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Applying caTissue to the Biospecimen Quality Problem

Applying caTissue to the Biospecimen Quality Problem. Carolyn C. Compton, M.D., Ph.D. Director, Office of Biorepositories and Biospecimen Research Acting Director, Office of Technology and Industrial Relations caBIG Annual Meeting 2008 Washington, DC.

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Applying caTissue to the Biospecimen Quality Problem

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  1. Applying caTissue to the Biospecimen Quality Problem Carolyn C. Compton, M.D., Ph.D. Director, Office of Biorepositories and Biospecimen Research Acting Director, Office of Technology and Industrial Relations caBIG Annual Meeting 2008 Washington, DC

  2. Genomics Proteomics Metabolomics Progress in Cancer Treatment and Research are Dependent on High Quality Human Biospecimens Identification of targets for drug development, treatment and prevention Identify biologic variations that determine drug efficacy and drug toxicity Defining markers for susceptibility, screening and reoccurrence Development of molecular based taxonomy of cancer Elucidation of molecular mechanisms of neoplasia Validation of new therapeutics All DependOn High-Quality, AnnotatedHuman Biospecimens

  3. Biospecimens Have Their Own Unique Biologic (and Molecular) Life History • Life history: parts I, II and III • Associated with the clinical history of the patient while in situ • Apart from the patient after removal until stabilization • Post-stabilization degradation • All influence the molecular profile of the specimen • What is the influence of each “part” of the continuum on a given molecular profile? • How can we tell biologic fact from biologic artifact?

  4. Medical/ Surgical Procedures Restocking Unused Sample Handling/ Processing Scientific Analysis Patient Acquisition Storage Distribution The Recorded Life History of a Biospecimen: A Story in Progress Compilation and Analysis of Biospecimen Information Compilation and Analysis of Scientific Data Clinical/Clinical Research Outcomes

  5. Annotated Variables are Key Pieces to the Puzzle: Which Elements of a Molecular Profile Reflect the Biology of the Disease vs. Artifact Post-acquisition: • SOPs for specimen processing? • Preservation and processing variables? • Storage and shipping conditions? • QA/QC measures for specimen processing methods and reagents used? • Key Data: • Pre-acquisition: • Pre-op treatments administered? • Intra-op drugs delivered? • Intra-operative events (bleeding; blood pressure changes)? • Surgical variables (duration; approaches; modifications)?

  6. Variables Surrounding Biospecimen Acquisition • Pre-acquisition variables: • Antibiotics • Other drugs • Type of anesthesia • Duration of anesthesia • Arterial clamp time • Blood pressure variations • Intra-op blood loss • Intra-op blood administration • Intra-op fluid administration • Pre-existing medical conditions • Patient gender Post-acquisition variables: • Time at room temperature • Temperature of room • Type of fixative • Time in fixative • Rate of freezing • Size of aliquots • Type of collection container • Biomolecule extraction method • Storage temperature • Storage duration • Storage in vacuum

  7. Framework for Understanding the Impact of Variables on Molecular Analysis VARIABLES OTHER TECHNOLOGIES CGH CGH CGH CGH CGH CGH CGH CGH Analysis Method FISH FISH FISH FISH FISH FISH FISH FISH PCR PCR PCR PCR PCR PCR PCR PCR • NORTHERN DNA PCR • RT-PCR WESTERN MICRO-ARRAY Feature of Interest RNA • MASS SPEC • SCANNING EM PROTEIN IMMUNOSTAINING • TRANSMISSION EM LIGHT MICROSCOPY (H&E) MORPHOLOGY Blood Serum Plasma Urine Saliva Normal Tissue Cancer Tissue Other Specimen Type

  8. Pre- and Post- Acquisition Variables Impact Clinical and Research Outcomes • Effects on Clinical Outcomes • Potential for incorrect diagnosis • Morphological/immunostaining artifact • Skewed clinical chemistry results • Potential for incorrect treatment • Therapy linked to a diagnostic test on a biospecimen (e.g., HER2 in breast cancer) • Effects on Research Outcomes • Irreproducible results • Variations in gene expression data • Variations in post-translational modification data • Misinterpretation of artifacts as biomarkers

  9. Biospecimen Research Network (BRN): Defining the influence of pre-and post-acquisition variables on downstream molecular analysis data BRN research addresses the following challenges in biospecimen science: • Bridging gaps between existing clinical practice and emerging technologies • Defining significant variables for prospective collections • Developing evidence-based SOPs and biospecimen quality indicators Activities of the BRN program to date: • Public outreach to define issues and needs in biospecimen standardization • Consulting on biospecimen issues for programs within NCI/NIH • BRN laboratory: research studies with intramural and extramural collaborators • Development of the Biospecimen Research Database • Searchable web tool for biospecimen literature/published data • Extramural research programs to define pre-analytical variables

  10. New Extramural Research Program An ordered approach to filling the knowledge gaps: RFP • Studies designed to assess effects of pre-analytical variables in human specimens on the results of genomic, epigenomic, and proteomic analyses • Model of variable-controlled and/or variable-annotated biospecimen acquisition and invariable molecular analysis • Trans-disciplinary and highly collaborative design • Addresses the many operational factors that influence specimen variation A creative approach to meeting existing challenges: BAA • Solicitation of solutions to unmet needs and difficult issues

  11. Tissue Acquisition and Processing Variables • Post-operative ischemia • Room temperature • Type of preservative • Rate of freezing/fixing • Tissue processing • Multiple formulaic variables • - Multiple time settings for each • Recorded/annotated • Anesthesia • Intra-operative ischemia • Many other variables Four hospital centers Cancer and normal tissues Yrs 1-2: Assess existing variables, compare among sites, same sample types Years 3-5: Systematically alter selected variables, intra-specimen comparisons H&E IHC FISH RNA isolation Storage

  12. Biospecimen Research Case Studies: Annotation of Tissue Acquisition Variables

  13. Annotation of Tissue Acquisition Variables: Data Capture Model

  14. Biospecimen Research Case Studies: Annotation of Blood Collection and Plasma Processing Variables

  15. Annotation of Blood Collection and Processing Variables: Data Capture Model

  16. Pathway to Scientifically Validated Specimen Handling Practices Data-Driven Quality SOPs Biospecimen Research Empirical NCI Best Practices for Biospecimen Resources 2007 Restocking Unused Sample Medical/ Surgical Procedures Handling/ Processing Storage Distribution QC/QA Acquisition

  17. Expected Program Outcomes • Publications and presentationsfrom the program on the effect of human specimen pre- and post-acquisition variables on downstream molecular analysis • Publicationsfrom members of the scientific community at large in response to raised awareness of the importance of such studies • Increased attention to QA/QC important to downstream molecular analysisby manufacturersof consumables, reagents, and robotics (e.g., vacutainers used for blood collection, tissue preservatives, tissue processors) • CAP guidelines based on new data with implementation in the clinical arena: Greater attention to QA/QC of hospital tissue preservation procedures and equipment, resulting in higher quality preserved tissues for patient molecular diagnosis and research • Implementation of data-driven standards for specimen handling in new venues: Inclusion of biospecimen handling parameters in clinical trials and in research, development, and regulation of cancer biomarkers • GREATER REPRODUCIBILITY OF RESEARCH AND CLINICAL RESULTS

  18. Applying caTissue to the Biospecimen Quality Problem Carolyn C. Compton, M.D., Ph.D. Director, Office of Biorepositories and Biospecimen Research Acting Director, Office of Technology and Industrial Relations caBIG Annual Meeting 2008 Washington, DC

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