Computational expression deconvolution in a complex mammalian organ

BACKGROUND: Microarray expression profiling has been widely used to identify differentially expressed genes in complex cellular systems. However, while such methods can be used to directly infer intracellular regulation within homogeneous cell populations, interpretation of in vivo gene expression data derived from complex organs composed of multiple cell types is more problematic. Specifically, observed changes in gene expression may be due either to changes in gene regulation within a given cell type or to changes in the relative abundance of expressing cell types. Consequently, bona fide changes in intrinsic gene regulation may be either mimicked or masked by changes in the relative proportion of different cell types. To date, few analytical approaches have addressed this problem. RESULTS: We have chosen to apply a computational method for deconvoluting gene expression profiles derived from intact tissues by using reference expression data for purified populations of the constituent cell types of the mammary gland. These data were used to estimate changes in the relative proportions of different cell types during murine mammary gland development and Ras-induced mammary tumorigenesis. These computational estimates of changing compartment sizes were then used to enrich lists of differentially expressed genes for transcripts that change as a function of intrinsic intracellular regulation rather than shifts in the relative abundance of expressing cell types. Using this approach, we have demonstrated that adjusting mammary gene expression profiles for changes in three principal compartments – epithelium, white adipose tissue, and brown adipose tissue – is sufficient both to reduce false-positive changes in gene expression due solely to changes in compartment sizes and to reduce false-negative changes by unmasking genuine alterations in gene expression that were otherwise obscured by changes in compartment sizes. CONCLUSION: By adjusting gene expression values for changes in the sizes of cell type-specific compartments, this computational deconvolution method has the potential to increase both the sensitivity and specificity of differential gene expression experiments performed on complex tissues. Given the necessity for understanding complex biological processes such as development and carcinogenesis within the context of intact tissues, this approach offers substantial utility and should be broadly applicable to identifying gene expression changes in tissues composed of multiple cell types

Genomic analysis of early murine mammary gland development using novel probe-level algorithms

We describe a novel algorithm (ChipStat) for detecting gene-expression changes utilizing probe-level comparisons of replicate Affymetrix oligonucleotide microarray data. A combined detection approach is shown to yield greater sensitivity than a number of widely used methodologies including SAM, dChip and logit-T. Using this approach, we identify alterations in functional pathways during murine neonatal-pubertal mammary development that include the coordinate upregulation of major urinary proteins and the downregulation of loci exhibiting reciprocal imprinting

Human CCAAT-binding proteins have heterologous subunits

We have characterized three distinct proteins present in HeLa cell extracts that specifically recognize different subsets of transcriptional elements containing the pentanucleotide sequence CCAAT. One of these CCAAT-binding proteins, CP1, binds with high affinity to CCAAT elements present in the human a-globin promoter and the adenovirus major late promoter (MLP). A second protein, CP2, binds with high affinity to a CCAAT element present in the rat γ-fibrinogen promoter. Finally, the third CCAAT-binding protein is nuclear factor I (NF-I), a cellular DNA-binding protein that binds to the adenovirus origin of replication and is required for the initiation of adenoviral replication. CPi, CP2, and NF-I are distinct activities in that each binds to its own recognition site with an affinity that is at least three orders of magnitude higher than that with which it binds to the recognition sites of the other two proteins. Surprisingly, CP1, CP2, and NF-I each appear to recognize their binding site with highest affinity as a multisubunit complex composed of heterologous subunits. In the case of CP1, two different types of subunits form a stable complex in the absence of a DNA-binding site. Moreover, both subunits are present in the CP1-DNA complex. We thus propose the existence of a family of related multisubunit CCAAT-binding proteins that are composed of heterologous subunits

Characterization of adjacent breast tumors using oligonucleotide microarrays

BACKGROUND: Current methodology often cannot distinguish second primary breast cancers from multifocal disease, a potentially important distinction for clinical management. In the present study we evaluated the use of oligonucleotide-based microarray analysis in determining the clonality of tumors by comparing gene expression profiles. METHOD: Total RNA was extracted from two tumors with no apparent physical connection that were located in the right breast of an 87-year-old woman diagnosed with invasive ductal carcinoma (IDC). The RNA was hybridized to the Affymetrix Human Genome U95A Gene Chip(®) (12,500 known human genes) and analyzed using the Gene Chip Analysis Suite(®) 3.3 (Affymetrix, Inc, Santa Clara, CA, USA) and JMPIN(®) 3.2.6 (SAS Institute, Inc, Cary, NC, USA). Gene expression profiles of tumors from five additional patients were compared in order to evaluate the heterogeneity in gene expression between tumors with similar clinical characteristics. RESULTS: The adjacent breast tumors had a pairwise correlation coefficient of 0.987, and were essentially indistinguishable by microarray analysis. Analysis of gene expression profiles from different individuals, however, generated a pairwise correlation coefficient of 0.710. CONCLUSION: Transcriptional profiling may be a useful diagnostic tool for determining tumor clonality and heterogeneity, and may ultimately impact on therapeutic decision making

Conditional activation of Neu in the mammary epithelium of transgenic mice results in reversible pulmonary metastasis

AbstractTo determine the impact of tumor progression on the reversibility of Neu-induced tumorigenesis, we have used the tetracycline regulatory system to conditionally express activated Neu in the mammary epithelium of transgenic mice. When induced with doxycycline, bitransgenic MMTV-rtTA/TetO-NeuNT mice develop multiple invasive mammary carcinomas, essentially all of which regress to a clinically undetectable state following transgene deinduction. This demonstrates that Neu-initiated tumorigenesis is reversible. Strikingly, extensive lung metastases arising from Neu-induced mammary tumors also rapidly and fully regress following the abrogation of Neu expression. However, despite the near universal dependence of both primary tumors and metastases on Neu transgene expression, most animals bearing fully regressed Neu-induced tumors ultimately develop recurrent tumors that have progressed to a Neu-independent state

Aberrant RET expression impacts on normal mammary gland post-lactation transition enhancing cancer potential

RET is a receptor tyrosine kinase with oncogenic potential in the mammary epithelium. Several receptors with oncogenic activity in the breast are known to participate in specific developmental stages. We found that RET is differentially expressed during mouse mammary gland development: RET is present in lactation and its expression dramatically decreases in involution, the period during which the lactating gland returns to a quiescent state after weaning. Based on epidemiological and pre-clinical findings, involution has been described as tumor promoting. Using the Ret/MTB doxycycline-inducible mouse transgenic system we show that sustained expression of RET in the mammary epithelium during the post-lactation transition to involution is accompanied by alterations in tissue remodeling and an enhancement of cancer potential. Following constitutive Ret expression we observed a significant increase in neoplastic lesions in the post-involuting versus the virgin mammary gland. Furthermore, we show that abnormal RET overexpression during lactation promotes factors that prime involution, including premature activation of Stat3 signaling and, using RNA-seq, an acute-phase inflammatory signature. Our results demonstrate that RET overexpression negatively affects the normal post-lactation transition.Fil: Vallone, Sabrina Aldana. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Fisiología, Biología Molecular y Neurociencias. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Fisiología, Biología Molecular y Neurociencias; ArgentinaFil: Garcia Sola, Martin Emilio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Fisiología, Biología Molecular y Neurociencias. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Fisiología, Biología Molecular y Neurociencias; ArgentinaFil: Schere Levy, Carolina Paula. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Fisiología, Biología Molecular y Neurociencias. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Fisiología, Biología Molecular y Neurociencias; ArgentinaFil: Meiss, Roberto P.. Academia Nacional de Medicina de Buenos Aires; ArgentinaFil: Hermida, Gladys Noemí. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Chodosh, Lewis A.. University of Pennsylvania; Estados UnidosFil: Kordon, Edith Claudia. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Fisiología, Biología Molecular y Neurociencias. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Fisiología, Biología Molecular y Neurociencias; ArgentinaFil: Hynes, Nancy E.. Friedrich Miescher Institute For Biomedical Research; SuizaFil: Gattelli, Albana. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Fisiología, Biología Molecular y Neurociencias. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Fisiología, Biología Molecular y Neurociencias; Argentin