Introduction to Personalized Medicine in the Czech Republic and BIOMEDREG Project as a New Research

Platform for Molecular and Translational Medicine

Marian Hajduch, MD, PhD Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacky University in Olomouc Czech Republic EuroBioForum 2012, Brussels

• Established in 1573 •The second oldest university after the Charles Universty in Prague •Olomouc Archibishop – center of Moravian religion and education – alumni or region associated scientists: Johann Gregor Mendel, Sigmund Freund, Konrad Zirm, Otto Wichterle, Frantisek Santavy, Jiri Bartek •Currently 23.000 students, approx. 7% of Czech university students and 3000 employees

Palacký University in Olomouc

OLOMOUC

Johann Gregor Mendel

Konrad Zirm

• Part I – Introduction to

Personalized Medicine in the

Czech Republic

• Part II – BIOMEDREG Project as a

New Research Platform for Molecular

and Translational Medicine

Biomarker use

Prognostic provides information about

patient outcome,

regardless of therapy

Predictive estimates the response

to a specific treatment

before the advance

of therapy

Pharmacological

estimates changes

after treatment

associated

with target hit

by therapy

Surrogate substitutes

a clinical endpoint

History of Personalized Medicine in the Czech Republic

(Oncology)

• Started in 2002 with introduction of trastuzumab (Herceptin) on the

Czech market

•Critical role of health insurance companies (request for centralized

diagnostics of HER-2 gene)

• 2002-2010 Reference Laboratory at Palacky University in Olomouc

•2005- Systemic collection of clinical information on patients treated

with biological therapies for evaluation of cost effectiveness (drug

registries)

•2008- Introduction of six new laboratories of predictive medicine across

the country for predictive cancer biomarkers

Predictive Cancer Biomarkers – Where we are?

Mutation present

Resistant to TK

inhibitros

Cellular proliferation

and survival

Gefitini

b

Erlotini

b

EG

F

GTP k-

Ras

Raf

Mek

MAPK

PI13

AKT

Part of the clinical routine#

• Her-2 in breast and gastric cancers (trastuzumab, lapatinib)

• KRAS/BRAF mutations – colorectal cancers (cetuximab, panitumumab)

• EGFR1 mutations – NSCLC (gefitinib, erlotinib)

• BRAF mutations – melanoma (vemurafenib)*

• ALK translocations – NSCLC (crizotinib)*

#diagnostics is paid from the health insurance

*not reimbursed yet

IHC:0

FISH: normal

IHC: 1+ to 2+

IHC: 3+

FISH: amplification

CEP 17

Her-2/neu

Specialized Molecular Diagnostics of

Cancers – HER-2 gene

Laboratory/Institute holds

accreditation decision according to

CSN ISO/IEC 17025/15189 to meet

European diagnostic standards

(www.cia.cz)

Immunohistochemistry discordances among RL a LLs >1 or

>2 IHC grades

Discordance

RL vs. LLs

0-6

months

(%)

6-12

months

(%)

12-18

months

(%)

18-24

months

(%)

24-30

months

(%)

30-35

months

(%)

0-35

months

(%)

≥ 2 IHC

14,08

19,51

12,59

19,33

31,52

36,99

21,33

≥ 1 IHC

28,17

43,90

37,04

40,34

50,00

53,42

41,61

Survival analysis (TTP) of mBRC Her-2

patients on trastuzumab based therapies.

Comparison of patients examined versus

not examined in the Reference laboratory

(RL).

Median TTP of RL examined pts.: RL 64,6

weeks

Median TTP of RL not examined pts: 37,7

weeks

Overall median TTP: 48,41 weeks

PD CR+PR_SDí

0 20 40 60 80 100 120 140 160 180 200

weeks

0 %

20 %

40 %

60 %

80 %

100 %

Perc

en

tag

e o

f patie

nts

not examined in RL

examined in RL

all pts. p=0.02

N = 42 N = 83

0%

20%

40%

60%

80%

100%

RL yes RL no

Pe

rce

nta

ge

of

pa

tien

ts

CR+PR+SD

PD

Therapeutic response of metastatic Her-2

positive breast cancer patients to

trastuzumab based therapies. Comparison

of patients examined versus not examined

in the Reference laboratory (RL).

(χ2 = 6,27, df = 1, p = 0,01)

Evaluation of HER-2 gene in breast cancer patients by FISH assay in Reference laboratory in Olomouc

32 68

285 287 274

350

785

726 742

679

610

0

100

200

300

400

500

600

700

800

900

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

nu

mb

er

of

pa

tien

ts

years

trastuzumab in local BRC

trastuzumab in metastatic BRC

Ústí n. L. Masaryk Hospital

in Usti nad Labem

Liberec Regional

Hospital Liberec

České Budějovice

Regional Hospital Ceske

Budejovice

University Hospital in

Motol

University Hospital Na

Bulovce and General

University Hospital

Prague

Plzeň

Hradec

Králové

University Hospital

Hradec Kralove i

Jihlava Regional Hospital Jihlava

Olomouc

Masaryk Memorial Cancer

Institute Brno

University Hospital Brno

and St. Anne's University

Hospital

Brno

University

Hospital Olomouc

Zlín Regional

Hospital

Zlin

Nový Jičín

Regional

Hospital

Novy Jicin

University Hospital

Ostrava

Ostrava

University

Hospital Plzen

Comprehensive oncology

centers

Hematooncology centers

Predicitive medicine

laboratories

Bioinformatics, biostatistics

and drug registries

Major Comprehensive Cancer Centers and

Diagnostic Laboratories – Self Learning System

Laboratories must hold accreditation decision according to CSN ISO/IEC 17025/15189 to meet

European diagnostic standards and perform external quality control.

Forum of Oncologists

Biannual Therapeutic Standards

Sample size in the registries: overview

(the system started with Herceptin in 2005)

Breast Registry

Herceptin – adjuvant

therapy 1852

Herceptin – mBC 1120

Herceptin – combined 194

Lapatinib 222

Avastin 85

NSCLC Registry

Tarceva 2183

Alimta 819

Avastin 59

Iressa 31

Alimta - MPM 124

Tarceva – Pancreatic cancer 58

Renis – mRCC Registry

Sutent 1221

Nexavar 719

Afinitor 204

Torisel 47

Avastin 40

Registry Corect – Colorectal Cancer

Avastin 3731

Erbitux 815

Vectibix 183

TOTAL:

> 13 500 valid records

Accessible follow-up (in months)

Registry Therapy Sample Median Min Max

Breast

Herceptin – adjuvancy 1593 17,5 0,0 63,9

Herceptin - mBRC 1005 18,5 0,1 112,8

Lapatinib 213 7,8 0,0 45,3

Avastin 83 11,2 0,7 38,2

Corect

Avastin 3612 11,9 0,0 70,4

Erbitux 787 9,0 0,0 68,3

Vectibix 168 6,7 0,0 29,5

Tulung –

NSCLC

Tarceva 2121 4,3 0,0 54,3

Alimta 786 5,6 0,0 43,0

Avastin 56 7,4 0,2 18,5

Iressa 28 3,3 0,0 14,6

0 20 40 60 80 100 120

Her-adjuvance

HER-mBC

lapatinib

avastin

Avastin-crc

erbitux

vectibix

Tarceva

Alimta

Avastin

Iress

Follow-up (months)

Median Max Min Follow-up (months)

Registry Therapy Sample Median 10% 90%

Breast

Herceptin – adjuvancy1) 1132 50,9 30,0 54,6

Herceptin – mBRC1) 727 45,6 11,0 124,1

Lapatinib 149 20,6 5,7 58,4

Avastin 55 25,0 6,0 55,0

Corect

Avastin 2610 26,0 7,8 66,4

Erbitux 612 19,1 2,1 52,1

Vectibix 119 16,9 4,0 46,0

Tulung –

NSCLC

Tarceva 1671 11,0 3,0 43,9

Alimta 683 9,0 3,0 18,4

Avastin 41 16,0 3,3 29,3

Iressa 13 9,0 4,1 31,7

0 25 50 75 100 125

Herceptin - adjuvance

Herceptin - mBC

Lapatinib

Avastin - Prs

Avastin - crc

erbitux

vectibix

tarceva

alimta

avastin

iressa

Duration of applied target therapy as example of quantitative

outcome (suitable for assessment of economic demands)

Median 90% percentile 10% percentile Therapy duration (weeks)

Therapy duration (weeks)

0 12 24 36 48 60 72 84 96

0,0

0,2

0,4

0,6

0,8

1,0

Herceptin (adj. therapy) – progression-free survival

PFS % patients

(95% IC)

1yr PFS 96,9 (96,0; 97,9)

2yr PFS 94,3 (92,9; 95,7)

5yr PFS 93,4 (91,7; 95,1)

PFS

Median PFS

(95% IS) Not reached

N*=1583 Survival time calculated since the therapy onset.

Time (months)

0 12 24 36 48 60 72 84 96 108 120

0,0

0,2

0,4

0,6

0,8

1,0

PFS % patients

(95% IC)

1yr PFS 56,5 (53,3; 59,8)

2yr PFS 27,4 (24,0; 30,8)

5yr PFS 17,6 (13,9; 21,3)

PFS

Median PFS

(95% IS) 14,5 months

(12,8; 16,2)

N= 1005

Herceptin (mBRC) – progression-free survival

Survival time calculated since the therapy onset.

Time (months)

Uniqueness of the Czech National Cancer Registry

• the Czech National Cancer Registry

(CNCR) contains almost 1.8 mil. records

on cancer patients since 1977

• population-based data, covering 100% of

the Czech population

• double control of mortality data: records

are independently verified against Death

Records Database

• mortality coding according to WHO

nomenclature

• all cancer diagnoses included

Predictive information system for cancer care: Step 2 = Predictive estimation of incidence and prevalence

INCIDENCE

2012

Number of cases

(90% confidence interval)

Stage I 3,353 (3,126; 3,580)

Stage II 2,212 (2,026; 2,399)

Stage III 1,004 (884; 1,123)

Stage IV 573 (498; 649)

Unstaged 214 (157; 269)

TOTAL 7,356 (6,691; 8,020)

PREVALENCE

2012

Number of cases

(90% confidence interval)

Stage I 30,933 (30,644; 31,222)

Stage II 28,131 (27,855; 28,407)

Stage III 7,490 (7,348; 7,632)

Stage IV 3,600 (3,501; 3,699)

Unstaged 2,228 (2,150; 2,306)

TOTAL 72,382 (71,498; 73,266)

Breast cancer (C50)

Success of the breast cancer screening program: (c) increasing proportion of early-stage cancers

there has been substantial increase in proportion of

early-stage cancers during recent years

0%

20%

40%

60%

80%

100%

1977

1978

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

Pro

port

ion o

f ca

se

s

Rok

Stage IV * DCO, cases diagnosed by autopsy, early

deaths, therapy had not been started due to

objective reasons

Unstaged

incomplete records

objective reasons*

Organised breast

cancer screening

Stage III

Stage II

Stage I Source of data:

Czech National Cancer Registry

Prof. Ladislav Dusek, Ph.D.

director

Institute of Biostatistics and Analyses

Masaryk University, Brno, Czech Republic

Jan Mužík, Ph.D., senior data analyst

Institute of Biostatistics and Analyses

Masaryk University, Brno, Czech

Republic

Data collection, mining, analysis

Conclusions

Personalized medicine (oncology) in the Czech Republic was centralized into

Comprehensive Cancer Centers and six „reference“ laboratories of predicitive

medicine.

The Czech Society for Oncology developed and implemented the full set of

registries monitoring segment of targeted anti-tumor therapy including

biomarkers.

The registries are able to collect representative multidimensional data which

cannot be obtained directly from the other sources.

Combination with other information sources allows to assess accessibility of care

and to predict incidence and prevalence of treated patients.

Registries offer comprehensive outcomes suitable for cost-effectiveness

analyses: direct and indirect care, hospital stays, dosage of medication and time

of medication, etc.

Registries offer reliable outcomes necessary for the evaluation of safety, efficacy

and quality of the care: adverse events, therapeutic response, survival,

biomarkers.

• Part I – Introduction to Personalized

Medicine in the Czech Republic

• Part II – BIOMEDREG Project as a

New Research Platform for

Molecular and Translational

Medicine

Infrastructural project for chemical biology and translational

medicine (BIOMEDREG) – concentrating, evaluating and

developing the national chemical and biomarker knowledge

Palacký University Olomouc

Biobanking

Compound

storage/library High throughput

screening

Data collection for

national &

international

databases Biomarkers

Clinical

trials

Therapeutic

standards

Universtiy Hospital Olomouc

Institute of Organic Chemistry and Biochemistry, ASCR

Institute of Chemical Technologies Prague

Preclinical

studies

Medicinal chemistry

Biomedicine for regional development and human resources

BIOMEDREG

Project Leader:

Palacký Universty in Olomouci

Partners:

University Hospital in Olomouc

Institute of Organic Chemistry and Biochemistry AS

CR

Institute of Chemical Technologies in Prague

Allocation:

Approx. 40 M €

EU Structural Funds -

2nd Priority Axis OP VaVpI

Phase of the Project:

Realization phase started on April 1, 2010

Information:

www.biomedreg.eu, www.imtm.cz

OLOMOUC

Primary aim:

To establish the Institute of

Molecular and Translational

Medicine at Palacky

University in Olomouc

Building of research infrastrucutres in the Czech Republic

2010-2012

Professor of Pathology R. Kodousek

1952-56

2012

(construction phase – 15 months,

4700 m2)

1956

Core facilities

• Genomics (HTS qPCR in 1536 format), Affymetrix platform, NGS, mass

spectrometry (Sequenome)

• Proteomics (2x MALDI-TOF/TOF, HPLC-MS, qTRAP, qTOF, orbitrap)

• Metabolomics (GC-TOF, qTRAP, orbitrap)

• Microscopy: AFM, Raman microscopy, IR microscopy, confocal spinning

disc and laser scanning microscopy, superresolution, PALM, SIM, TIRF,

transmission and raster EM)

• HTS/HCA analysis (compound library+dispensing, 3-arm robotic system for

screening of small molecules in BSL2+/BSL3 and/or hypoxic environment,

readers: fluorescence, luminisence, radioactivity, absorbance, wide field

confocal HCA, mass spectrometry based screening)

• BSL3 laboratories

• Small animal imaging centre: optical (fluorescence, luminiscence)., X-ray,

PET/CPECT/CT, ultrasound

• Radiochemistry, medicinal and combinatiorial chemistry

• Biobank

Research programs

1.Molecular basis of diseases and molecular

targets

2.Medicinal chemistry

3.Chemical biology nad experimental therapeutics

4.Biomarkers

5.Pharmacology and toxicology

6.Translational medicine

Selected outcomes of the project (since April 2010)

Publications with IF total: 96, cummulative IF=440, average IF=4,8 (IF<3: 45, IF 3-5: 27; IF

5-10: 14; IF>10: 6)

Patents: 6 national, 6 international, 1 spin-off

9 graduated PhD. students

83 scientists/PhD. students

IMTM is the national node for EATRIS: Relationship to other ESFRI and interest in

further collaborations

•BBMRI – interface: tissue and bio-banks, expertise in human and animal (model) pathology, quality standards, policies, patient data banks, disease-specific data banks;

• ECRIN – interface: transfer of projects that successfully passed clinical phase 0, I and IIa studies to progress with late phase II and beyond; use of ECRIN where multi-centre studies are needed even for early phase clinical trials; exchange observations from the clinic back to scientists (reverse translation), expertise in regulatory affairs, common training courses; • INFRAFRONTIER – interface: consultation in choosing the right animal model for pre-clinical studies, characterisation of novel and disease-specific (mouse) models; archiving of such; quality standards and regulatory standards (animal husbandry, animal studies, etc.), training courses; • INSTRUCT – interface: service in /access to specialty infrastructure components in structural biology, e.g. in small molecule characterization, elaboration of a biological mechanism of action; • EU-Openscreen – interface: collaborative use of technology and interdisciplinary expertise for small molecule discovery and development, access to large compound libraries or chemoinformatics, databases; • EuroBioImaging – interface: collaboration on nonstandard/sophisticated problems in biomolecular or biomedical imaging, training possibilities; • ELIXIR (bioinformatics and databases) – interface: exchange on IT management, standard definitions for data collection, storage, utilisation, and on a mid- to long-term basis, agreements on data hosting etc.

OLOMOUC

BRNO

BIOMEDREG EATRIS

CEITEC INSTRUCT ICRC ECRIN RECAMO BBMR

PERSONALIZED MEDICINE THE RIGHT THERAPY TO THE RIGHT PATIENT ON RIGHT

TIME LEADING TO OPTIMIZATION OF RISK/BENEFIT RATIO FOR INDIVIDUAL PATIENT

Translational Medicine Personalized Medicine

THANK YOU FOR ATTENTION

marian.hajduch@upol.cz hajduchm@gmail.com www.imtm.cz www.medchembio.cz