhibited a protein-protein interaction network centred on avian erythroblastic leukemia viral oncogene homolog 2 (Erbb2), epidermal growth factor receptor (Egfr) and platelet-derived growth factor receptor alpha (PDGFRa) and displayed enhanced tyrosine phosphorylation of ERBB receptor feedback inhibitor 1 (Errfi1). In contrast, the PyMT network displayed significant enrichment for components of the phosphatidylinositol-3-kinase signaling pathway, whilst p53 tumours exhibited increased tyrosine phosphorylation of Met and components or regulators of the cytoskeleton, and shared signaling network characteristics with basal and claudin-low breast cancer cells. A subset of p53 tumours displayed markedly elevated cellular tyrosine phosphorylation and Met expression, and Met gene amplification. Treatment of cultured p53-null cells exhibiting Met amplification with a selective Met TKI abrogated aberrant tyrosine phosphorylation and blocked cell proliferation. The effects on proliferation were re-capitulated when Met was knocked down using siRNA. Additional subtypes of p53 tumours exhibited increased tyrosine phosphorylation of other oncogenes, including Peak1/SgK269 and Prex2.Conclusion This study provides network-level insights into signaling in these breast cancer models and demonstrates that comparative phosphoproteomics can identify conserved oncogenic signaling pathways. The Met-amplified, p53-null tumours provide a new pre-clinical model for a subset of triple-negative breast cancers.Breast cancer research: BCR 09/2014; 16(5):437. DOI:10.1186/s13058-014-0437-3 · 5.88 Impact Factor