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Abstract Background Recent studies indicate that microRNAs (miRNAs) are mechanistically involved in the development of various human malignancies, suggesting that they represent a promising new class of cancer biomarkers. However, previously reported methods for measuring miRNA expression consume large amounts of tissue, prohibiting high-throughput miRNA profiling from typically small clinical samples such as excision or core needle biopsies of breast or prostate cancer. Here we describe a novel combination of linear amplification and labeling of miRNA for highly sensitive expression microarray profiling requiring only picogram quantities of purified microRNA. Results Comparison of microarray and qRT-PCR measured miRNA levels from two different prostate cancer cell lines showed concordance between the two platforms (Pearson correlation R2 = 0.81); and extension of the amplification, labeling and microarray platform was successfully demonstrated using clinical core and excision biopsy samples from breast and prostate cancer patients. Unsupervised clustering analysis of the prostate biopsy microarrays separated advanced and metastatic prostate cancers from pooled normal prostatic samples and from a non-malignant precursor lesion. Unsupervised clustering of the breast cancer microarrays significantly distinguished ErbB2-positive/ER-negative, ErbB2-positive/ER-positive, and ErbB2-negative/ER-positive breast cancer phenotypes (Fisher exact test, p = 0.03); as well, supervised analysis of these microarray profiles identified distinct miRNA subsets distinguishing ErbB2-positive from ErbB2-negative and ER-positive from ER-negative breast cancers, independent of other clinically important parameters (patient age; tumor size, node status and proliferation index). Conclusion In sum, these findings demonstrate that optimized high-throughput microRNA expression profiling offers novel biomarker identification from typically small clinical samples such as breast and prostate cancer biopsies.

Background: Recent studies indicate that microRNAs (miRNAs) are mechanistically involved in the development of various human malignancies, suggesting that they represent a promising new class of cancer biomarkers. However, previously reported methods for measuring miRNA expression consume large amounts of tissue, prohibiting high-throughput miRNA profiling from typically small clinical samples such as excision or core needle biopsies of breast or prostate cancer. Here we describe a novel combination of linear amplification and labeling of miRNA for highly sensitive expression microarray profiling requiring only picogram quantities of purified microRNA. Results: Comparison of microarray and qRT-PCR measured miRNA levels from two different prostate cancer cell lines showed concordance between the two platforms (Pearson correlation R2 = 0.81); and extension of the amplification, labeling and microarray platform was successfully demonstrated using clinical core and excision biopsy samples from breast and prostate cancer patients. Unsupervised clustering analysis of the prostate biopsy microarrays separated advanced and metastatic prostate cancers from pooled normal prostatic samples and from a non-malignant precursor lesion. Unsupervised clustering of the breast cancer microarrays significantly distinguished ErbB2-positive/ER-negative, ErbB2-positive/ERpositive, and ErbB2-negative/ER-positive breast cancer phenotypes (Fisher exact test, p = 0.03); as well, supervised analysis of these microarray profiles identified distinct miRNA subsets distinguishing ErbB2- positive from ErbB2-negative and ER-positive from ER-negative breast cancers, independent of other clinically important parameters (patient age; tumor size, node status and proliferation index). Conclusion: In sum, these findings demonstrate that optimized high-throughput microRNA expression profiling offers novel biomarker identification from typically small clinical samples such as breast and prostate cancer biopsies. [ABSTRACT FROM AUTHOR]

The global physiological effects of glucocorticoids are well established, and the framework of transcriptional regulation by the glucocorticoid receptor (GR) has been described. However, the genes directly under GR control that trigger these physiological effects are largely unknown. To address this issue in a single cell type, we identified glucocorticoid-responsive genes in A549 human lung adenocarcinoma cells by microarray analysis and quantitative real-time PCR. Reduction of GR expression by RNA interference diminished the effects of dexamethasone on all tested target genes, thus confirming the essential role of GR in glucocorticoid-regulated gene expression. To identify primary GR target genes, in which GR is a component of the transcriptional regulatory complex, we developed a strategy that uses chromatin immunoprecipitation to scan putative regulatory regions of target genes for sites occupied by specifically bound GR. We screened 11 glucocorticoid-regulated genes, and we identified GR-binding regions for eight of them (five induced and three repressed). Thus, our approach provides a means for rapid identification of primary GR target genes and glucocorticoid-response elements, which will facilitate analyses of transcriptional regulatory mechanisms and determination of hormone-regulated gene networks. [ABSTRACT FROM AUTHOR]

There is growing evidence for a role of HOX homeodomain proteins in normal hematopoiesis. Several HOX genes, including HOXA9 and HOXA10, are expressed in primitive hematopoietic cells, implying a role in early hematopoietic differentiation. To identify potential target genes of these two closely related transcription factors, human CD34+ umbilical cord blood cells were transduced with vectors expressing either HOXA9 or HOXA10 and analyzed with cDNA micro-arrays. Statistical analysis using significance analysis of microarrays revealed a common signature of several hundred genes, demonstrating that the transcriptomes of HOXA9 and HOXA10 largely overlap in this cellular context. Seven genes that were upregulated by both HOX proteins were validated by real-time reverse transcription polymerase chain reaction. HOXA9 and HOXA10 showed positive regulation of genes in the Wnt pathway, including Wnt10B and two Wnt receptors Frizzled 1 and Frizzled 5, an important pathway for hematopoietic stem cell (HSC) self-renewal. Other validated genes included v-ets-related gene (ERG), Iroquois 3 (IRX3), aldehyde dehydrogenase 1 (ALDH1), and very long-chain acyl-CoA synthetase homolog 1 (VLCS-H1). GenMAPP (Gene Micro Array Pathway Profiler) analysis indicated that HOXA10 repressed expression of several genes involved in heme biosynthesis and three globin genes, indicating a general suppression of erythroid differentiation. A number of genes regulated by HOXA9 and HOXA10 are expressed in normal HSC populations.