Biomedical subjects

Catalin Barbacioru

Publications and source records attributed to Catalin Barbacioru.

8 recordsLinked to original sources

PubMed2006

Large scale real-time PCR validation on gene expression measurements from two commercial long-oligonucleotide microarrays.

BACKGROUND: DNA microarrays are rapidly becoming a fundamental tool in discovery-based genomic and biomedical research. However, the reliability of the microarray results is being challenged due to the existence of different technologies and non-standard methods of data analysis and interpretation. In the absence of a "gold standard"/"reference method" for the gene expression measurements, studies evaluating and comparing the performance of various microarray platforms have often yielded subjective and conflicting conclusions. To address this issue we have conducted a large scale TaqMan Gene Expression Assay based real-time PCR experiment and used this data set as the reference to evaluate the performance of two representative commercial microarray platforms. RESULTS: In this study, we analyzed the gene expression profiles of three human tissues: brain, lung, liver and one universal human reference sample (UHR) using two representative commercial long-oligonucleotide microarray platforms: (1) Applied Biosystems Human Genome Survey Microarrays (based on single-color detection); (2) Agilent Whole Human Genome Oligo Microarrays (based on two-color detection). 1,375 genes represented by both microarray platforms and spanning a wide dynamic range in gene expression levels, were selected for TaqMan Gene Expression Assay based real-time PCR validation. For each platform, four technical replicates were performed on the same total RNA samples according to each manufacturer's standard protocols. For Agilent arrays, comparative hybridization was performed using incorporation of Cy5 for brain/lung/liver RNA and Cy3 for UHR RNA (common reference). Using the TaqMan Gene Expression Assay based real-time PCR data set as the reference set, the performance of the two microarray platforms was evaluated focusing on the following criteria: (1) Sensitivity and accuracy in detection of expression; (2) Fold change correlation with real-time PCR data in pair-wise tissues as well as in gene expression profiles determined across all tissues; (3) Sensitivity and accuracy in detection of differential expression. CONCLUSION: Our study provides one of the largest "reference" data set of gene expression measurements using TaqMan Gene Expression Assay based real-time PCR technology. This data set allowed us to use an alternative gene expression technology to evaluate the performance of different microarray platforms. We conclude that microarrays are indeed invaluable discovery tools with acceptable reliability for genome-wide gene expression screening, though validation of putative changes in gene expression remains advisable. Our study also characterizes the limitations of microarrays; understanding these limitations will enable researchers to more effectively evaluate microarray results in a more cautious and appropriate manner.

Gene Expression Profiling↗

PubMed2006

Prediction of anticancer drug potency from expression of genes involved in growth factor signaling.

PURPOSE: This study develops and evaluates a systematic approach to finding biomarker genes for predicting potency of anticancer drugs against tumor cells, focusing on gene families related to growth factor signaling. METHODS: Cytotoxic potencies of 119 drugs against 60 neoplastic cell lines (NCI-60) were correlated with expression of 343 genes, including 90 growth factors and receptors, 63 metalloproteinases, and 92 ras-like GTPases as downstream signaling factors. Progressively more stringent criteria and predictive models aim at identifying the smallest subset of genes predictive of cytotoxic potency. RESULTS: Comparing gene expression with drug potency across the NCI-60 yielded genes with negative and positive correlations (p < 0.001), indicative of a role in chemoresistance and chemosensitivity, respectively. Of 17 genes with multiple negative correlations, 8 are known chemoresistance factors, validating the approach. Negatively correlated genes clustered into two main groups with distinct expression profiles and drug correlations, represented by EGFR and ERBB2 (Her-2/Neu). Accordingly, no synergism was observed between EGFR and ERBB2 inhibitors. However, combinations with classical anticacer drugs were not correlated with EGFR and ERBB2 expression in four cell lines tested, suggesting complex interactions in combination treatments. Finally, a subset of only 13 genes was found to be sufficient for near optimal prediction of drug potency against the NCI-60. CONCLUSIONS: Our approach using a small subset of genes reveals known and potential biomarkers in cancer chemotherapy, providing a strategy for genome-wide analysis.

Algorithms↗

PubMed2005

Cystine-glutamate transporter SLC7A11 in cancer chemosensitivity and chemoresistance.

SLC7A11 (xCT), together with SLC3A2 (4F2hc), encodes the heterodimeric amino acid transport system x(c)-, which mediates cystine-glutamate exchange and thereby regulates intracellular glutathione levels. We used microarrays to analyze gene expression of transporters in 60 human cancer cell lines used by the National Cancer Institute for drug screening (NCI-60). The expression of SLC7A11 showed significant correlation with that of SLC3A2 (r = 0.66), which in turn correlated with SLC7A5 (r = 0.68), another known partner for SLC3A2, and with T1A-2 (r = 0.60; all P < 0.0001). Linking expression of SLC7A11 with potency of 1,400 candidate anticancer drugs identified 39 showing positive correlations, e.g., amino acid analogue, L-alanosine, and 296 with negative correlations, e.g., geldanamycin. However, no significant correlation was observed with the geldanamycin analogue 17-allylamino, 17-demethoxygeldanamycin (17-AAG). Inhibition of transport system x(c)- with glutamate or (S)-4-carboxyphenylglycine in lung A549 and HOP-62, and ovarian SK-OV-3 cells, reduced the potency of L-alanosine and lowered intracellular glutathione levels. This further resulted in increased potency of geldanamycin, with no effect on 17-AAG. Down-regulation of SLC7A11 by small interfering RNA affected drug potencies similarly to transport inhibitors. The inhibitor of gamma-glutamylcysteine synthetase, buthionine sulfoximine, also decreased intracellular glutathione levels and enhanced potency of geldanamycin, but did not affect L-alanosine. These results indicate that SLC7A11 mediates cellular uptake of L-alanosine but confers resistance to geldanamycin by supplying cystine for glutathione maintenance. SLC7A11 expression could serve as a predictor of cellular response to L-alanosine and glutathione-mediated resistance to geldanamycin, yielding a potential target for increasing chemosensitivity to multiple drugs.

Amino Acid Transport System y+↗

PubMed2004

Membrane transporters and channels: role of the transportome in cancer chemosensitivity and chemoresistance.

Membrane transporters and channels (collectively the transportome) govern cellular influx and efflux of ions, nutrients, and drugs. We used oligonucleotide arrays to analyze gene expression of the transportome in 60 human cancer cell lines used by the National Cancer Institute for drug screening. Correlating gene expression with the potencies of 119 standard anticancer drugs identified known drug-transporter interactions and suggested novel ones. Folate, nucleoside, and amino acid transporters positively correlated with chemosensitivity to their respective drug substrates. We validated the positive correlation between SLC29A1 (nucleoside transporter ENT1) expression and potency of nucleoside analogues, azacytidine and inosine-glycodialdehyde. Application of an inhibitor of SLC29A1, nitrobenzylmercaptopurine ribonucleoside, significantly reduced the potency of these two drugs, indicating that SLC29A1 plays a role in cellular uptake. Three ABC efflux transporters (ABCB1, ABCC3, and ABCB5) showed significant negative correlations with multiple drugs, suggesting a mechanism of drug resistance. ABCB1 expression correlated negatively with potencies of 19 known ABCB1 substrates and with Baker's antifol and geldanamycin. Use of RNA interference reduced ABCB1 mRNA levels and concomitantly increased sensitivity to these two drugs, as expected for ABCB1 substrates. Similarly, specific silencing of ABCB5 by small interfering RNA increased sensitivity to several drugs in melanoma cells, implicating ABCB5 as a novel chemoresistance factor. Ion exchangers, ion channels, and subunits of proton and sodium pumps variably correlated with drug potency. This study identifies numerous potential drug-transporter relationships and supports a prominent role for membrane transport in determining chemosensitivity. Measurement of transporter gene expression may prove useful in predicting anticancer drug response.

ATP-Binding Cassette Transporters↗

PubMed2004

CITED1 protein expression suggests Papillary Thyroid Carcinoma in high throughput tissue microarray-based study.

Molecular markers of papillary thyroid carcinoma (PTC) are relatively unknown. Recently, the CITED1 gene was reported to be greatly upregulated in PTC relative to normal thyroid. The CITED1 protein, a 27-kd transcriptional transactivator nuclear protein is expressed in PTC, melanocytes, breast epithelial cells, and several embryonic tissues. However, its expression in other thyroid masses and non-thyroid tumors is not known. We evaluated CITED1 protein expression in tissue microarrays comprising various thyroid and nonthyroid tissues by immunohistochemistry using a polyclonal anti-CITED1 antibody. CITED1 expression was seen in 63 of 68 PTC (93%), 3 of 12 follicular carcinomas (25%), 2 of 7 Hürthle cell carcinomas (28%), 2 of 21 adenomas (10%), 2 of 6 follicular neoplasms of undetermined malignant behavior (33%), and 2 of 24 nodular goiters (8%). Normal thyroids (n = 27), thyrotoxic hyperplasias (n = 14), and anaplastic thyroid carcinomas (n = 5) did not express CITED1. Among nonthyroid tumors, 6 of 23 melanomas (26%), 11 of 65 prostatic carcinomas (17%), 3 of 25 glioblastomas (12%), 4 of 67 breast carcinomas (6%), 1 of 49 lymphomas (2%), 1 of 65 lung carcinomas (2%), 1 of 68 colon carcinomas (2%), and none of 49 ovarian carcinomas (0%) expressed CITED1. The accuracy of CITED1 in differentiating PTC from benign thyroid nodules, other thyroid carcinomas, and nonthyroid carcinomas was 93%, 89%, and 94%, respectively. CITED1 is preferentially expressed in PTC and may be used as a diagnostic marker of it.

Adenocarcinoma, Follicular↗

PubMed2003

Pharmacokinetic mapping of breast tumors: a new statistical analysis technique for dynamic magnetic resonance imaging.

Breast cancer is the most common malignancy among women, constituting a major health problem. Different MRI techniques have been investigated in the past in order to improve the detection and diagnosis of breast tumors. One such technique is the dynamic contrast-enhanced T1-weighted magnetic resonance imaging (DCE-MRI), using diffusible CM (contrast media), such as Gd-DTPA. Here we employ a two compartment CM kinetics model (blood plasma and surrounding interstitial space being the two compartments), where the exchange of contrast agent between these compartments is bidirectionally linear. In this study we use images from 29 suspected breast carcinoma patients who underwent whole breast DCE-MRI. Each of these studies has 64 coronal sections of the whole breast, taken at 6 or 7 time points (the sampling period being about 2 minutes). Subsequent histo-pathological analysis of these patients reveal: 22 intraductal carcinomas (IDC), 3 intralobular carcinomas (ILC), 2 ductal carcinomas in-situ (DCIS) and 3 benign tumors.

Breast Neoplasms↗

PubMed2003

Order sets utilization in a clinical order entry system.

An order set is a predefined template that has been utilized in the standard care of hospitals for many years. While in the past, it took the form of pen and paper, today, it is, indeed, electronic. Within order sets are distinct ordering patterns that may yield fruitful results for clinicians and informaticians, alike. Protocols like there electronic counterpart, order sets, provide an 'indication' identifying the clinical scenario of the patient's condition when the ordering event occurred. This 'indication' is rarely captured by individual orders, and provides difficult challenges to developers of information systems. While mandating an 'indication' be entered for every medication or lab order makes the job much more tasking on the physician provider, it is appealing to researchers and accountants. We have attempted to bypasses that consideration by identifying ordering patterns that predict diagnostic related codes (DRGs) and diagnostic codes which would greatly facilitate the information gathering process and still provide a flexible and user friendly physician interface.

Forms and Records Control↗

PubMed2003

Proteomic patterns analysis: a new era of screening cancers.

Cancer is the second leading cause of death among Americans. It is estimated that 1.28 million new Americans are diagnosed with cancer annually (1). The estimated overall annual cost of cancer being $171 Billion (1). Decreasing the costs of the screening and diagnostic tests will automatically decrease the total cost of cancer by limiting not only the direct medical costs but also by containing the indirect costs of morbidity and mortality. New screening and diagnostic tests are obviously needed. Screening methods are emerging in the evaluation of proteomic patterns. In proteomic pattern analysis, we can screen for not only one cancer but a chip may be able to screen for multiple cancers. New screening and diagnostic methods (2) investigated by NCI and FDA (3) (4) are correlating gene and protein expression patterns for early detection of cancer. Many papers have been published in the last 12 months (3) (4) (5) utilizing this new technique of molecular analysis in screening and diagnosing cancers with high sensitivity and specificity.

Health Care Costs↗