This document discusses personalized medicine in the Czech Republic and the BIOMEDREG project. It provides background on Palacky University in Olomouc, Czech Republic and its role in molecular and translational medicine. It then discusses the history and current state of personalized medicine in oncology in the Czech Republic, including predictive cancer biomarkers routinely used in clinical practice and specialized molecular diagnostic laboratories. Finally, it introduces the BIOMEDREG project as a new research platform for advancing personalized medicine through molecular diagnostics, clinical registries, and predictive modeling.

1. 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

2. Palacký University in Olomouc
• 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
OLOMOUC
Johann Gregor Mendel
Konrad Zirm

3. • Part I – Introduction to
Personalized Medicine in the
Czech Republic
• Part II – BIOMEDREG Project as a
New Research Platform for Molecular
and Translational Medicine

4. Biomarker use
Prognostic Predictive
estimates the response
provides information about
to a specific treatment
patient outcome,
before the advance
regardless of therapy
of therapy
Pharmacological
estimates changes Surrogate
after treatment substitutes
associated a clinical endpoint
with target hit
by therapy

5. 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

6. Predictive Cancer Biomarkers – Where we are?
Part of the clinical routine#
• Her-2 in breast and gastric cancers (trastuzumab, lapatinib)
• KRAS/BRAF mutations – colorectal cancers (cetuximab,
panitumumab)
Mutation present
EG
F
Resistant to TK
• EGFR1 mutations – NSCLC (gefitinib, erlotinib) Gefitini
b
GTP
inhibitros
Erlotini k-
b Ras
PI13
• BRAF mutations – melanoma (vemurafenib)* Raf
AKT
Mek
• ALK translocations – NSCLC (crizotinib)* MAPK
#diagnostics
is paid from the health insurance
Cellular proliferation
*not reimbursed yet and survival

7. Specialized Molecular Diagnostics of
Cancers – HER-2 gene
IHC:0
FISH: normal
Her-2/neu
CEP 17
IHC: 1+ to 2+
IHC: 3+
FISH: amplification
Laboratory/Institute holds
accreditation decision according to
CSN ISO/IEC 17025/15189 to meet
European diagnostic standards
(www.cia.cz)

8. Immunohistochemistry discordances among RL a LLs >1 or
>2 IHC grades
Discordance 0-6 6-12 12-18 18-24 24-30 30-35 0-35
RL vs. LLs months months months months months months 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

9. Survival analysis (TTP) of mBRC Her-2
Therapeutic response of metastatic Her-2 patients on trastuzumab based therapies.
positive breast cancer patients to Comparison of patients examined versus
trastuzumab based therapies. Comparison not examined in the Reference laboratory
of patients examined versus not examined (RL).
in the Reference laboratory (RL). Median TTP of RL examined pts.: RL 64,6
(χ2 = 6,27, df = 1, p = 0,01) weeks
Median TTP of RL not examined pts: 37,7
weeks
Overall median CR+PR_SDí
PD TTP: 48,41 weeks
100 %
Percentage of patients
not examined in RL
100% p=0.02
examined in RL
80 % all pts.
80% Percentage of patients
CR+PR+SD
60% 60 %
PD
40%
20% 40 %
0%
20 %
RL yes RL no
N = 42 N = 83
0%
0 20 40 60 80 100 120 140 160 180 200

10. Evaluation of HER-2 gene in breast cancer patients by FISH
assay in Reference laboratory in Olomouc
trastuzumab in local
900 BRC
800
785
726 742
700 679
610
600
number of patients
500
400
350
300
trastuzumab 285 287 274
in metastatic
200
BRC
100 68
32
0
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
years

11. Major Comprehensive Cancer Centers and Comprehensive oncology
Diagnostic Laboratories – Self Learning System centers
Hematooncology centers
Predicitive medicine
laboratories
Ústí n. L.
Masaryk Hospital Liberec
in Usti nad Labem Regional Bioinformatics, biostatistics
Hospital Liberec and drug registries
Hradec
Králové
Prague
University Hospital in University Hospital
Hradec Kralove i
Plzeň Motol
University Hospital Na
University
Hospital Plzen
Bulovce and General Forum of Oncologists
University Hospital
Biannual Therapeutic Standards Ostrava
University Hospital
Ostrava
Jihlava Olomouc
Regional Hospital Jihlava University Nový Jičín
Hospital Olomouc
Regional
České Budějovice Hospital
Brno Novy Jicin
Regional Hospital Ceske Masaryk Memorial Cancer
Budejovice Institute Brno
University Hospital Brno Zlín
and St. Anne's University Regional
Hospital Hospital
Zlin
Laboratories must hold accreditation decision according to CSN ISO/IEC 17025/15189 to meet
European diagnostic standards and perform external quality control.

12. Sample size in the registries: overview
(the system started with Herceptin in 2005)
Breast Registry Renis – mRCC Registry
Herceptin – adjuvant Sutent 1221
1852
therapy
Nexavar 719
Herceptin – mBC 1120
Afinitor 204
Herceptin – combined 194
Torisel 47
Lapatinib 222
Avastin 40
Avastin 85
Registry Corect – Colorectal Cancer
NSCLC Registry
Avastin 3731
Tarceva 2183
Erbitux 815
Alimta 819
Vectibix 183
Avastin 59
Iressa 31 TOTAL:
Alimta - MPM 124 > 13 500 valid records
Tarceva – Pancreatic cancer 58

13. Accessible follow-up (in months)
Follow-up (months) Min Median Max
Registry Therapy Sample Median Min Max
Herceptin – adjuvancy 1593 17,5 0,0 63,9 Her-adjuvance
Herceptin - mBRC 1005 18,5 0,1 112,8 HER-mBC
Breast
Lapatinib 213 7,8 0,0 45,3 lapatinib
Avastin 83 11,2 0,7 38,2 avastin
Avastin 3612 11,9 0,0 70,4 Avastin-crc
Corect Erbitux 787 9,0 0,0 68,3 erbitux
Vectibix 168 6,7 0,0 29,5 vectibix
Tarceva 2121 4,3 0,0 54,3 Tarceva
Tulung – Alimta 786 5,6 0,0 43,0 Alimta
NSCLC Avastin 56 7,4 0,2 18,5 Avastin
Iressa 28 3,3 0,0 14,6 Iress
0 20 40 60 80 100 120
Follow-up (months)

14. Duration of applied target therapy as example of quantitative
outcome (suitable for assessment of economic demands)
Therapy duration (weeks) 10% percentile Median 90% percentile
Registry Therapy Sample Median 10% 90%
Herceptin – adjuvancy1) 1132 50,9 30,0 54,6 Herceptin - adjuvance
Herceptin – mBRC1) 727 45,6 11,0 124,1 Herceptin - mBC
Breast
Lapatinib 149 20,6 5,7 58,4 Lapatinib
Avastin 55 25,0 6,0 55,0 Avastin - Prs
Avastin 2610 26,0 7,8 66,4 Avastin - crc
Corect Erbitux 612 19,1 2,1 52,1 erbitux
Vectibix 119 16,9 4,0 46,0 vectibix
Tarceva 1671 11,0 3,0 43,9 tarceva
Tulung – Alimta 683 9,0 3,0 18,4 alimta
NSCLC Avastin 41 16,0 3,3 29,3 avastin
Iressa 13 9,0 4,1 31,7 iressa
0 25 50 75 100 125
Therapy duration (weeks)

15. Herceptin (adj. therapy) – progression-free survival
N*=1583
Survival time calculated since the therapy onset.
1,0
0,8 PFS
Median PFS
Not reached
(95% IS)
0,6
% patients
PFS
(95% IC)
0,4
1yr PFS 96,9 (96,0; 97,9)
2yr PFS 94,3 (92,9; 95,7)
0,2 5yr PFS 93,4 (91,7; 95,1)
0,0
0 12 24 36 48 60 72 84 96
Time (months)

16. Herceptin (mBRC) – progression-free survival
N= 1005
Survival time calculated since the therapy onset.
1,0
PFS
0,8
Median PFS 14,5 months
(95% IS) (12,8; 16,2)
0,6
% patients
PFS
(95% IC)
0,4 1yr PFS 56,5 (53,3; 59,8)
2yr PFS 27,4 (24,0; 30,8)
0,2 5yr PFS 17,6 (13,9; 21,3)
0,0
0 12 24 36 48 60 72 84 96 108 120
Time (months)

17. 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

18. Predictive information system for cancer care:
Step 2 = Predictive estimation of incidence and prevalence
Breast cancer (C50)
INCIDENCE Number of cases
2012 (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 Number of cases
2012 (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)

19. 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
100% Organised breast
Proportion of cases
cancer screening
80%
60%
40%
20%
0%
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
2099
2000
2001
2002
2003
2004
2005
2006
2007
2008
09
19
Rok
Stage IV * DCO, cases diagnosed by autopsy, early
Stage III Unstaged deaths, therapy had not been started due to
objective reasons
Stage II incomplete records
Stage I objective reasons* Source of data:
Czech National Cancer Registry

20. Data collection, mining, analysis
Prof. Ladislav Dusek, Ph.D. Jan Mužík, Ph.D., senior data analyst
director Institute of Biostatistics and Analyses
Institute of Biostatistics and Analyses Masaryk University, Brno, Czech
Masaryk University, Brno, Czech Republic Republic

21. 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.

22. • Part I – Introduction to Personalized
Medicine in the Czech Republic
• Part II – BIOMEDREG Project as a
New Research Platform for
Molecular and Translational
Medicine

23. Infrastructural project for chemical biology and translational
medicine (BIOMEDREG) – concentrating, evaluating and
developing the national chemical and biomarker knowledge
Compound
storage/library Clinical
High throughput
trials
screening
Preclinical
studies
Institute of Organic Chemistry and Biochemistry, ASCR
Institute of Chemical Technologies Prague
Medicinal chemistry
Palacký University Olomouc
Universtiy Hospital Olomouc
Data collection for
national &
Biomarkers international
databases
Biobanking Therapeutic
standards

24. Biomedicine for regional development and human
resources
BIOMEDREG
Project Leader:
Primary aim:
Palacký Universty in Olomouci
To establish the Institute of
Partners: OLOMOUC Molecular and Translational
University Hospital in Olomouc
Medicine at Palacky
Institute of Organic Chemistry and Biochemistry AS
University in Olomouc
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

25. Building of research infrastrucutres in the Czech Republic
1952-56 2010-2012
Professor of Pathology R. Kodousek

26. 1956
2012
(construction phase – 15 months,
4700 m2)

27. 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

28. 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

29. 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

30. 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 BIOMEDREG
biology, e.g. in small molecule characterization, elaboration of a biological mechanism of action; EATRIS
• EU-Openscreen – interface: collaborative use of technology and interdisciplinary expertiseCEITEC
for
OLOMOUC
small molecule discovery and development, access to large compound libraries or INSTRUCT
ICRC
chemoinformatics, databases; ECRIN
RECAMO
• EuroBioImaging – interface: collaboration on nonstandard/sophisticated problems in BBMR BRNO
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.

31. 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

32. THANK YOU FOR
ATTENTION
marian.hajduch@upol.cz
hajduchm@gmail.com
www.imtm.cz
www.medchembio.cz