Biomedical subjects

Qian Xie

Publications and source records attributed to Qian Xie.

At least 19 recordsLinked to original sources

PubMed2026

DNA hypermethylation of abscisic-acid-related genes helps enhance the cold tolerance of tetraploid rice.

Polyploid plants exhibit enhanced stress resistance and superior adaptability to extreme environments, but the underlying molecular mechanisms remain incompletely understood. Here we confirm that tetraploid rice exhibits stronger cold tolerance than diploid rice. This improved tolerance is mediated by reduced malondialdehyde accumulation, elevated antioxidant enzyme activity, and epigenetic regulation of genes involved in abscisic acid (ABA) biosynthesis and signaling. Under cold stress, tetraploid rice induces stress-responsive genes (especially in the ABA pathway) more rapidly and to higher levels than diploid rice. This enhanced gene expression coincides with increased endogenous ABA accumulation. Furthermore, polyploidization and cold stress synergistically induce high methylation at CG, CHG, and CHH sites in genes and transposons (TEs). Notably, the methylation level of class II TEs in tetraploid rice is significantly higher than in diploid rice under low temperatures. To suppress TE activation in gene promoter regions under cold stress, tetraploid rice enhances the methylation level of ABA pathway-related gene promoters, thereby silencing TEs and maintaining genome stability. Collectively, these results enrich the theoretical understanding of the strong stress tolerance in polyploid plants and provide theoretical support for breeding cold-tolerant polyploid rice varieties.

ABA↗

PubMed2025

Efficacy of MET-targeting CAR T cells against glioblastoma patient-derived xenograft models.

BACKGROUND: Genetic alteration of the MET receptor tyrosine kinase frequently occurs in glioblastoma (GBM). Clinically, bevacizumab treatment results in MET signaling activation, leading to GBM recurrence with a more malignant phenotype. While MET has been a promising therapeutic target, MET inhibitors have not been successful in treating GBM patients. MET-directed chimeric antigen receptor (CAR) T cells hold the promise of targeting MET-positive GBM regardless of genetic alterations or kinase activity. METHODS: GBM patient-derived xenografts (PDX) harboring MET amplification (METamp) or PTPRZ-MET fusion (ZM) were propagated in vivo followed by glioma stem cell (GSC) isolation. Cell-based assays were used for comparing GSC survival in response to MET inhibitors and CAR T cells. Multi-panel cytokine release was analyzed to profile MET-CAR T cell activation during co-culture with GBM. Orthotopic tumor growth and real-time imaging were performed to evaluate MET-CAR T cell therapeutic efficacy in vivo. RESULTS: Although GBM are heterogeneous tumors, neuro-sphere cells isolated from METamp or ZM fusion PDX tumors showed universal cognate genetic MET alteration along with GSC markers such as SOX2 and nestin. Both METamp and ZM fusion tumors showed MET overexpression but only the METamp cells presented activated MET signaling which was vulnerable to MET inhibitors. In contrast, MET-CAR T cells specifically inhibited all MET-positive tumor growth regardless of MET activation status. CONCLUSIONS: Whereas MET inhibitors are effective in MET-active tumors, MET-CAR T cells eradicate MET-positive GBM growth in an antigen-dependent manner, demonstrating a promising therapeutic approach for treating MET-positive GBM. MET overexpression, especially METamp and ZM fusion may be used to predefine the GBM patients for treating with MET-CAR T cell therapy.

Glioblastoma↗

PubMed2006

Gene expression profile exploration of a large dataset on chronic fatigue syndrome.

OBJECTIVE: To gain understanding of the molecular basis of chronic fatigue syndrome (CFS) through gene expression analysis using a large microarray data set in conjunction with clinically administrated questionnaires. METHOD: Data from the Wichita (KS, USA) CFS Surveillance Study was used, comprising 167 participants with two self-report questionnaires (multidimensional fatigue inventory [MFI] and Zung depression scale [Zung]), microarray data, empiric classification, and others. Microarray data was analyzed using bioinformatics tools from ArrayTrack. RESULTS: Correspondence analysis was applied to the MFI questionnaire to select the 23 samples having either the most or the least fatigue, and to the Zung questionnaire to select the 26 samples having either the most or least depression; ten samples were common, resulting in a total of 39 samples. The MFI and Zung-based CFS/non-CFS (NF) classifications on the 39 samples were consistent with the empiric classification. Two differentially-expressed gene lists were determined, 188 fatigue-related genes and 164 depression-related genes, which shared 24 common genes and involved 11 common pathways. Principal component analysis based on 24 genes clearly separates 39 samples with respect to their likelihood to be CFS. Most of the 24 genes are not previously reported for CFS, yet their functions are consistent with the prevailing model of CFS, such as immune response, apoptosis, ion channel activity, signal transduction, cell-cell signaling, regulation of cell growth and neuronal activity. Hierarchical cluster analysis was performed based on 24 genes to classify 128 (=167-39) unassigned samples. Several of the 11 identified common pathways are supported by earlier findings for CFS, such as cytokine-cytokine receptor interaction and neuroactive ligand-receptor interaction. Importantly, most of the 11 common pathways are interrelated, suggesting complex biological mechanisms associated with CFS. CONCLUSION: Bioinformatics is critical in this study to select definitive sample groups, analyze gene expression data and gain insight into biological mechanisms. The 24 identified common genes and 11 common pathways could be important in future studies of CFS at the molecular level.

Adult↗

PubMed2006

[Synthetic radiation-inducible promoter mediated CDglyTK gene in treatment of Tca8113 cells].

OBJECTIVE: To observe the therapeutic effect of CDglyTK gene mediated by synthetic radiation-inducible promoter in the treatment of Tca8113 cells. METHODS: CDglyTK gene in pCEA-CDglyTK was subcloned into pcDNA3.1 (+) to construct plasmid pcDNA3.1 (+)-CDglyTK, and then the synthetic radiation-inducible promoter in pMD18 -T -E was inserted into pcDNA3.1 (+) -CDglyTK to construct plasmid pcDNA3.1 (+ )/E -CDglyTK. The recombinant plasmid was transfected into Tca8113 cells by lipofectamine, and then exposed to 3 Gy irradiation. Cytotoxicity was evaluated by MTT. The expression of CDglyTK gene was detected by RT-PCR. The apoptosis and proliferation were examined by flow cytomtery. RESULTS: The plasmid pcDNA3.1 (+)/E-CDglyTK was constructed successfully. The comparative survival rate of Tca8113 cells was markedly decreased by induction irradiation. Up-regulation of CDglyTK expression was found in Tca8113 cells exposed to irradiation. The apoptosis index (AI) of Tca8113 cells exposed to irradiation was higher than that of Tca8113 cells without irradiation, the other way round, the proliferation index (PI) of Tca8113 cells exposed to irradiation was lower than that of Tca8113 cells without irradiation. CONCLUSION: The synthetic radiation-inducible promoter can be served as a molecular switch to improve the expression of CDglyTK gene in Tca8113 cells, and low dose induction radiation can significantly improve the therapeutic efficiency.

Apoptosis↗

PubMed2005

Geldanamycin derivative inhibition of HGF/SF-mediated Met tyrosine kinase receptor-dependent urokinase-plasminogen activation.

Ansamycins, including geldanamycin and the derivative 17-allylamino-17-demethoxygeldanamycin, and radicicol are known for their ability to tightly bind to the ATP-binding site of the amino-terminal domain region of heat shock protein 90. We have found that geldanamycin and some of its derivatives can inhibit hepatocyte growth factor/scatter factor-mediated Met tyrosine kinase receptor-dependent urokinase-plasminogen activation at femtomolar levels. Assessment is made of structural requirements for such an activity and evidence is given that distinguishes the target of such an activity from that of heat shock protein 90.

Benzoquinones↗

PubMed2005

Proliferation and invasion: plasticity in tumor cells.

Invasive and proliferative phenotypes are fundamental components of malignant disease, yet basic questions persist about whether tumor cells can express both phenotypes simultaneously and, if so, what are their properties. Suitable in vitro models that allow characterization of cells that are purely invasive are limited because proliferation is required for cell maintenance. Here, we describe glioblastoma cells that are highly invasive in response to hepatocyte growth factor/scatter factor (HGF/SF). From this cell population, we selected subclones that were highly proliferative or displayed both invasive and proliferative phenotypes. The biological activities of invasion, migration, urokinase-type plasminogen activation, and branching morphogenesis exclusively partitioned with the highly invasive cells, whereas the highly proliferative subcloned cells uniquely displayed anchorage independent growth in soft agar and were highly tumorigenic as xenografts in immune-compromised mice. In response to HGF/SF, the highly invasive cells signal through the MAPK pathway, whereas the selection of the highly proliferative cells coselected for signaling through Myc. Moreover, in subcloned cells displaying both invasive and proliferative phenotypes, both signaling pathways are activated by HGF/SF. These results show how the mitogen-activated protein kinase and Myc pathways can cooperate to confer both invasive and proliferative phenotypes on tumor cells and provide a system for studying how transitions between invasion and proliferation can contribute to malignant progression.

Animals↗

PubMed2005

Microarray scanner calibration curves: characteristics and implications.

BACKGROUND: Microarray-based measurement of mRNA abundance assumes a linear relationship between the fluorescence intensity and the dye concentration. In reality, however, the calibration curve can be nonlinear. RESULTS: By scanning a microarray scanner calibration slide containing known concentrations of fluorescent dyes under 18 PMT gains, we were able to evaluate the differences in calibration characteristics of Cy5 and Cy3. First, the calibration curve for the same dye under the same PMT gain is nonlinear at both the high and low intensity ends. Second, the degree of nonlinearity of the calibration curve depends on the PMT gain. Third, the two PMTs (for Cy5 and Cy3) behave differently even under the same gain. Fourth, the background intensity for the Cy3 channel is higher than that for the Cy5 channel. The impact of such characteristics on the accuracy and reproducibility of measured mRNA abundance and the calculated ratios was demonstrated. Combined with simulation results, we provided explanations to the existence of ratio underestimation, intensity-dependence of ratio bias, and anti-correlation of ratios in dye-swap replicates. We further demonstrated that although Lowess normalization effectively eliminates the intensity-dependence of ratio bias, the systematic deviation from true ratios largely remained. A method of calculating ratios based on concentrations estimated from the calibration curves was proposed for correcting ratio bias. CONCLUSION: It is preferable to scan microarray slides at fixed, optimal gain settings under which the linearity between concentration and intensity is maximized. Although normalization methods improve reproducibility of microarray measurements, they appear less effective in improving accuracy.

Calibration↗

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

Decision forest analysis of 61 single nucleotide polymorphisms in a case-control study of esophageal cancer; a novel method.

BACKGROUND: Systematic evaluation and study of single nucleotide polymorphisms (SNPs) made possible by high throughput genotyping technologies and bioinformatics promises to provide breakthroughs in the understanding of complex diseases. Understanding how the millions of SNPs in the human genome are involved in conferring susceptibility or resistance to disease, or in rendering a drug efficacious or toxic in the individual is a major goal of the relatively new fields of pharmacogenomics. Esophageal squamous cell carcinoma is a high-mortality cancer with complex etiology and progression involving both genetic and environmental factors. We examined the association between esophageal cancer risk and patterns of 61 SNPs in a case-control study for a population from Shanxi Province in North Central China that has among the highest rates of esophageal squamous cell carcinoma in the world. METHODS: High-throughput Masscode mass spectrometry genotyping was done on genomic DNA from 574 individuals (394 cases and 180 age-frequency matched controls). SNPs were chosen from among genes involving DNA repair enzymes, and Phase I and Phase II enzymes. We developed a novel adaptation of the Decision Forest pattern recognition method named Decision Forest for SNPs (DF-SNPs). The method was designated to analyze the SNP data. RESULTS: The classifier in separating the cases from the controls developed with DF-SNPs gave concordance, sensitivity and specificity, of 94.7%, 99.0% and 85.1%, respectively; suggesting its usefulness for hypothesizing what SNPs or combinations of SNPs could be involved in susceptibility to esophageal cancer. Importantly, the DF-SNPs algorithm incorporated a randomization test for assessing the relevance (or importance) of individual SNPs, SNP types (Homozygous common, heterozygous and homozygous variant) and patterns of SNP types (SNP patterns) that differentiate cases from controls. For example, we found that the different genotypes of SNP GADD45B E1122 are all associated with cancer risk. CONCLUSION: The DF-SNPs method can be used to differentiate esophageal squamous cell carcinoma cases from controls based on individual SNPs, SNP types and SNP patterns. The method could be useful to identify potential biomarkers from the SNP data and complement existing methods for genotype analyses.

Algorithms↗

PubMed2005

Quality control and quality assessment of data from surface-enhanced laser desorption/ionization (SELDI) time-of flight (TOF) mass spectrometry (MS).

BACKGROUND: Proteomic profiling of complex biological mixtures by the ProteinChip technology of surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry (MS) is one of the most promising approaches in toxicological, biological, and clinic research. The reliable identification of protein expression patterns and associated protein biomarkers that differentiate disease from health or that distinguish different stages of a disease depends on developing methods for assessing the quality of SELDI-TOF mass spectra. The use of SELDI data for biomarker identification requires application of rigorous procedures to detect and discard low quality spectra prior to data analysis. RESULTS: The systematic variability from plates, chips, and spot positions in SELDI experiments was evaluated using biological and technical replicates. Systematic biases on plates, chips, and spots were not found. The reproducibility of SELDI experiments was demonstrated by examining the resulting low coefficient of variances of five peaks presented in all 144 spectra from quality control samples that were loaded randomly on different spots in the chips of six bioprocessor plates. We developed a method to detect and discard low quality spectra prior to proteomic profiling data analysis, which uses a correlation matrix to measure the similarities among SELDI mass spectra obtained from similar biological samples. Application of the correlation matrix to our SELDI data for liver cancer and liver toxicity study and myeloma-associated lytic bone disease study confirmed this approach as an efficient and reliable method for detecting low quality spectra. CONCLUSION: This report provides evidence that systematic variability between plates, chips, and spots on which the samples were assayed using SELDI based proteomic procedures did not exist. The reproducibility of experiments in our studies was demonstrated to be acceptable and the profiling data for subsequent data analysis are reliable. Correlation matrix was developed as a quality control tool to detect and discard low quality spectra prior to data analysis. It proved to be a reliable method to measure the similarities among SELDI mass spectra and can be used for quality control to decrease noise in proteomic profiling data prior to data analysis.

Female↗

PubMed2005

Geldanamycins exquisitely inhibit HGF/SF-mediated tumor cell invasion.

Induction of the urokinase-type plasminogen activator (uPA) by hepatocyte growth factor/scatter factor (HGF/SF) plays an important role in tumor cell invasion and metastasis that is mediated through the Met receptor tyrosine kinase. Geldanamycins (GA) are antitumor drugs that bind and inhibit HSP90 chaperone activity at nanomolar concentrations (nM-GAi) by preventing proper folding and functioning of certain oncoproteins. Previously, we have shown that a subset of GA derivatives exhibit exquisite potency, inhibiting HGF/SF-induced uPA-plasmin activation at femtomolar concentrations (fM-GAi) in canine MDCK cells. Here, we report that (1) inhibition of HGF/SF-induced uPA activity by fM-GAi is not uncommon, in that several human tumor glioblastoma cell lines (DBTRG, U373 and SNB19), as well as SK-LMS-1 human leiomyosarcoma cells are also sensitive to fM-GAi; (2) fM-GAi drugs only display inhibitory activity against HGF/SF-induced uPA activity (rather than basal activity), and only when the observed magnitude of uPA activity induction by HGF/SF is at least 1.5 times basal uPA activity; and (3) not only do fM-GAi derivatives strongly inhibit uPA activity but they also block MDCK cell scattering and in vitro invasion of human glioblastoma cells at similarly low drug concentrations. These effects of fM-GAi drugs on the Met-activated signaling pathway occur at concentrations well below those required to measurably affect Met expression or cell proliferation. We also examined the effect of Radicicol (RA), a drug with higher affinity than GA for HSP90. RA displays uPA activity inhibition at nanomolar levels, but not at lower concentrations, indicating that HSP90 is not likely the fM-GAi molecular target. Thus, we show that certain GA drugs (fM-GAi) in an HGF/SF-dependent manner block uPA-plasmin activation in tumor cells at femtomolar levels. This inhibition can also be observed in scattering and in vitro invasion assays. Our findings also provide strong circumstantial evidence for a novel non-HSP90 molecular target that is involved in HGF/SF-mediated tumor cell invasion.

Animals↗

PubMed2005

[The effect of galla chinensis on the growth of cariogenic bacteria in vitro].

OBJECTIVE: The purples of this study was to investigate the role of different components of Galla Chinensis extract on the growth of 6 kinds of cariogenic bacteria, and to find out the most effective components of Galla Chinensis extract. METHODS: Four different components (GCE1, GCE2, GCE3 and GCE4) were separated from Galla Chinensis and there antibacterial activities to Streptococcus mutans ATCC 25175, Streptococcus sanguis ATCC 10556, Streptococcus salivarius SS 196, Actinomyces naeslundii WVU 627, Actinomyces viscosus ATCC 19246 and Lactobacillus rhamnosus AC 413 were checked. There effects on the growth curve of Streptococcus mutans ATCC 25175 were also investigated. RESULTS: The most effective part of Galla Chinensis was found to be GCE2 and GCE4, which were found to be a mixture of polyphenol-rich fractions. All of the different components had an inhibitory effect to the growth of Streptococcus mutans ATCC 25175. CONCLUSION: All of the 4 different components of Galla Chinensis extract could inhibit the growth of the tested bacteria. These results suggest that the antibacterial activity of Galla Chinensis extract is caused by a synergistic effect of monomeric polyphenols, which can easily bind to proteins.

Actinomyces viscosus↗

PubMed2005

[An in vitro study on effect of Nidus vespae extract on the acid production of three strains of oral bacteria].

OBJECTIVE: To inquire into the effect of different of Nidus Vespae extract (NVE) on growth and acid production of Streptococcus mutans, Streptococcus sanguis and Actinomyces viscosus. METHODS: Streptococcus mutans ATCC 25175, Streptococcus sanguis ATCC 10556 and Actinomyces viscosus ATCC 19246 were chosen as the experimental bacteria. Four extracts of Nidus Vespae were prepared and then the effects of these Nidus Vespae extracts on the acid production were determined. RESULTS: All of Nidus Vespae extracts could inhibit the growth the of the three strains, and NVE1, NVE3, NVE4 could inhibit the acid production of the three strains, NVE2 could inhibit the acid production of Actinomyces viscosus. CONCLUSION: Four extracts of Nidus Vespae could inhibit the acid production of three bacteria strains.

Acids↗

PubMed2005

[Clinical study on reconstruction of hemifacial atrophy with serratus anterior free-muscle flap].

OBJECTIVE: To study the method of treating hemifacial atrophy with free serratus muscle flap. METHODS: Three patients diagnosed as having serious hemifacial atrophy was treated with free serratus muscle flap. The root of the flap was thoracodorsal artery and thoracodorsal vein, which was anastomosed with superficial temporal artery and vein, facial artery and vein, lingual artery and vein, and so on. During the operation, long thoracic nerve was dissected and anastomosed with facial nerve. The sizes of the flaps were 12 cm x 8 cm - 16 cm x 12 cm. RESULTS: All free-muscle flaps healed well after the transplant. The face and buccal area looked chubby and rounded. There were no obvious protuberance and discontentment on the buccal area. The shoulders of all patients moved well. The facial contour of the patients recovered well during the follow-up period (1-3 years). CONCLUSION: The method has a good result. The long-term effect needs further study.

Adolescent↗

PubMed2004

RNA interference reveals that ligand-independent met activity is required for tumor cell signaling and survival.

Hepatocyte growth factor/scatter factor-Met signaling has been implicated in tumor growth, invasion, and metastasis. Suppression of this signaling pathway by targeting the Met protein tyrosine kinase may be an ideal strategy for suppressing malignant tumor growth. Using RNA interference technology and adenovirus vectors carrying small-interfering RNA constructs (Ad Met small-interfering RNA) directed against mouse, canine, and human Met, we can knock down c-met mRNA. We show a dramatic dependence on Met in both ligand-dependent and ligand-independent mouse, canine, and human tumor cell lines. Mouse mammary tumor (DA3) cells and Met-transformed NIH3T3 (M114) cells, as well as both human and canine prostate cancer (PC-3 and TR6LM, human sarcoma (SK-LMS-1), glioblastoma (DBTRG), and gastric cancer (MKN45) cells, all display a dramatic reduction of Met expression after infection with Ad Met small-interfering RNA. In these cells, we observe suppression of tumor cell growth and viability in vitro as well as inhibition of hepatocyte growth factor/scatter factor-mediated scattering and invasion in vitro, whether Met activation was ligand dependent or not. Importantly, Ad Met small-interfering RNA led to apoptotic cell death in many of the tumor cell lines, especially DA3 and MKN45, but did not adversely affect MDCK canine kidney cells. Met small-interfering RNA also abrogated downstream Met signaling to molecules such as Akt and p44/42 mitogen-activated protein kinase. We further show that intratumoral infection with c-met small-interfering RNA adenovirus results in a substantial reduction in tumor growth. Thus, Met small-interfering RNA adenoviruses are reliable tools for studying Met function and raise the possibility of their application for cancer therapy.

Adenoviridae↗

PubMed2004

Building an organ-specific carcinogenic database for SAR analyses.

FDA reviewers need a means to rapidly predict organ-specific carcinogenicity to aid in evaluating new chemicals submitted for approval. This research addressed the building of a database to use in developing a predictive model for such an application based on structure-activity relationships (SAR). The Internet availability of the Carcinogenic Potency Database (CPDB) provided a solid foundation on which to base such a model. The addition of molecular structures to the CPDB provided the extra ingredient necessary for SAR analyses. However, the CPDB had to be compressed from a multirecord to a single record per chemical database; multiple records representing each gender, species, route of administration, and organ-specific toxicity had to be summarized into a single record for each study. Multiple studies on a single chemical had to be further reduced based on a hierarchical scheme. Structural cleanup involved removal of all chemicals that would impede the accurate generation of SAR type descriptors from commercial software programs; that is, inorganic chemicals, mixtures, and organometallics were removed. Counterions such as Na, K, sulfates, hydrates, and salts were also removed for structural consistency. Structural modification sometimes resulted in duplicate records that also had to be reduced to a single record based on the hierarchical scheme. The modified database containing 999 chemicals was evaluated for liver-specific carcinogenicity using a variety of analysis techniques. These preliminary analyses all yielded approximately the same results with an overall predictability of about 63%, which was comprised of a sensitivity of about 30% and a specificity of about 77%.

Animals↗

PubMed2004

Development of public toxicogenomics software for microarray data management and analysis.

A robust bioinformatics capability is widely acknowledged as central to realizing the promises of toxicogenomics. Successful application of toxicogenomic approaches, such as DNA microarray, inextricably relies on appropriate data management, the ability to extract knowledge from massive amounts of data and the availability of functional information for data interpretation. At the FDA's National Center for Toxicological Research (NCTR), we are developing a public microarray data management and analysis software, called ArrayTrack. ArrayTrack is Minimum Information About a Microarray Experiment (MIAME) supportive for storing both microarray data and experiment parameters associated with a toxicogenomics study. A quality control mechanism is implemented to assure the fidelity of entered expression data. ArrayTrack also provides a rich collection of functional information about genes, proteins and pathways drawn from various public biological databases for facilitating data interpretation. In addition, several data analysis and visualization tools are available with ArrayTrack, and more tools will be available in the next released version. Importantly, gene expression data, functional information and analysis methods are fully integrated so that the data analysis and interpretation process is simplified and enhanced. ArrayTrack is publicly available online and the prospective user can also request a local installation version by contacting the authors.

Databases, Genetic↗

PubMed2004

Multiclass Decision Forest--a novel pattern recognition method for multiclass classification in microarray data analysis.

The wealth of knowledge imbedded in gene expression data from DNA microarrays portends rapid advances in both research and clinic. Turning the prodigious and noisy data into knowledge is a challenge to the field of bioinformatics, and development of classifiers using supervised learning techniques is the primary methodological approach for clinical application using gene expression data. In this paper, we present a novel classification method, multiclass Decision Forest (DF), that is the direct extension of the two-class DF previously developed in our lab. Central to DF is the synergistic combining of multiple heterogenic but comparable decision trees to reach a more accurate and robust classification model. The computationally inexpensive multiclass DF algorithm integrates gene selection and model development, and thus eliminates the bias of gene preselection in crossvalidation. Importantly, the method provides several statistical means for assessment of prediction accuracy, prediction confidence, and diagnostic capability. We demonstrate the method by application to gene expression data for 83 small round blue-cell tumors (SRBCTs) samples belonging to one of four different classes. Based on 500 runs of 10-fold crossvalidation, tumor prediction accuracy was approximately 97%, sensitivity was approximately 95%, diagnostic sensitivity was approximately 91%, and diagnostic accuracy was approximately 99.5%. Among 25 genes selected to distinguish tumor class, 12 have functional information in the literature implicating their involvement in cancer. The four types of SRBCTs samples are also distinguishable in a clustering analysis based on the expression profiles of these 25 genes. The results demonstrated that the multiclass DF is an effective classification method for analysis of gene expression data for the purpose of molecular diagnostics.

Carcinoma, Small Cell↗