Search PubMed⌕ Search

Biomedical subjects

Uwe Scherf

Publications and source records attributed to Uwe Scherf.

8 recordsLinked to original sources
PubMed2006

Asparagine synthetase as a causal, predictive biomarker for L-asparaginase activity in ovarian cancer cells.

L-Asparaginase (l-ASP), a bacterial enzyme used since the 1970s to treat acute lymphoblastic leukemia, selectively starves cells that cannot synthesize sufficient asparagine for their own needs. Molecular profiling of the NCI-60 cancer cell lines using five different microarray platforms showed strong negative correlations of asparagine synthetase (ASNS) expression and DNA copy number with sensitivity to l-ASP in the leukemia and ovarian cancer cell subsets. To assess whether the ovarian relationship is causal, we used RNA interference to silence ASNS in three ovarian lines and observed 4- to 5-fold potentiation of sensitivity to l-ASP with two of the lines. For OVCAR-8, the line that expresses the least ASNS, the potentiation was >500-fold. Significantly, that potentiation was >700-fold in the multidrug-resistant derivative OVCAR-8/ADR, showing that the causal relationship between ASNS expression and l-ASP activity survives development of classical multidrug resistance. Tissue microarrays confirmed low ASNS expression in a subset of clinical ovarian cancers as well as other tumor types. Overall, this pharmacogenomic/pharmacoproteomic study suggests the use of l-ASP for treatment of a subset of ovarian cancers (and perhaps other tumor types), with ASNS as a biomarker for patient selection.

Antineoplastic Agents↗
PubMed2005

Cross-platform comparability of microarray technology: intra-platform consistency and appropriate data analysis procedures are essential.

BACKGROUND: The acceptance of microarray technology in regulatory decision-making is being challenged by the existence of various platforms and data analysis methods. A recent report (E. Marshall, Science, 306, 630-631, 2004), by extensively citing the study of Tan et al. (Nucleic Acids Res., 31, 5676-5684, 2003), portrays a disturbingly negative picture of the cross-platform comparability, and, hence, the reliability of microarray technology. RESULTS: We reanalyzed Tan's dataset and found that the intra-platform consistency was low, indicating a problem in experimental procedures from which the dataset was generated. Furthermore, by using three gene selection methods (i.e., p-value ranking, fold-change ranking, and Significance Analysis of Microarrays (SAM)) on the same dataset we found that p-value ranking (the method emphasized by Tan et al.) results in much lower cross-platform concordance compared to fold-change ranking or SAM. Therefore, the low cross-platform concordance reported in Tan's study appears to be mainly due to a combination of low intra-platform consistency and a poor choice of data analysis procedures, instead of inherent technical differences among different platforms, as suggested by Tan et al. and Marshall. CONCLUSION: Our results illustrate the importance of establishing calibrated RNA samples and reference datasets to objectively assess the performance of different microarray platforms and the proficiency of individual laboratories as well as the merits of various data analysis procedures. Thus, we are progressively coordinating the MAQC project, a community-wide effort for microarray quality control.

Databases, Genetic↗
PubMed2005

The External RNA Controls Consortium: a progress report.

Standard controls and best practice guidelines advance acceptance of data from research, preclinical and clinical laboratories by providing a means for evaluating data quality. The External RNA Controls Consortium (ERCC) is developing commonly agreed-upon and tested controls for use in expression assays, a true industry-wide standard control.

Animals↗
PubMed2003

Diagnostic markers that distinguish colon and ovarian adenocarcinomas: identification by genomic, proteomic, and tissue array profiling.

Colon and ovarian cancers can be difficult to distinguish in the abdomen, and the distinction is important because it determines which drugs will be used for therapy. To identify molecular markers for that differential diagnosis, we developed a multistep protocol starting with the 60 human cancer cell lines used by the National Cancer Institute to screen for new anticancer agents. The steps included: (a) identification of candidate markers using cDNA microarrays; (b) verification of clone identities by resequencing; (c) corroboration of transcript levels using Affymetrix oligonucleotide chips; (d) quantitation of protein expression by "reverse-phase" protein microarray; and (e) prospective validation of candidate markers on clinical tumor sections in tissue microarrays. The two best candidates identified were villin for colon cancer cells and moesin for ovarian cancer cells. Because moesin stained stromal elements in both types of cancer, it would probably not have been identified as a marker if we had started with mRNA or protein profiling of bulk tumors. Villin appears at least as useful as the currently used colon cancer marker cytokeratin 20, and moesin also appears to have utility. The multistep process introduced here has the potential to produce additional markers for cancer diagnosis, prognosis, and therapy.

Adenocarcinoma↗
PubMed2003

Induced dendritic cell differentiation of chronic myeloid leukemia blasts is associated with down-regulation of BCR-ABL.

Although differentiation of leukemic blasts to dendritic cells (DC) has promise in vaccine strategies, the mechanisms underlying this differentiation and the differences between leukemia and normal progenitor-derived DC are largely undescribed. In the case of chronic myeloid leukemia (CML), understanding the relationship between the induction of DC differentiation and the expression of the BCR-ABL oncogene has direct relevance to CML biology as well as the development of new therapeutic approaches. We now report that direct activation of protein kinase C (PKC) by the phorbol ester PMA in the BCR-ABL(+) CML cell line K562 and primary CML blasts induced nonterminal differentiation into cells with typical DC morphology (cytoplasmic dendrites), characteristic surface markers (MHC class I, MHC class II, CD86, CD40), chemokine and transcription factor expression, and ability to stimulate T cell proliferation (equivalent to normal monocyte-derived DC). PKC-induced differentiation was associated with down-regulation of BCR-ABL mRNA expression, protein levels, and kinase activity. This down-regulation appeared to be signaled through the mitogen-activated protein kinase pathway. Therefore, PKC-driven differentiation of CML blasts into DC-like cells suggests a potentially novel strategy to down-regulate BCR-ABL activity, yet raises the possibility that CML-derived DC vaccines will be less effective in presenting leukemia-specific Ags.

Blast Crisis↗
PubMed2003

Exploration, normalization, and summaries of high density oligonucleotide array probe level data.

In this paper we report exploratory analyses of high-density oligonucleotide array data from the Affymetrix GeneChip system with the objective of improving upon currently used measures of gene expression. Our analyses make use of three data sets: a small experimental study consisting of five MGU74A mouse GeneChip arrays, part of the data from an extensive spike-in study conducted by Gene Logic and Wyeth's Genetics Institute involving 95 HG-U95A human GeneChip arrays; and part of a dilution study conducted by Gene Logic involving 75 HG-U95A GeneChip arrays. We display some familiar features of the perfect match and mismatch probe (PM and MM) values of these data, and examine the variance-mean relationship with probe-level data from probes believed to be defective, and so delivering noise only. We explain why we need to normalize the arrays to one another using probe level intensities. We then examine the behavior of the PM and MM using spike-in data and assess three commonly used summary measures: Affymetrix's (i) average difference (AvDiff) and (ii) MAS 5.0 signal, and (iii) the Li and Wong multiplicative model-based expression index (MBEI). The exploratory data analyses of the probe level data motivate a new summary measure that is a robust multi-array average (RMA) of background-adjusted, normalized, and log-transformed PM values. We evaluate the four expression summary measures using the dilution study data, assessing their behavior in terms of bias, variance and (for MBEI and RMA) model fit. Finally, we evaluate the algorithms in terms of their ability to detect known levels of differential expression using the spike-in data. We conclude that there is no obvious downside to using RMA and attaching a standard error (SE) to this quantity using a linear model which removes probe-specific affinities.

Algorithms↗
PubMed2002

Transcriptional regulation of mitotic genes by camptothecin-induced DNA damage: microarray analysis of dose- and time-dependent effects.

cDNA microarray technology can be used to establish associations between characteristic gene expression patterns and molecular responses to drug therapy. In this study, we used cDNA microarrays of 1694 cancer-related genes to monitor the gene expression consequences of the treatment of HCT116 colon cancer cells with the topoisomerase I inhibitor camptothecin (CPT). To obtain a more homogeneous cellular response, we synchronized the cells in S-phase using aphidicolin (APH) before CPT treatment. Brief incubation with 20 and 1000 nM CPT caused reversible and irreversible G(2) arrest, respectively, and the patterns of gene expression change (with reference to untreated controls) were strikingly different at the two concentrations. Thirty-three genes, mainly divided into three groups, showed characteristic changes in the first 20 h as a consequence of treatment. Northern blots performed for five of these genes (each under eight experimental conditions) were quite consistent with the microarray results (average correlation coefficient, 0.86). Several p53-activated stress response genes were up-regulated after treatment with 1000 nM CPT or prolonged exposure to APH, but it seemed that the up-regulation did not directly cause cell cycle arrest because the up-regulation induced by prolonged treatment with APH did not prevent cell cycle progression after removal of APH. In contrast, cell cycle-dependent up-regulation of a group of mitosis-related genes was delayed or blocked after CPT treatments. The interrupted up-regulation of this group of genes was directly associated with G(2) arrest. In addition, we observed down-regulation of gene expression in cells that were recovering from cell cycle delay. The observations reported here suggest a fundamental difference at the gene expression level between the molecular mechanism of reversible G(2) delay that follows mild DNA damage and the mechanism of permanent G(2) arrest that follows more extensive DNA damage.

Aphidicolin↗