ABSTRACT
More than 160,000 people are expected to die from invasive urothelial carcinoma (iUC) this year worldwide. Research in relevant animal models is essential to improving iUC management. Naturally-occurring canine iUC closely resembles human iUC in histopathology, metastatic behavior, and treatment response, and could provide a relevant model for human iUC. The molecular characterization of canine iUC, however, has been limited. Work was conducted to compare gene expression array results between tissue samples from iUC and normal bladder in dogs, with comparison to similar expression array data from human iUC and normal bladder in the literature. Considerable similarities between enrichment patterns of genes in canine and human iUC were observed. These included patterns mirroring basal and luminal subtypes initially observed in human breast cancer and more recently noted in human iUC. Canine iUC samples also exhibited enrichment for genes involved in P53 pathways, as has been reported in human iUC. This is particularly relevant as drugs targeting these genes/pathways in other cancers could be repurposed to treat iUC, with dogs providing a model to optimize therapy. As part of the validation of the results and proof of principal for evaluating individualized targeted therapy, the overexpression of EGFR in canine bladder iUC was confirmed. The similarities in gene expression patterns between dogs and humans add considerably to the value of naturally-occurring canine iUC as a relevant and much needed animal model for human iUC. Furthermore, the finding of expression patterns that cross different pathologically-defined cancers could allow studies of dogs with iUC to help optimize cancer management across multiple cancer types. The work is also expected to lead to a better understanding of the biological importance of the gene expression patterns, and the potential application of the cross-species comparisons approach to other cancer types as well.
Subject(s)
Carcinoma, Transitional Cell/genetics , Gene Expression Regulation, Neoplastic , Urinary Bladder Neoplasms/genetics , Urothelium/pathology , Animals , Carcinoma, Transitional Cell/pathology , Disease Models, Animal , Dogs , Female , Gene Expression , Humans , Male , Oligonucleotide Array Sequence Analysis , Urinary Bladder Neoplasms/pathologySubject(s)
Chromosomes, Human, X/genetics , Alternative Splicing , Amino Acid Sequence , Base Sequence , Chromosome Mapping , Computational Biology , DNA, Complementary/genetics , Databases, Genetic , Databases, Protein , Exons , Humans , Molecular Sequence Data , Open Reading Frames/physiology , Sequence AlignmentABSTRACT
The rapid pace at which genomic and proteomic data is being generated necessitates the development of tools and resources for managing data that allow integration of information from disparate sources. The Human Protein Reference Database (http://www.hprd.org) is a web-based resource based on open source technologies for protein information about several aspects of human proteins including protein-protein interactions, post-translational modifications, enzyme-substrate relationships and disease associations. This information was derived manually by a critical reading of the published literature by expert biologists and through bioinformatics analyses of the protein sequence. This database will assist in biomedical discoveries by serving as a resource of genomic and proteomic information and providing an integrated view of sequence, structure, function and protein networks in health and disease.
Subject(s)
Databases, Protein , Proteins/metabolism , Proteomics , Computational Biology , Disease , Genomics , Humans , Information Storage and Retrieval , Internet , Protein Binding , Protein Processing, Post-Translational , Proteins/chemistry , Proteins/genetics , Proteome/chemistry , Proteome/genetics , Proteome/metabolism , Substrate Specificity , Vocabulary, ControlledABSTRACT
Human Protein Reference Database (HPRD) is an object database that integrates a wealth of information relevant to the function of human proteins in health and disease. Data pertaining to thousands of protein-protein interactions, posttranslational modifications, enzyme/substrate relationships, disease associations, tissue expression, and subcellular localization were extracted from the literature for a nonredundant set of 2750 human proteins. Almost all the information was obtained manually by biologists who read and interpreted >300,000 published articles during the annotation process. This database, which has an intuitive query interface allowing easy access to all the features of proteins, was built by using open source technologies and will be freely available at http://www.hprd.org to the academic community. This unified bioinformatics platform will be useful in cataloging and mining the large number of proteomic interactions and alterations that will be discovered in the postgenomic era.
