Biomedical subjects

Thomas P Dooley

Publications and source records attributed to Thomas P Dooley.

7 recordsLinked to original sources

PubMed2005

Methods for gene expression profiling in dermatology research using DermArray nylon filter DNA microarrays.

Here we present methods of gene expression profiling using nylon filter deoxyribonucleic acid (DNA) microarrays and radiolabeled and nonradiolabeled hybridization probes. DermArray(R) nylon filter DNA microarrays were designed specifically for use in dermatology research. A patent-pending method was used to select approx 4400 highly informative, sequence-verified human cDNA clones for this DNA micro array. Using DermArray(R) filters, biomarkers have been discovered for normal and pathologic cells from skin, and for responses to dermatologic drugs. As an example, gene expression profiling was performed with hydroquinone-treated SKMel-28 cells, a melanoma cell line. Also included are the methods for bioinformatic analysis using Pathwaystrade mark software.

Computational Biology↗

PubMed2004

Cross-species application of cDNA microarrays to profile gene expression using UV-induced melanoma in Monodelphis domestica as the model system.

This study established the utility of cross-species application of the cDNA microarray technique for investigating differential gene expression. Using both total RNA and mRNA samples recovered from two opossum cell lines derived from UVB-induced melanoma, we analyzed expression of ca. 4400 genes on the human DermArray DNA microarrays. The signals generated on the DermArrays were clear, strong, and reproducible. A cDNA dot blot consisting of differentially expressed genes representative of different functional clusters was used to validate the DermArray results. We also cloned a Monodelphis gene, keratin 18 (KRT18), and characterized its expression patterns in tumor samples of different progression stages. Up-regulated expression was observed for the KRT18 gene in advanced melanomas, a finding consistent with the DermArray analysis. These results provide evidence that cross-species application of cDNA microarrays is a useful strategy for investigating gene expression patterns in animal models for which species-specific cDNA microarrays are not available.

Amino Acid Sequence↗

PubMed2004

Regulation of gene expression in inflammatory bowel disease and correlation with IBD drugs: screening by DNA microarrays.

Potential biomarkers for Crohn's disease (CD) and ulcerative colitis (UC) were identified from two sets of full thickness pathologic samples utilizing DermArray and PharmArray DNA microarrays relative to uninvolved (Un) colon or normal colon. Seven of the over-expressed genes were verified using quantitative RT-PCR (i.e., TMPT, FABP1, IFI27, LCN2, COL11A2, HXB, and metallothionein). By correlating gene expression profiles between inflammatory bowel disease (IBD) tissue samples and IBD drug-treated cell cultures it might be possible to identify new candidate molecular target genes for IBD therapy and drug discovery. Potential biomarkers for CaCo2 cell cultures, which are routinely used as a GI tract surrogate model for in vitro pharmacokinetic studies, treated with azathioprine, 5-aminosalicylic acid, metronidazole, and prednisone were also identified from another experiment. Metallothionein mRNA expression was found to be down-regulated in azathioprine-treated CaCo2 cells, and was coincidentally up-regulated in the CD sample, thus resulting in an anti-correlation. These results suggest that this new screening methodology is feasible, that metallothioneins might be biomarkers for azathioprine therapy in vivo in CD, and that azathioprine might mechanistically down-regulate metallothionein gene expression. Correlations were also observed between IBD samples and either metronidazole- or 5-aminosalicylic acid-treated CaCo2 cells. Similar comparisons of disease tissue samples in vivo vs drug-treated cell cultures in vitro might reveal new mechanistic insights concerning established or experimental drug therapies. This affordable in vitro methodology is promising for expanded studies of IBD and other diseases.

Adult↗

PubMed2003

Biomarkers of human cutaneous squamous cell carcinoma from tissues and cell lines identified by DNA microarrays and qRT-PCR.

Squamous cell carcinoma (SCC) is the second most common form of skin cancer in Caucasians. Here we report on the identification of biomarkers of human cutaneous SCC cell lines in vitro and tissue samples in vivo using DermArray and PharmArray DNA microarrays, consisting of ca. 7400 unique human cDNAs. Differentially expressed genes were identified in two facial skin SCC cell lines (SCC 12 and SCC 13) compared to normal keratinocytes, and three cutaneous SCC tissue samples compared to normal skin. Quantitative validations of up- and down-regulated biomarkers were performed by qRT-PCR on 23 biomarker genes for the cell lines and 20 biomarker genes for the tumor tissues. In addition, three oral SCC cell lines were also included in the qRT-PCR validations for comparison, and the biomarker profiles were highly similar between the cutaneous and the oral SCC cell lines for all 23 biomarkers examined. The expression profiles for a variety of non-cutaneous SCC types, such as head-and-neck, oral, and lung, have been previously published. This report is the first to describe biomarkers for cutaneous SCC in two contexts, in vitro and in vivo. Although there was minimal overlap between the two different contexts using DNA microarrays, five genes were found common to both the cell lines and tissues, namely fibronectin 1, annexin A5, glyceraldehyde 3-phosphate dehydrogenase, zinc-finger protein 254, and huntingtin-associated protein interacting protein. Some of our previously published biomarkers of normal keratinocytes were down-regulated in SCC, suggestive of the dedifferentiated status of the transformed cells. While recent reports have identified some of the same genes as SCC biomarkers, for instance in head-and-neck cancer, thereby validating our approach, we have identified some novel biomarkers for cutaneous disease. These biomarker lists may be useful in molecular diagnostics of non-melanoma skin cancer, and a subset of the biomarkers might serve as suitable targets for drug discovery efforts of therapies for SCC.

Biomarkers, Tumor↗

PubMed2003

A method to improve selection of molecular targets by circumventing the ADME pharmacokinetic system utilizing PharmArray DNA microarrays.

DNA microarrays may be used to identify potential molecular targets for drug discovery. Yet, DNA microarray experiments provide massive amounts of data. To limit the choice of potential molecular targets, it may be desirable to eliminate genes coincidentally up-regulated in tissues implicated in absorption, distribution, metabolism, and excretion (ADME) pharmacokinetics. DNA microarray experiments were performed to demonstrate a gene-exclusion approach using as an example RNA samples of neural origin, i.e., a human neuroblastoma cell line (SK-N-SH) and brain tissue, as the intended hypothetical site(s) of drug action. Biomarkers were identified using PharmArray DNA microarrays. The lists of neuroblastoma and neural biomarkers were constrained by limiting selection to the subset of genes that were not highly expressed in three transformed cell lines from liver, colon, and kidney (HepG2, Caco-2, and 786-O, respectively) that are routinely used as representatives of the ADME system during in vitro pharmacology and toxicology experiments. Principal component analysis methods with likelihood ratio-related bioinformatic tools were utilized to identify robust potential biomarker genes for the three ADME-related cell lines, neuroblastoma, and normal brain. Biomarkers of each sample were identified and selected genes were validated by qRT-PCR. Hundreds of biomarkers of the three ADME-related cell types, representing hepatocytes, kidney epithelium, and gastrointestinal tract, may now be used as a valuable database to restrict selection of biomarkers as potential molecular targets from the intended samples (e.g., neuroblastoma in this work). In addition to biomarker discovery per se, this demonstration suggests that our model method may be viable to help restrict gene lists during selection of potential molecular targets for subsequent drug discovery.

Adult↗

PubMed2003

DNA microarrays and likelihood ratio bioinformatic methods: discovery of human melanocyte biomarkers.

In this article, some of the advantages and limitations of DNA microarray technologies for gene expression profiling are summarized. As a model experiment, DermArray DNA microarrays were utilized to identify potential biomarkers of cultured normal human melanocytes in two different experimental comparisons. In the first case, melanocyte RNA was compared with vastly dissimilar non-melanocytic RNA samples of normal skin keratinocytes and fibroblasts. In the second case, melanocyte RNA was compared with a primary cutaneous melanoma line (MS7) and a metastatic melanoma cell line (SKMel-28). The alternative approaches provide dramatically different lists of 'normal melanocyte' biomarkers. The most robust biomarkers were identified using principal component analysis bioinformatic methods related to likelihood ratios. Only three of 25 robust biomarkers in the melanocyte-proximal study (i.e. melanocytes vs. melanoma cells) were coincidentally identified in the melanocyte-distal study (i.e. melanocytes vs. non-melanocytic cells). Selected up-regulated biomarkers of melanocytes (i.e. TRP-1, melan-A/MART-1, silver/Pmel17, and nidogen-2) were validated by qRT-PCR. Some of the melanocytic biomarkers identified here may be useful in molecular diagnostics, as potential molecular targets for drug discovery, and for understanding the biochemistry of melanocytic cells.

Aged↗

PubMed2002

Biomarkers of human skin cells identified using DermArray DNA arrays and new bioinformatics methods.

Biomarker genes of human skin-derived cells were identified by new simple bioinformatic methods and DNA microarray analysis utilizing in vitro cultures of normal neonatal human epidermal keratinocytes, melanocytes, and dermal fibroblasts. A survey of 4405 human cDNAs was performed using DermArray DNA microarrays. Biomarkers were rank ordered by "likelihood ratio" algorithms and stringent selection criteria that have general applicability for analyzing a minimum of three RNA samples. Signature biomarker genes (up-regulated in one cell type) and anti-signature biomarker genes (down-regulated in one cell type) were determined for the three major skin cell types. Many of the signature genes are known biomarkers for these cell types. In addition, 17 signature genes were identified as ESTs, and 22 anti-signature biomarkers were discovered. Quantitative RT-PCR was used to verify nine signature biomarker genes. A total of 158 biomarkers of normal human skin cells were identified, many of which may be valuable in diagnostic applications and as molecular targets for drug discovery and therapeutic intervention.

Algorithms↗