AUTOMATED BIOSPECIMENS ANNOTATION MODEL FOR SCALABLE MESOTHELIOMA BIOBANKING (HTTP://WWW.MESOTISSUE.ORG) SUPPORTED BY CDC/NIOSH GRANT 2U24OH009077-08HTTP://WWW.MESOTISSUE.ORG.

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Presentation transcript:

AUTOMATED BIOSPECIMENS ANNOTATION MODEL FOR SCALABLE MESOTHELIOMA BIOBANKING ( SUPPORTED BY CDC/NIOSH GRANT 2U24OH HTTP:// Waqas Amin, MD Senior Research Scientist Department of Biomedical Informatics University of Pittsburgh

Disclosure "I disclose that neither I nor my partner have relevant financial relationships with commercial interests."

Overview:  The National Mesothelioma Virtual Bank (NMVB) provides de-identified annotated mesothelioma biospecimens to the mesothelioma research community.  We collect retrospective and prospective mesothelioma cases at New York University (NYU), University of Pennsylvania (U Penn), University of Pittsburgh (U Pitt) and Rowell Park Cancer Institute (new collection site).  Key to this resource is continued annotation of mesothelioma biospecimens including demographic, epidemiologic, clinicopathologic, follow-up and recurrence data for all biospecimens collected.  The NMVB database allows a user to query the biospecimen resource to identify cohorts for translational research.  We then provide well-annotated high quality mesothelioma biospecimens and data to approved researchers via a Letter of Intent – see

Accomplishments :  Established biobanking infrastructure at four collaborative sites.  Collected more than 1150 mesothelioma pleural and peritoneal biospecimens (biopsies and surgical resections).  Established a centralized NMVB database for specimen annotation and query.  Fulfilled over 35 specimen and data requests across the country and overseas. Represent a total of 531 patients’ material shared with the mesothelioma research community.  Developed three distinct Tissue Microarray slides to examine the distribution of marker molecules in hundreds of different tissues displayed on a single slide.

NMVB-CAE Model:  Built upon the caTISSUE Clinical Annotation Engine (CAE) developed by DBMI as part of the NCI-caBIG project.  Takes a UML Domain Model as input.  Generates core application components:  Database  Metadata  Query capability  Data viewers  Data entry forms

NMVB-CAE Model:  Achieved semantic and syntectic interoperability by describing the common data elements in the form of metadata or data descriptors and by using a controlled vocabulary.  Emphasis has been placed to provide user access at three levels.  NMVB statistical data for public view  Approved investigator database query that allows seeing individual patient de-identified clinical data  Data manger access to query and edit the stored data. Patient privacy is of utmost importance at all levels of user's access.

NMVB-CAE Model: Limitations  Existing informatics solution is expensive, laborious and quickly exhausts the resource available to sustain the operation of tumor bank.  Discouraging to share datasets to multi-institutional studies.  Self contained model that doesn’t offer modularity and self scaling.  Data elements are not recorded or normalized to standardized terminologies (SNOMED-CT, ICD-9 etc…).

 Ongoing Aim: To continue to serve the needs of the mesothelioma cancer research community by collecting tissue, blood and clinical data and providing efficient access to these federated resources.  Expansion Aim: To expand the NMVB to the Roswell Park Cancer Institute (RPCI) as a collection site.  Sustainability Aim: To automate biospecimen annotation through electronic extraction of clinical and pathology data from electronic health records (EHR) and cancer registry system. Implementing a more sustainable informatics federation model by deploying i2b2 (Informatics for Integrating Biology and the Bedside) and SHRINE (Shared Health Research Information Network) to maximize the effectiveness of the data mining process across NMVB sites. Sustaining the Expansion of the National Mesothelioma Virtual Bank (NMVB)

Design Principles (Sustaining Aim):  To automate the biospecimen annotation through electronic extraction of clinical and pathology data from electronic health records (EHR), TIES and cancer registry system.  Adopting the Text Information Extraction System (TIES), a clinical document search engine, to identify the cases and reports.  Adopting a new informatics federated model by deploying i2b2 (Informatics for Integrating Biology and the Bedside) and SHRINE (Shared Health Research Information Network) to maximize the effectiveness of the data mining process across collaborations.  New Informatics model will leverage the existing funding from other funding sources (CTSA-ACTS and PCORI).

Design Principles (Sustaining Aim):  Provide data contributors with full ownership of and access to their own data.  Minimize barriers for data owners to collaboratively contribute their data to new or existing datasets.  Support a tiered sharing model which provides a granular, permissioned, and audit-capable data sharing framework.  Enable near real-time access to data, supporting a virtuous cycle in which immediate data access promotes further data contribution and collaboration.  Encourage ongoing incorporation of outside datasets from multiple sources.

Common Data Elements (CDEs):  With leadership of the MVB Coordinating Committee, we established a CDE subcommittee to develop CDEs pertinent to mesothelioma: demographic, epidemiologic, clinical, pathologic specimen and block annotation, follow up and outcome.  Major standards used to build CDEs:  North American Association of Central Cancer Registry (NAACCR) core elements.  College of American Pathology (CAP) checklists.  American Joint Commission on Cancer (AJCC) staging.  Association of Directors of Anatomic and Surgical Pathology (ADASP) guidelines.

TIES NLP process for Surgical Pathology Reports

Specimen Collection:  Specimen Types: Tissue Microarray with Clinical Data Annotation Fresh Frozen Tissues Blood Products: Serum, RBC, Plasma, Whole blood, Buffy Coat, etc… Paraffin embedded blocks

Type of Blood ProductsNumber of Cases Serum400 Whole Blood305 Buffy Coat225 Plasma401 Red Blood Cells245 NMVB Accrual-Blood Products:

NMVB Accrual-Surgical Specimens: Specimen Type Surgical Procedure Type Biopsy SpecimenResected Specimen Paraffin Fresh Frozen42360 Bulk Frozen12108

NMVB Related and Supported Publications: 1.Amin W, Parwani AV, Melamed J, Raja F, Pennathur A, Valdevieso F, Whelan NB, Landreneau R, Luketich J, Feldman M, Pass HI, Becich MJ. National Mesothelioma Virtual Bank: A Platform for Collaborative Research and Mesothelioma Biobanking Resource to Support Translational Research, Lung Cancer International, vol. 2013, Article ID , 9 pages, doi: /2013/ Amin W, Srinivasan M, Song S, Parwani AV, Becich MJ. Use of Automated Image Analysis in Evaluation of Mesothelioma Tissue Microarray (TMA) from National Mesothelioma Virtual Bank. Pathology Research and Practice February, 210(2) 79–82 PMID: Amin W, Kang HP, Egloff AM, Singh H, Trent K, Ridge-Hetrick J, Seethala RR, Grandis J, Parwani AV. An informatics supported web-based data annotation and query tool to expedite translational research for head and neck malignancies. BMC Cancer Nov 13;9:396. PMID: PMCID: PMC Mohanty SK, Mistry AT, Amin W, Parwani AV, Pople AK, Schmandt L, Winters SB, Milliken E, Kim P, Whelan NB, Farhat G, Melamed J, Taioli E, Dhir R, Pass HI, and Becich MJ. The development and deployment of Common Data Elements for tissue banks for translational research in cancer - an emerging standard based approach for the Mesothelioma Virtual Tissue Bank. BMC Cancer Apr 8;8:91. PMID: PMCID: PMC Pass HI, Lott D, Lonardo F et al. Asbestos exposure, pleural mesothelioma, and serum osteopontin levels. N Engl J Med Oct 13;353(15): Zhang X, Shen W, Dong X, Fan J, Liu L, Gao X, Kernstine KH, Zhong L. Identification of novel autoantibodies for detection of malignant mesothelioma. PLoS One Aug 19;8(8):e doi: /journal.pone PMID: Newick K, Cunniff B, Preston K, Held P, Arbiser J, Pass H, Mossman B, Shukla A, Heintz N. Peroxiredoxin 3 is a redox- dependent target of thiostrepton in malignant mesothelioma cells. PLoS One. 2012;7(6):e doi: /journal.pone Epub 2012 Jun 25.

Acknowledgment: Collaborators:  Center for Disease Control and Prevention (CDC)  National Institute of Occupational Safety & Health (NIOSH)  Mesothelioma Foundation (Meso Fndn)  Mount Sinai School of Medicine (MSSM)  New York University (NYU), New York City, NY  University of Pennsylvania (U Penn), Philadelphia, PA  University of Pittsburgh (U Pitt), Pittsburgh, PA  Roswell Park Cancer Institutes (RPCI), Buffalo, NY Future Partners: NCI Meso SPORE Core to NMVB in 2015 with the University of Hawaii (UHCC) via Meso SPORE to also include Mayo Clinic. Leadership: Michael J. Becich MD, PhD (U Pitt)Michael Feldman MD (U Penn) Harvey I. Pass MD (NYU) Jonathan Melamed MD (NYU) Rebecca Jacobson MD, MS (U Pitt)Anil V. Parwani MD, PhD (U Pitt) Steven Abelda, MD (U Penn) David Bartlett, MD (U Pitt) Carl Morrison, MD (RPCI)Carmelo Gaudioso (RPCI) Angela R. Omilian (RPCI)James Luketich M.D (U Pitt) Mary Hesdorfer (Meso Fndn) James Pingpank, MD (U Pitt) Raja Flores, MD (MSSM)

Thank you