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Unlocking the power of cross-species genomic analyses: identification of evolutionarily conserved breast cancer networks and validation of preclinical models

Laboratory of Cancer Biology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA.
Breast cancer research: BCR (Impact Factor: 5.88). 10/2008; 10(5):213. DOI: 10.1186/bcr2125
Source: PubMed

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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Available from: Jeffrey E Green, Aug 30, 2015
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    • "On the sequence level, the conservation of protein sequence between species has been extensively studied. A more recent development has been the study of genomic alterations, some of which appear to be highly relevant in translational efforts from model organisms to human [1]. For example, several genetic mutations in acute promyelocytic leukemia have been shown to be conserved between human and mouse and are expected to be relevant for the disease [2]. "
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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.
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    • "Secondly and most importantly, tumors from the rat model recapitulate the immunophenotypes of triple negative (ER–, PR–, Her2–) or Her2-positive cancers observed in sub-sets of human breast cancers. Although several GEM models including the Brca +/− , p53 +/− , Brca co/co , MMTV-Cre/p53 −/− , and some chemically induced tumor models display basal-type characteristics and certain molecular features similar to the human basal-type, triple-negative tumors (Bennett and Green 2008; Deeb et al. 2007; Herschkowitz et al. 2007; Xu et al. 1999), the C3(1)/Tag mouse mammary cancer model was identified as having the strongest molecular relationships to human basal-type, triple-negative breast cancer (Deeb et al. 2007; Herschkowitz et al. 2007). Although expression profiling could not be performed on the rat tumors, it seems likely that they share similar molecular signatures of the triplenegative tumors as documented for the mouse model. "
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    • "Comparative genomic approaches have shown promise to highlight mouse models reliably mirroring the corresponding human disease [34], [35] and to unravel evolutionarily conserved and important genes [36]. A pertinent question is whether the differential gene expression patterns between the Gprc5a−/− adenocarcinoma MDA-F471 cells and the normal lung Gprc5a−/−cells are relevant to human lung carcinogenesis. "
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