Liang-Chuan Lai

Genomic Analyses of Anaerobically Induced Genes in Saccharomyces cerevisiae: Functional Roles of Rox1 and Other Factors in Mediating the Anoxic Response

DNA arrays were used to investigate the functional role of Rox1 in mediating acclimatization to anaerobic conditions in Saccharomyces cerevisiae. Multiple growth conditions for wild-type and rox1 null strains were used to identify open reading frames with a statistically robust response to this repressor. These results were compared to those obtained for a wild-type strain in response to oxygen availability. Transcripts of nearly one-sixth of the genome were differentially expressed (P < 0.05) with respect to oxygen availability, the majority (>65%) being down-regulated under anoxia. Of the anaerobically induced genes, about one-third (106) contain putative Rox1-binding sites in their promoters and were significantly (P < 0.05) up-regulated in the rox1 null strains under aerobiosis. Additional promoter searches revealed that nearly one-third of the anaerobically induced genes contain an AR1 site(s) for the Upc2 transcription factor, suggesting that Upc2 and Rox1 regulate the majority of anaerobically induced genes in S. cerevisiae. Functional analyses indicate that a large fraction of the anaerobically induced genes are involved in cell stress (approximately 1/3), cell wall maintenance (approximately 1/8), carbohydrate metabolism (approximately 1/10), and lipid metabolism (approximately 1/12), with both Rox1 and Upc2 predominating in the regulation of this latter group and Upc2 predominating in cell wall maintenance. Mapping the changes in expression of functional regulons onto metabolic pathways has provided novel insight into the role of Rox1 and other trans-acting factors in mediating the physiological response of S. cerevisiae to anaerobic conditions.

miRSystem: An Integrated System for Characterizing Enriched Functions and Pathways of MicroRNA Targets

Background Many prediction tools for microRNA (miRNA) targets have been developed, but inconsistent predictions were observed across multiple algorithms, which can make further analysis difficult. Moreover, the nomenclature of human miRNAs changes rapidly. To address these issues, we developed a web-based system, miRSystem, for converting queried miRNAs to the latest annotation and predicting the function of miRNA by integrating miRNA target gene prediction and function/pathway analyses. Results First, queried miRNA IDs were converted to the latest annotated version to prevent potential conflicts resulting from multiple aliases. Next, by combining seven algorithms and two validated databases, potential gene targets of miRNAs and their functions were predicted based on the consistency across independent algorithms and observed/expected ratios. Lastly, five pathway databases were included to characterize the enriched pathways of target genes through bootstrap approaches. Based on the enriched pathways of target genes, the functions of queried miRNAs could be predicted. Conclusions MiRSystem is a user-friendly tool for predicting the target genes and their associated pathways for many miRNAs simultaneously. The web server and the documentation are freely available at http://mirsystem.cgm.ntu.edu.tw/.

Identification of a Novel Biomarker, SEMA5A, for Non–Small Cell Lung Carcinoma in Nonsmoking Women

Background: Although cigarette smoking is the major risk factor for lung cancer, only 7% of female lung cancer patients in Taiwan have a history of smoking. The genetic mechanisms of carcinogenesis in nonsmokers are unclear, but semaphorins have been suggested to play a role as lung tumor suppressors. This report is a comprehensive analysis of the molecular signature of nonsmoking female lung cancer patients in Taiwan, with a particular focus on the semaphorin gene family. Methods: Sixty pairs of tumor and adjacent normal lung tissue specimens were analyzed by using Affymetrix U133plus2.0 expression arrays. Differentially expressed genes in tumor tissues were identified by a paired t test and validated by reverse transcriptase-PCR and immunohistochemistry. Functional analysis was conducted by using Ingenuity Pathway Analysis as well as gene set enrichment analysis and sigPathway algorithms. Kaplan-Meier survival analyses were used to evaluate the association of SEMA5A expression and clinical outcome. Results: We identified 687 differentially expressed genes in non–small cell lung carcinoma (NSCLC). Many of these genes, most notably the semaphorin family, were participants in the axon guidance signaling pathway. The downregulation of SEMA5A in tumor tissue, both at the transcriptional and translational levels, was associated with poor survival among nonsmoking women with NSCLC. Conclusions: In summary, several semaphorin gene family members were identified as potential therapeutic targets, and SEMA5A may be useful as a prognostic biomarker for NSCLC, which may also be gender specific in Taiwanese patients. Impact: A novel biomarker for NSCLC is identified. Cancer Epidemiol Biomarkers Prev; 19(10); 2590–7. ©2010 AACR.

Metabolic-State-Dependent Remodeling of the Transcriptome in Response to Anoxia and Subsequent Reoxygenation in Saccharomyces cerevisiae

ABSTRACT We conducted a comprehensive genomic analysis of the temporal response of yeast to anaerobiosis (six generations) and subsequent aerobic recovery (≈2 generations) to reveal metabolic-state (galactose versus glucose)-dependent differences in gene network activity and function. Analysis of variance showed that far fewer genes responded (raw P value of ≤10−8) to the O2 shifts in glucose (1,603 genes) than in galactose (2,388 genes). Gene network analysis reveals that this difference is due largely to the failure of “stress”-activated networks controlled by Msn2/4, Fhl1, MCB, SCB, PAC, and RRPE to transiently respond to the shift to anaerobiosis in glucose as they did in galactose. After ≈1 generation of anaerobiosis, the response was similar in both media, beginning with the deactivation of Hap1 and Hap2/3/4/5 networks involved in mitochondrial functions and the concomitant derepression of Rox1-regulated networks for carbohydrate catabolism and redox regulation and ending (≥2 generations) with the activation of Upc2- and Mot3-regulated networks involved in sterol and cell wall homeostasis. The response to reoxygenation was rapid (<5 min) and similar in both media, dominated by Yap1 networks involved in oxidative stress/redox regulation and the concomitant activation of heme-regulated ones. Our analyses revealed extensive networks of genes subject to combinatorial regulation by both heme-dependent (e.g., Hap1, Hap2/3/4/5, Rox1, Mot3, and Upc2) and heme-independent (e.g., Yap1, Skn7, and Puf3) factors under these conditions. We also uncover novel functions for several cis-regulatory sites and trans-acting factors and define functional regulons involved in the physiological acclimatization to changes in oxygen availability.

Dynamical remodeling of the transcriptome during short-term anaerobiosis in Saccharomyces cerevisiae : Differential response and role of Msn2 and/or Msn4 and other factors in galactose and glucose media

ABSTRACT In contrast to previous steady-state analyses of the O2-responsive transcriptome, here we examined the dynamics of the response to short-term anaerobiosis (2 generations) in both catabolite-repressed (glucose) and derepressed (galactose) cells, assessed the specific role that Msn2 and Msn4 play in mediating the response, and identified gene networks using a novel clustering approach. Upon shifting cells to anaerobic conditions in galactose medium, there was an acute (∼10 min) yet transient (<45 min) induction of Msn2- and/or Msn4-regulated genes associated with the remodeling of reserve energy and catabolic pathways during the switch from mixed respiro-fermentative to strictly fermentative growth. Concomitantly, MCB- and SCB-regulated networks associated with the G1/S transition of the cell cycle were transiently down-regulated along with rRNA processing genes containing PAC and RRPE motifs. Remarkably, none of these gene networks were differentially expressed when cells were shifted in glucose, suggesting that a metabolically derived signal arising from the abrupt cessation of respiration, rather than O2 deprivation per se, elicits this “stress response.” By ∼0.2 generation of anaerobiosis in both media, more chronic, heme-dependent effects were observed, including the down-regulation of Hap1-regulated networks, derepression of Rox1-regulated networks, and activation of Upc2-regulated ones. Changes in these networks result in the functional remodeling of the cell wall, sterol and sphingolipid metabolism, and dissimilatory pathways required for long-term anaerobiosis. Overall, this study reveals that the acute withdrawal of oxygen can invoke a metabolic state-dependent “stress response” but that acclimatization to oxygen deprivation is a relatively slow process involving complex changes primarily in heme-regulated gene networks.

IL-1β-driven neutrophilia preserves antibacterial defense in the absence of the kinase IKKβ

Transcription factor NF-κB and its activating kinase IKKβ are associated with inflammation and are believed to be critical for innate immunity. Despite the likelihood of immune suppression, pharmacological blockade of IKKβ–NF-κB has been considered as a therapeutic strategy. However, we found neutrophilia in mice with inducible deletion of IKKβ (IkkβΔ mice). These mice had hyperproliferative granulocyte-macrophage progenitors and pregranulocytes and a prolonged lifespan of mature neutrophils that correlated with the induction of genes encoding prosurvival molecules. Deletion of interleukin 1 receptor 1 (IL-1R1) in IkkβΔ mice normalized blood cellularity and prevented neutrophil-driven inflammation. However, IkkβΔIl1r1−/− mice, unlike IkkβΔ mice, were highly susceptible to bacterial infection, which indicated that signaling via IKKβ–NF-κB or IL-1R1 can maintain antimicrobial defenses in each others absence, whereas inactivation of both pathways severely compromises innate immunity.

A whole genome methylation analysis of systemic lupus erythematosus: hypomethylation of the IL10 and IL1R2 promoters is associated with disease activity

The etiology of systemic lupus erythematosus (SLE) involves a complex interaction of genetic and environmental factors. Investigations have shown that environmentally driven epigenetic changes contribute to the etiology of SLE. Here, we hypothesize that aberrant DNA methylation may contribute to the activation of the immune machinery and trigger lupus disease activity. A whole genome methylation array was applied to investigate the DNA methylation changes between 12 pairs of active SLE patients and healthy controls. The results were further confirmed in 66 SLE patients, 102 healthy controls. The methylation statuses of the IL10 and IL1R2 genes were significantly reduced in the SLE patient samples relative to the healthy controls (age-adjusted odds ratios, 64.2 and 16.9, respectively, P<0.0001). There was a trend toward SLE patients having hypomethylated IL10 and IL1R2 genes accompanied by greater disease activity. We observed that the methylation degree of IL10 and IL1R2 genes were reduced in the rheumatoid arthritis (RA) patients as well but the hypomethylation change was more significant in IL1R2 genes than in the IL10 genes in RA patients. This study demonstrated that DNA hypomethylation might be associated with SLE. Hypomethylated IL10 and IL1R2 genes may provide potential epigenetic markers as clinical predictors for autoimmune diseases.

Deregulated microRNAs in triple-negative breast cancer revealed by deep sequencing

BackgroundMicroRNAs (miRNAs) are short, non-coding RNA molecules that play critical roles in human malignancy. However, the regulatory characteristics of miRNAs in triple-negative breast cancer, a phenotype of breast cancer that does not express the genes for estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2, are still poorly understood.MethodsIn this study, miRNA expression profiles of 24 triple-negative breast cancers and 14 adjacent normal tissues were analyzed using deep sequencing technology. Expression levels of miRNA reads were normalized with the quantile-quantile scaling method. Deregulated miRNAs in triple-negative breast cancer were identified from the sequencing data using the Student’s t-test. Quantitative reverse transcription PCR validations were carried out to examine miRNA expression levels. Potential target candidates of a miRNA were predicted using published target prediction algorithms. Luciferase reporter assay experiments were performed to verify a putative miRNA-target relationship. Validated molecular targets of the deregulated miRNAs were retrieved from curated databases and their associations with cancer progression were discussed.ResultsA novel 25-miRNA expression signature was found to effectively distinguish triple-negative breast cancers from surrounding normal tissues in a hierarchical clustering analysis. We documented the evidence of seven polycistronic miRNA clusters preferentially harboring deregulated miRNAs in triple-negative breast cancer. Two of these miRNA clusters (miR-143-145 at 5q32 and miR-497-195 at 17p13.1) were markedly down-regulated in triple-negative breast cancer, while the other five miRNA clusters (miR-17-92 at 13q31.3, miR-183-182 at 7q32.2, miR-200-429 at 1p36.33, miR-301b-130b at 22q11.21, and miR-532-502 at Xp11.23) were up-regulated in triple-negative breast cancer. Moreover, miR-130b-5p from the miR-301b-130b cluster was shown to directly repress the cyclin G2 (CCNG2) gene, a crucial cell cycle regulator, in triple-negative breast cancer cells. Luciferase reporter assays showed that miR-130b-5p-mediated repression of CCNG2 was dependent on the sequence of the 3′-untranslated region. The findings described in this study implicate a miR-130b-5p-CCNG2 axis that may be involved in the malignant progression of triple-negative breast cancer.ConclusionsOur work delivers a clear picture of the global miRNA regulatory characteristics in triple-negative breast cancer and extends the current knowledge of microRNA regulatory network.

Molecular Characteristics and Metastasis Predictor Genes of Triple-Negative Breast Cancer: A Clinical Study of Triple-Negative Breast Carcinomas

Background Triple-negative breast cancer is a subtype of breast cancer with aggressive tumor behavior and distinct disease etiology. Due to the lack of an effective targeted medicine, treatment options for triple-negative breast cancer are few and recurrence rates are high. Although various multi-gene prognostic markers have been proposed for the prediction of breast cancer outcome, most of them were proven clinically useful only for estrogen receptor-positive breast cancers. Reliable identification of triple-negative patients with a favorable prognosis is not yet possible. Methodology/Principal Findings Clinicopathological information and microarray data from 157 invasive breast carcinomas were collected at National Taiwan University Hospital from 1995 to 2008. Gene expression data of 51 triple-negative and 106 luminal breast cancers were generated by oligonucleotide microarrays. Hierarchical clustering analysis revealed that the majority (94%) of triple-negative breast cancers were tightly clustered together carrying strong basal-like characteristics. A 45-gene prognostic signature giving 98% predictive accuracy in distant recurrence of our triple-negative patients was determined using the receiver operating characteristic analysis and leave-one-out cross validation. External validation of the prognostic signature in an independent microarray dataset of 59 early-stage triple-negative patients also obtained statistical significance (hazard ratio 2.29, 95% confidence interval (CI) 1.04–5.06, Cox P = 0.04), outperforming five other published breast cancer prognostic signatures. The 45-gene signature identified in this study revealed that TGF-β signaling of immune/inflammatory regulation may play an important role in distant metastatic invasion of triple-negative breast cancer. Conclusions/Significance Gene expression data and recurrence information of triple-negative breast cancer were collected and analyzed in this study. A novel set of 45-gene signature was found to be statistically predictive in disease recurrence of triple-negative breast cancer. The 45-gene signature, if further validated, may be a clinically useful tool in risk assessment of distant recurrence for early-stage triple-negative patients.

Integrated Analyses of Copy Number Variations and Gene Expression in Lung Adenocarcinoma

Numerous efforts have been made to elucidate the etiology and improve the treatment of lung cancer, but the overall five-year survival rate is still only 15%. Identification of prognostic biomarkers for lung cancer using gene expression microarrays poses a major challenge in that very few overlapping genes have been reported among different studies. To address this issue, we have performed concurrent genome-wide analyses of copy number variation and gene expression to identify genes reproducibly associated with tumorigenesis and survival in non-smoking female lung adenocarcinoma. The genomic landscape of frequent copy number variable regions (CNVRs) in at least 30% of samples was revealed, and their aberration patterns were highly similar to several studies reported previously. Further statistical analysis for genes located in the CNVRs identified 475 genes differentially expressed between tumor and normal tissues (p<10−5). We demonstrated the reproducibility of these genes in another lung cancer study (p = 0.0034, Fishers exact test), and showed the concordance between copy number variations and gene expression changes by elevated Pearson correlation coefficients. Pathway analysis revealed two major dysregulated functions in lung tumorigenesis: survival regulation via AKT signaling and cytoskeleton reorganization. Further validation of these enriched pathways using three independent cohorts demonstrated effective prediction of survival. In conclusion, by integrating gene expression profiles and copy number variations, we identified genes/pathways that may serve as prognostic biomarkers for lung tumorigenesis.