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Biomarker Analysis in Prostate Ca : Potential Uses

Prostate Cancer Recurrence Risk Assessment and the Role of Genomic Profiling and Somatic Mutational Analysis Charles J Ryan, MD Professor of Clinical Medicine and Urology Helen Diller Family Comprehensive Cancer Center University of California, San Francisco.

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Biomarker Analysis in Prostate Ca : Potential Uses

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  1. Prostate Cancer Recurrence Risk Assessment and the Role of Genomic Profiling and Somatic Mutational Analysis Charles J Ryan, MD Professor of Clinical Medicine and Urology Helen Diller Family Comprehensive Cancer Center University of California, San Francisco

  2. Biomarker Analysis in Prostate Ca:Potential Uses • Whom to biopsy • Whom to Re-Biopsy • Whom to treat or not to treat • Outcome on therapy in metastatic disease (CRPC) • Prognosis • Prediction

  3. Biomarker Analysis in Prostate Ca:Potential Uses • Whom to biopsy- what is the risk of cancer? • PSA • PHI • Capra • PCA3

  4. Biomarker Analysis in Prostate Ca:Potential Uses • Whom to Re-Biopsy

  5. Methylation Field Effect: Application to False Biopsy Challenge with current methods: • Standard of care for biopsy =12 cores • The needle may miss cancer • Pathologists can only interpret what is seen on the slide Biopsy Cancer • A biopsy procedure samples less than 1% of the entire gland • Taneja et al.: The American Urological Association (AUA) Optimal Techniques of Prostate Biopsy and Specimen Handling. 2013. • 2. Shen et al.: Three-Dimensional Sonography With Needle Tracking - Role in Diagnosis and Treatment of Prostate Cancer. J. Ultrasound Med. 2008; Jun; 27(6): 895-905.

  6. Cycle of • Follow Up • & Anxiety Fear of Undetected Cancer Leads to High Rate of Repeat Biopsy 43% have 1st repeat biopsy 44% have a 2nd repeat biopsy 43% have a 3rd repeat biopsy • Elevated • PSA • Negative • Pathology • Results • Prostate • Biopsy Approximately 700,000 repeat biopsies annually. • Welch HG et al: Detection of Prostate Cancer via Biopsy in the Medicare SEER Population During the PSA Era. J Natl Cancer Inst 2007;99: 1395 – 400. • Pinsky PF et al: Repeat Prostate Biopsy in the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. BJU International 99, no. 4 (April 2007): 775–779.

  7. Epigenetic Field Effect ConfirmMDx ConfirmMDx detects a field effect or halo associated with the presence of cancer at the DNA level. • This epigenetic “halo” around a cancer lesion can be present despite having a normal appearance under the microscope. • Residual tissues from previous negative biopsy are tested to help rule-out cancer. Halo Cancer Biopsy Henrique R, et al., Epigenetic Heterogeneity of High-Grade Prostatic Intraepithelial Neoplasia: Clues for Clonal Progression in Prostate Carcinogenesis, Mol Cancer Res 2006;4:1-8

  8. Multivariate Analysis of Known Risk Factors and Assay Performance (p-value) ConfirmMDx applicable to all patients, compared to rare event with atypical histology. Stewart G, et al., Clinical Utility of an Epigenetic Assay to Detect Occult Prostate Cancer in Histopathologically Negative Biopsies: Results of the MATLOC Study. JURO 2013.189, 1110-1116

  9. Biomarker Analysis in Prostate Ca:Potential Uses • Whom to treat or not to treat

  10. Active surveillance Early local therapy Multimodal therapy Systemic therapy Risk Adapted Treatment • Goal: inform physician-patient decisions about optimal initial treatment approach and timing • Numerous existing instruments • D’Amico / AUA risk groups • >120 nomograms • UCSF-CAPRA

  11. Risk Assessment: D’Amico / AUA Low PSA ≤10, GS ≤6, and stage T1-2a Intermediate PSA 10-20, GS 7, or stage T2b High PSA >20, GS ≥8, or stage T2c / T3a D’Amico et al. JAMA 1998; 280:969

  12. New tool must improve on a reference standard Validation Studies Graefenet al. JCO 2002; 20:3206 Graefen et al. UrolOncol 2002; 7:141 Bianco et al. J Urol 2003; 170:73 Greene et al. J Urol 2004; 171:2255 Zhao et al. Urology 2008; 78:396 C-index 0.71 --> 0.88 Shariat et al. JCO 2008; 26:1526 Kattanet al. JNCI 1998; 90:766

  13. Many candidate assays • Tissue: DNA CNV, RNA expression, methylation, IHC/FISH • Blood: miRNA, metabolic analytes, proteins • Urine/EPS: RNA transcripts (post-DRE), metabolic analytes • Imaging: PET, MRSI

  14. The Prolaris Assay • Material = RNA expression • 31 cell cycle progression (CCP) genes, normalized to 15 housekeeper genes • Score is expressed as average centered expression of CCP genes relative to housekeeper genes; negative scores = less active CCP, positive scores = more active CCP Cuzick J et al. Lancet Oncol 2011; 12:245

  15. Well established and validated method for quantifying the amount of a gene of interest relative to a reference sample after normalization by housekeeper genes

  16. Prolaris - Advancement Prostatectomy  Relapse Needle biopsy -> Death

  17. CCP and CAPRA combined. Cooperberg et al, JCO 31:1428, 2013

  18. Watchful waiting cohort….10 yr risk for death from PC

  19. Oncotype DX Genomic Prostate Score (GPS) Androgen Signaling AZGP1 FAM13C KLK2 SRD5A2 Cellular Organization FLNC GSN GSTM2 TPM2 • Quantitative 17-gene RT-PCR assay on manually microdissected tumor tissue from needle biopsy • Genes and biological pathways predictive of multiple endpoints, with emphasis on clinical recurrence • Optimized for very small tissue input: six 5 micron sections of single needle biopsy block with as little as 1 mm tumor length Stromal Response BGN COL1A1 SFRP4 Reference ARF1 ATP5E CLTC GPS1 PGK1 Proliferation TPX2 GPS= 0.735*Stromal Response group -0.352*Androgen Signaling group +0.095*Proliferation group -0.368*Cellular Organization group Scaled between 0 and 100

  20. GPS Test Development: Two Major Challenges Addressed • Biopsy under-sampling and tumor heterogeneity: Identified genes that predict clinical outcome in both dominant and highest grade regions • Very small biopsy tumor volumes: Developed standardized quantitative methods for reliable gene expression measurement in prostate needle biopsies Prostate Biopsy Prostatectomy TURP Klein et. al. ASCO GU 2011; Klein et. al. ASCO 2012.

  21. GPS Validation:Prediction of Adverse Pathology Prostate Cancer Technical Feasibility Prostatectomy Study (Cleveland Clinic) Two tumor foci per patient (n=441) Clinical Recurrence, PCSS, Adverse Pathology at RP BiopsyStudy (Cleveland Clinic) Biopsy specimens (n=167) Adverse Pathology at RP • Prospectively-designed independent validation study in contemporary, early-stage patients • Pre-specified, analytically validated GPS assay performed on needle biopsy specimens • Primary endpoint of adverse pathology to address concerns regarding understaging and biopsy undersampling for grade Assay Finalization and Analytical Validation17-Gene GPS Assay UCSF Clinical Validation Study Biopsy Specimens (n=395) Adverse Pathology at RP

  22. GPS Prediction of Grade And Stage • Binary univariatelogistic regression • 20 GPS units analogous to comparison of top vs. bottom quartiles of patients Cooperberg et al, AUA 2013

  23. The UCSF-CAPRA Score to predict PCSM % of biopsy cores positive Gleason (primary/ secondary) Sum points from each variable for 0-10 score Cooperberg et al. J Urol 2005; 173:1938

  24. Capra Score and GC are Correlated

  25. Multivariable Performance of GPS Cooperberg et al, AUA 2013

  26. 70 yo PSA=4.4 Biopsy 1/12 Gleason 3+3=6 1/12 Gleason 3+4 =7 10/12 cores negative Wanted active surveillance….

  27. Decipher: Risk of Metastases post RP • Decipher is a 22-gene genomic classifier, with genes chosen purely by statistical selection to predict metastasis among high-risk RP patients at Mayo, no pathway analysis (includes non-coding genes, 3 unknowns) • Rather than RT-PCR on established gene set, clinical assay is run using Affy Human Exon 1.0ST GeneChip (1.4M probe sets interrogating 5.5M features of whole exome) • Decipher score is calculated, but an enormous trove of data is kept in the databank for ongoing / future discovery Erho et al., PLoS ONE 8:e66855, 2013

  28. Biomarker testing has multiple clinical uses in localized disease. Crawford and Shore

  29. What about CRPC? • Candidate Biomarkers 1. AR status 2. TMPRSS-ERG 3. Androgens 4. Clinical Factors

  30. mCRPC Pre-Chemotherapy Nomogram

  31. mCRPC Tissue Collection and Analysis

  32. Ryan Proc GU ASCO 2013 Profile of Distinct and Emerging Clinical States. Resistance with Phenotypic Change: e.g. Neuro-endocrine Primary Resistance(Non-response) Acquired Resistance: (compensatory /adaptive) ASI or ART Therapy Response Death Non-PC Cause CRPC ASI= Androgen Synthesis Inhibitor ART = AR Targeted Therapy

  33. CRPC: Sample Mutational Screen

  34. AR Amplification (Reported to Patients) Analysis Pending: Primary vs Secondary Resistance Enzalutamide Resistance Unknowns: Effect on subsequent AR-targeted rx Marker-guided therapy Small EJ AACR Prostate Meeting, San Diego 2014

  35. PARADIGM Integrative Analysis(Josh Stuart, UCSC) • Integrate data for pathway-based PARADIGM analysis • Focused analysis to assess Adaptive Pathway activity in each sample • Inferred activities reflect neighborhood of influence around a pathway. • Unbiased analysis will identify additional pathways Multimodal Data mCRPC Tumors Pathway Model of Cancer Inferred Activities • Adaptive Pathways • Unbiased Analysis Vaske et al Bioinformatics (2010); TCGA Network, Nature 2011; Heiser et al PNAS 2011

  36. Pathway Analysis Goals: Unbiased analysis across all patients (n = 300) Biomarker and therapeutic applications. Interim (Subset) Analyses - Caveat Emptor! Hypothesis-generating experiments Compare pathway analysis across discrete, clinically dichotomized groups: Abiraterone naïve vs resistant Enzalutamide naïve vs resistant Primary Resistance vs Acquired Resistance EnzalutamidevsAbiraterone resistance Liver vs non-liver Aggressive variant vs conventional

  37. Pathway Analysis Differentially expressed genes + connections Small EJ AACR Prostate Meeting, San Diego 2014

  38. Conclusion Genomics is coming to prostate cancer For localized disease it is here as a prognostic tool. 3. It has not yet become a predictive tool linked to treatment (like OncotypeDx Breast) 4. There is no evidence (yet) that outcomes in advanced prostate cancer are better when a “personalized” or risk adapted approach is utilized.

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