055D-Amin-Development and Experience with Tissue Banking Tools to Support Cancer Research

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055D-Amin-Development and Experience with Tissue Banking Tools to Support Cancer Research Powered By Docstoc
					 Development and Experience with Tissue
Banking Tools to Support Cancer Research



Waqas Amin M.D, Anil V. Parwani M.D PhD and Michael J. Becich M.D, PhD1
 Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh,
 PA.USA 2Department of Pathology, University of Pittsburgh Medical Center,
                           Pittsburgh, PA. USA
Introduction:



  Over the last decade, the Department of Biomedical Informatics
   (DBMI) at the University of Pittsburgh has developed and deployed
   various tissue banking informatics tools to expedite translational
   medicine research.

  Deals with management of clinicopathologic annotation, inventory
   management and distribution of biospecimens that are collected and
   stored for translational research use by the scientific community.
Tissue Banking Informatics:



  Aggregation: Process to associate tissue samples with valuable data
   including demographic, epidemiology, pathology, progression, vital
   status, therapy and outcomes related data.

  Standardization: Collected data must be uniform or shareable. This
   standardized approach to annotation is to ensure uniformity,
   consistency, and quality of collected data. This facilitates information
   sharing across multiple institutions.

  Searchable: Development of an information model supported by
   standardized data collection approach allows annotated tissue
   samples to be matched with the research queries, thereby facilitating
   better understanding of the experimental design and result.
Data Requirement in Cancer Research:

     High quality, accurate and comprehensive data is required to
      support genomic, proteomic, clinical and translation research.
     Data must be acquired in accordance with legal and ethical subject
      polices.

   Type of Data Collection:
         Demographic data
         Patient clinical data
         Pathology block level data
         Patient treatment data
         Outcome and follow up data
         Biochemical data
         Genomic level data
         Cell and tissue level data
Data Collection Standards:

    Development of Common Data Element (CDE):

      Standardized clinical annotations defined in detail utilizing
       metadata. Allows uniform, consistent shareable data collection
       across multiple institutes/systems.

      Development of CDEs are supervised by multidisciplinary team
       and CDE subcommittee developed consensus CDE incorporating
       following standards applicable for a organ specific tissue.

          ADASP (Association of Directors of Anatomic and Surgical
           Pathology (ADASP) Cancer Reporting Guidelines
          American Joint Committee on Cancer (AJCC) Cancer Staging
           Manual
          NAACCR (North American Association of Central Cancer
           Registry) Data Standards for Cancer Registries
 Data Sources:
        Data import from automated electronic systems like AP-LIS,
         CP-LIS, Radiology and Registry information System (RIS).
        Patient questionnaire, patient health record and treatment
         charts, existing databases, consultation with referring
         physicians, archived data and pathology reports.

De-Identification of PHI:
 The purpose is to ensure proper confidentiality and privacy of human
  subjects based upon Institutional Review Board approved protocols.

 De-identification of PHI is done by an Honest Broker according to
  Health Insurance Portability and Accountability Act (HIPAA).
  regulations by designating unique codes to patient data related
  identifiers.
Specimen collection and standardization

     Biospecimens are collected according to pathology and tissue
      banking standardized protocol. Biospecimens are collected and
      stored for tissue banking project , includes:

             Paraffin Blocks
             Fresh Frozen Tissue
             Blood Products includes:
                      Serum

                      Plasma

                      Buffy Coat

                      RBC

                      WBC
        Tissue Banking Information Models and
                     Architecture:

 Two types of information models that have been utilized in the
  development of tissue bank.

        Organ-specific databases (OSD)
            Cooperative Prostate Cancer Tissue Resource (CPCTR)
             (www.cpctr.info)
            Pennsylvania Cancer Alliance for Bioinformatics Consortium
             (PCABC) (www.pcabc.upmc.edu)
            Early Detection Research Network (EDRN) Colorectal and
             Pancreatic Neoplasm database
            SPORE Head and Neck Neoplasm Database


        Model Driven Approach (Database)
            National Mesothelioma Virtual Bank (NMVB)
             (www.mesotissue.org)
OSD (Organ Specific Database):


  OSD is a three-tiered architecture, and implemented on an Oracle
   Application Server v10.1.2.3 running on a Windows 2003 and Oracle
   RDBMS v.10.2.0.2 running on an AIX 5L virtual host definition
   supported by IBM x3850 system hardware.

  Dynamic web pages are generated using Oracle http server and
   mod_plsql extensions for the database users.

  The data annotation engine is a flexible dynamic web-based tool,
   while the data query engine facilitates investigators to search de-
   identified information within the warehouse through a “point and
    click” interface.
OSD Multi Tier Architecture:


     Presentation          Metadata Engine                Physical Data


       Metadata
       Curation         Common Data Elements (CDE)        Application Data
                               Definitions                     Layer


        Admin                   HELP Builder
       Security
                    Business Rules              Mapping
                        Engine                  Engine     Metadata Data
                                                               Layer
       Manual
      Annotation




      Data Query             Security Engine
                                Registration               Security Data
                                                              Layer
                                Authorization
      Data Import
        Export                 Authentication
OSD (Meta Data Builder Tool):
OSD Feature List:


  To address the needs of the heterogeneous users we identified
   numerous criteria for success. Some requirements and features are
   listed below:
          Quick Statistics on overall data.
          Multi-mode search: Multiplex search and Advance search.
          Mechanism for keeping user’s orientated (e.g. help,
           persistence of last entered query text)
          Results in tabular forms, sorting on each column including
           access to full case report.
          Both Honest Broker and De-identified (researcher) access.
          Controlled access to subjects for different studies
Feature List (Contd..)


      Standard and customized query results of the data.
      Individual research and consent based access to information.
      Quick search using cases saved in “My Cases”.
      Query Builder interface.
      On Line Help Manual Builder.
      This model can support multi institutional data enterprise
       model.
      User Management Module helps create, revoke, control users
       access and activities within the database.
      Business layer allows for creation of complex/logical data
       fields based on data interpretation by experts.
OSD model Based Head and Neck Neoplasm
         Virtual Biorepository:

 It is Developing bioinformatics driven system to utilize multi model
  data sets from patient questionnaire, clinical, pathological, radiology
  and molecular systems

 Results in one architecture supported by a set of CDEs to facilitate
  basic science, clinical as well translational research

 Systems designed to facilitate semantic and syntactic interoperability
  in development of data elements (i.e., metadata or data descriptors
  using controlled vocabulary and ontology)

 Provides data entry, data mining and analysis tools.
OSD Integration with other Data Sources:

                   Genotype Lab
                       data                   BIOS

 AP-LIS/ CP-LIS                                         Patient
                                                      Insurance
                                                     information



 Bio-marker                SPORE H&N                    Human Papilloma
  data                  Neoplasm Database                   Virus
                                                         Questionnaire
                                                             data




     Radiology                                       RIS
                           Epidemiology
   (PET/CT) data
                             Project-1
                         questionnaire data
Data Collection & Annotation Tool




User
Authentication
Data Collection & Annotation Tool:



 User
 Management
 Module
Data Collection & Annotation Tool


Administrator
can create,
edit, revoke
control user’s &
their access to
different
applications
Data Collection & Annotation Tool:


Manual
data
collection
module




Case
summary
Data Collection & Annotation Tool



 Can switch
 quickly
 between
 different
 available
 applications as
 per user
 access rights
Data Collection & Annotation Tool



Quick over
all review
of
Statistics
on the
collected
database
Data Collection & Annotation Tool




Data
Query
template
Data Collection & Annotation Tool:




Standard
view
Data Collection & Annotation Tool


Descriptions
of different
views for
reference
Data Collection & Annotation Tool




                                    Allows data
                                    export for
                                    Statistical
                                    analysis
                                    packages,
                                    such as SAS,
                                    etc.
Data Collection & Annotation Tool




                                    User can
Full Case                           have
Report                              multiple
View                                “My
(Identified                         Case”
or De-                              lists for
identified                          different
as per                              studies
access
level
Data Collection & Annotation Tool




                                    User can also
                                    select any
                                    data field to
                                    create
                                    personalized
                                    views & save
                                    under ”My
                                    Views”
Data Collection & Annotation Tool




Administrator
can edit or
create data
views
  OSD based Databases Accruals:

                                                   Total # Cases,         Total Number of Biospecimens



Virtual Biorepository         Tissue type
                                                                                               Frozen          Blood/seru
                                                                          Paraffin Blocks      Blocks          m/Plasma


CPCTR                         Prostate             7000                   34641                17508           17508

                              Breast               3645                   1760                 847             823

PCABC

                              Melanoma             1762                   1885                 168             112

                              Prostate             7327                   5457                 1642            415

EDRN Colorectal and           Pancreas and colon   2459                   175                  942             1254
Pancreatic Neoplasm Virtual
Biorepository
SPORE’s Head & Neck           Head and Neck        11622                  2237                 0               1038
Neoplasm Virtual              Neoplasm
Biorepository


                                                                Amin et al. Tissue banking informatics 2010)
Model Driven Database (MDD):



   NMVB is developed using a model-driven approach (MDD).

   Application components are generated from UML domain models.

   Java based application designed using a Model-Driven Development
    framework.
MDD (contd.…)



    Web Tier: Construct web pages upon metadata dictionary

    Business Tier: Provides an object/relational mapping
     mechanism, a metadata interrogation mechanism, an application
     programming Interface and a set of shared services.

    Data Tier: Consists of domain database that houses clinically
     annotated data, indexes to support the query mechanism and
     security data.
Virtual Component of NMVB:



  Statistical Data Query Interface

  Approved Investigator Query Interface

  Data Entry Interface
www.mesotissue.org
NMVB Accruals:


 Year             Retrospective Cases   Prospective Cases   Overall NMVB Total


 2006                     515                   8                   523



 2007                     585                  50                   635



 2008                     605                  105                  710



 2009                     674                  162                  836



 2010 (to date)           674                  183                  865
Conclusion:

    Informatics supported tissue banking initiatives act as a large source
     of annotated biospecimens and facilitates basic and clinical science
     research.

    Tissue banking infrastructure allows efficient governess,
     standardized capture of data and detailed standardized annotation
     at local institute and across multiple collaborating sites.

    Finally, tissue banking tools developed at DBMI (Department of
     biomedical informatics) provides an important knowledgebase for
     the development of integrated tissue banking efforts and benefit
     other tissue banking initiatives by providing consultation.
Thank you

				
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posted:4/15/2012
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