Manfred P. WirthManfred P. WirthDepartment of Urology Department of Urology

Technical University of DresdenTechnical University of Dresden

[supported by a grant from the DFG] [supported by a grant from the DFG]

Diagnostic potential Diagnostic potential of transcript signatures in of transcript signatures in minimal minimal prostate tissue specimensprostate tissue specimens

•main problem: early identification of main problem: early identification of significant PCa for therapeutic significant PCa for therapeutic decisionsdecisions

•need for new additional PCa-need for new additional PCa-markers to improve diagnostic and markers to improve diagnostic and prognostic powerprognostic power

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

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

ObjectiveObjective

• establishment of standardized quantitativeestablishment of standardized quantitativePCR-assays (using gene-specific fluorescent PCR-assays (using gene-specific fluorescent probes)probes)

• 169 matched pairs of malignant and non-169 matched pairs of malignant and non-malignant prostate tissue specimens (Tu + Tf) malignant prostate tissue specimens (Tu + Tf) from RPE specimensfrom RPE specimens

• evaluation of 4 housekeeping genes as referenceevaluation of 4 housekeeping genes as referencefor internal normalization:for internal normalization: different expression between Tu and Tf?different expression between Tu and Tf?

Material & methods IMaterial & methods I

Material & methods IIMaterial & methods II

Tf Tu

lg (

TB

P/ R

NA

) in

zm

ol /

µg

to

tal R

NA

-1,0

-0,5

0,0

0,5

1,0

1,5

2,0

Tf Tu

lg (

PB

GD

/ R

NA

) in

zm

ol /

µg

to

tal R

NA

-1,0

-0,5

0,0

0,5

1,0

1,5

2,0

Tf Tu

lg (

HP

RT

/ R

NA

) in

zm

ol /

µg

to

tal R

NA

-1,0

-0,5

0,0

0,5

1,0

1,5

2,0

Tf Tu

lg (

GA

PD

H /

RN

A)

in a

mo

l / µ

g t

ota

l RN

A

-1,5

-1,0

-0,5

0,0

0,5

1,0

1,5p = 0.036 p < 0.001 p = 0.531p = 0.038

GAPDH TBPPBGDHPRT

• different expression of 3 reference genes:different expression of 3 reference genes:- GAPDH = glyceraldehyde-3-phosphate dehydrogenaseGAPDH = glyceraldehyde-3-phosphate dehydrogenase- HPRT = hypoxanthine phosphoribosyltransferaseHPRT = hypoxanthine phosphoribosyltransferase- PBGD = porphobilinogen deaminasePBGD = porphobilinogen deaminase

only TATA box binding protein (TBP) suitableonly TATA box binding protein (TBP) suitable(no different expression)(no different expression)

transcript marker nametranscript marker name

AMACRAMACR

AR *AR *

D-GPCR D-GPCR (OR51E1) (OR51E1)

EZH2EZH2

hepsinhepsin

PCA3 (DD3)PCA3 (DD3)

PDEFPDEF

Prostein *Prostein *

PSA *PSA *

PSGR (OR51E2)PSGR (OR51E2)

PSMAPSMA

TRPM8TRPM8

-methylacyl-CoA-racemase-methylacyl-CoA-racemase

androgen receptorandrogen receptor

G protein-coupled receptor (olfactory G protein-coupled receptor (olfactory receptor) receptor)

enhancer of zeste homolog 2enhancer of zeste homolog 2

membrane associated protease membrane associated protease

prostate cancer antigen 3prostate cancer antigen 3

prostate-derived Ets factorprostate-derived Ets factor

prostate cancer-associated gene 6prostate cancer-associated gene 6

prostate specific antigenprostate specific antigen

prostate specific G protein-coupled receptor prostate specific G protein-coupled receptor

prostate specific membrane antigenprostate specific membrane antigen

transient receptor protein M8transient receptor protein M8

Material & methods IIIMaterial & methods III12 PCa-related genes known from literature were tested12 PCa-related genes known from literature were tested

* prostate-specific genes, but not highly overexpressed in PCa* prostate-specific genes, but not highly overexpressed in PCa

• evaluation of evaluation of single & combined markerssingle & combined markers

(ROC-analyses) (ROC-analyses)

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

transcript signaturestranscript signatures

• goals: goals: -- prediction of PCa-presence prediction of PCa-presence

- prediction of - prediction of tumor extension tumor extension

- prediction of tumor aggressiveness- prediction of tumor aggressiveness

final aim: bioprofiling of PCafinal aim: bioprofiling of PCa

Material & methods IIIMaterial & methods III

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 & PSMAPCA3 (=DD3), AMACR, PSGR, hepsin, TRPM8 & PSMA most promising PCa transcript markersmost promising PCa transcript markers

n=169

Optimized 4-gene-model for PCa-prediction:Optimized 4-gene-model for PCa-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 = 0.89(95% CI 0.76 ... 1.00)

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

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

n=169

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

tissue samples:tissue samples:

median p for Tu 81%median p for Tu 81%median p for Tf 21%median p for Tf 21%

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

stage:stage:Discrimination between organ-confined disease (OCD) Discrimination between 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- vs. Tu-samples of OCD vs. Tu-samples NOCDcomparison of Tf- 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

TfTf: n=169 : n=169 OCDOCD: n=90 : n=90 NOCDNOCD: n=79: n=79

• translation of the techniques to prostate translation of the techniques to prostate biopsiesbiopsies

additional diagnostic tool on minimal prostateadditional diagnostic tool on minimal prostate tissue samples for better PCa-detectiontissue samples for better PCa-detection

11 selected PCa-related genes and TBP11 selected PCa-related genes and TBP

first results of application and validation of first results of application and validation of two two

multi-gene-models for PCa predictionmulti-gene-models for PCa prediction

Transfer to artificial biopsiesTransfer to artificial biopsies

•artificial biopsies: Tf & Tu from one RPE specimen artificial biopsies: Tf & Tu from one RPE specimen

•snap-frozen in planar direction on paper strip in liquid Nsnap-frozen in planar direction on paper strip in liquid N22

cryo-cuttings for RNA-isolation & cryo-cuttings for RNA-isolation & pathological pathological surveysurvey

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

Tu-prostate tissue sample Tf-prostate tissue Tu-prostate tissue sample Tf-prostate tissue samplesample

Artificial needle core biopsies from RPE Artificial needle core biopsies from RPE

explantsexplants

Handling and processing of artificial Handling and processing of artificial

biopsiesbiopsies

liquid nitrogen

prostate tissue sample between

glass plates

biopsy on paper strip

artificial biopsies

(cryo conservation):

Cryo-cuttings:

-- for RNA isolation

and 6 representaive cryo-slices

for histopthaological examination

biopsy profilecryo-slices

•11 patients with a primary PCa 11 patients with a primary PCa

•age: age: 51 to 71 years51 to 71 years ( (median 66 yearsmedian 66 years) )

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

Histopathological examinationHistopathological examination: according to the UICC : according to the UICC systemsystem

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

4 patients (36%)4 patients (36%) with with non organ-confined disease (NOCD; non organ-confined disease (NOCD; pT3/T4)pT3/T4)

Tumor gradingTumor grading: : 2 patients 2 patients withwith low grade low grade (GS 6) (GS 6)

8 patients 8 patients withwith intermediate grade intermediate grade (GS 7) (GS 7)

and and 1 patient 1 patient withwith high grade high grade (GS 8)(GS 8)

Patient cohort of the pilot studyPatient cohort of the pilot study

relative expression levels [zmol gene/ zmol TBP] relative expression levels [zmol gene/ zmol TBP] (n = 40 (n = 40 samples)samples)

transcriptranscript markert markernamename

malignant (Tu)malignant (Tu)n=26n=26

medianmedian

non-malignant (Tf)non-malignant (Tf)n=14n=14

medianmedian

P-valuesP-values(unpaire(unpaire

ddt-test)t-test)

over-over-expressionexpression (Tu (Tu vs.vs. Tf) Tf)

LNCaPLNCaP(contro(contro

l)l)

AMACRAMACR

PCA3PCA3

PSMAPSMA

2,104 (25.4 to 4,800)2,104 (25.4 to 4,800)

36.45 (5.4 to 166.3)36.45 (5.4 to 166.3)

25.87 (1.7 to 221.5)25.87 (1.7 to 221.5)

91.65 (5.4 to 91.65 (5.4 to 640.2)640.2)

1.67 (0.1 to 34.4)1.67 (0.1 to 34.4)

2.49 (0 to 72.6)2.49 (0 to 72.6)

<0.001<0.001

<0.001<0.001

<0.001<0.001

23.023.0

21.821.8

10.410.4

25.8325.83

0.190.19

24.8324.83

PSGRPSGR

TRPM8TRPM8

EZH2EZH2

hepsinhepsin

PDEFPDEF

PSAPSA

47.67 (2.2 to 222.9)47.67 (2.2 to 222.9)

31.71 (6.8 to 218.1)31.71 (6.8 to 218.1)

0.80 (0.1 to 1.807)0.80 (0.1 to 1.807)

0.38 (0.2 to 1.080)0.38 (0.2 to 1.080)

34.13 (1.8 to 136.1)34.13 (1.8 to 136.1)

174.36 (26.8 to 1,395)174.36 (26.8 to 1,395)

8.80 (0.2 to 8.80 (0.2 to 313.4)313.4)

6.95 (0.1 to 58.7)6.95 (0.1 to 58.7)

0.17 (0 to 1.222)0.17 (0 to 1.222)

0.12 (0 to 0.80)0.12 (0 to 0.80)

14.34 (0.2 to 63.2)14.34 (0.2 to 63.2)

78.18 (0.2 to 78.18 (0.2 to 737.0)737.0)

0.0060.006

<0.001<0.001

0.0010.001

<0.001<0.001

0.0760.076

0.0210.021

5.45.4

4.64.6

4.74.7

3.23.2

2.42.4

2.22.2

0.020.02

1.991.99

4.484.48

0.050.05

3.393.39

5.385.38

prosteinprostein

ARAR

8.74 (0.9 to 47.0)8.74 (0.9 to 47.0)

14.52 (4.3 to 31.8)14.52 (4.3 to 31.8)

6.99 (0 to 45.3)6.99 (0 to 45.3)

11.77 (0.5 to 18.7)11.77 (0.5 to 18.7)

0.4890.489

0.0300.030

1.31.3

1.21.2

1.541.54

14.2314.23

Marker expression in artificial biopsiesMarker expression in artificial biopsies

Validation of the multi-gene Validation of the multi-gene modelmodel

on artificial biopsies on artificial biopsies 4-gene model4-gene model(EZH2, TRPM8, PCA3, (EZH2, TRPM8, PCA3,

prostein)prostein)

Tu-biopsiesTu-biopsies

(n = 26)(n = 26)PCa-prediction:PCa-prediction:

77 % 77 %

(20 biopsies)(20 biopsies)

Tf-biopsiesTf-biopsies

(n = 14)(n = 14)„„false positive“:false positive“:

43 % 43 %

(6 biopsies)(6 biopsies)

„ „false-positive“: meaning?false-positive“: meaning? verification in future studies with increased sample numbersverification in future studies with increased sample numbers

• translation of the techniques to diagnostic translation of the techniques to diagnostic biopsies biopsies improvement of PCa detectionimprovement of PCa detection (Are false-positives really false-positives?)(Are false-positives really false-positives?)

• correct prediction of tumor aggressivenesscorrect prediction of tumor aggressiveness active surveillance active surveillance vs. vs. curative treatmentcurative treatment

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

Outlook IOutlook I

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

PCA3 (DD3) detection in urine samples in PCA3 (DD3) detection in urine samples in validation (APTIMA PCA3; Gen-probe incorp.)validation (APTIMA PCA3; Gen-probe incorp.)

(PCA3 is a non-coding RNA (PCA3 is a non-coding RNA only at transcript level measurable) only at transcript level measurable)

transcript quantification in urine samplestranscript quantification in urine samplesas a promising toolas a promising tool

Outlook IIOutlook II

• Dept. of Urology, Technical University of Dresden:Dept. of Urology, Technical University of Dresden:

Laboratory: Laboratory: Axel Meye, Susanne Füssel, Susanne Unversucht,Axel Meye, Susanne Füssel, Susanne Unversucht,

Andrea Lohse, Silke Tomasetti, Uta SchmidtAndrea Lohse, Silke Tomasetti, Uta Schmidt

Clinic:Clinic: Michael Fröhner, Stefan Zastrow, Marc-Oliver Michael Fröhner, Stefan Zastrow, Marc-Oliver

GrimmGrimm

• Inst. of Pathology, Technical University of Dresden:Inst. of Pathology, Technical University of Dresden:

Gustavo Baretton, Michael Haase, Marietta TomaGustavo Baretton, Michael Haase, Marietta Toma

• Inst. of Medical Informatics and BiometryInst. of Medical Informatics and Biometry

Rainer KochRainer Koch

AcknowledgmentAcknowledgment