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As essential cofactor in many proteins and redox enzymes, copper and iron are involved in a wide range of biological processes. Mild dietary deficiency of metals represents an underestimated problem for human health, because it does not cause clear signs and clinical symptoms, but it is associated to long-term deleterious effects in cardiovascular system and alterations in lipid metabolism. The aim of this work was to study the biological processes significantly affected by mild dietary deficiency of both metals in rat intestine, in order to better understand the molecular bases of the systemic metabolic alterations, as hypercholesterolemia and hypertriglyceridemia observed in copper-deficient rats. A gene-microarray differential analysis was carried out on the intestinal transcriptome of copper- and iron-deficient rats, thus highlighting the biological processes significantly modulated by the dietary restrictions. The gene array analysis showed a down-regulation of genes involved in mitochondrial and peroxisomal fatty acids beta-oxidation and an up-regulation of genes involved in plasmatic cholesterol transport (apoprotein E and lecithin:cholesterol acyltransferase) in copper deficiency. Furthermore, a severe down-regulation of ApoH was pointed out in iron-deficient animals.

Microarray-based gene expression profiling is well suited for parallel quantitative analysis of large numbers of RNAs, but its application to cancer biopsies, formalin-fixed paraffin-embedded (FFPE) archived tissues in particular, is limited by the poor quality of the RNA recovered. This represents a serious drawback, since FFPE tumor tissue banks are available with clinical and prognostic annotations, which could be exploited for molecular profiling studies, provided that reliable analytical technologies are found. We applied and evaluated here a microarray-based cDNA-mediated annealing, selection, extension and ligation (DASL) assay for analysis of 502 mRNAs in highly degraded total RNA extracted from cultured cells or FFPE breast cancer biopsies. The study included quantitative and qualitative comparison of data obtained by analysis of the same RNAs with genome-wide oligonucleotide microarrays vs. DASL arrays and, by DASL, before and after extensive in vitro RNA fragmentation. The DASL-based expression profiling assay applied to RNA extracted from MCF-7 cells before or after 24 hours stimulation with a mitogenic dose of 17β-estradiol consistently allowed to detect hormone-induced gene expression changes also following extensive RNA degradation in vitro. Comparable results where obtained with tumor RNA extracted from FFPE breast cancer biopsies (6 to 19 years old). The method proved itself sensitive, reproducible and accurate, when compared with results obtained by microarray analysis of RNA extracted from snap-frozen tissue of the same tumor.

Background Estrogen receptors alpha (ERα) and beta (ERβ) are transcription factors (TFs) that mediate estrogen signaling and define the hormone-responsive phenotype of breast cancer (BC). The two receptors can be found co-expressed and play specific, often opposite, roles, with ERβ being able to modulate the effects of ERα on gene transcription and cell proliferation. ERβ is frequently lost in BC, where its presence generally correlates with a better prognosis of the disease. The identification of the genomic targets of ERβ in hormone-responsive BC cells is thus a critical step to elucidate the roles of this receptor in estrogen signaling and tumor cell biology. Results Expression of full-length ERβ in hormone-responsive, ERα-positive MCF-7 cells resulted in a marked reduction in cell proliferation in response to estrogen and marked effects on the cell transcriptome. By ChIP-Seq we identified 9702 ERβ and 6024 ERα binding sites in estrogen-stimulated cells, comprising sites occupied by either ERβ, ERα or both ER subtypes. A search for TF binding matrices revealed that the majority of the binding sites identified comprise one or more Estrogen Response Element and the remaining show binding matrixes for other TFs known to mediate ER interaction with chromatin by tethering, including AP2, E2F and SP1. Of 921 genes differentially regulated by estrogen in ERβ+ vs ERβ- cells, 424 showed one or more ERβ site within 10 kb. These putative primary ERβ target genes control cell proliferation, death, differentiation, motility and adhesion, signal transduction and transcription, key cellular processes that might explain the biological and clinical phenotype of tumors expressing this ER subtype. ERβ binding in close proximity of several miRNA genes and in the mitochondrial genome, suggests the possible involvement of this receptor in small non-coding RNA biogenesis and mitochondrial genome functions. Conclusions Results indicate that the vast majority of the genomic targets of ERβ can bind also ERα, suggesting that the overall action of ERβ on the genome of hormone-responsive BC cells depends mainly on the relative concentration of both ERs in the cell.

C/EBPs are a family of B-Zip transcription factors -TFs- involved in the regulation of differentiation in several tissues. The two most studied members -C/EBPα and C/EBPβ- play important roles in skin homeostasis and their ablation reveals cells with stem cells signatures. Much less is known about C/EBPδ which is highly expressed in the granular layer of interfollicular epidermis and is a direct target of p63, the master regular of multilayered epithelia. We identified C/EBPδ target genes in human primary keratinocytes by ChIP on chip and profiling of cells functionally inactivated with siRNA. Categorization suggests a role in differentiation and control of cell-cycle, particularly of G2/M genes. Among positively controlled targets are numerous genes involved in barrier function. Functional inactivation of C/EBPδ as well as overexpressions of two TF targets -MafB and SOX2- affect expression of markers of keratinocyte differentiation. We performed IHC on skin tumor tissue arrays: expression of C/EBPδ is lost in Basal Cell Carcinomas, but a majority of Squamous Cell Carcinomas showed elevated levels of the protein. Our data indicate that C/EBPδ plays a role in late stages of keratinocyte differentiation. © 2010 Borrelli et al.

Background & Aims Mice lacking c-jun in the liver display impaired regeneration after partial hepatectomy (PH), and were reported to be more resistant to chemically-induced hepatocellular carcinoma (HCC). We investigated the role of c-jun in normal and preneoplastic hepatocyte proliferation induced by ligands of nuclear receptors, which cause liver hyperplasia in the absence of cell loss/death. Methods The effect of 1,4-bis[2-(3,5-dichloropyridyloxy)]benzene (TCPOBOP) on hepatocyte proliferation was determined in c-jun conditional knockout ( c-jun Δli ) or in mouse liver where c-jun has been silenced. To study the role of c-jun in HCC development, c-jun Δli and WT mice were given diethylnitrosamine (DENA) followed by repeated injections of TCPOBOP. Results Hepatocyte proliferation induced by TCPOBOP was associated with a stronger proliferative response and earlier S phase entry in c-jun Δli mice, compared to WT animals. Moreover, silencing of c-jun in the liver of CD-1 mice caused increased hepatocyte proliferation. A stronger hepatocyte proliferative response of c-jun Δli mice was observed also following treatment with a ligand of thyroid hormone receptor. Finally, loss of c-jun did not inhibit the development of HCC induced by DENA and promoted by TCPOBOP. Conclusions (i) c-jun may, under certain conditions, negatively regulate proliferation of normal hepatocytes, (ii) c-jun is not an absolute requirement for DENA/TCPOBOP-induced HCC formation, suggesting that the therapeutic potential of c-jun/JNK inhibition in liver tumors might be impaired by an increased stimulation of cell growth due to blockade of the c-jun pathway.

BACKGROUND: Transposable Elements (TEs) comprise nearly 45% of the entire genome and are part of sophisticated regulatory network systems that control developmental processes in normal and pathological conditions. The retroviral/retrotransposon gene machinery consists mainly of Long Interspersed Nuclear Elements (LINEs-1) and Human Endogenous Retroviruses (HERVs) that code for their own endogenous reverse transcriptase (RT). Interestingly, RT is typically expressed at high levels in cancer cells. Recent studies report that RT inhibition by non-nucleoside reverse transcriptase inhibitors (NNRTIs) induces growth arrest and cell differentiation in vitro and antagonizes growth of human tumors in animal model. In the present study we analyze the anticancer activity of Abacavir (ABC), a nucleoside reverse transcription inhibitor (NRTI), on PC3 and LNCaP prostate cancer cell lines. PRINCIPAL FINDINGS: ABC significantly reduces cell growth, migration and invasion processes, considerably slows S phase progression, induces senescence and cell death in prostate cancer cells. Consistent with these observations, microarray analysis on PC3 cells shows that ABC induces specific and dose-dependent changes in gene expression, involving multiple cellular pathways. Notably, by quantitative Real-Time PCR we found that LINE-1 ORF1 and ORF2 mRNA levels were significantly up-regulated by ABC treatment. CONCLUSIONS: Our results demonstrate the potential of ABC as anticancer agent able to induce antiproliferative activity and trigger senescence in prostate cancer cells. Noteworthy, we show that ABC elicits up-regulation of LINE-1 expression, suggesting the involvement of these elements in the observed cellular modifications.

Luminal-like breast tumor cells express estrogen receptor alpha (ERalpha), a member of the nuclear receptor family of ligand-activated transcription factors that controls their proliferation, survival, and functional status. To identify the molecular determinants of this hormone-responsive tumor phenotype, a comprehensive genome-wide analysis was performed in estrogen stimulated MCF-7 and ZR-75.1 cells by integrating time-course mRNA expression profiling with global mapping of genomic ERalpha binding sites by chromatin immunoprecipitation coupled to massively parallel sequencing, microRNA expression profiling, and in silico analysis of transcription units and receptor binding regions identified. All 1270 genes that were found to respond to 17beta-estradiol in both cell lines cluster in 33 highly concordant groups, each of which showed defined kinetics of RNA changes. This hormone-responsive gene set includes several direct targets of ERalpha and is organized in a gene regulation cascade, stemming from ligand-activated receptor and reaching a large number of downstream targets via AP-2gamma, B-cell activating transcription factor, E2F1 and 2, E74-like factor 3, GTF2IRD1, hairy and enhancer of split homologue-1, MYB, SMAD3, RARalpha, and RXRalpha transcription factors. MicroRNAs are also integral components of this gene regulation network because miR-107, miR-424, miR-570, miR-618, and miR-760 are regulated by 17beta-estradiol along with other microRNAs that can target a significant number of transcripts belonging to one or more estrogen-responsive gene clusters.

Background Microarray experiments enable simultaneous measurement of the expression levels of virtually all transcripts present in cells, thereby providing a ‘molecular picture’ of the cell state. On the other hand, the genomic responses to a pharmacological or hormonal stimulus are dynamic molecular processes, where time influences gene activity and expression. The potential use of the statistical analysis of microarray data in time series has not been fully exploited so far, due to the fact that only few methods are available which take into proper account temporal relationships between samples. Results We compared here four different methods to analyze data derived from a time course mRNA expression profiling experiment which consisted in the study of the effects of estrogen on hormone-responsive human breast cancer cells. Gene expression was monitored with the innovative Illumina BeadArray platform, which includes an average of 30-40 replicates for each probe sequence randomly distributed on the chip surface. We present and discuss the results obtained by applying to these datasets different statistical methods for serial gene expression analysis. The influence of the normalization algorithm applied on data and of different parameter or threshold choices for the selection of differentially expressed transcripts has also been evaluated. In most cases, the selection was found fairly robust with respect to changes in parameters and type of normalization. We then identified which genes showed an expression profile significantly affected by the hormonal treatment over time. The final list of differentially expressed genes underwent cluster analysis of functional type, to identify groups of genes with similar regulation dynamics. Conclusions Several methods for processing time series gene expression data are presented, including evaluation of benefits and drawbacks of the different methods applied. The resulting protocol for data analysis was applied to characterization of the gene expression changes induced by estrogen in human breast cancer ZR-75.1 cells over an entire cell cycle.