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caBIG Biospecimen and Pathology Tools by oyc99684

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									                caBIG Biospecimen
                and Pathology Tools




                Ian Fore, D.Phil.
                NCI Center for Biomedical
                Informatics and Information
                Technology




December 2006
Outline


•   Role of biospecimens
•   NCI biospecimen initiatives
     • Best Practices for NCI supported biorepositories
     • Explaining caBIG
     • Biospecimen Research Network
•   caBIG Applications developed
•   Other areas of interest
The Foundation of Science: Reproducibility


 • First rule of science: Valid data are reproducible
 • The enemy of reproducibility is variation
 • Because of biological complexity, some
   variation cannot be eliminated
 • Much of the variation seen in “omics” studies in
   results from sources other than biological
   complexity
The Discovery “Pipeline”:
Potential Sources of Variation



                                                                  Analytical tools are
   Hypothesis                                                       inadequate to
                           Experimental materials,
       is                                                        complexity of data or
                            e.g., biospecimens, are
     wrong                                                          flawed at core
                           highly variable in quality




             Experimental                      Tools are inadequate,
               design is                         not applicable to
                flawed                         experimental design,
                                                  or even broken




Hypothesis      Experimental    Experimental      Experimental     Data Collection
                  Design          Materials       Technologies      and Analysis
Molecular Research and Analyte Variation




The challenges:
• Varying methods of collection, processing, and storage can
  alter the physical/biologic state of the specimen
• Varying associated specimen data elements alter what the
  scientist knows about the character/nature of the specimen
• Variable clinical information alters what the scientist knows
  about the patient (biologic context of the specimen)
• Variable restrictions (patient consent; other ethical, legal, and
  policy issues) alter what the scientist may do with the
  specimen and/or data
NCI Best Practices for Biospecimen
Resources


                                  Objective:
                                      • Unify policies and procedures for
                                        NCI-supported biospecimen
                                        resources
                                      • Previously published as “First
                                        Generation Guidelines for NCI-
                                        Supported Biospecimen
                                        Resources”
                                      • Public comments received and
                                        addressed
                                      • Final to be published as “NCI Best
                                        Practices for Biospecimen
 http://biospecimens.cancer.gov         Resources” and awaiting approval
                                        of the NCAB
Informatics in the NCI Best Practices

• General Functionality
      Tracking the “life cycle” of a biospecimen
      QA/QC
      Monitoring and reporting biospecimen quality
      Security of sites
• Identification of Biospecimens
    Unique identification to each biospecimen
    Biospecimen tracking
• Integration with Local Systems
• Interoperability
• Ethical and Legal Issues
    Meet privacy and human subjects regulations
    Meet State and Federal requirements
Informatics Systems are a Key Tool for
Biospecimen Resources

• Informatics systems should be robust and reliable to sustain day-
  to-day operation of a biospecimen resource
• Informatics systems should be able to meet changing scientific
  needs
• Interoperability of system is key to exchanging data and
  biospecimens
• System should support all aspects of biospecimen resource
  operation
• Use informatics systems that support the linking of specimens
  with associated data and protect the health information of
  patients
• Adhere to or initiate review of NCI Center for Bioinformatics guidelines
  and tools; caBIG™ “silver-level” compatibility is recommended
Biospecimen Best Practices Toolkit:
Written Background Materials

• Items for distribution at meetings and through the OBBR Web site
    NCI Best Practices for Biospecimen Resources
    Biospecimen Basics: An Overview of the NCI Best Practices for
     Biospecimen Resources
    Implementing caBIG™ for Biospecimen Resources: An Overview
    Implementing caBIG™ for Biospecimen Resources: Next Steps
    Providing Your Tissue for Research
    Other biospecimen-related articles, publications, and news stories of
     interest
Implementing caBIGTM for Biospecimen
Resources: An Overview

• One-page document with broad overview of caBIGTM for Biospecimen
  Resources

• Target audiences include:
    Patients and Patient Advocates
    NCI-designated Cancer Center Directors
    Strategic Thinkers at Institutes and Biospecimen Resources


• Topics Covered:
      What is caBIGTM and What does it offer Biospecimen Resources?
      Strategic Considerations
      Benefits to patients and advocates
      Benefits to researchers and resource directors
Implementing caBIGTM for Biospecimen
Resources: Next Steps

• 9-page document highlighting “The Road to caBIGTM
  Compatibility”
• Designed for resources interested in the specific steps required
  for implementing caBIGTM compatibility
• Addresses public comments and frequently asked questions

• Setting the Stage:
    Core Concepts
    How does caBIGTM compatibility work
    FAQs
• Turning to Solutions:
    Available software tools
    Overview of Alternatives
    Skills, Technology, and Resources Required
Many SOPs Around the World:
Which are the best?




• Impossible to call any one “best” (even NCI’s)
   • All have strengths and weaknesses
   • No single set of SOPs are applicable to all clinical and research
     analytical platforms
   • Very few SOPs are based on scientific evidence




                                       Where we need to go
Biospecimen Research:
What Needs to Be Understood?




 Variables (examples):                      Variables (examples):
  Antibiotics         Time 0                Time at room temperature
  Other drugs                               Temperature of room
  Type of anesthesia                        Type of fixative
  Duration of anesthesia                    Time in fixative
  Arterial clamp time                       Rate of freezing
                                             Size of aliquots




            Medical/                                                                       Restocking
                                         Handling/                            Scientific
 Patient    Surgical    Acquisition                  Storage   Distribution                 Unused
                                        Processing                            Analysis
           Procedures                                                                       Sample


       Pre-acquisition                Post-acquisition
Biospecimen Research Program:
Projects Related to Goals

• “Bridging the gap” between existing clinical practice for
  biospecimens and emerging technologies for personalized
  diagnostics and therapies
   •   Tissue preservation variables and their impact on downstream applications
   •   Robotic surgery vs. manual surgery for prostate

• Defining the most significant variables for prospective collection
  of tissues, blood, and body fluids
   •   Effects of pre-acquisition variables and biomolecule extraction methods on
       biomolecule analysis results in blood

• Developing evidence-based biospecimen quality indicators for
  specific analytical platforms
   •   In conjunction with above study, with accepted proper and improper conditions for
       collection and biomolecule analysis in blood
BRN Pilot Project Example:
HER2 Testing

•   HER2 (ERBB2) gene is amplified in ~ 20% of breast cancers
•   HER2 over-expression (“positive” status): important measure of clinical
    outcome and recommended therapy
•   Clinical testing for HER2 status:
     •   Formalin-fixed paraffin-embedded
         excised breast tissue:
          •   Immunohistochemical test (0-3+)
          •   2+ cases: FISH
     •   Pathologist uses scoring system
         to report status
•   Positive result triggers therapy: ~$55K/year
•   False-positive: risk of cardiotoxicity, no clinical benefit
•   False-negative: missing potentially beneficial treatment
•   Genentech estimates 5,000 false positives and 7,000 false negatives
    occur per year: problem not the tests but where they are performed.
Short List of Critical Variables:
HER2 Immunohistochemistry

• Was the tissue fixed in formalin? Buffered formalin?
• How long was it fixed?
• How long was it in the processing machine?
• How long was it processed through each step in the
  processing machine?
• What temperature was the paraffin in the processing
  machine?
• Additional factors include:
    • different immunostaining protocols/automated processors
    • Differential pathologist readings of the stained tissue
• Collaboration underway with Walter Reed
  Army Medical Center (WRAMC) to evaluate
  HER2 fixation variables
Other BRN Pilot Projects




   • Effect of warm ischemic time on gene expression for colon and renal
     cancers
   • Effect of resected specimen size and weight on RNA and protein
     analyses
   • Comparison of RNA and protein yields and quality from different laser
     microdissection platforms
   • Effect of necrotic tissue on DNA analyses
   • Effect of tumor tissue DNA extraction methodologies on downstream
     analyses
   • Determination of FineFIX on histologic quality and recovery of RNA from
     human prostate tissue
   • Effect of different formalin fixation times on DNA analyses
   • Effect of variations in urine collection and storage on ELISA detection of
     VEGF
Defining a minimal clinical dataset


   •   Specified in the Best Practices document
   •   Minimal set of clinical data that should be recorded with Biospecimens
   •   Drafted by NCI Biorepository Coordination Committee
   •   Seeking review with various groups
   •   Including ISBER
Minimal clinical dataset (1)


                              Item                           Notes

  Age                                     or >= 90, at collection

                             Smoking
  Exposures (where age
                             Drinking
  > 18)
                             Occupation

  Gender

  Race

  Ethnicity

  Disease diagnosis/ Normal

  Source/ method of diagnosis

  Treatment type/ none

  Height

  Weight


  Family history of cancer
Minimal Clinical Dataset (2)

                                                            Also record for blood specimens in blood
                            Histologic Type
                                                            borne cancers
                            Grade

                            Size

  For tissue specimens      Nodal status (pos/neg, #
  only,                     pos/total nodes, etc)

                            TNM stage


                            Procedure                       Procedure by which specimen was obtained

                                                            Biomarkers used in routine care e.g.
  Biomarkers                                                Estrogen and Progesterone receptor
                                                            sensitvity
                            Death                           Year only
  Outcome - or will it be
  possible to get these     Date of last cancer follow-up   Year only
  data when outcome is
  known                     recurrence (local, distant,
                            unknown)
  Collection method

  Comorbidity
Tissue Banks and Pathology Applications

      • caTISSUE Core (WU) – Core specimen
        handling and tracking functions

      • caTIES (UPMC) - Text extraction and de-
        identification of surgical pathology reports

      • caTISSUE Clinical Annotation Engine
        (UPMC) - Annotation of specimens with
        clinical data
caTissue Core


•   Version 1.0 - March 2006
•   Version 1.1 - February 2007
•   Version 1.2 - June 2007

•   Developed by Washington University in St Louis
•   Requirements and testing
     • Thomas Jefferson University
     • Indiana University
     • University of Pennsylvania
     • University of Pittsburgh
caTissue Core 1.2 enhancements


•   Usability enhancements
•   Easy access to edit from any search
     • ... but only if you are authorized to edit
•   Support for a “Collection Calendar”
     • Named events
     • Default addition of planned specimens
•   User interface improvements
•   Propagate collection values for all specimens in a group
•   More intelligent storage container allocation
•   Default pages now relevant to logged in user
Login
Admin blank
Add container type
Add container
Add CP
Collection events
Biospecimen menu
Full screen option
Patient list
Search
Search Results
caTIES Query
caTIES - Surgical Pathology Report coding
caTissue Suite 1.0


•   Integration
     • caTissue Core
     • caTIES
     • Clinical Annotation
•   Much work already done
     • Put on hold in preference to caTissue Core 1.2 usability
•   Due March 2008
caTissue Suite 1.0 - features


•   Dynamic Extension
     • Data models
     • Data elements
     • Ability to add and share custom data
•   Saved queries and reports
•   Consent tracking
•   Ordering
•   Shipping
•   Query across multiple caTissue sites
•   Site configurable security scheme
Specimen Locator
Reporting mechanism - Cooperative Groups


•   By Clinical Trial Protocol
     • No. of patients enrolled

     •   No. of specimens stipulated
           •   FFPE
           •   Frozen tissue
           •   Whole blood
           •   …
           •   Total:

     •   No. of specimens collected
           •   FFPE
           •   Frozen tissue
           •   Whole blood
           •   …
           •   Total:

•   Specimens distributed by type and protocol
How is the grid relevant to biorepositories?


•   Aim is to enable interoperation of Tissue Banks
•   Proposal
     • Establish a simple standard for a web service to allow communication of
        summary level information
     • Numbers and types of specimens
     • Directory of banks offering this information
     • Ability to query multiple banks
     • Mapping to terminology
Integrating data from repositories



                    Report aggregator




                      Common model

    Service           Service           Service
    implementation    implementation    implementation

        Text File      Local system        caTissue
How is the grid relevant to biorepositories?


•Aim is to enable interoperation of Tissue Banks
•Proposal
     • Establish a simple standard for a web service to allow communication of
         summary level information
     • Numbers and types of specimens
     • Directory of banks offering this information
     • Ability to query multiple banks
     • Mapping to terminology
•Keep it simple
This is complex!
This is simple
How is the grid relevant to biorepositories?


•Aim is to enable interoperation of Tissue Banks
•Proposal
     • Establish a simple standard for a web service to allow communication of
         summary level information
     • Numbers and types of specimens
     • Directory of banks offering this information
     • Ability to query multiple banks
     • Mapping to terminology
•Keep it simple
•Keep it agile
     • Try it out
     • Be ready to modify it based on feedback
•Can/Should we make it international?
Strategic plan


•   Virtual microscopy
     • Distributed review
•   Tissue microarray (TMA) support
     • TMA Design
     • Image Analysis
     • Annotation
     • Imaging
     • TMA Facility management
     • Image query
     • Expt design
     • Data Stds
     • Image scoring
Additional Information




•   http://biospecimens.cancer.gov   •   https://cabig.nci.nih.gov/workspaces/TBPT

								
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