Identification of thioredoxin reductase 1-regulated genes using small interference RNA and cDNA microarray.

Thioredoxin reductase 1 (TrxR1) is a cytosolic enzyme that plays a central role in controlling cellular redox homeostasis. TrxR1 can transduce regulatory redox signals through NADPH-dependent reduction of thioredoxin (Trx), which is able to reduce a broad spectrum of target enzymes and regulate the activity of several transcription factors (e.g., p53 and NF-kappaB). The TrxR1/Trx system is involved in every step of cancer biology, ranging from transformation and progression to invasion, metastasis and resistance to therapy. TrxR1 was also recently identified as one key enzyme involved in cell death induced by interferon-beta (IFN-beta)/all-trans retinoic acid (ATRA) anti-cancer treatment. Our study employed small interference RNA (siRNA) and microarray techniques to investigate the effect of TrxR1 silencing on gene expression in HepG2 cells. We also investigated TrxR1-mediated cell response to IFN-beta/ATRA treatment. We identified TrxR1-dependent genes with functions related to several cellular processes such as apoptosis (SOX4), ubiquitination (Ubiquitin D, F-box protein 25), organization of cytoskeletal/extracellular matrix (Keratin 19, Fibronectin 1) and transport (Cystine/Glutamate transporter). We also investigated the effect of TrxR1 siRNA on the protein profile using surface enhanced laser desorption ionization time-of-flight (SELDI-TOF) technology. Profiles confirmed significant involvement of TrxR1 in cell response to IFN-beta/ATRA.

Distinct organization of the candidate tumor suppressor gene RFP2 in human and mouse: multiple mRNA isoforms in both species- and human-specific antisense transcript RFP2OS.

In the present study, we describe the human and mouse RFP2 gene structure, multiple RFP2 mRNA isoforms in the two species that have different 5' UTRs and a human-specific antisense transcript RFP2OS. Since the human RFP2 5' UTR is not conserved in mouse, these findings might indicate a different regulation of RFP2 in the two species. The predicted human and mouse RFP2 proteins are shown to contain a tripartite RING finger-B-box-coiled-coil domain (RBCC), also known as a TRIM domain, and therefore belong to a subgroup of RING finger proteins that are often involved in developmental and tumorigenic processes. Because homozygous deletions of chromosomal region 13q14.3 are found in a number of malignancies, including chronic lymphocytic leukemia (CLL) and multiple myeloma (MM), we suggest that RFP2 might be involved in tumor development. This study provides necessary information for evaluation of the role of RFP2 in malignant transformation and other biological processes.

Development of a new reference standard for microarray experiments.

Often microarray studies require a reference to indirectly compare the samples under observation. References based on pooled RNA from different cell lines have already been described (here referred to as RNA-R), but they usually do not exhaustively represent the set of genes printed on a chip, thus requiring many adjustments during the analyses. A reference could also be generated in vitro transcribing the collection of cDNA clones printed on the microarray in use (here referred to as T3-R). Here we describe an alternative and simpler PCR-based methodology to construct a similar reference (Chip-R), and we extensively test and compare it to both RNA-R and T3-R. The use of both Chip-R and T3-R dramatically increases the number of signals on the slides and gives more reproducible results than RNA-R. Each reference preparation is also evaluated in a simple microarray experiment comparing two different RNA populations. Our results show that the introduction of a reference always interferes with the analysis. Indeed, the direct comparison is able to identify more up- or down-regulated genes than any reference-mediated analysis. However, if a reference has to be used, Chip-R and T3-R are able to guarantee more reliable results than RNA-R.

Microarrays in cancer research.

Microarray technology has presented the scientific community with a compelling approach that allows for simultaneous evaluation of all cellular processes at once. Cancer, being one of the most challenging diseases due to its polygenic nature, presents itself as a perfect candidate for evaluation by this approach. Several recent articles have provided significant insight into the strengths and limitations of microarrays. Nevertheless, there are strong indications that this approach will provide new molecular markers that could be used in diagnosis and prognosis of cancers. To achieve these goals it is essential that there is a seamless integration of clinical and molecular biological data that allows us to elucidate genes and pathways involved in various cancers. To this effect we are currently evaluating gene expression profiles in human brain, ovarian, breast and hematopoetic, lung, colorectal, head and neck and biliary tract cancers. To address the issues we have a joint team of scientists, doctors and computer scientists from two Virginia Universities and a major healthcare provider. The study has been divided into several focus groups that include; Tissue Bank Clinical & Pathology Laboratory Data, Chip Fabrication, QA/QC, Tissue Devitalization, Database Design and Data Analysis, using multiple microarray platforms. Currently over 300 consenting patients have been enrolled in the study with the largest number being that of breast cancer patients. Clinical data on each patient is being compiled into a secure and interactive relational database and integration of these data elements will be accomplished by a common programming interface. This clinical database contains several key parameters on each patient including demographic (risk factors, nutrition, co-morbidity, familial history), histopathology (non genetic predictors), tumor, treatment and follow-up information. Gene expression data derived from the tissue samples will be linked to this database, which allows us to query the data at multiple levels. The challenge of tissue acquisition and processing is of paramount importance to the success of this venture. A tissue devitalization timeline protocol was devised to ensure sample and RNA integrity. Stringent protocols are being employed to ascertain accurate tumor homogeneity, by serial dissection of each tumor sample at 10 microM frozen sections followed by histopathological evaluation. The multiple platforms being utilized in this study include Affimetrix, Oligo-Chips and custom-designed cDNA arrays. Selected RNA samples will be evaluated on each platform between the groups. Analysis steps will involve normalization and standardization of gene expression data followed by hierarchical clustering to determine co-regulation profiles. The aim of this conjoint effort is to elucidate pathways and genes involved in various cancers, resistance mechanisms, molecular markers for diagnosis and prognosis.

Genomic profiling: cDNA arrays and oligoarrays.

The introduction of microarray technology, which is a multiplexed hybridization-based process, allows simultaneous analysis of a large number of nucleic acid transcripts. This massively parallel analysis of a cellular genome will become essential for guiding disease diagnosis and molecular profiling of an individual patient's tumor. Nucleic acid based microarrays can be used for: gene expression profiling, single-nucleotide polymorphisms (SNPs) detection, array-comparative genomic hybridizations, comparisons of DNA-methylation status, and microRNA evaluation.A multitude of commercial platforms are available to construct and analyze the microarrays. Typical workflow for a microarray experiment is: preparation of cDNA or gDNA, array construction, hybridization, fluorescent detection, and analysis. Since many sources of variability can affect the outcome of one experiment and there is a multitide of microarray platforms available, microarray standards have been developed to provide industry-wide quality control and information related to each microarray. In this chapter, we review array construction, methodologies, and applications relevant to molecular profiling.

Hepatic gene expression in patients with obesity-related non-alcoholic steatohepatitis.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is among the most common causes of chronic liver disease. NAFLD includes a spectrum of clinicopathologic syndromes that includes non-alcoholic steatohepatitis (NASH) that has potential for progression. The pathogenesis of NASH is poorly characterized. AIM: This study was designed to identify differences in hepatic gene expression in patients with NASH and to relate such differences to their clinical characteristics. DESIGN: Consecutive patients undergoing bariatric surgery were prospectively recruited. Extensive clinical data and two liver biopsy specimens were obtained at the time of enrollment. A single hepatopathologist reviewed and classified the liver biopsies. Patients with excessive alcohol use and other causes of liver disease were excluded. A group of 29 NASH patients, 12 with steatosis alone, seven obese controls and six non-obese controls were selected for further investigation. Customized cDNA microarrays containing 5220 relevant genes were designed specifically for this study. Microarray experiments were run in triplicate for each sample and a selected group of genes were confirmed using real-time PCR. OUTCOME MEASURE: Differential hepatic gene expressions in patients with NASH as compared with controls. RESULTS: Thirty-four genes with significant differential expression were identified in patients with NASH when compared with non-obese controls. Moreover, 19 of these genes showed no significant expression differences in obese vs. non-obese controls, suggesting a stronger association of these genes to NASH. CONCLUSIONS: Several differentially expressed genes in patients with NASH are related to lipid metabolism and extracellular matrix remodeling. Additionally, genes related to liver regeneration, apoptosis, and the detoxification process were differentially expressed. These findings may help clarify the molecular pathogenesis of NASH and identify potential targets for therapeutic intervention.

A genomic and proteomic study of the spectrum of nonalcoholic fatty liver disease.

Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease, and some of its forms are progressive. This study describes the profiling of hepatic gene expression and serum protein content in patients with different subtypes of NAFLD. Liver biopsy specimens from 98 bariatric surgery patients were classified as normal, steatosis alone, steatosis with nonspecific inflammation, and nonalcoholic steatohepatitis (NASH). Microarray hybridizations were performed in triplicate and the microarray expression levels of a selected group of genes were confirmed using real-time quantitative reverse-transcriptase polymerase chain reaction. Serum protein profiles of the same patients were determined by SELDI-TOF mass spectrometry. Of 98 obese patients, 91 were diagnosed with NAFLD (12 steatosis alone, 52 steatosis with nonspecific inflammation, and 27 NASH), and 7 patients without NAFLD served as obese controls. Each group of NAFLD patients was compared with the obese controls, and 22 genes with more than twofold differences in expression levels were revealed. Proteomics analyses were performed for the same group comparisons and revealed twelve significantly different protein peaks. In conclusion, this genomic/proteomic analysis suggests differential expression of several genes and protein peaks in patients within and across the forms of NAFLD. These findings may help clarify the pathogenesis of NAFLD and identify potential targets for therapeutic intervention.