Bedeutung des EU Spidia Projekts für Biobanken Standardization and Improvement of Generic PreanalyticalTools and Procedures for In Vitro Diagnostics 11. Jahrestagung Sektion Molekulare Diagnostik der DGKL Tutzing, 10. May 2012 Dr. Uwe Oelmüller QIAGEN GmbH (Koordinator)
Agenda � SPIDIA Project History and Goals � Results & Status � New Technologies & Tools � Pan-European Guidelines � Sample Quality Markers
Diagnostic Workflow From Patients to Clinical Results Patient Pre-analytical Clinical Patient Analytical Assays Sample Workflow Results Patient Sample Sample Bioanalyte Anesthesia Collection Logistics Preparation Treatment e.g. Drugs e.g. Arterial Life Style Clamp Time Time 0
It is Real Problem “Preanalytical errors still account for nearly 60%-70% of all problems occurring in laboratory diagnostics, most of them attributable to mishandling procedures during collection, handling, preparing or storing the specimens”. Lippi G. et al.. Preanalytical quality improvement: from dream to reality. Clin Chem Lab Med. 2011 Jul; 49(7):1113-26. Epub 2011 Apr 25. Preanalytics Costs of ~ 347,000 € / year in 68 % an average German hospital Analytics caused by pre-analytical errors 13 % Frost & Sullivan 2011 on behalf of BD 19 % Postanalytics
Project Main Goals 1. Pan-European guidelines (Molecular) 2. New tools & technologies 3. Sample quality biomarkers 4. Training and dissemination 5. Co-work with other international initiatives � NCI / OBBR, CLSI, EFCC etc.
SPIDIA Project Facts � Consortium 7 public research organizations 8 companies 1 standards organization (CEN) � Coordinator QIAGEN GmbH � October 2008 Kick Off Meeting � Duration 4 years (6 months prolongation intended) � Budget 13 Mio € � EC Contribution 9 Mio € � Web page www.spidia.eu � Newsletter
Agenda � SPIDIA Project Project History and Goals � Results & Status � New Technologies & Tools � Pan-European Guidelines � Sample Quality Markers
New Tissue Collection & Stabilization PAXgene Tissue � > 1.500 compounds and mixtures screened (3 years) � > 8.000 tissue samples processed to date � Fixation & Stabilization (non-cross linking) � Linked RNA, DNA, protein isolation procedures RNA miRNA DNA Resect Fix Stabilize Process & Gross H&E IHC Allows histomorphology and molecular testing from the same specimen Western Blot ISH For Research Use Only
Histomorphology and IHC Research Study - PFPE vs. FFPE H&E Staining Estrogen Receptor a (clone 1D5) IDC of Breast IDC of Breast FFPE PFPE PFPE revealed preservation of morphology and antigenicity comparable to FFPE Groelz D. et al ., unpublished data. Cap M. et al., PLoS ONE 6(11): e27704 (2011) Viertler C. et al. , Journal of Molecular Diagnostics 2012, accepted for publication.
Ct 10 15 20 25 30 35 40 45 50 5 Groelz et al ., unpublished data Viertler et al ., Journal of Molecular Diagnostics 2012, accepted for publication). 18s CTNNB 1 COL1A1 Human molecular mechanism of cancer TaqMan Array Gene Signature 96-Well Plate: FN1 RHOA FOS Gapdh CCND1 SP P1 E RB B2 IGF1R CDH1 NFKBIA A KT1 CDKN1B B CL2L1 CDK4 SHC1 ITGAV TP 53 A KT2 GSK 3B B AX CDKN1A ITGB1 TGFB 1 ��������������� ���� �� ������� ���� �������������� ���� A BL1 HP RT1 M AP K14 TCF3 SRC NFK B1 GUS B E LK1 VE GFA K RA S GRB2 B CA R1 RA C1 B CL2 SM A D4 genes (sorted by Ct cryo) M DM 2 CRK NFK B2 BRAF M AP K3 FADD PTEN CCND3 JUN RE LA P TK 2 DVL1 PIK3R1 M Y C CDK2 NRA S TGFBR2 CDKN2A M AP K1 M AP 2K1 RB1 HRA S TGFBR1 PTK2B E2F1 AP C FZD1 CAS P9 SOS1 CAS P8 ITGB3 BID KDR BCL2L11 M AP K8 RAF1 P IK 3CA CCND2 M AP 3K5 FA S CCNE1 FY N LEF1 FGF2 E GFR IGF1 CYCS HGF FAS LG ITGA2B K IT CDC42 M AX CDKN2B W NT1 PFPE FFPE CRYO
ccfNA Profiles in Whole Blood What is missing? � Studies for understanding fcDNA and ccfRNA profile stability / changes in whole blood and in plasma � Development of ccfDNA and ccfRNA profile preservation technologies EDTA blood was incubated for up to 6 days at room temperature. Blood fcDNA pattern stability was determined by separating the purified plasma DNA on a 2100 Agilent Bioanalyzer Horlitz M. et al., unpublished data
Ongoing Technology & Tools Developments for Other Sample Types � Fine Needle Aspirates � Stabilization of morphology, antigenicity, DNA, RNA, proteome � Whole Blood � Stabilization of cell morphology and biomolecule profiles � Swabs � Stabilization and improved processing of respiratory and samples for molecular analysis � Stabilized Whole Blood � Integrated automated sample-to-result workflows (cellular RNA, ncRNAs incl. miRNAs)
Agenda � SPIDIA Project Project History and Goals � Results & Status � New Technologies & Tools � Pan-European Guidelines � Sample Quality Markers
Evidence Based Guidelines Examples Blood DNA & RNA, Plasma ccfDNA � Phase 1 Trials - Laboratories used their workflows & tools � Let by Prof. Pazzagli (Univ. Florence), supported by the EFCC � Guidelines / Standards Concepts - CEN � Phase 2 Trials – Laboratories use SPIDIA’s optimized workflows � Guidelines / Technical Reports Developments - CEN No. of Participants Percentage of Participants (29 who sent NA NA samples SPIDIA Trials countries) samples back sent back Blood RNA 102 93 91 % Blood DNA 130 121 93 % Plasma DNA 67 62 93 % Total 299 276 92 %
Blood DNA Trial 1 - Examples for Pre-analytical Workflow Variations � Blood storage time before DNA extraction ≤ 6 days • 39 labs: • 60 labs: 6 – 10 days ≥ 10 days • 53 labs: � Blood storage temperature before DNA extraction • 18 labs: -20 ˚C • 129 labs: +4 ˚C • 9 labs: ambient temp. � Isolated DNA storage before analysis • 20 labs: -20 ˚C • 111 labs: +4 ˚C • 27 labs: ambient temp. Pazzagli M. et al., manuscript in preparation
DNA Length Variation – Pulse Field Gel Electrophoresis 3 17 63 82 88 103 118 120 130 138 175 183 207 1 14 49 52 65 78 100 124 125 169 195 203 [kb] 194,0 145,5 97,0 195 kb 4.36 kb 48,5 23,1 9,42 6,55 4,36 � High molecular weight DNA integrity: degradation, fragmentation � High variability among samples Hartmann C. et al., unpublished results Pazzagli M. et al., manuscript in preparation
Impact of DNA quality on Immune T cell Repertoire Analysis (ImmunID Technologies) V contribution for each J gene – Research Trial (ImmunID Technologies, France) Ref. DNA from UNFI (DIV 54%) Sample 38 (Poor quality) (DIV 32%) � Lost of all long V–J rearrangements � Lost of part of intermediate length rearrangements L. Barraud et al. Unpublished data. Pazzagli M. et al., manuscript in preparation
Individual Samples React Differently Changes of Transcripts Profiles in Blood Human EDTA Blood stored at Room Temperature over 3 days ���� β β β β mRNA Guenther K. et al.. AMP Poster (2005)
Learning from Blood RNA Ring Trial 1 � No pooling of different donors’ blood • Accept that only sub-groups of ring trial participating laboratories get the same blood samples � No usual blood collection bags • Use dedicated EDTA bags � Immediate cooling of blood bags • Artificial gene induction and down regulation to be avoided � Use of intracellular RNA markers • External markers will behave differently
Proficiency Testing for Preanalytical Workflows used for Blood RNA Analysis K. Günther, F. Malentacchi, P. Verderio, S. Pizzamiglio, C. M. Ciniselli, A. Tichopad, M. Kubista, R. Wyrich, M. Pazzagli, S. Gelmini. Implementation of a proficiency testing for the assessment of the preanalytical phase of blood samples used for RNA based analysis. Clin Chim Acta. 2012 Apr 11;413(7-8):779-86.
Blood Sample Shipment - RNA Profile Changes Stabilized vs. EDTA Blood Box plots reflecting the mRNA expression of GAPDH (Panel A), IL1B (Panel B), IL8 (Panel C), and FOS (Panel D) measured in the three sample types REF, RNA A (PAXgene Blood RNA) and RNA B (EDTA). Each box indicates the 25th and 75th percentiles. The horizontal line inside the box indicates the median, and the whiskers indicate the extreme measured values. The dotted horizontal line indicates the median value of the REF samples (prior shipment) and serves for comparison. Guenther K. et al.. Clin Chim Acta. 2012 Apr 11;413(7-8):779-86.
Agenda � SPIDIA Project Project History and Goals � Results & Status � New Technologies & Tools � Pan-european Guidelines � Sample Quality Markers
Blood RNA Quality Marker Discovery � Quality markers measuring RNA up- & down-regulation • >150 micro arrays & RT-PCR studies (time course experiments) • 17 candidates (gene induction, gene down regulation, RNA degradation) • Technical assay validation • Next step: Performance validation within larger donor cohorts hLMNA_SFw 5.0 p=0.46 p=0.33 4.0 3.0 p=3.17*10 -6 2.0 p=4.28*10 -7 p=7.29*10 -7 1.0 0.0 0 2 6 24 48 72 -1.0 Rian E. et al. , unpublished data
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