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Le Biobanche di Campioni Inclusi
Bari, 16/12/14
Giorgio Stanta, Dipartimento di Scienze Mediche - Università di Trieste
MOLECULAR PATHOLOGY WGBIOBANKING AND MOLECULAR PATHOBIOLOGY WG
ARCHIVE TISSUES: IMPROVING MOLECULAR MEDICINE RESEARCH AND CLINICAL PRACTICEwww.impactsnetwork.eu
G. Stanta
Technical working groups#DNA and RNA extraction SOPs and IQC rules in AT (OECI, ESP)- G. Stanta, A. Jung, S. Bonin # NGS in diagnostics and clinical research (ESP)- G. Hoefler, K. Kashofer# Proteomics SOPs in AT (ESP, OECI)- K. Becker# Preanalytical conditions in tissues (ESP, OECI)- M. Dietel, G. Bussolati, A. Sapino# Heterogeneity (inter-WGs of ESP - OECI) – ESP WGs chairman, G. Stanta# CEN–New ISO 15189 rules-DNA, RNA and proteins from tissues – K. Becker, P. Riegman, G. Stanta, K. Zatloukal
Courses
MOLECULAR PATHOLOGY WG
BIOBANKING AND MOLECULAR PATHOBIOLOGY WG
BBMRI-ERIC CLINICAL BIOBANKS MEETINGBerlin 17/09/14
G. Stanta
ARCHIVE TISSUES WG
CLINICAL BIOBANKING WG
MEDICO-BIOLOGICAL RESEARCH
PATI
ENTS
BASIC RESEARCH………………
TRANSLATIONAL RESEARCH
RETROSPECTIVE CLINICAL RESEARCH
> 10 years on average > short timedevoted to future patients today’s patients
-verification of clinical cases-efficacy of the new therapies-therapy response subgroups-intrinsic and acquired resistance BM -very long follow-up studies-performance evaluation -to establish costs and benefits
G. Stanta
Applied medicine and clinical research are today an integrated and indissoluble process
CONCLUSIONS IN REVIEWS AND METANALYSIS……..“In conclusion, it is clearly evident from all these studies that, as with previous studies on gene profiling, most emerging miRNA signatures are not fully overlapping. These results might be explained by different specimens (frozen vs paraffin-embedded, micro- vs non-microdissected), experimental platforms used (quantitative PCR vs different miRNA array or in situ hybridization systems), tumour types, stage, and regimens as well as small sample size, ethnic differences in the study populations, lack of multivariate analysis and correction for multiple testing.” E Giovannetti et al Critical Reviews in Oncology/Hematology 81 (2012) 103–122
Takashi Akiyoshi et al “Recent approaches to identifying biomarkers for high-risk stage II colon cancer” Surg Today DOI 10.1007/s00595-012-0324-4 - 2012
Gene expression signatures for predicting the outcome in stage II colorectal cancer meta-analysis
Participating Organizations Organization SiteAustrian BBMRI Node www.bbmri.at
BBMRI-ERIC – Biobanking and Biomolecular Resources Research Infrastructure- European Research Infrastructure Consortium
www.bbmri-eric.eu
Czech BBMRI Node www.recamo.cz/en/bbmri
EATRIS – European Infrastructure for Translational Medicine
www.eatris.eu
ECCO – European CanCer Organisation
www.ecco-org.eu
ECPC – European Cancer Patient Coalition
www.ecpc.eu
EPAAC – European Partnership for Action Against Cancer
www.epaac.eu
ESP – European Society of Pathology
www.esp-pathology.org
EurocanPlatform http://eurocanplatform.eu/
French BBMRI Node www.biobanques.eu
German BBMRI Node forthcoming
German Society of Pathology www.dgp-berlin.de
Italian BBMRI Node www.bbmri-eric.it
Medical University of Graz www.meduni-graz.at
OECI – Organisation of European Cancer Institutes
www.oeci.eu
Royal College Pathologists www.rcpath.org
WHITE PAPER http://www.impactsnetwork.eu/Sections.aspx?section=170
Solutions: -RSS new study designs-Networks for accessibility of AT-Standardization of analysis methods
G. Stanta
Solutions: -RSS new study designs-Networks for accessibility of AT-Standardization of analysis methods
G. Stanta
RETROSPECTIVE SURVIVAL STUDIES (RSS) CASES: POPULATION BASED or HIGH NUMBER UNSELECTED CASES
STUDY DESIGN: WELL DEFINED AT THE BEGINNING OF THE STUDY
COLLECTION OF CASES: WITHOUT FOLLOW-UP DATA
MOLECULAR ANALYSES: -ACCURATE MICRODISSECTION -DEFINED SOPs AND IQCs
OUTCOMES: PROSPECTIVELY-LIKE COLLECTED
NEGATIVE RESULTSPOSITIVE RESULTS
ADDITIONAL STUDIES IN DIFFERENT POPULATION
PROCESS OF VERIFICATION AND VALIDATION G. Stanta
Solutions: -RSS new study designs-Networks for accessibility of AT-Standardization of analysis methods
G. Stanta
MODELS OF CLINICAL DATA AND TISSUE COLLECTION
G. Stanta
RETR
OSP
ECTI
VE S
URV
IVAL
STU
DIE
S
Hospital Clinical Information
Archive of FFPE Tissues
TumorRegistry
Hospital
Pathology
EPAACMODEL
PathologyNetwork
Hospital Clinical Information
Archive of FFPE Tissues
BBMRIMODEL
Hospital Clinical Information
Archive of FFPE Tissues
RegionalOrganiz.
Hospital
Pathology
AREAMODEL
Hospital Clinical Information
Archive of FFPE Tissues
Cancer Inst
Pathology
OECIMODEL
NIPABNetwork of Italian Pathology
Archive Biobanks
Pathology Departments joined to develop a national network
Tissue paraffin blocks stored for a minimum of 20 years by law.
It is estimated that in pathology archives over 300 million cases and around one billion tissue specimens are stored
SIAPEC
How to organize the network?#The network is set up as a virtual network of pathology archives (samples + associated clinical data) for clinical research.
# Participation in the network and in the projects is voluntary and collaborative (these materials are residues from clinical procedures with specific requirements).
# Clinical and follow-up information can be directly collected by pathologists because they also deal with the diagnostic procedures.
# Privacy is guaranteed by the professional secrecy of pathologists, who have the duty to pseudo-anonymize the cases.
# There can be different network models for different strategies that can be embedded in BBMRI-ERIC.
Solutions: -RSS new study designs-Networks for accessibility of AT-Standardization of analysis methods
G. Stanta
G. Stanta
Clinical research irreproducibility
Biological complexity
Technological complexity
SOURCES OF VARIABILITY #Tissue and macromolecule pre-analytical preservation
#Selection and standardization of analytical procedures
#Heterogeneity at the clinical, morphological or molecular level
BIOLOGICAL COMPLEXITY
G. Stanta
Clinical research irreproducibility
Biological complexity
Technological complexity
SOURCES OF VARIABILITY #Tissue and macromolecule pre-analytical preservation
#Selection and standardization of analytical procedures
#Heterogeneity at the clinical, morphological or molecular level
BIOLOGICAL COMPLEXITY
Pre-analytical Conditions in IHC
G. Stanta
Outside the pathology lab Inside the pathology labProteins during the preanalytical phase may be categorized into three groups:
(1) predictable stable; (2) predictable unstable; (3) unpredictable.
RNA is always degraded and needs specific technical capabilities for extraction and degradation standardization.CEN (the European Committee for Standardization) is developing preanalytic technical specifications on proteins, DNA and RNA in tissues to ISO 15189 which might become instrumental in 2015.
G. Stanta
Clinical research irreproducibility
Biological complexity
Technological complexity
SOURCES OF VARIABILITY #Tissue and macromolecule pre-analytical preservation
#Selection and standardization of analytical procedures
#Heterogeneity at the clinical, morphological or molecular level
BIOLOGICAL COMPLEXITY
Serena Bonin, Falk Hlubek, Jean Benhattar, Carsten Denkert, Manfred Dietel, Pedro L. Fernandez, Gerald Höfler, Hannelore Kothmaier, Bozo Kruslin, Chiara Maria Mazzanti, Aurel Perren, Helmuth Popper, Aldo Scarpa, Paula Soares, Giorgio Stanta and Patricia JTA Groenen.”MULTICENTRE VALIDATION STUDY OF NUCLEIC ACIDS EXTRACTION FROM FFPE TISSUES” Virchow Arch 2009
“Reverse transcription yield, indeed, can vary up to 100-fold depending on priming strategy, on the used enzyme, on the starting quantity of target RNA and even on the type of sequence that is going to be detected.”
G. Stanta
SOURCES OF VARIABILITY #Selection and standardization of analytical procedures
Bonin S , Stanta G. Nucleic acids extraction methods in fixed and paraffin-embedded tissues in cancer diagnostics. Exp Rev Mol. Diagn. 2013,13.
Serena Bonin, Falk Hlubek, Jean Benhattar, Carsten Denkert, Manfred Dietel, Pedro L. Fernandez, Gerald Höfler, Hannelore Kothmaier, Bozo Kruslin, Chiara Maria Mazzanti, Aurel Perren, Helmuth Popper, Aldo Scarpa, Paula Soares, Giorgio Stanta and Patricia JTA Groenen.”MULTICENTRE VALIDATION STUDY OF NUCLEIC ACIDS EXTRACTION FROM FFPE TISSUES” Virchow Arch 2009
“Reverse transcription yield, indeed, can vary up to 100-fold depending on priming strategy, on the used enzyme, on the starting quantity of target RNA and even on the type of sequence that is going to be detected.”
G. Stanta
SOURCES OF VARIABILITY #Selection and standardization of analytical procedures
Bonin S , Stanta G. Nucleic acids extraction methods in fixed and paraffin-embedded tissues in cancer diagnostics. Exp Rev Mol. Diagn. 2013,13.
SOPs-IQCs!!!
G. Stanta
Clinical research irreproducibility
Biological complexity
Technological complexity
SOURCES OF VARIABILITY #Tissue and macromolecule pre-analytical preservation
#Selection and standardization of analytical procedures
#Heterogeneity at the clinical, morphological or molecular level
BIOLOGICAL COMPLEXITY
The complex problem of heterogeneityMACROSCOPIC HETEROGENEITYETHNIC HETEROGENEITYCLINICAL HETEROGENEITY
MICROSCOPIC TISSUE HETEROGENEITYHISTOLOGIC TISSUE COMPOSITIONTISSUE REACTION
MOLECULAR HETEROGENEITYGENETIC CLONAL EVOLUTION EPIGENETIC CLONAL EVOLUTIONPHENOTYPIC PLASTICITYHOMO/HETERO-TYPIC INTERACTIONS
The complex problem of heterogeneityMACROSCOPIC HETEROGENEITYETHNIC HETEROGENEITYCLINICAL HETEROGENEITY
MICROSCOPIC TISSUE HETEROGENEITYHISTOLOGIC TISSUE COMPOSITIONTISSUE REACTION
MOLECULAR HETEROGENEITYGENETIC CLONAL EVOLUTION EPIGENETIC CLONAL EVOLUTIONPHENOTYPIC PLASTICITYHOMO/HETERO-TYPIC INTERACTIONS
Design of the study
Micro-dissection
The complex problem of heterogeneityMACROSCOPIC HETEROGENEITYETHNIC HETEROGENEITYCLINICAL HETEROGENEITY
MICROSCOPIC TISSUE HETEROGENEITYHISTOLOGIC TISSUE COMPOSITIONTISSUE REACTION
MOLECULAR HETEROGENEITYGENETIC CLONAL EVOLUTION EPIGENETIC CLONAL EVOLUTIONPHENOTYPIC PLASTICITYHOMO/HETERO-TYPIC INTERACTIONS
Design of the study
Micro-dissection
NGS
In situ methods
T.Centre T. Invasion
Hlubek et al.,Int J Cancer, 2007 F Elloumi et al BMC Medical Genomics 4:54;2011
G. Stanta
MICROSCOPIC TISSUE HETEROGENEITY
TMA ARRAYER MICRODISSECTION GENE - EXPRESSION QUANTITATIVE ANALYSIS - CtGene β-Actin mRNA CDK2 mRNASample Coring 1 Coring 2 Coring 1 Coring 2
1 21.48 21.64 29.43 29.162 28.45 28.22 32.92 32.92
3 23.71 23.72 32.32 31.994 28.84 28.75 33.29 33.295 28.08 28.36 33.24 33.24
#Treatment after coring 50°C for 30 min plus 60°C for 10 min (especially for 5mm cores)#Expected RNA yield from 5 sections (1cm2), 5 μm thick: 5 - 25 μg (related to tissue type and extraction method)
#1
TMA
#1
Gene β-Actin mRNA CDK2 mRNASample Tissues Coring Tissues Coring
1 23.01* 21.64 30.11 29.16
2 28.48 28.22 33.13 32.92
3 24.53 23.72 31.76 31.99
4 29.72 28.75 33.25 33.29
5 29.15 28.36 33.56 33.24*Cts after real time amplification of 10 ng of cDNA after reverse transcription with random hexamers - not standardized Cts
G. Stanta