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Prostate Cancer Recurrence Risk Assessment and the Role of Genomic

Profiling and Somatic Mutational Analysis

Charles J Ryan, MDProfessor of Clinical Medicine and Urology

Helen Diller Family Comprehensive Cancer CenterUniversity of California, San Francisco

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

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Biomarker Analysis in Prostate Ca:Potential Uses

• Whom to biopsy- what is the risk of cancer?

– PSA

– PHI

– Capra

– PCA3

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Biomarker Analysis in Prostate Ca:Potential Uses

•

• Whom to Re-Biopsy

•

•

4

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

1. 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.

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

Approximately 700,000 repeat biopsies annually. 1) 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. 2) 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.

Cycle of Follow

Up & Anxiety

Elevated PSA

Prostate Biopsy

NegativePatholog

y Results

ConfirmMDx

ConfirmMDx detects a field effect or halo associated with the presence of cancer at the DNA level.

Epigenetic Field Effect

Biopsy

Cancer

• 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

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

Multivariate Analysis of Known Risk Factors and Assay Performance

Age (0.51)

HGPIN (0.5)

Suspicious DRE

(0.3)

PSA < or > 10

(0.18)

Atypical Cells (0.011)

ConfirmMDx (<0.0001)

0

0.5

1

1.5

2

2.5

3

3.5

Odds Ratios of Clinical Risk Factors

(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

Biomarker Analysis in Prostate Ca:Potential Uses

• Whom to treat or not to treat

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• Goal: inform physician-patient decisions about optimal initial treatment approach and timing

• Numerous existing instruments– D’Amico / AUA risk groups– >120 nomograms– UCSF-CAPRA

Active surveillanceEarly local therapyMultimodal therapySystemic therapy

Risk Adapted Treatment

Risk Assessment: D’Amico / AUA

D’Amico et al. JAMA 1998; 280:969

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

New tool must improve on a reference standard

Kattan et al. JNCI 1998; 90:766

Validation Studies1. Graefen et al. JCO 2002; 20:32062. Graefen et al. Urol Oncol 2002; 7:1413. Bianco et al. J Urol 2003; 170:734. Greene et al. J Urol 2004; 171:22555. Zhao et al. Urology 2008; 78:396

Shariat et al. JCO 2008; 26:1526

C-index 0.71 --> 0.88

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

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

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

Needle biopsy -> Death

Prostatectomy Relapse

Prolaris - Advancement

CCP and CAPRA combined.

Cooperberg et al, JCO 31:1428, 2013

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

Oncotype DX Genomic Prostate Score (GPS)

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

Cellular Organization

FLNCGSN

GSTM2 TPM2

Stromal Response

BGNCOL1A1SFRP4

ProliferationTPX2

Androgen Signaling

AZGP1 FAM13C

KLK2SRD5A2

ReferenceARF1ATP5ECLTCGPS1PGK1

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

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 BiopsyTURPProstatectomy

Klein et. al. ASCO GU 2011; Klein et. al. ASCO 2012.

• 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

UCSF Clinical Validation StudyBiopsy Specimens (n=395) Adverse Pathology at RP

GPS Validation:Prediction of Adverse Pathology

Prostatectomy Study (Cleveland Clinic)Two tumor foci per patient (n=441)

Clinical Recurrence, PCSS, Adverse Pathology at RP

Prostate Cancer Technical Feasibility

Assay Finalization and Analytical Validation17-Gene GPS Assay

Biopsy Study (Cleveland Clinic)Biopsy specimens (n=167)

Adverse Pathology at RP

GPS Prediction of Grade And Stage

OddsRatio 95% CI LR Chi-

Square P-value

• Binary univariate logistic regression• 20 GPS units analogous to comparison of top vs. bottom

quartiles of patients

Prediction of High Grade Disease

GPS per 20 units 2.48 (1.60, 3.85)

16.78 <0.001Prediction of pT3GPS per 20 units 2.20 (1.46,

3.31)14.44 <0.001

Cooperberg et al, AUA 2013

Variable Level Points Variable Level Points

PSA ≤6 0 T-stage T1/T2 0

6.1-10 1 T3a 1

10.1-20 2

20.1-30 3 <34% 0

>30 4 >34% 1

1-3/1-3 0

1-3/4-5 1 Age <50 0

4-5/1-5 3 >50 1

Sum points from each variable for 0-10 score

Cooperberg et al. J Urol 2005; 173:1938

The UCSF-CAPRA Score to predict PCSM

% of biopsycores positive

Gleason(primary/secondary)

Capra Score and GC are Correlated

Multivariable Performance of GPS

Model VariableOdds

Ratio95% CI P-value

1 GPS (per 20 units) 1.85 (1.23, 2.81) 0.003

  Age (continuous) 1.05 (1.01, 1.09) 0.004

  PSA (continuous) 1.11 (1.04, 1.18) 0.002

  Clinical Stage T2 vs. T1 1.57 (0.98, 2.51) 0.059

  Biopsy Gleason Score (7 v.

6)

1.70 (1.00, 2.88) 0.050

2 GPS (per 20 units) 2.13 (1.44, 3.16) <0.001

CAPRA 1.58 (1.24, 2.02) <0.001

Cooperberg et al, AUA 2013

70 yo PSA=4.4Biopsy1/12 Gleason 3+3=61/12 Gleason 3+4 =710/12 cores negativeWanted active surveillance….

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

Condition Test Readout Negative Biopsy MDXHealth:

_MethylationConfirmMDx

Rules out – NO PCRules in – Need subsequent Bx

Positive Biopsy Prolaris

Oncotype DX

Death from PC

Recurrence, PCSS

Post Prostatectomy

Decipher

Prolaris

Risk of Metastasis

Biochemical Recurrence

Biomarker testing has multiple clinical uses in localized disease.

Crawford and Shore

What about CRPC?

• Candidate Biomarkers

1. AR status2. TMPRSS-ERG3. Androgens4. Clinical Factors

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mCRPC Pre-Chemotherapy Nomogram

mCRPC Tissue Collection and Analysis

Profile of Distinct and Emerging Clinical States.

CRPC

ASI or ARTTherapy

Primary Resistance(Non-

response)

Response

Acquired Resistance:

(compensatory /adaptive)

Death Non-PC Cause

Resistance with Phenotypic Change:e.g. Neuro-endocrine

ASI= Androgen Synthesis InhibitorART = AR Targeted Therapy

Ryan Proc GU ASCO 2013

CRPC: Sample Mutational Screen

AR Amplification(Reported to Patients)

AR Amplification by FISH ( n = 33)Abiraterone naive 10/13 (77%)

Abiraterone resistant 3/14 (21%)

Analysis Pending: Primary vs Secondary

ResistanceEnzalutamide Resistance

Unknowns:Effect on subsequent AR-

targeted rxMarker-guided therapy

Small EJ AACR Prostate Meeting, San Diego 2014

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 Pathway Modelof Cancer

mCRPC Tumors

Inferred Activities

1) Adaptive Pathways

2) Unbiased Analysis

Vaske et al Bioinformatics (2010); TCGA Network, Nature 2011; Heiser et al PNAS 2011

Pathway Analysis

Goals: Unbiased analysis across all patients (n = 300) Biomarker and therapeutic applications.

Interim (Subset) Analyses - Caveat Emptor!Hypothesis-generating experimentsCompare pathway analysis across discrete, clinically

dichotomized groups:Abiraterone naïve vs resistantEnzalutamide naïve vs resistantPrimary Resistance vs Acquired ResistanceEnzalutamide vs Abiraterone resistanceLiver vs non-liverAggressive variant vs conventional

Pathway Analysis

Differentially expressed genes + connections

Small EJ AACR Prostate Meeting, San Diego 2014

4040

1. Genomics is coming to prostate cancer

2. For localized disease it is here as a prognostic tool.

3. It has not yet become a predictive tool linked to treatment (like Oncotype Dx Breast)

4. There is no evidence (yet) that outcomes in advanced prostate cancer are better when a “personalized” or risk adapted approach is utilized.

Conclusion