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Commonalities and differences between hormonal pathways in breast, endometrium and prostate cancer. Rob, Angel, Isaac, Zenon, Crina InfoBiomed 2nd Training Challenge Les Avellanes, 2006. Cancer stages. Hormone sensitive cancers. Medical focus. Environmental Diet: high fat, low vegetables
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Commonalities and differences between hormonal pathways in breast, endometrium and prostate cancer Rob, Angel, Isaac, Zenon, Crina InfoBiomed 2nd Training Challenge Les Avellanes, 2006
Medical focus Environmental Diet: high fat, low vegetables Ethnicity: BC-caucasian PC: afro-american Family history: tumours 1degree relative Age: BC>35, PC>45y Genetic factors: BC: BRCA1, BRCA2 PC: BRCA1, BRCA2, RNASEL, HPC1; MXI1 Hormonal factors:increase steroid hormone Estrogen, Progesteron, Androgen BC, EC: early menarche late menopause EC: nuliparity infertility Breast cancer/endometrium cancer Prostate cancer Breast cancer cell ER-A, ER-B: initiate, promotion PR-A, PR-B BRCA1 role: -coactivate p53 -modulate p300/cPB expression -ligand –corepressor for ER, AR, PR Prostate cancer cell AR ER-B highly expressed ER-A BRCA1, BRCA2, RNASEL, HPC1;MXI1, KAI1, PCAP, HPCX Estrogen cancer cell ER-A, ER-B: expression (for 70-80%) PR PAX2 – expression
Why look for similarities? • Prostate, breast and endometrial cancers have frequently maintained hormone sensitivity. Treatments are similar as well as disease progression. • The hormone receptors involved are of the same family: the nuclear hormone receptors. The involved hormones are similar.
Nuclear Hormone Receptors • Androgen, Estrogen and Progesterone Receptors
How can computers help? Genome Databases Ensembl GenAtlas GeneCard UniGene EntrezGeneGDB Plant genomics DNA sequecing Protein modeling Clinical DB PubMed Cohrane Embase OMIM Syst.review/meta-analysis? Sequence analysis Tool: Blast Find common sequences among genes EMBL Model organism databases: GDB, MGI Proteomics/Expression data? Microarray analysis Protein modelling Find protein structure pitfalls Metabolic pathways databases Modeling steroid pathways Tool: SBML
What information is available • Literature • Microarray data • Sequence data • Protein Structure data • Ligand specificity data • etc.
The Team Crina: medicine, data mining Rob: molecular biology and text mining Isaac: bioinformatics, sequence analysis, protein-protein interactions Angel: bioinformatics, microarray analysis Zenon: informatics, statistical analysis
Objectives • Develop research set-up to find similarities and/or differences between the three cancers and NHR receptor pathways. • Assess the usefulness of this approach.
The Approach in General • Detect patterns of similarity • High throughput data, e.g. microarray data analysis of cancer stages or NHR stimulation. • Transfer of knowledge • E.g. co-regulators of NHRs, such as SRC1, show frequent cross-reactivity and some are involved in the development of cancer.
Patterns of Similarity • DNA microarray data: stimulation of the estrogen, androgen and progesterone receptors. • Co-expression • Genomic co-location • Gene ontologies • Protein-Protein Interaction data
Patterns of Similarity: data analysis Step 1: Making the heterogeneous datasets comparable.
Patterns of Similarity: co-location • Are there areas on the genome that show a remarkable difference in transcription activity following the stimulation of the three NHRs? • Genomic instability in these regions maybe important in cancer progression. • Link to CGH data
Comparative Genomic Hybridization (CGH) A molecular cytogenetic method of screening a tumor for genetic changes. The alterations are classified as DNA gains and losses and reveal a characteristic pattern that includes mutations at chromosomal and subchromosomal levels.
Transfer of Knowledge • Which genes interact with the Estrogen Receptor? • Literature and pathway databases
Transfer of Knowledge • General model of NHRs: • amino-terminal activation • DNA-binding domain • carboxy-terminal ligand binding domain, containing second activation function • without ligand: sequestered with a.o. heat shock proteins • with ligand: series of events leading to binding to hormone-response elements in the regulatory regions of genes.
Transfer of Knowledge Infobiomed WP6.1
Transfer of Knowledge: PELP1 • Coregulator of ER • Association to BC recent (2005) • New mechanism (cytoplasmic location of PELP1) to tamoxifen resistance.
Transfer of Knowledge: PELP1 • Is PELP1 also involved in AR activity regulation? • Could there be another protein fulfilling a similar role? BRCA3 RAL14
Lessons Learned: • Working in a interdisciplinary team is difficult. • Communication is a hard skill to learn • Forming a team requires patience not ambition. • The more difficult the challenge, the more rewarding.