Hsueh-Fen Juan

Molecular signatures of metaplastic carcinoma of the breast by large-scale transcriptional profiling: identification of genes potentially related to epithelial-mesenchymal transition.

Metaplastic carcinoma of the breast (MCB) is a poorly understood subtype of breast cancer. It is generally characterized by the coexistence of ductal carcinomatous and transdifferentiated sarcomatous components, but the underlying molecular alterations, possibly related to epithelial–mesenchymal transition (EMT), remain elusive. We performed transcriptional profiling using half-a-genome oligonucleotide microarrays to elucidate genetic profiles of MCBs and their differences to those of ductal carcinoma of breasts (DCBs) using discarded specimens of four MCBs and 34 DCBs. Unsupervised clustering disclosed distinctive expression profiles between MCBs and DCBs. Supervised analysis identified gene signatures discriminating MCBs from DCBs and between MCB subclasses. Notably, many of the discriminator genes were associated with downregulation of epithelial phenotypes and with synthesis, remodeling and adhesion of extracellular matrix, with some of them have known or inferred roles related to EMT. Importantly, several of the discriminator genes were upregulated in a mutant Snail-transfected MCF7 cell known to exhibit features of EMT, thereby indicating a crucial role for EMT in the pathogenesis of MCBs. Finally, the identification of SPARC and vimentin as poor prognostic factors reinforced the role of EMT in cancer progression. These data advance our understanding of MCB and offer clues to the molecular alterations underlying EMT.

Comparative analysis of differentially expressed genes in normal and white spot syndrome virus infected Penaeus monodon

BackgroundWhite spot syndrome (WSS) is a viral disease that affects most of the commercially important shrimps and causes serious economic losses to the shrimp farming industry worldwide. However, little information is available in terms of the molecular mechanisms of the host-virus interaction. In this study, we used an expressed sequence tag (EST) approach to observe global gene expression changes in white spot syndrome virus (WSSV)-infected postlarvae of Penaeus monodon.ResultsSequencing of the complementary DNA clones of two libraries constructed from normal and WSSV-infected postlarvae produced a total of 15,981 high-quality ESTs. Of these ESTs, 46% were successfully matched against annotated genes in National Center of Biotechnology Information (NCBI) non-redundant (nr) database and 44% were functionally classified using the Gene Ontology (GO) scheme. Comparative EST analyses suggested that, in postlarval shrimp, WSSV infection strongly modulates the gene expression patterns in several organs or tissues, including the hepatopancreas, muscle, eyestalk and cuticle. Our data suggest that several basic cellular metabolic processes are likely to be affected, including oxidative phosphorylation, protein synthesis, the glycolytic pathway, and calcium ion balance. A group of immune-related chitin-binding protein genes is also likely to be strongly up regulated after WSSV infection. A database containing all the sequence data and analysis results is accessible at http://xbio.lifescience.ntu.edu.tw/pm/.ConclusionThis study suggests that WSSV infection modulates expression of various kinds of genes. The predicted gene expression pattern changes not only reflect the possible responses of shrimp to the virus infection but also suggest how WSSV subverts cellular functions for virus multiplication. In addition, the ESTs reported in this study provide a rich source for identification of novel genes in shrimp.

Characterization of microRNA-regulated protein-protein interaction network

We have performed topological analysis to elucidate the global correlation between microRNA (miRNA) regulation and protein‐protein interaction network in human. The analysis showed that target genes of individual miRNA tend to be hubs and bottlenecks in the network. While proteins directly regulated by miRNA might not form a network module themselves, the miRNA‐target genes and their interacting neighbors jointly showed significantly higher modularity. Our findings shed light on how miRNA may regulate the protein interaction network.

Targeting Therapy for Breast Carcinoma by ATP Synthase Inhibitor Aurovertin B

Targeting of tumor tissues is one of the most powerful approaches to accelerate the efficiency of anticancer treatments. The investigation of effective targets, including proteins specifically and abundantly expressed in abnormal regions, has been one of the most important research topics in cancer therapy. In this study, we performed a proteomic analysis on human breast carcinoma tissues to investigate the tumor-specific protein expression in breast carcinoma. Our study showed that ATP synthase was up-regulated in tumor tissues and was present on the plasma membrane of breast cancer cells. Furthermore, we treated the breast cancer cells with ATP synthase inhibitors and examined the inhibitory efficiency. Aurovertin B, an ATP synthase inhibitor, has strong inhibition on the proliferation of several breast cancer cell lines, but little influence on the normal cell line MCF-10A. Aurovertin B inhibits proliferation of breast cancer cells by inducing apoptosis and arresting cell cycle at the G0/G1 phase. This study showed aurovertin B can be used as an antitumorigenic agent and may be exploited in cancer chemotherapy.

TCMGeneDIT: a database for associated traditional Chinese medicine, gene and disease information using text mining

BackgroundTraditional Chinese Medicine (TCM), a complementary and alternative medical system in Western countries, has been used to treat various diseases over thousands of years in East Asian countries. In recent years, many herbal medicines were found to exhibit a variety of effects through regulating a wide range of gene expressions or protein activities. As available TCM data continue to accumulate rapidly, an urgent need for exploring these resources systematically is imperative, so as to effectively utilize the large volume of literature.MethodsTCM, gene, disease, biological pathway and protein-protein interaction information were collected from public databases. For association discovery, the TCM names, gene names, disease names, TCM ingredients and effects were used to annotate the literature corpus obtained from PubMed. The concept to mine entity associations was based on hypothesis testing and collocation analysis. The annotated corpus was processed with natural language processing tools and rule-based approaches were applied to the sentences for extracting the relations between TCM effecters and effects.ResultsWe developed a database, TCMGeneDIT, to provide association information about TCMs, genes, diseases, TCM effects and TCM ingredients mined from vast amount of biomedical literature. Integrated protein-protein interaction and biological pathways information are also available for exploring the regulations of genes associated with TCM curative effects. In addition, the transitive relationships among genes, TCMs and diseases could be inferred through the shared intermediates. Furthermore, TCMGeneDIT is useful in understanding the possible therapeutic mechanisms of TCMs via gene regulations and deducing synergistic or antagonistic contributions of the prescription components to the overall therapeutic effects. The database is now available at http://tcm.lifescience.ntu.edu.tw/.ConclusionTCMGeneDIT is a unique database that offers diverse association information on TCMs. This database integrates TCMs with biomedical studies that would facilitate clinical research and elucidate the possible therapeutic mechanisms of TCMs and gene regulations.

Discovery of biomarkers for gastric cancer: A proteomics approach

Gastric cancer is the second leading cause of cancer-related deaths worldwide. Although many treatment options exist for patients with gastric tumors, the incidence and mortality rate of gastric cancer are on the rise. The early stages of gastric cancer are non-symptomatic, and the treatment response is unpredictable. This situation is further aggravated by a lack of diagnostic biomarkers that can aid in the early detection and prognosis of gastric cancer and in the prediction of chemoresistance. Moreover, clinical surgical specimens are rarely obtained, and traditional biomarkers of gastric cancer are not very effective. Many studies in the field of proteomics have contributed to the discovery and establishment of powerful diagnostic tools (e.g., ProteinChip array) in the management of cancer. The evolution in proteomic technologies has not only enabled the screening of a large number of samples but also enabled the identification of pathologically significant proteins, such as phosphoproteins, and the quantitation of difference in protein expression under different conditions. Multiplexed assays are used widely to accurately fractionate various complex samples such as blood, tissue, cells, and Helicobacter pylori-infected specimens to identify differentially expressed proteins. Biomarker detection studies have substantially contributed to the areas of secretome, metabolome, and phosphoproteome. Here, we review the development of potential biomarkers in the natural history of gastric cancer, with specific emphasis on the characteristics of target protein convergence.

A Novel Sialyltransferase Inhibitor Suppresses FAK/Paxillin Signaling and Cancer Angiogenesis and Metastasis Pathways

Increased sialyltransferase (ST) activity promotes cancer cell metastasis, and overexpression of cell surface sialic acid correlates with poor prognosis in cancer patients. To seek therapies targeting metastasis for cancer treatment, we developed a novel ST inhibitor, Lith-O-Asp, and investigated its antimetastatic and antiangiogenic effects and mechanisms. We found that cells treated with Lith-O-Asp showed a reduction of activity on various ST enzymes by in vitro and cell-based activity analyses. Lith-O-Asp inhibited migration and invasion abilities in various cancer cell lines and showed inhibitory effect on the angiogenic activity of human umbilical vein endothelial cells. Indeed, Lith-O-Asp treatment consequently delayed cancer cell metastasis in experimental and spontaneous metastasis assays in animal models. Importantly, Lith-O-Asp decreased the sialic acid modification of integrin-β1 and inhibited the expression of phospho-FAK, phospho-paxillin, and the matrix metalloprotease (MMP) 2 and MMP9. Lith-O-Asp attenuated the Rho GTPase activity leading to actin dynamic impairment. In addition, 2DE-MS/MS and immunoblotting analyses showed that Lith-O-Asp altered the protein expression level and phosphorylation status of various proteins involved in crucial metastasis and angiogenesis pathways such as vimentin and ribonuclease/angiogenin inhibitor RNH1. Furthermore, Lith-O-Asp treatment significantly inhibited the invasive ability exerted by ectopic overexpression of various ST enzymes catalyzing α-2,6- or α-2,3-sialylation. Our results provide compelling evidence that the potential pan-ST inhibitor, Lith-O-Asp, suppressed cancer cell metastasis likely by inhibiting FAK/paxillin signaling and expressing antiangiogenesis factors. Lith-O-Asp is worthy for further testing as a novel antimetastasis drug for cancer treatment.

Integrative network analysis reveals active microRNAs and their functions in gastric cancer.

BackgroundMicroRNAs (miRNAs) are a class of endogenous, small and highly conserved noncoding RNAs that control gene expression either by degradation of target mRNAs or by inhibition of protein translation. They play important roles in cancer progression. A single miRNA can provoke a chain reaction and further affect protein interaction network (PIN). Therefore, we developed a novel integrative approach to identify the functional roles and the regulated PIN of oncomirs.ResultsWe integrated the expression profiles of miRNA and mRNA with the human PIN to reveal miRNA-regulated PIN in specific biological conditions. The potential functions of miRNAs were determined by functional enrichment analysis and the activities of miRNA-regulated PINs were evaluated by the co-expression of protein-protein interactions (PPIs). The function of a specific miRNA, miR-148a, was further examined by clinical data analysis and cell-based experiments. We uncovered several miRNA-regulated networks which were enriched with functions related to cancer progression. One miRNA, miR-148a, was identified and its function is to decrease tumor proliferation and metastasis through its regulated PIN. Furthermore, we found that miR-148a could reduce the invasiveness, migratory and adhesive activities of gastric tumor cells. Most importantly, elevated miR-148a level in gastric cancer tissues was strongly correlated with distant metastasis, organ and peritoneal invasion and reduced survival rate.ConclusionsThis study provides a novel method to identify active oncomirs and their potential functions in gastric cancer progression. The present data suggest that miR-148a could be a potential prognostic biomarker of gastric cancer and function as a tumor suppressor through repressing the activity of its regulated PIN.

Coregulation of transcription factors and microRNAs in human transcriptional regulatory network

BackgroundMicroRNAs (miRNAs) are small RNA molecules that regulate gene expression at the post-transcriptional level. Recent studies have suggested that miRNAs and transcription factors are primary metazoan gene regulators; however, the crosstalk between them still remains unclear.MethodsWe proposed a novel model utilizing functional annotation information to identify significant coregulation between transcriptional and post-transcriptional layers. Based on this model, function-enriched coregulation relationships were discovered and combined into different kinds of functional coregulation networks.ResultsWe found that miRNAs may engage in a wider diversity of biological processes by coordinating with transcription factors, and this kind of cross-layer coregulation may have higher specificity than intra-layer coregulation. In addition, the coregulation networks reveal several types of network motifs, including feed-forward loops and massive upstream crosstalk. Finally, the expression patterns of these coregulation pairs in normal and tumour tissues were analyzed. Different coregulation types show unique expression correlation trends. More importantly, the disruption of coregulation may be associated with cancers.ConclusionOur findings elucidate the combinatorial and cooperative properties of transcription factors and miRNAs regulation, and we proposes that the coordinated regulation may play an important role in many biological processes.

GeneNetwork: an interactive tool for reconstruction of genetic networks using microarray data

UNLABELLED Inferring genetic network architecture from time series data generated from high-throughput experimental technologies, such as cDNA microarray, can help us to understand the system behavior of living organisms. We have developed an interactive tool, GeneNetwork, which provides four reverse engineering models and three data interpolation approaches to infer relationships between genes. GeneNetwork enables a user to readily reconstruct genetic networks based on microarray data without having intimate knowledge of the mathematical models. A simple graphical user interface enables rapid, intuitive mapping and analysis of the reconstructed network allowing biologists to explore gene relationships at the system level. AVAILABILITY Download from http://genenetwork.sbl.bc.sinica.edu.tw/. SUPPLEMENTARY INFORMATION Supplement documentation of algorithms for the four approaches is downloadable at the above location.