The biorepository portal toolkit: an honest brokered, modular service oriented software tool set for biospecimen-driven translational research

Abstract

BackgroundHigh throughput molecular sequencing and increased biospecimen variety have introduced significant informatics challenges for research biorepository infrastructures. We applied a modular system integration approach to develop an operational biorepository management system. This method enables aggregation of the clinical, specimen and genomic data collected for biorepository resources.MethodsWe introduce an electronic Honest Broker (eHB) and Biorepository Portal (BRP) open source project that, in tandem, allow for data integration while protecting patient privacy. This modular approach allows data and specimens to be associated with a biorepository subject at any time point asynchronously. This lowers the bar to develop new research projects based on scientific merit without institutional review for a proposal.ResultsBy facilitating the automated de-identification of specimen and associated clinical and genomic data we create a future proofed specimen set that can withstand new workflows and be connected to new associated information over time. Thus facilitating collaborative advanced genomic and tissue research.ConclusionsAs of Janurary of 2016 there are 23 unique protocols/patient cohorts being managed in the Biorepository Portal (BRP). There are over 4000 unique subject records in the electronic honest broker (eHB), over 30,000 specimens accessioned and 8 institutions participating in various biobanking activities using this tool kit. We specifically set out to build rich annotation of biospecimens with longitudinal clinical data; BRP/REDCap integration for multi-institutional repositories; EMR integration; further annotated specimens with genomic data specific to a domain; build application hooks for experiments at the specimen level integrated with analytic software; while protecting privacy per the Office of Civil Rights (OCR) and HIPAA.

Analysis of Racial/Ethnic Representation in Select Basic and Applied Cancer Research Studies

“…Racial/ethnic data from TARP biorepository was obtained at https://ccrod.cancer.gov/confluence/display/CCRTARP/Home . Racial/ethnic information of The Penn-CHOP Tumor Tissue Bank and the CBTTC were obtained through the Biorepository Portal Toolkit 2 .…”

“…Fundamental research intends to understand the principles of cancer biology. This has been studied using tumor samples, which have been used to develop patient-derived oncological models (cell lines and xenografts) 1 , biobanks 2 and genomic-based molecular classifications 3 . The knowledge acquired in basic research has been exploited for anti-cancer drug development and further clinical trials.…”

“…Another important aspect of basic research is the identification of tumor biomarkers, which can be used for early cancer detection, diagnosis and prognosis. Cancer biomarkes are usually studied using body liquid biopsies or tissue samples deposited in biobanks 2 , 7 , 8 . One of these biobanks has been developed by the NCI Tissue Array Research Program (TARP).…”

Pediatric High Grade Glioma Resources From the Children’s Brain Tumor Tissue Consortium (CBTTC) and Pediatric Brain Tumor Atlas (PBTA)

“…A research proposal request for biospecimens and/or data (clinical, imaging, histology slides, genomics) goes through a peer review process to approve specimen distribution and data sharing. 5 After approval, the specimens are delivered to investigators while CBTTC data is available for viewing and download from the Gabriella Miller Kids First Data Resource Center (KF-DRC, https://kidsfirstdrc.org). Clinical reports can be downloaded as PDFs and Aperio SVS histology images viewed with QuPath.…”

Cell Ecosystem and Signaling Pathways of Primary and Metastatic Pediatric Posterior Fossa Ependymoma

“…De-identified raw RNA-seq data of 40 pediatric ependymal tumors located in the posterior fossa were provided by the CBTTC biorepository (Felmeister et al, 2016) (CBTTC Approved Data Project 19). Gene expression was quantified for each tumor using Kallisto (version 0.45.1) (Bray et al, 2016) with the human reference genome GRCh38.…”