THEME: a web tool for loop-design microarray data analysis

The Classification of Sini Decoction Pattern in Traditional Chinese Medicine by Gene Expression Profiling

We investigated the syndromes of the Sini decoction pattern (SDP), a common ZHENG in traditional Chinese medicine (TCM). The syndromes of SDP were correlated with various severe Yang deficiency related symptoms. To obtain a common profile for SDP, we distributed questionnaires to 300 senior clinical TCM practitioners. According to the survey, we concluded 2 sets of symptoms for SDP: (1) pulse feels deep or faint and (2) reversal cold of the extremities. Twenty-four individuals from Taipei City Hospital, Linsen Chinese Medicine Branch, Taiwan, were recruited. We extracted the total mRNA of peripheral blood mononuclear cells from the 24 individuals for microarray experiments. Twelve individuals (including 6 SDP patients and 6 non-SDP individuals) were used as the training set to identify biomarkers for distinguishing the SDP and non-SDP groups. The remaining 12 individuals were used as the test set. The test results indicated that the gene expression profiles of the identified biomarkers could effectively distinguish the 2 groups by adopting a hierarchical clustering algorithm. Our results suggest the feasibility of using the identified biomarkers in facilitating the diagnosis of TCM ZHENGs. Furthermore, the gene expression profiles of biomarker genes could provide a molecular explanation corresponding to the ZHENG of TCM.

Comparative transcriptome profiling of an SV40-transformed human fibroblast (MRC5CVI) and its untransformed counterpart (MRC-5) in response to UVB irradiation

Simian virus 40 (SV40) transforms cells through the suppression of tumor-suppressive responses by large T and small t antigens; studies on the effects of these two oncoproteins have greatly improved our knowledge of tumorigenesis. Large T antigen promotes cellular transformation by binding and inactivating p53 and pRb tumor suppressor proteins. Previous studies have shown that not all of the tumor-suppressive responses were inactivated in SV40-transformed cells; however, the underlying cause is not fully studied. In this study, we investigated the UVB-responsive transcriptome of an SV40-transformed fibroblast (MRC5CVI) and that of its untransformed counterpart (MRC-5). We found that, in response to UVB irradiation, MRC-5 and MRC5CVI commonly up-regulated the expression of oxidative phosphorylation genes. MRC-5 up-regulated the expressions of chromosome condensation, DNA repair, cell cycle arrest, and apoptotic genes, but MRC5CVI did not. Further cell death assays indicated that MRC5CVI was more sensitive than MRC-5 to UVB-induced cell death with increased caspase-3 activation; combining with the transcriptomic results suggested that MRC5CVI may undergo UVB-induced cell death through mechanisms other than transcriptional regulation. Our study provides a further understanding of the effects of SV40 transformation on cellular stress responses, and emphasizes the value of SV40-transformed cells in the researches of sensitizing neoplastic cells to radiations.

Gene expression profiling of dendritic cells in different physiological stages under Cordyceps sinensis treatment

Cordyceps sinensis (CS) has been commonly used as herbal medicine and a health supplement in China for over two thousand years. Although previous studies have demonstrated that CS has benefits in immunoregulation and anti-inflammation, the precise mechanism by which CS affects immunomodulation is still unclear. In this study, we exploited duplicate sets of loop-design microarray experiments to examine two different batches of CS and analyze the effects of CS on dendritic cells (DCs), in different physiology stages: naïve stage and inflammatory stage. Immature DCs were treated with CS, lipopolysaccharide (LPS), or LPS plus CS (LPS/CS) for two days, and the gene expression profiles were examined using cDNA microarrays. The results of two loop-design microarray experiments showed good intersection rates. The expression level of common genes found in both loop-design microarray experiments was consistent, and the correlation coefficients (Rs), were higher than 0.96. Through intersection analysis of microarray results, we identified 295 intersecting significantly differentially expressed (SDE) genes of the three different treatments (CS, LPS, and LPS/CS), which participated mainly in the adjustment of immune response and the regulation of cell proliferation and death. Genes regulated uniquely by CS treatment were significantly involved in the regulation of focal adhesion pathway, ECM-receptor interaction pathway, and hematopoietic cell lineage pathway. Unique LPS regulated genes were significantly involved in the regulation of Toll-like receptor signaling pathway, systemic lupus erythematosus pathway, and complement and coagulation cascades pathway. Unique LPS/CS regulated genes were significantly involved in the regulation of oxidative phosphorylation pathway. These results could provide useful information in further study of the pharmacological mechanisms of CS. This study also demonstrates that with a rigorous experimental design, the biological effects of a complex compound can be reliably studied by a complex system like cDNA microarray.

Intra- and inter-individual variance of gene expression in clinical studies

Background

Variance in microarray studies has been widely discussed as a critical topic on the identification of differentially expressed genes; however, few studies have addressed the influence of estimating variance.

Methodology/Principal Findings

To break intra- and inter-individual variance in clinical studies down to three levels–technical, anatomic, and individual–we designed experiments and algorithms to investigate three forms of variances. As a case study, a group of “inter-individual variable genes” were identified to exemplify the influence of underestimated variance on the statistical and biological aspects in identification of differentially expressed genes. Our results showed that inadequate estimation of variance inevitably led to the inclusion of non-statistically significant genes into those listed as significant, thereby interfering with the correct prediction of biological functions. Applying a higher cutoff value of fold changes in the selection of significant genes reduces/eliminates the effects of underestimated variance.

Conclusions/Significance

Our data demonstrated that correct variance evaluation is critical in selecting significant genes. If the degree of variance is underestimated, “noisy” genes are falsely identified as differentially expressed genes. These genes are the noise associated with biological interpretation, reducing the biological significance of the gene set. Our results also indicate that applying a higher number of fold change as the selection criteria reduces/eliminates the differences between distinct estimations of variance.