Not all fat is equal: differential gene expression and potential therapeutic targets in subcutaneous adipose, visceral adipose, and endometrium of obese women with and without endometrial cancer.

OBJECTIVE: To identify obesity-related cancer genes in endometrial and adipose tissue depots of body mass index-matched morbidly obese women with and without endometrial cancer. METHODS: Eight women undergoing hysterectomy (4 women with and 4 women without endometrial cancer) were matched by age (52.6 years) and body mass index (44.5 kg/m). Endometrium, visceral adipose tissue, and subcutaneous adipose tissue were collected and subjected to microarray analysis using Affymetrix Human Genome U133 Plus 2.0 Arrays. Gene set enrichment analysis used to extract biological information from the gene expression data and t test metric ranked and compared genes in the expression data set. Protein expression was measured in the endometrial samples, and serum was collected for hormone/metabolite assays. RESULTS: No significant differences were detected in hormone/metabolite levels between groups. Gene set enrichment analysis comparisons demonstrated that endometrial, visceral adipose and subcutaneous adipose tissues displayed 40, 47, and 38 alternatively regulated gene set pathways when comparing patients with and without cancer. Nineteen gene sets were alternately regulated in both visceral and subcutaneous adipose tissues; however, eighteen of these were regulated in the opposite direction. Five pathways were significantly and alternately regulated in all 3 tissue types and included glycolysis/gluconeogenesis, ribosome, peroxisome proliferator activated receptor signaling, pathogenic Escherichia coli infection, and natural killer-mediated cytotoxicity. In the malignant endometrium, liver kinase B1 underexpression was observed in all patients with cancer. Liver kinase B1 underexpression decreased adenosine monophosphate-activated protein kinase activity toward acetyl-CoA carboxylase and implied enhanced lipid biosynthesis in obesity-induced endometrial cancer. CONCLUSIONS: Subcutaneous and visceral adipose tissue depots have opposite patterns of gene expression in obese patients with and without endometrial cancer. The altered de novo lipogenesis and individual gene targets identified provide new potential targets for cancer treatment and prevention for at-risk obese women.

HPD: an online integrated human pathway database enabling systems biology studies.

BACKGROUND: Pathway-oriented experimental and computational studies have led to a significant accumulation of biological knowledge concerning three major types of biological pathway events: molecular signaling events, gene regulation events, and metabolic reaction events. A pathway consists of a series of molecular pathway events that link molecular entities such as proteins, genes, and metabolites. There are approximately 300 biological pathway resources as of April 2009 according to the Pathguide database; however, these pathway databases generally have poor coverage or poor quality, and are difficult to integrate, due to syntactic-level and semantic-level data incompatibilities. RESULTS: We developed the Human Pathway Database (HPD) by integrating heterogeneous human pathway data that are either curated at the NCI Pathway Interaction Database (PID), Reactome, BioCarta, KEGG or indexed from the Protein Lounge Web sites. Integration of pathway data at syntactic, semantic, and schematic levels was based on a unified pathway data model and data warehousing-based integration techniques. HPD provides a comprehensive online view that connects human proteins, genes, RNA transcripts, enzymes, signaling events, metabolic reaction events, and gene regulatory events. At the time of this writing HPD includes 999 human pathways and more than 59,341 human molecular entities. The HPD software provides both a user-friendly Web interface for online use and a robust relational database backend for advanced pathway querying. This pathway tool enables users to 1) search for human pathways from different resources by simply entering genes/proteins involved in pathways or words appearing in pathway names, 2) analyze pathway-protein association, 3) study pathway-pathway similarity, and 4) build integrated pathway networks. We demonstrated the usage and characteristics of the new HPD through three breast cancer case studies. CONCLUSION: HPD http://bio.informatics.iupui.edu/HPD is a new resource for searching, managing, and studying human biological pathways. Users of HPD can search against large collections of human biological pathways, compare related pathways and their molecular entity compositions, and build high-quality, expanded-scope disease pathway models. The current HPD software can help users address a wide range of pathway-related questions in human disease biology studies.