Biomedical subjects

Qing-Rong Chen

Publications and source records attributed to Qing-Rong Chen.

9 recordsLinked to original sources

PubMed2006

Increased WSB1 copy number correlates with its over-expression which associates with increased survival in neuroblastoma.

Gain of chromosome 17 is the most prevalent genetic abnormality identified in neuroblastoma (NB) and distal 17q gain has prognostic significance in NB. In this report, we have combined array-based comparative genomic hybridization (A-CGH) and gene expression analysis to investigate gene copy number changes and its impact on the gene expression level as well as their association with prognosis genes located on chromosome 17 in NB tumors. We observed differential gains of chromosome 17 between Stages 4- and 4S tumors. We found that WSB1, mapping to 17q11.1, which was frequently gained in 4S- tumors and not changed in 4- tumors, showed strong correlations between expression level and copy number. Furthermore, the increase of WSB1 gene expression is associated with good outcome in patients with NB of all stages. WSB1 also enhances the prognostic prediction when combined with other current prognostic factors in NB. Our results demonstrate that WSB1 copy number correlates with its expression level and that its high expression associates with good prognosis suggesting a possible role of this gene in the biology of favorable outcome NB. This article contains Supplementary Material available at http://www.interscience.wiley.com/jpages/1045-2257/suppmat.

Cell Line, Tumor↗

PubMed2005

High-resolution cDNA microarray-based comparative genomic hybridization analysis in neuroblastoma.

Neuroblastoma (NB) is one of the most common pediatric solid tumors and displays a broad variety of genomic alterations. Array-based comparative genomic hybridization (A-CGH) is a novel technology enabling the high-resolution detection of DNA copy number aberrations. In this article, we outline features of this new technology and approaches of data analysis. We focus on stage specific DNA copy number variations in neuroblastoma detected by cDNA array-based comparative genomic hybridization (A-CGH). We also discuss hypothetic evolutionary models of neuroblastoma progression that can be derived from A-CGH data.

DNA, Complementary↗

PubMed2005

Inferring a tumor progression model for neuroblastoma from genomic data.

PURPOSE: The knowledge of the key genomic events that are causal to cancer development and progression not only is invaluable for our understanding of cancer biology but also may have a direct clinical impact. The task of deciphering a model of tumor progression by requiring that it explains (or at least does not contradict) known clinical and molecular evidence can be very demanding, particularly for cancers with complex patterns of clinical and molecular evidence. MATERIALS AND METHODS: We formalize the process of model inference and show how a progression model for neuroblastoma (NB) can be inferred from genomic data. The core idea of our method is to translate the model of clonal cancer evolution to mathematical testable rules of inheritance. Seventy-eight NB samples in stages 1, 4S, and 4 were analyzed with array-based comparative genomic hybridization. RESULTS: The pattern of recurrent genomic alterations in NB is strongly stage dependent and it is possible to identify traces of tumor progression in this type of data. CONCLUSION: A tumor progression model for neuroblastoma is inferred, which is in agreement with clinical evidence, explains part of the heterogeneity of the clinical behavior observed for NB, and is compatible with existing empirical models of NB progression.

Child↗

PubMed2005

Altered expression of cell cycle genes distinguishes aggressive neuroblastoma.

In this study, gene expression profiling was performed on 103 neuroblastoma (NB) tumors, stages 1-4 with and without MYCN amplification, using cDNA microarrays containing 42,578 elements. Using principal component analysis (PCA) to analyse the relationships among these samples, we confirm that the global patterns of gene expression reflect the phenotype of the tumors. To explore the biological processes that may contribute to increasing aggressive phenotype of the tumors, we utilized a statistical approach based on PCA. We identified a specific subset of the cell cycle and/or chromosome segregation genes that distinguish stage 4 NB tumors from all lower stage tumors, including stage 3. Furthermore, the control of the kinetochore assembly emerges from the Gene Ontology analysis as one of the key biological processes associated with an aggressive NB phenotype. Finally, we establish that these genes are further upregulated in the most aggressive MYCN-amplified tumors.

Cell Cycle↗

PubMed2005

Database of mRNA gene expression profiles of multiple human organs.

Genome-wide expression profiling of normal tissue may facilitate our understanding of the etiology of diseased organs and augment the development of new targeted therapeutics. Here, we have developed a high-density gene expression database of 18,927 unique genes for 158 normal human samples from 19 different organs of 30 different individuals using DNA microarrays. We report four main findings. First, despite very diverse sample parameters (e.g., age, ethnicity, sex, and postmortem interval), the expression profiles belonging to the same organs cluster together, demonstrating internal stability of the database. Second, the gene expression profiles reflect major organ-specific functions on the molecular level, indicating consistency of our database with known biology. Third, we demonstrate that any small (i.e., n approximately 100), randomly selected subset of genes can approximately reproduce the hierarchical clustering of the full data set, suggesting that the observed differential expression of >90% of the probed genes is of biological origin. Fourth, we demonstrate a potential application of this database to cancer research by identifying 19 tumor-specific genes in neuroblastoma. The selected genes are relatively underexpressed in all of the organs examined and belong to therapeutically relevant pathways, making them potential novel diagnostic markers and targets for therapy. We expect this database will be of utility for developing rationally designed molecularly targeted therapeutics in diseases such as cancer, as well as for exploring the functions of genes.

Cluster Analysis↗

PubMed2004

Detection of low level genomic alterations by comparative genomic hybridization based on cDNA micro-arrays.

MOTIVATION: The accumulation of genomic alterations is an important process in tumor formation and progression. Comparative genomic hybridization performed on cDNA arrays (cDNA aCGH) is a common method to investigate the genomic alterations on a genome-wide scale. However, when detecting low-level DNA copy number changes this technology requires the use of noise reduction strategies due to a low signal to noise ratio. RESULTS: Currently a running average smoothing filter is the most frequently used noise reduction strategy. We analyzed this strategy theoretically and experimentally and found that it is not sensitive to very low level genomic alterations. The presence of systematic errors in the data is one of the main reasons for this failure. We developed a novel algorithm which efficiently reduces systematic noise and allows for the detection of low-level genomic alterations. The algorithm is based on comparison of the biological relevant data to data from so-called self-self hybridizations, additional experiments which contain no biological information but contain systematic errors. We find that with our algorithm the effective resolution for +/-1 DNA copy number changes is about 2 Mb. For copy number changes larger than three the effective resolution is on the level of single genes.

Algorithms↗

PubMed2004

Prediction of clinical outcome using gene expression profiling and artificial neural networks for patients with neuroblastoma.

Currently, patients with neuroblastoma are classified into risk groups (e.g., according to the Children's Oncology Group risk-stratification) to guide physicians in the choice of the most appropriate therapy. Despite this careful stratification, the survival rate for patients with high-risk neuroblastoma remains <30%, and it is not possible to predict which of these high-risk patients will survive or succumb to the disease. Therefore, we have performed gene expression profiling using cDNA microarrays containing 42,578 clones and used artificial neural networks to develop an accurate predictor of survival for each individual patient with neuroblastoma. Using principal component analysis we found that neuroblastoma tumors exhibited inherent prognostic specific gene expression profiles. Subsequent artificial neural network-based prognosis prediction using expression levels of all 37,920 good-quality clones achieved 88% accuracy. Moreover, using an artificial neural network-based gene minimization strategy in a separate analysis we identified 19 genes, including 2 prognostic markers reported previously, MYCN and CD44, which correctly predicted outcome for 98% of these patients. In addition, these 19 predictor genes were able to additionally partition Children's Oncology Group-stratified high-risk patients into two subgroups according to their survival status (P = 0.0005). Our findings provide evidence of a gene expression signature that can predict prognosis independent of currently known risk factors and could assist physicians in the individual management of patients with high-risk neuroblastoma.

Antineoplastic Combined Chemotherapy Protocols↗

PubMed2004

cDNA array-CGH profiling identifies genomic alterations specific to stage and MYCN-amplification in neuroblastoma.

BACKGROUND: Recurrent non-random genomic alterations are the hallmarks of cancer and the characterization of these imbalances is critical to our understanding of tumorigenesis and cancer progression. RESULTS: We performed array-comparative genomic hybridization (A-CGH) on cDNA microarrays containing 42,000 elements in neuroblastoma (NB). We found that only two chromosomes (2p and 12q) had gene amplifications and all were in the MYCN amplified samples. There were 6 independent non-contiguous amplicons (10.4-69.4 Mb) on chromosome 2, and the largest contiguous region was 1.7 Mb bounded by NAG and an EST (clone: 757451); the smallest region was 27 Kb including an EST (clone: 241343), NCYM, and MYCN. Using a probabilistic approach to identify single copy number changes, we systemically investigated the genomic alterations occurring in Stage 1 and Stage 4 NBs with and without MYCN amplification (stage 1-, 4-, and 4+). We have not found genomic alterations universally present in all (100%) three subgroups of NBs. However we identified both common and unique patterns of genomic imbalance in NB including gain of 7q32, 17q21, 17q23-24 and loss of 3p21 were common to all three categories. Finally we confirm that the most frequent specific changes in Stage 4+ tumors were the loss of 1p36 with gain of 2p24-25 and they had fewer genomic alterations compared to either stage 1 or 4-, indicating that for this subgroup of poor risk NB requires a smaller number of genomic changes are required to develop the malignant phenotype. CONCLUSIONS: cDNA A-CGH analysis is an efficient method for the detection and characterization of amplicons. Furthermore we were able to detect single copy number changes using our probabilistic approach and identified genomic alterations specific to stage and MYCN amplification.

Cell Line, Tumor↗

PubMed2002

Optimal transfection with the HK polymer depends on its degree of branching and the pH of endocytic vesicles.

We have recently reported that liposomes in combination with histidine (HK)-containing polymers enhanced the expression of luciferase in transfected cells. In transformed or malignant cell lines, branched HK polymers (combined with liposome carriers) were significantly more effective than the linear HK polymer in stimulating gene expression. In the current study, we found that the linear HK polymer enhanced gene expression in primary cell lines more effectively than the branched polymers. The differences in the optimal carrier (linear versus branched) were not due to initial cellular uptake, size of the complexes or level of gene expression. There was, however, a strong association between the optimal type of HK polymer and the pH of endocytic vesicles (P = 0.0058). By altering the percentage of histidines carrying a positive charge, the endosomal pH of a cell may determine the amount of DNA released from the linear or branched HK polymer. In the two cell lines in which the linear HK was the optimal polymer, the endocytic vesicles were strongly acidic with a pH of <5.0. Conversely, in the four cell lines in which the branched polymers were optimal transfection agents, the pH of endocytic vesicles was >6.0. Furthermore, binding data support the relationship between DNA release from the optimal HK polymer and endosomal pH. The interplay between optimal HK polymers and the endosomal pH may lead to improved gene-delivery polymers tailored to a particular cell.

Animals↗