Cargando…

A Novel Cross-Disciplinary Multi-Institute Approach to Translational Cancer Research: Lessons Learned from Pennsylvania Cancer Alliance Bioinformatics Consortium (PCABC)

BACKGROUND: The Pennsylvania Cancer Alliance Bioinformatics Consortium (PCABC, http://www.pcabc.upmc.edu) is one of the first major project-based initiatives stemming from the Pennsylvania Cancer Alliance that was funded for four years by the Department of Health of the Commonwealth of Pennsylvania....

Descripción completa

Detalles Bibliográficos
Autores principales: Patel, Ashokkumar A., Gilbertson, John R., Showe, Louise C., London, Jack W., Ross, Eric, Ochs, Michael F., Carver, Joseph, Lazarus, Andrea, Parwani, Anil V., Dhir, Rajiv, Beck, J. Robert, Liebman, Michael, Garcia, Fernando U., Prichard, Jeff, Wilkerson, Myra, Herberman, Ronald B., Becich, Michael J.
Formato: Texto
Lenguaje:English
Publicado: Libertas Academica 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2675833/
https://www.ncbi.nlm.nih.gov/pubmed/19455246
_version_ 1782166717030465536
author Patel, Ashokkumar A.
Gilbertson, John R.
Showe, Louise C.
London, Jack W.
Ross, Eric
Ochs, Michael F.
Carver, Joseph
Lazarus, Andrea
Parwani, Anil V.
Dhir, Rajiv
Beck, J. Robert
Liebman, Michael
Garcia, Fernando U.
Prichard, Jeff
Wilkerson, Myra
Herberman, Ronald B.
Becich, Michael J.
author_facet Patel, Ashokkumar A.
Gilbertson, John R.
Showe, Louise C.
London, Jack W.
Ross, Eric
Ochs, Michael F.
Carver, Joseph
Lazarus, Andrea
Parwani, Anil V.
Dhir, Rajiv
Beck, J. Robert
Liebman, Michael
Garcia, Fernando U.
Prichard, Jeff
Wilkerson, Myra
Herberman, Ronald B.
Becich, Michael J.
author_sort Patel, Ashokkumar A.
collection PubMed
description BACKGROUND: The Pennsylvania Cancer Alliance Bioinformatics Consortium (PCABC, http://www.pcabc.upmc.edu) is one of the first major project-based initiatives stemming from the Pennsylvania Cancer Alliance that was funded for four years by the Department of Health of the Commonwealth of Pennsylvania. The objective of this was to initiate a prototype biorepository and bioinformatics infrastructure with a robust data warehouse by developing a statewide data model (1) for bioinformatics and a repository of serum and tissue samples; (2) a data model for biomarker data storage; and (3) a public access website for disseminating research results and bioinformatics tools. The members of the Consortium cooperate closely, exploring the opportunity for sharing clinical, genomic and other bioinformatics data on patient samples in oncology, for the purpose of developing collaborative research programs across cancer research institutions in Pennsylvania. The Consortium’s intention was to establish a virtual repository of many clinical specimens residing in various centers across the state, in order to make them available for research. One of our primary goals was to facilitate the identification of cancer-specific biomarkers and encourage collaborative research efforts among the participating centers. METHODS: The PCABC has developed unique partnerships so that every region of the state can effectively contribute and participate. It includes over 80 individuals from 14 organizations, and plans to expand to partners outside the State. This has created a network of researchers, clinicians, bioinformaticians, cancer registrars, program directors, and executives from academic and community health systems, as well as external corporate partners - all working together to accomplish a common mission. The various sub-committees have developed a common IRB protocol template, common data elements for standardizing data collections for three organ sites, intellectual property/tech transfer agreements, and material transfer agreements that have been approved by each of the member institutions. This was the foundational work that has led to the development of a centralized data warehouse that has met each of the institutions’ IRB/HIPAA standards. RESULTS: Currently, this “virtual biorepository” has over 58,000 annotated samples from 11,467 cancer patients available for research purposes. The clinical annotation of tissue samples is either done manually over the internet or semi-automated batch modes through mapping of local data elements with PCABC common data elements. The database currently holds information on 7188 cases (associated with 9278 specimens and 46,666 annotated blocks and blood samples) of prostate cancer, 2736 cases (associated with 3796 specimens and 9336 annotated blocks and blood samples) of breast cancer and 1543 cases (including 1334 specimens and 2671 annotated blocks and blood samples) of melanoma. These numbers continue to grow, and plans to integrate new tumor sites are in progress. Furthermore, the group has also developed a central web-based tool that allows investigators to share their translational (genomics/proteomics) experiment data on research evaluating potential biomarkers via a central location on the Consortium’s web site. CONCLUSIONS: The technological achievements and the statewide informatics infrastructure that have been established by the Consortium will enable robust and efficient studies of biomarkers and their relevance to the clinical course of cancer. Studies resulting from the creation of the Consortium may allow for better classification of cancer types, more accurate assessment of disease prognosis, a better ability to identify the most appropriate individuals for clinical trial participation, and better surrogate markers of disease progression and/or response to therapy.
format Text
id pubmed-2675833
institution National Center for Biotechnology Information
language English
publishDate 2007
publisher Libertas Academica
record_format MEDLINE/PubMed
spelling pubmed-26758332009-05-19 A Novel Cross-Disciplinary Multi-Institute Approach to Translational Cancer Research: Lessons Learned from Pennsylvania Cancer Alliance Bioinformatics Consortium (PCABC) Patel, Ashokkumar A. Gilbertson, John R. Showe, Louise C. London, Jack W. Ross, Eric Ochs, Michael F. Carver, Joseph Lazarus, Andrea Parwani, Anil V. Dhir, Rajiv Beck, J. Robert Liebman, Michael Garcia, Fernando U. Prichard, Jeff Wilkerson, Myra Herberman, Ronald B. Becich, Michael J. Cancer Inform Original Research BACKGROUND: The Pennsylvania Cancer Alliance Bioinformatics Consortium (PCABC, http://www.pcabc.upmc.edu) is one of the first major project-based initiatives stemming from the Pennsylvania Cancer Alliance that was funded for four years by the Department of Health of the Commonwealth of Pennsylvania. The objective of this was to initiate a prototype biorepository and bioinformatics infrastructure with a robust data warehouse by developing a statewide data model (1) for bioinformatics and a repository of serum and tissue samples; (2) a data model for biomarker data storage; and (3) a public access website for disseminating research results and bioinformatics tools. The members of the Consortium cooperate closely, exploring the opportunity for sharing clinical, genomic and other bioinformatics data on patient samples in oncology, for the purpose of developing collaborative research programs across cancer research institutions in Pennsylvania. The Consortium’s intention was to establish a virtual repository of many clinical specimens residing in various centers across the state, in order to make them available for research. One of our primary goals was to facilitate the identification of cancer-specific biomarkers and encourage collaborative research efforts among the participating centers. METHODS: The PCABC has developed unique partnerships so that every region of the state can effectively contribute and participate. It includes over 80 individuals from 14 organizations, and plans to expand to partners outside the State. This has created a network of researchers, clinicians, bioinformaticians, cancer registrars, program directors, and executives from academic and community health systems, as well as external corporate partners - all working together to accomplish a common mission. The various sub-committees have developed a common IRB protocol template, common data elements for standardizing data collections for three organ sites, intellectual property/tech transfer agreements, and material transfer agreements that have been approved by each of the member institutions. This was the foundational work that has led to the development of a centralized data warehouse that has met each of the institutions’ IRB/HIPAA standards. RESULTS: Currently, this “virtual biorepository” has over 58,000 annotated samples from 11,467 cancer patients available for research purposes. The clinical annotation of tissue samples is either done manually over the internet or semi-automated batch modes through mapping of local data elements with PCABC common data elements. The database currently holds information on 7188 cases (associated with 9278 specimens and 46,666 annotated blocks and blood samples) of prostate cancer, 2736 cases (associated with 3796 specimens and 9336 annotated blocks and blood samples) of breast cancer and 1543 cases (including 1334 specimens and 2671 annotated blocks and blood samples) of melanoma. These numbers continue to grow, and plans to integrate new tumor sites are in progress. Furthermore, the group has also developed a central web-based tool that allows investigators to share their translational (genomics/proteomics) experiment data on research evaluating potential biomarkers via a central location on the Consortium’s web site. CONCLUSIONS: The technological achievements and the statewide informatics infrastructure that have been established by the Consortium will enable robust and efficient studies of biomarkers and their relevance to the clinical course of cancer. Studies resulting from the creation of the Consortium may allow for better classification of cancer types, more accurate assessment of disease prognosis, a better ability to identify the most appropriate individuals for clinical trial participation, and better surrogate markers of disease progression and/or response to therapy. Libertas Academica 2007-06-08 /pmc/articles/PMC2675833/ /pubmed/19455246 Text en © 2007 The authors. http://creativecommons.org/licenses/by/3.0 This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Original Research
Patel, Ashokkumar A.
Gilbertson, John R.
Showe, Louise C.
London, Jack W.
Ross, Eric
Ochs, Michael F.
Carver, Joseph
Lazarus, Andrea
Parwani, Anil V.
Dhir, Rajiv
Beck, J. Robert
Liebman, Michael
Garcia, Fernando U.
Prichard, Jeff
Wilkerson, Myra
Herberman, Ronald B.
Becich, Michael J.
A Novel Cross-Disciplinary Multi-Institute Approach to Translational Cancer Research: Lessons Learned from Pennsylvania Cancer Alliance Bioinformatics Consortium (PCABC)
title A Novel Cross-Disciplinary Multi-Institute Approach to Translational Cancer Research: Lessons Learned from Pennsylvania Cancer Alliance Bioinformatics Consortium (PCABC)
title_full A Novel Cross-Disciplinary Multi-Institute Approach to Translational Cancer Research: Lessons Learned from Pennsylvania Cancer Alliance Bioinformatics Consortium (PCABC)
title_fullStr A Novel Cross-Disciplinary Multi-Institute Approach to Translational Cancer Research: Lessons Learned from Pennsylvania Cancer Alliance Bioinformatics Consortium (PCABC)
title_full_unstemmed A Novel Cross-Disciplinary Multi-Institute Approach to Translational Cancer Research: Lessons Learned from Pennsylvania Cancer Alliance Bioinformatics Consortium (PCABC)
title_short A Novel Cross-Disciplinary Multi-Institute Approach to Translational Cancer Research: Lessons Learned from Pennsylvania Cancer Alliance Bioinformatics Consortium (PCABC)
title_sort novel cross-disciplinary multi-institute approach to translational cancer research: lessons learned from pennsylvania cancer alliance bioinformatics consortium (pcabc)
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2675833/
https://www.ncbi.nlm.nih.gov/pubmed/19455246
work_keys_str_mv AT patelashokkumara anovelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT gilbertsonjohnr anovelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT showelouisec anovelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT londonjackw anovelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT rosseric anovelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT ochsmichaelf anovelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT carverjoseph anovelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT lazarusandrea anovelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT parwanianilv anovelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT dhirrajiv anovelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT beckjrobert anovelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT liebmanmichael anovelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT garciafernandou anovelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT prichardjeff anovelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT wilkersonmyra anovelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT herbermanronaldb anovelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT becichmichaelj anovelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT anovelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT patelashokkumara novelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT gilbertsonjohnr novelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT showelouisec novelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT londonjackw novelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT rosseric novelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT ochsmichaelf novelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT carverjoseph novelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT lazarusandrea novelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT parwanianilv novelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT dhirrajiv novelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT beckjrobert novelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT liebmanmichael novelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT garciafernandou novelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT prichardjeff novelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT wilkersonmyra novelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT herbermanronaldb novelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT becichmichaelj novelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc
AT novelcrossdisciplinarymultiinstituteapproachtotranslationalcancerresearchlessonslearnedfrompennsylvaniacanceralliancebioinformaticsconsortiumpcabc