NY Prostate Cancer Conference - C. Foster - Session 1: From cancer biomarkers to therapeutic targets
1. From Cancer Biomarkers to Therapeutic Targets A Stratified Medicines Approach Christopher S. FOSTER Professor of Cellular Pathology and Molecular Genetics University of Liverpool, UK Christopher S. FOSTER Professor of Cellular Pathology and Molecular Genetics University of Liverpool, UK From Cancer Biomarkers to Therapeutic Targets A Stratified Medicines Approach
3. LIVERPOOL PROSTATE CANCER BIOMARKER STUDIES Novel prostate cancer biomarkers identified and published from the Division of Pathology, The University of Liverpool Marker Identifies Application Reference P170 Drug resistance glycoprotein Drug resistance of cancer cells Bashir et al., 1998 PKC- & PKC- Prostate cancer neoplasia and aggressive prostate cancer phenotype Distinction of reactive vs malignant in prostate biopsies with accurate prediction of cancer behaviour Cornford et al., 1999 Yao et al., 2010 HSP-27 Prostate cancer neoplasia and aggressive prostate cancer phenotype Distinction of reactive vs malignant prostate biopsies with accurate prediction of behaviour Cornford et al., 2000 Poorly-responding breast cancer Assessment of diagnostic breast biopsies O'Neill et al., 2003 Detection of urothelial cells Identifies microinvasive bladder cancer (pTa vs pT1 disease) in biopsies Philip et al., 2004 Aggressive prostate cancer phenotype Accurate prediction of aggressive behaviour at diagnosis (p > 0.001) Foster et al., 2009 TIG-1 Tumour suppressor gene in prostate cancer Prediction of behaviour Jing et al., 2002 FABP Metastasis inducer of prostate cancer Phenotypic assessment of prostatic biopsies Adamson et al., 2003; Jing et al., 2000 P9Ka Detects metastatic phenotype of breast and prostate cancers Immunohistochemical assessment of tissue biopsies Rudland et al., 2000 Na V1.2 Prostate cancer metastatic phenotype Prediction of behaviour Diss et al., 2005 E2F3 Predicts poor clinical outcome of prostate cancer Phenotypic assessment of prostatic biopsies Foster et al., 2004 AGR-2 Detects transition from benign to malignant prostatic epithelium before morphological changes occur Immunohistochemical assessment of diagnostic biopsies Zhang et al., 2007 OPN Detects metastatic phenotype Accurate prediction of poor clinical outcome Forootan et al., 2006 RPL-19 Aggressive prostate cancer phenotype Accurate prediction of behaviour Bee et al., 2006 Brn-3a Prostate cancer invasive phenotype Accurate prediction of metastatic behaviour Diss et al., 2006 Id-1 Prostate cancer metastatic phenotype Accurate prediction of poor clinical survival Forootan et al., 2007 TMPRSS2-ERG fusion Prostate cancer metastatic phenotype Accurate prediction of poor clinical survival Attard et al., 2008 BRCA1/ BRCA2 Prostate cancer metastatic phenotype Association with a defined group with poor clinical survival Mitra et al., 2008 RAD51 Aggressive prostate cancer phenotype Accurate prediction of behaviour Mitra et al., 2009
10. Genes in the TP53 network modulated by PKC- knockdown Mutated in exon 5 in PC3-M cells RAD-51 over-expressed in aggressive primary prostate cancers
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14. Isoform-specific PKC- ζ inhibition 3-hydroxy-2-(3-hydroxyphenyl)-4 H -1- benzopyran-4-ones
16. PC-3M cells - #14 inhibitor 10 M – Day 6 Control PC-3M
17. Human prostate cancer : Diagnosis to stratifed treatment Active management Watchful waiting Initial neoplastic events defined by neo-expression of AGR-2 before morphological changes apparent AGR-2 Established neoplasia signified by loss in expression of Hsp-27 Hsp-27 Good clinical prognosis defined by continued absence of Hsp-27 and aggressive cancers by Hsp-27 neoexpression Hsp-27 Hsp-27 Malignant change defined by enhanced expression of PKC- vn and neoexpression of PKC- vL PKC- “a” PKC- “PrC”