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Biomedical subjects

Mark A van de Wiel

Publications and source records attributed to Mark A van de Wiel.

6 recordsLinked to original sources
PubMed2005

Expression microarray analysis and oligo array comparative genomic hybridization of acquired gemcitabine resistance in mouse colon reveals selection for chromosomal aberrations.

Gemcitabine is a commonly used therapy for many solid tumors. Acquired resistance to this nucleoside analogue, however, diminishes the long-term effectiveness in a majority of patients. To better define the molecular background of gemcitabine resistance, a mouse colon tumor was selected during successive rounds of transplantation with continued treatment of gemcitabine. Expression microarray analysis was applied to determine which genes are consistently and highly overexpressed or underexpressed in the resistant versus the nonresistant tumor. For the statistical interpretation of the microarray data, a parametric model was implemented, which returns model-based differential gene expression (log-) ratios and their uncertainties. This defined a set of 13 genes, putatively responsible for the gemcitabine resistance in solid tumors. One of these, RRM1, was previously identified as an important marker for gemcitabine resistance in human cell lines. Five of the 13 genes, including RRM1, are located within a 3 Mb region at chromosome 7E1 of which four are highly overexpressed, suggesting a chromosomal amplification. Therefore, chromosomal copy number changes were measured, using oligo array comparative genomic hybridization. A narrow and high amplification area was identified on 7E1 that encompassed all five genes. In addition, reduced RNA expression of two other genes at 8E1 encoding COX4I1 and RPL13 could be explained by a decrease in chromosomal copy number on chromosome 8. In conclusion, the array comparative genomic hybridization biologically validates our statistical approach and shows that gemcitabine is capable to select for chromosomally aberrant tumor cells, where changed gene expression levels lead to drug resistance.

Animals↗
PubMed2005

Genome-wide estimation of transcript concentrations from spotted cDNA microarray data.

A method providing absolute transcript concentrations from spotted microarray intensity data is presented. Number of transcripts per microg total RNA, mRNA or per cell, are obtained for each gene, enabling comparisons of transcript levels within and between tissues. The method is based on Bayesian statistical modelling incorporating available information about the experiment from target preparation to image analysis, leading to realistically large confidence intervals for estimated concentrations. The method was validated in experiments using transcripts at known concentrations, showing accuracy and reproducibility of estimated concentrations, which were also in excellent agreement with results from quantitative real-time PCR. We determined the concentration for 10,157 genes in cervix cancers and a pool of cancer cell lines and found values in the range of 10(5)-10(10) transcripts per microg total RNA. The precision of our estimates was sufficiently high to detect significant concentration differences between two tumours and between different genes within the same tumour, comparisons that are not possible with standard intensity ratios. Our method can be used to explore the regulation of pathways and to develop individualized therapies, based on absolute transcript concentrations. It can be applied broadly, facilitating the construction of the transcriptome, continuously updating it by integrating future data.

Bayes Theorem↗
PubMed2004

Microarray data analysis: from hypotheses to conclusions using gene expression data.

We review several commonly used methods for the design and analysis of microarray data. To begin with, some experimental design issues are addressed. Several approaches for pre-processing the data (filtering and normalization) before the statistical analysis stage are then discussed. A common first step in this type of analysis is gene selection based on statistical testing. Two approaches, permutation and model-based methods are explained and we emphasize the need to correct for multiple testing. Moreover, powerful approaches based on gene sets are mentioned. Clustering of either genes or samples is frequently performed when analyzing microarray data. We summarize the basics of both supervised and unsupervised clustering (classification). The latter may be of use for creating diagnostic arrays, for example. Construction of biological networks, such as pathways, is a statistically challenging but complex task that is a relatively new development and hence mentioned only briefly. We finish with some remarks on literature and software. The emphasis in this paper is on the philosophy behind several statistical issues and on a critical interpretation of microarray related analysis methods.

Cluster Analysis↗
PubMed2003

Mortality and progression to AIDS after starting highly active antiretroviral therapy.

OBJECTIVES: To examine survival and progression to AIDS among HIV-infected patients after starting highly active antiretroviral therapy (HAART). METHODS: The study population consisted of 3724 patients from the ATHENA observational cohort who initiated HAART. We considered progression to either an AIDS-defining disease or death, distinguishing HIV-related and non-related (including therapy-related) deaths. A time-dependent multivariate hazards model was fitted to the patient data and 5-year survival probabilities under various therapy scenarios estimated. RESULTS: A total of 459 patients developed AIDS and 346 died during 12 503 person-years of follow-up. HIV-related mortality decreased from 3.8 to 0.7 per 100 person-years between 1996 and 2000 whereas non-HIV-related mortality did not change (0.4 and 0.9, respectively, P = 0.25). For asymptomatic and symptomatic therapy naive patients younger than 50 years with CD4 counts above 10 x 10(6) and 150 x 10(6) cells/l, respectively, predicted 5-year survival probabilities were above 90% when HAART was used continuously. This limit was 450 x 10(6) cells/l when HAART was used during 20 weeks in each 24 week-period of follow-up, and 110 x 10(6) cells/l when patients delayed initiation of HAART for 1 year after becoming eligible for treatment. CONCLUSIONS: Survival probabilities were high among HIV-infected patients initiating HAART at an early stage of infection. The best therapy strategy is therefore to start HAART at this stage of infection. However, deferring HAART in patients with high CD4 cell counts may be clinically more appropriate given toxicity and adherence problems. The lack of any change in non-HIV-related mortality suggests that toxicity has not yet become a major risk factor for death.

Acquired Immunodeficiency Syndrome↗
PubMed2003

Differential effects of amlodipine and atorvastatin treatment and their combination on atherosclerosis in ApoE*3-Leiden transgenic mice.

This study was designed to investigate the potential antiatherosclerotic effects of the calcium antagonist amlodipine as compared with the HMG-CoA reductase inhibitor atorvastatin and the combination of both in ApoE*3-Leiden transgenic mice. Four groups of 15 ApoE*3-Leiden mice were put on a high-cholesterol diet. One group received 0.002% (wt/wt) amlodipine in the diet, which had no effect on plasma cholesterol levels. Another group received 0.01% (wt/wt) atorvastatin, resulting in a decrease of plasma cholesterol by 50% by a reduction in very low density lipoprotein production. The combination group received both amlodipine and atorvastatin. After 28 weeks, atherosclerosis in the aortic root was quantified. Treatment with amlodipine had no significant effect on atherosclerotic lesion area, whereas atorvastatin markedly reduced atherosclerosis by 77% compared with the control group. Atorvastatin also reduced inflammation markers. The combination of amlodipine and atorvastatin tended to reduce lesion area by 61% compared with the atorvastatin-only group; however, this effect did not reach statistical significance. Amlodipine treatment significantly reduced calcification in the lesions, whereas atorvastatin alone had no effect. The combination of amlodipine and atorvastatin resulted in a near absence of calcium deposits in the lesions. This study demonstrates that amlodipine treatment alone does not significantly reduce atherosclerotic lesion development. Atorvastatin was shown to have strong antiatherosclerotic effects, and cotreatment with amlodipine may potentiate the antiatherosclerotic effect of atorvastatin.

Amlodipine↗