National Mesothelioma Virtual Bank: A standard based biospecimen and clinical data resource to enhance translational research

Amin, Waqas; Parwani, Anil V.; Schmandt, Linda; Mohanty, Sambit K.; Farhat, Ghada N.; Pople, Andrew K; Winters, Sharon; Whelan, Nancy; Schneider, Althea M; Milnes, John T; Valdivieso, Federico A; Feldman, Michael D.; Pass, Harvey I.; Dhir, Rajiv; Melamed, Jonathan; Becich, Michael J.

doi:10.1186/1471-2407-8-236

Cited by 38 publications

(29 citation statements)

References 6 publications

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“…TCRN differs from other recent data and biospecimen resource sharing initiatives (3–7) in the use of de-identified clinical text, which requires NLP methods to characterize phenotype. Investigators using retrospective tissue specimens typically require detailed information, which is usually available only through such clinical documents.…”

Section: Discussionmentioning

confidence: 99%

“…Cancer researchers have been at the forefront of developing biomedical data and resource sharing consortia (3–7), but these have typically employed centralized models in which a single institution acts as central broker between requesting researchers and contributing institutions. This centralized approach has several advantages, including ease of distribution using a single point of contact and relatively uncomplicated information technology requirements.…”

Section: Introductionmentioning

confidence: 99%

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A Federated Network for Translational Cancer Research Using Clinical Data and Biospecimens

et al. 2015

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Advances in cancer research and personalized medicine will require significant new bridging infrastructures, including more robust biorepositories that link human tissue to clinical phenotypes and outcomes. In order to meet that challenge, four cancer centers formed the TIES Cancer Research Network, a federated network that facilitates data and biospecimen sharing among member institutions. Member sites can access pathology data that is de-identified and processed with the TIES natural language processing system, which creates a repository of rich phenotype data linked to clinical biospecimens. TIES incorporates multiple security and privacy best practices that, combined with legal agreements, network policies and procedures, enable regulatory compliance. The TIES Cancer Research Network now provides integrated access to investigators at all member institutions, where multiple investigator-driven pilot projects are underway. Examples of federated search across the network illustrate the potential impact on translational research, particularly for studies involving rare cancers, rare phenotypes, and specific biologic behaviors. The network satisfies several key desiderata including local control of data and credentialing, inclusion of rich phenotype information, and applicability to diverse research objectives. The TIES Cancer Research Network presents a model for a national data and biospecimen network.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Federated Network for Translational Cancer Research Using Clinical Data and Biospecimens

et al. 2015

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“…All specimens in this study including 5 MM tissue samples and 215 serum samples (108 MM patients and 107 normal controls) were obtained from the National Mesothelioma Virtual Bank under the approval of the Institutional Review Board (IRB) of University of Pennsylvania Medical Center [32]. All the samples were collected from individuals with histologically confirmed MM after written consent forms were obtained and the details were shown in Table 1.…”

Section: Methodsmentioning

confidence: 99%

Identification of Novel Autoantibodies for Detection of Malignant Mesothelioma

et al. 2013

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BackgroundThe malignant mesothelioma (MM) survival rate has been hampered by the lack of efficient and accurate early detection methods. The immune system may detect the early changes of tumor progression by responding with tumor-associated autoantibody production. Hence, in this study, we translated the humoral immune response to cancer proteins into a potential blood test for MM.Methodology/Principal FindingsA T7 phage MM cDNA library was constructed using MM tumor tissues and biopanned for tumor-associated antigens (TAAs) using pooled MM patient and normal serum samples. About 1008 individual phage TAA clones from the biopanned library were subjected to protein microarray construction and tested with 53 MM and 52 control serum samples as a training group. Nine candidate autoantibody markers were selected from the training group using Tclass system and logistic regression statistical analysis, which achieved 94.3% sensitivity and 90.4% specificity with an AUC value of 0.89 in receiver operating characteristic analysis. The classifier was further evaluated with 50 patient and 50 normal serum samples as an independent blind validation, and the sensitivity of 86.0% and the specificity of 86.0% were obtained with an AUC of 0.82. Sequencing and BLASTN analysis of the classifier revealed that five of these nine candidate markers were found to have strong homology to cancer related proteins (PDIA6, MEG3, SDCCAG3, IGHG3, IGHG1).Conclusions/SignificanceOur results indicated that using a panel of 9 autoantibody markers presented a promising accuracy for MM detection. Although the results need further validation in high-risk groups, they provided the potentials in developing a serum-based assay for MM diagnosis.

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“…The National Mesothelioma Virtual Bank is based on the caTISSUE Clinical Annotation Engine developed in cooperation with the Cancer Biomedical Informatics Grid and includes paraffin embedded tissues, tissue microarrays, serum and genomic DNA. It provides real-time access to de-identified data depending on user authorization (Amin et al 2008). Internationally, practices also vary.…”

Section: Biobanks As Laboratories For Data Sharingmentioning

confidence: 99%