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Biomedical subjects

Antoine Veldhoven

Publications and source records attributed to Antoine Veldhoven.

3 recordsLinked to original sources

Evolution of the androgen receptor pathway during progression of prostate cancer.

The present work focused on the potential involvement of selective adaptations of the androgen receptor pathway in the initiation and progression of prostate cancer. We defined the androgen receptor pathway by selecting 200 genes that were androgen responsive in prostate cancer cell lines and/or xenografts. This androgen receptor pathway gene signature was then used for profiling prostate cancer xenografts and patient-derived samples. Approximately half of the androgen receptor pathway genes were up-regulated in well-differentiated prostate cancer compared with normal prostate. Functionally distinct parts of the androgen receptor pathway were specifically down-regulated in high-grade cancers. Unexpectedly, metastases have down-regulated the vast majority of androgen receptor pathway genes. The significance of this progressive down-regulation of androgen receptor pathway genes was shown for a few androgen receptor-regulated genes. Lower mRNA expression of HERPUD1, STK39, DHCR24, and SOCS2 in primary prostate tumors was correlated with a higher incidence of metastases after radical prostatectomy. HERPUD1 mRNA expression predicted the occurrence of metastases almost perfectly. In vitro experiments showed that overexpression of the stress response gene HERPUD1 rapidly induces apoptosis. Based on the functions of the genes within the distinct subsets, we propose the following model. Enhanced androgen receptor activity is involved in the early stages of prostate cancer. In well-differentiated prostate cancer, the androgen receptor activates growth-promoting as well as growth-inhibiting and cell differentiation genes resulting in a low growth rate. The progression from low-grade to high-grade prostate carcinoma and metastases is mediated by a selective down-regulation of the androgen receptor target genes that inhibit proliferation, induce differentiation, or mediate apoptosis.

Animals↗

Storing, linking, and mining microarray databases using SRS.

BACKGROUND: SRS (Sequence Retrieval System) has proven to be a valuable platform for storing, linking, and querying biological databases. Due to the availability of a broad range of different scientific databases in SRS, it has become a useful platform to incorporate and mine microarray data to facilitate the analyses of biological questions and non-hypothesis driven quests. Here we report various solutions and tools for integrating and mining annotated expression data in SRS. RESULTS: We devised an Auto-Upload Tool by which microarray data can be automatically imported into SRS. The dataset can be linked to other databases and user access can be set. The linkage comprehensiveness of microarray platforms to other platforms and biological databases was examined in a network of scientific databases. The stored microarray data can also be made accessible to external programs for further processing. For example, we built an interface to a program called Venn Mapper, which collects its microarray data from SRS, processes the data by creating Venn diagrams, and saves the data for interpretation. CONCLUSION: SRS is a useful database system to store, link and query various scientific datasets, including microarray data. The user-friendly Auto-Upload Tool makes SRS accessible to biologists for linking and mining user-owned databases.

Computational Biology↗

CoPub Mapper: mining MEDLINE based on search term co-publication.

BACKGROUND: High throughput microarray analyses result in many differentially expressed genes that are potentially responsible for the biological process of interest. In order to identify biological similarities between genes, publications from MEDLINE were identified in which pairs of gene names and combinations of gene name with specific keywords were co-mentioned. RESULTS: MEDLINE search strings for 15,621 known genes and 3,731 keywords were generated and validated. PubMed IDs were retrieved from MEDLINE and relative probability of co-occurrences of all gene-gene and gene-keyword pairs determined. To assess gene clustering according to literature co-publication, 150 genes consisting of 8 sets with known connections (same pathway, same protein complex, or same cellular localization, etc.) were run through the program. Receiver operator characteristics (ROC) analyses showed that most gene sets were clustered much better than expected by random chance. To test grouping of genes from real microarray data, 221 differentially expressed genes from a microarray experiment were analyzed with CoPub Mapper, which resulted in several relevant clusters of genes with biological process and disease keywords. In addition, all genes versus keywords were hierarchical clustered to reveal a complete grouping of published genes based on co-occurrence. CONCLUSION: The CoPub Mapper program allows for quick and versatile querying of co-published genes and keywords and can be successfully used to cluster predefined groups of genes and microarray data.

Algorithms↗