4. DPKK Workshop in Bonn/Königswinter4. DPKK Workshop in Bonn/Königswinter 1.-2.12.20061.-2.12.2006

Quantitative multi-gene expression Quantitative multi-gene expression

analysesanalyses

on paired prostate tissue samples from on paired prostate tissue samples from

radical prostatectomies and on radical prostatectomies and on artificial artificial

prostate biopsiesprostate biopsiesSusanne Füssel & Susanne UnversuchtSusanne Füssel & Susanne Unversucht

Axel Meye, Michael Haase, Andrea Lohse, Silke Tomasetti, Michael Axel Meye, Michael Haase, Andrea Lohse, Silke Tomasetti, Michael

Fröhner, Uta Schmidt, Rainer Koch, Gustavo Baretton, Manfred. P. Fröhner, Uta Schmidt, Rainer Koch, Gustavo Baretton, Manfred. P.

WirthWirth

Dept. of Urology & Institute of Medical Informatics and Biometry & Institute Dept. of Urology & Institute of Medical Informatics and Biometry & Institute

of Pathologyof Pathology

Technical University of DresdenTechnical University of Dresden

•main problemmain problem: : early identificationearly identification of of aggressive PCaaggressive PCa for therapeutic for therapeutic decisionsdecisions

•need for need for new additional PCa-markersnew additional PCa-markers to improve diagnostic and prognostic to improve diagnostic and prognostic powerpower

•quantification of transcript markersquantification of transcript markers as promising toolas promising tool

•expression signaturesexpression signatures more reliable more reliable than single markersthan single markers

ObjectiveObjective

• establishment of establishment of standardized QPCR-assaysstandardized QPCR-assays

• 1. study1. study: 9 PCa-related genes + 4 housekeeping genes: 9 PCa-related genes + 4 housekeeping genes

• 2. study2. study: 4 new PCa-related genes, TBP as reference : 4 new PCa-related genes, TBP as reference

genegene

• 169 paired tissue samples169 paired tissue samples (Tu + Tf) from RPE explants (Tu + Tf) from RPE explants

• evaluation of evaluation of single & combined markerssingle & combined markers (ROC- (ROC-

analyses)analyses)

• mathematical modelsmathematical models for PCa-specific transcript for PCa-specific transcript

signaturessignatures

• aim: prediction of PCa-presenceaim: prediction of PCa-presence and and tumor tumor extensionextension using minimal tissue specimens (prostate using minimal tissue specimens (prostate biopsies)biopsies)

Material & MethodsMaterial & Methods

Evaluation of single markers: Evaluation of single markers: overexpression in PCa?overexpression in PCa?

PCA3 AMACR PSGR hepsin TRPM8 PSMA D-GPCR EZH2 PDEF PSA prostein AR

Tu

:Tf

rati

os

(pai

red

anal

ysis

)

10-2

10-1

100

101

102

103

104

0.866 0.843 0.775 0.842 0.814 0.751 0.652 0.792 0.763 0.655 0.569 0.565

univariate ROC analyses: AUC values of single markers

11.9 x

43.0 x

6.6 x 6.5 x3.7 x3.9 x

2.1 x 2.0 x2.0 x1.1 x1.6 x

1.1 x

median overexpression (paired analysis)

PCA3 (=DD3), AMACR, PSGR, hepsin, TRPM8 & PSMA PCA3 (=DD3), AMACR, PSGR, hepsin, TRPM8 & PSMA most promising PCa transcript markersmost promising PCa transcript markers

1. Study: optimized 4-gene-model for PCa-1. Study: optimized 4-gene-model for PCa-

prediction:prediction:

EZH2 + PCA3 + prostein + TRPM8EZH2 + PCA3 + prostein + TRPM8

ROC Prädiktor aus Publikation alte+neue Daten

Sens

itivi

ty

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1 Specifity0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

1- Specificity

AUC = 0.893(95% CI 0.756 ... 1.000)

ROC-analysis of theROC-analysis of the4-gene-combination4-gene-combination

probability (p) of PCa presence probability (p) of PCa presence in the analyzed tissue samples in the analyzed tissue samples

(Tf and Tu)(Tf and Tu)median p Tu 0.81 Tf 0.21median p Tu 0.81 Tf 0.21

tumorfrei Tumor0

0.25

0.50

0.75

1.00predictedprobability

for tumor

pre

dic

ted

pro

bab

ility

of

tum

or

• classification of relative expression levels of these 4 genes classification of relative expression levels of these 4 genes according optimized cut-offs according optimized cut-offs logit-value for each tissue sample logit-value for each tissue sample (Tu and Tf)(Tu and Tf)

• logit-model 1logit-model 1: p = exp(logit)/[1+exp(logit)] : p = exp(logit)/[1+exp(logit)] 

correctly predictedcorrectly predicted::•with pwith p0.7 for Tu :0.7 for Tu : 70 % of Tu- 70 % of Tu-samplessamples•with pwith p0.3 for Tf :0.3 for Tf : 73 % of Tf- 73 % of Tf-samplessamples•sensitivity 79.3% & specificity 84.0%sensitivity 79.3% & specificity 84.0%

2. Study: optimized 8-gene-model for PCa-2. Study: optimized 8-gene-model for PCa-

prediction:prediction:AMACR + AR + EZH2 + hepsin + PCA3 + PDEF + prostein + AMACR + AR + EZH2 + hepsin + PCA3 + PDEF + prostein +

TRPM8TRPM8• using log-transformed relative expression levelsof these 8 genes using log-transformed relative expression levelsof these 8 genes

as continuous values as continuous values logit-value for each tissue sample (Tu and logit-value for each tissue sample (Tu and Tf)Tf)

• 2. logit-model:2. logit-model: p = exp(logit)/[1+exp(logit)]p = exp(logit)/[1+exp(logit)]

ROC Neuer Prädiktor alte +neue Daten

Sen

sitiv

ity

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1 Specifity0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

1- Specificity

AUC = 0.94(95% CI 0.79 ... 1.00)

tumorfrei Tumor0

0.25

0.50

0.75

1.00predictedprobability

for tumor

pre

dic

ted

pro

bab

ility

of

tum

or

ROC-analysis of theROC-analysis of the8-gene-combination8-gene-combination

probability (p) of PCa presence probability (p) of PCa presence in the analyzed tissue samples in the analyzed tissue samples

(Tf and Tu)(Tf and Tu)median p Tu 0.93 Tf 0.07median p Tu 0.93 Tf 0.07

correctly predictedcorrectly predicted::•with pwith p0.7 for Tu :0.7 for Tu : 78 % of Tu- 78 % of Tu-samplessamples•with pwith p0.3 for Tf :0.3 for Tf : 78 % of Tf- 78 % of Tf-samplessamples•sensitivity 89.3% & specificity 86.4%sensitivity 89.3% & specificity 86.4%

Dependence of marker expression on tumor Dependence of marker expression on tumor

stage:stage:Discrimination between of organ-confined disease (OCD) Discrimination between of organ-confined disease (OCD)

and non- organ-confined disease (NOCD) for therapeutic and non- organ-confined disease (NOCD) for therapeutic

decision?decision?

• comparison only of Tu-samples of OCD vs. NOCD comparison only of Tu-samples of OCD vs. NOCD oror

• comparison of TF-samples vs. Tu-samples of OCD vs. Tu-samples NOCDcomparison of TF-samples vs. Tu-samples of OCD vs. Tu-samples NOCD

mathematical models for OCD-prediction in processmathematical models for OCD-prediction in process

prostein

Tf OCD NOCD

pro

stei

n /

TB

P (

zmol

/ zm

ol)

0

20

40

60

80

100TRPM8

Tf OCD NOCD

TR

PM

8 / T

BP

(zm

ol /

zmol

)

0

50

100

150

200

PSA

Tf OCD NOCD

PS

A /

TB

P (

zmol

/ zm

ol)

0

500

1000

1500

• translation of the techniques to prostate biopsiestranslation of the techniques to prostate biopsies additional diagnostic tools for better PCa-prediction?additional diagnostic tools for better PCa-prediction?

• correct prediction of tumor stage & aggressivenesscorrect prediction of tumor stage & aggressiveness RPE or not, adjuvant hormone therapy or CT or notRPE or not, adjuvant hormone therapy or CT or not

• correlation of transcript signatures with outcome?correlation of transcript signatures with outcome? follow-up needed for prognostic purposesfollow-up needed for prognostic purposes

• detection of PCa-specific transcripts in urine samplesdetection of PCa-specific transcripts in urine samples non-invasive tumor detection?non-invasive tumor detection?

OutlookOutlook

AimAim::

• transfer of techniques/ statistical models to transfer of techniques/ statistical models to artificial prostate biopsies from RPE explantsartificial prostate biopsies from RPE explants

additional diagnostic tools on minimal prostateadditional diagnostic tools on minimal prostate tissue samplestissue samples

11 selected PCa-related genes and TBP 11 selected PCa-related genes and TBP (reference)(reference)

first results of application and validation of two first results of application and validation of two multi-gene-models for PCa predictionmulti-gene-models for PCa prediction

Quantitative multi-gene expression Quantitative multi-gene expression analyses analyses

on on artificial prostate needle core biopsies artificial prostate needle core biopsies

from radical prostatectomiesfrom radical prostatectomies

Artificial prostate needle core biopsies Artificial prostate needle core biopsies

from radical prostatectomiesfrom radical prostatectomies

Material & methodsMaterial & methods:: •artificial biopsies (11 patients): Tf/Tu from one RPE explant artificial biopsies (11 patients): Tf/Tu from one RPE explant

•snap-frozen in liquid nitrogensnap-frozen in liquid nitrogen

cryo-cuttings for RNA-isolation / cryo-cuttings for RNA-isolation / pathological surveypathological survey

H&E-stained cuttings (PCa-patient: pT2a, pN0, pMx Gleason Score: 7 [3+4])

Tu-prostate tissue sample Tf-prostate tissue sample

Artificial prostate needle core biopsies Artificial prostate needle core biopsies

from radical prostatectomiesfrom radical prostatectomies

Patient`s cohortPatient`s cohort::

11 patients with a primary PCa

age: 51 to 71 years (median 66 years)

serum PSA levels: 1.29 to 24.32 ng/ml (median 6.9 ng/ml)

Histopathological examinations: (according to the UICC system)

7 patients (64%) with organ-confined disease (OCD; pT2)

4 patients (36%) with non organ-confined disease (NOCD; pT3/ pT4)

Tumor grading: 2 patients with low grade (GS 2 to 6)

8 patients with intermediate grade (GS 7)

and 1 patient with high grade (GS 8 to 10)

Artificial prostate needle core biopsies Artificial prostate needle core biopsies

from radical prostatectomiesfrom radical prostatectomies

relative expression levels [zmol gene/ zmol TBP] (n = 38 samples)

Transcript markername

malignant (Tu)n=26

median

non-malignant (Tf)n=12

median

P-values(unpaire

dt-test)

median over

expression (Tu vs. Tf)

LNCaP(contro

l)mean

AMACR

PCA3

PSMA

2,104 (25.4 to 4,800)

36.45 (5.4 to 166.3)

25.87 (1.7 to 221.5)

91.65 (5.4 to 640.2)

1.67 (0.1 to 34.4)

2.49 (0 to 72.6)

<0.001

0.001

0.062

22.96

21.83

10.39

25.83

0.19

24.83

PSGR

TRPM8

EZH2

hepsin

PDEF*

PSA

47.67 (2.2 to 222.9)

31.71 (6.8 to 218.1)

0.80 (0.1 to 1.807)

0.38 (0.2 to 1.080)

34.13 (1.8 to 136.1)

174.36 (26.8 to 1,395)

8.80 (0.2 to 313.4)

6.95 (0.1 to 58.7)

0.17 (0 to 1.222)

0.12 (0 to 0.80)

14.34 (0.2 to 63.2)

78.18 (0.2 to 737.0)

0.611

0.017

0.004

0.002

0.076

0.207

5.41

4.56

4.71

3.16

2.38

2.23

0.02

1.99

4.48

0.05

3.39

5.38

prostein

AndrRec*

8.74 (0.9 to 47.0)

14.52 (4.3 to 31.8)

6.99 (0 to 45.3)

11.77 (0.5 to 18.7)

0.502

0.030

1.25

1.23

1.54

14.23

* n (Tu-specimens) = 25; n (Tf-specimens) = 10

Artificial prostate needle core biopsies Artificial prostate needle core biopsies

from radical prostatectomiesfrom radical prostatectomies

Validation of two multi-gene models:

4-gene model

(EZH2, TRPM8, PCA3, prostein)

8-gene model(PDEF, AndrRec,

EZH2, PCA3, hepsin, AMACR,

prostein, TRPM8)

Tu-prostate biopsies(n = 26)

PCa-prediction:

77 % (20 biopsies)

PCa-prediction:100 %

(26 biopsies)

Tf-prostate biopsies(n = 14)

„false postive“:

43 % (6 biopsies)

„false postive“:57 %

(8 biopsies)