Biomedical subjects

Zixing Fang

Publications and source records attributed to Zixing Fang.

8 recordsLinked to original sources

PubMed2007

Matrix metalloproteinase-9 is differentially expressed in nonfunctioning invasive and noninvasive pituitary adenomas and increases invasion in human pituitary adenoma cell line.

The complete resection of pituitary adenomas (PAs) is unlikely when there is an extensive local dural invasion and given that the molecular mechanisms remain primarily unknown. DNA microarray analysis was performed to identify differentially expressed genes between nonfunctioning invasive and noninvasive PAs. Gene clustering revealed a robust eightfold increase in matrix metalloproteinase (MMP)-9 expression in surgically resected human invasive PAs and in the (nonfunctioning) HP75 human pituitary tumor-derived cell line treated with phorbol-12-myristate-13-acetate; these results were confirmed by real-time polymerase chain reaction, gelatin zymography, reverse transcriptase-polymerase chain reaction, Western blot, immunohistochemistry, and Northern blot analyses. The activation of protein kinase C (PKC) increased both MMP-9 activity and expression, which were blocked by some PKC inhibitors (Gö6976, bisindolylmaleimide, and Rottlerin), PKC-alpha, and PKC-delta small interfering (si)RNAs but not by hispidin (PKC-beta inhibitor). In a transmembrane invasion assay, phorbol-12-myristate-13-acetate (100 nmol/L) increased the number of invaded HP75 cells, a process that was attenuated by PKC inhibitors, MMP-9 antibody, PKC-alpha siRNA, or PKC-delta siRNA. These results demonstrate that MMP-9 and PKC-alpha or PKC-delta may provide putative therapeutic targets for the control of PA dural invasion.

Adenoma↗

PubMed2006

Gene connectivity, function, and sequence conservation: predictions from modular yeast co-expression networks.

BACKGROUND: Genes and proteins are organized into functional modular networks in which the network context of a gene or protein has implications for cellular function. Highly connected hub proteins, largely responsible for maintaining network connectivity, have been found to be much more likely to be essential for yeast survival. RESULTS: Here we investigate the properties of weighted gene co-expression networks formed from multiple microarray datasets. The constructed networks approximate scale-free topology, but this is not universal across all datasets. We show strong positive correlations between gene connectivity within the whole network and gene essentiality as well as gene sequence conservation. We demonstrate the preservation of a modular structure of the networks formed, and demonstrate that, within some of these modules, it is possible to observe a strong correlation between connectivity and essentiality or between connectivity and conservation within the modules particularly within modules containing larger numbers of essential genes. CONCLUSION: Application of these techniques can allow a finer scale prediction of relative gene importance for a particular process within a group of similarly expressed genes.

Base Sequence↗

PubMed2005

Targeted disruption of glycerol kinase gene in mice: expression analysis in liver shows alterations in network partners related to glycerol kinase activity.

Glycerol kinase deficiency (GKD) is an X-linked inborn error of metabolism with metabolic and neurological crises. Liver shows the highest level of glycerol kinase (GK) activity in humans and mice. Absence of genotype-phenotype correlations in patients with GKD indicates the involvement of modifier genes, including other network partners. To understand the molecular pathogenesis of GKD, we performed microarray analysis on liver mRNA from neonatal glycerol kinase (Gyk) knockout (KO) and wild-type (WT) mice. Unsupervised learning revealed that the overall gene expression profile of the KO mice was different from that of WT. Real-time PCR confirmed the differences for selected genes. Functional gene enrichment analysis was used to find 56 increased and 37 decreased gene functional categories. PathwayAssist analysis identified changes in gene expression levels of genes involved in organic acid metabolism indicating that GK was part of the same metabolic network which correlates well with the patients with GKD having metabolic acidemia during their episodic crises. Network component analysis (NCA) showed that transcription factors sterol regulatory element-binding protein (SREBP)-1c, carbohydrate response element-binding protein (ChREBP), hepatocyte nuclear factor-4 alpha (HNF-4alpha) and peroxisome proliferative-activated receptor-alpha (PPARalpha) had increased activity in the Gyk KO mice compared with WT mice, whereas SREBP-2 was less active in the Gyk KO mice. These studies show that Gyk deletion causes alterations in expression of genes in several regulatory networks and is the first time NCA has been used to expand on microarray data from a mouse KO model of a human disease.

Animals↗

PubMed2005

Distinct gene expression profiles in adult mouse heart following targeted MAP kinase activation.

Three major MAP kinase signaling cascades, ERK, p38, and JNK, play significant roles in the development of cardiac hypertrophy and heart failure in response to external stress and neural/hormonal stimuli. To study the specific function of each MAP kinase branch in adult heart, we have generated three transgenic mouse models with cardiac-specific and temporally regulated expression of activated mutants of Ras, MAP kinase kinase (MKK)3, and MKK7, which are selective upstream activators for ERK, p38, and JNK, respectively. Gene expression profiles in transgenic adult hearts were determined using cDNA microarrays at both early (4-7 days) and late (2-4 wk) time points following transgene induction. From this study, we revealed common changes in gene expression among the three models, particularly involving extracellular matrix remodeling. However, distinct expression patterns characteristic for each pathway were also identified in cell signaling, growth, and physiology. In addition, genes with dynamic expression differences between early vs. late stages illustrated primary vs. secondary changes on MAP kinase activation in adult hearts. These results provide an overview to both short-term and long-term effects of MAP kinase activation in heart and support some common as well as unique roles for each MAP kinase cascade in the development of heart failure.

Animals↗

PubMed2004

Gene expression profiling of gliomas strongly predicts survival.

In current clinical practice, histology-based grading of diffuse infiltrative gliomas is the best predictor of patient survival time. Yet histology provides little insight into the underlying biology of gliomas and is limited in its ability to identify and guide new molecularly targeted therapies. We have performed large-scale gene expression analysis using the Affymetrix HG U133 oligonucleotide arrays on 85 diffuse infiltrating gliomas of all histologic types to assess whether a gene expression-based, histology-independent classifier is predictive of survival and to determine whether gene expression signatures provide insight into the biology of gliomas. We found that gene expression-based grouping of tumors is a more powerful survival predictor than histologic grade or age. The poor prognosis samples could be grouped into three different poor prognosis groups, each with distinct molecular signatures. We further describe a list of 44 genes whose expression patterns reliably classify gliomas into previously unrecognized biological and prognostic groups: these genes are outstanding candidates for use in histology-independent classification of high-grade gliomas. The ability of the large scale and 44 gene set expression signatures to group tumors into strong survival groups was validated with an additional external and independent data set from another institution composed of 50 additional gliomas. This demonstrates that large-scale gene expression analysis and subset analysis of gliomas reveals unrecognized heterogeneity of tumors and is efficient at selecting prognosis-related gene expression differences which are able to be applied across institutions.

Adolescent↗

PubMed2004

Brain cancer mortality in the United States, 1986 to 1995: a geographic analysis.

The Atlas of Cancer Mortality in the United States, 1950-94 (Devesa et al.) published in 1999 by the National Institutes of Health suggests that there are elevated rates of brain and other nervous system cancer in the northwestern, north central, and southeastern parts of the country. Being descriptive in nature, the atlas does not evaluate whether observed patterns are simply due to random variation or if they are reflective of true geographical differences in disease risk or treatment practices. To formally test for geographical clustering of disease, we analyzed U.S. brain cancer mortality data from 1986 to 1995 with Tango's Excess Events test, the Cuzick-Edwards k-Nearest-Neighbors test, and the spatial scan statistic. All tests revealed statistically significant geographical clustering for both adult men and women. The spatial scan statistic indicated that the most likely cluster of high mortality was in parts of Arkansas, Mississippi, and Oklahoma (relative risk [RR] = 1.22, P < 0.0001) for women and in parts of Tennessee and Kentucky (RR = 1.15, P < 0.0001) for men. Several secondary clusters were detected, but there were no statistically significant clusters of a very localized nature and a high RR. For childhood brain cancer, there were no statistically significant geographical clusters. It is reassuring that no local brain cancer mortality "hot spots" with very high RRs were found. While the causes of the large geographical clusters with modest RRs are unclear, the geographical pattern of brain cancer mortality provides valuable information that can help in formulating etiological hypotheses and in targeting high-risk populations for further epidemiological and health services research.

Adolescent↗

PubMed2003

A tree-based scan statistic for database disease surveillance.

Many databases exist with which it is possible to study the relationship between health events and various potential risk factors. Among these databases, some have variables that naturally form a hierarchical tree structure, such as pharmaceutical drugs and occupations. It is of great interest to use such databases for surveillance purposes in order to detect unsuspected relationships to disease risk. We propose a tree-based scan statistic, by which the surveillance can be conducted with a minimum of prior assumptions about the group of occupations/drugs that increase risk, and which adjusts for the multiple testing inherent in the many potential combinations. The method is illustrated using data from the National Center for Health Statistics Multiple Cause of Death Database, looking at the relationship between occupation and death from silicosis.

Databases, Factual↗

PubMed2002

Retrospective evaluation and adjustment of dual energy X-ray absorptiometry measurements for bone mineral density research studies.

Dual-energy X-ray absorptiometry (DXA) is widely used for bone mineral density (BMD) measurements. Prospective daily quality control procedures such as cumulative sum (CUSUM) plots and Shewhart charts are very important and commonly used for routine monitoring of DXA measurements. These procedures are less suitable for post hoc adjustment of DXA measurements for clinical research studies, if and when that is needed. Extending previous methods, we propose and illustrate a simple statistical method for retrospective quality evaluation that may be used to adjust BMD measurements before they are analyzed in clinical research studies. Using multivariate regression, this method allows for simultaneous adjustment of different types of temporal variation such as sudden jumps, simple linear trends, changes in the slope of these trends, quadratic terms, and seasonal fluctuations. Adjusting the measurements to account for different types of temporal trends decreases the variance of bone mass density measurements and is an inexpensive way to increase the power of a study without increasing the sample size. The method is illustrated with measurements of two different phantoms used on the same DXA, with 2 and 3 yr of data, respectively. Results were consistent for both phantoms, with a gradual trend and a sudden jump, as well as a seasonal fluctuation term.

Absorptiometry, Photon↗