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 deidentified information within the warehouse through a “point and
click” interface.
OSD Multi Tier Architecture:
Presentation
Metadata
Curation
Admin
Security
Metadata Engine
Physical Data
Common Data Elements (CDE)
Definitions
Application Data
Layer
HELP Builder
Business Rules
Engine
Mapping
Engine
Metadata Data
Layer
Manual
Annotation
Data Query
Security Engine
Registration
Authorization
Data Import
Export
Authentication
Security Data
Layer
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
Bio-marker
data
Radiology
(PET/CT) data
Patient
Insurance
information
SPORE H&N
Neoplasm Database
Epidemiology
Project-1
questionnaire data
Human Papilloma
Virus
Questionnaire
data
RIS
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
Full Case
Report
View
(Identified
or Deidentified
as per
access
level
User can
have
multiple
“My
Case”
lists for
different
studies
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,
Virtual Biorepository
CPCTR
Total Number of Biospecimens
Tissue type
Paraffin Blocks
Frozen
Blocks
Blood/seru
m/Plasma
Prostate
7000
34641
17508
17508
Breast
3645
1760
847
823
Melanoma
1762
1885
168
112
Prostate
7327
5457
1642
415
EDRN Colorectal and
Pancreatic Neoplasm Virtual
Biorepository
Pancreas and colon
2459
175
942
1254
SPORE’s Head & Neck
Neoplasm Virtual
Biorepository
Head and Neck
Neoplasm
11622
2237
0
1038
PCABC
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