METEOR-Data Synthesis and Transfer (METEOR-DST)

NIH RePORTER · NIH · U54 · $126,513 · view on reporter.nih.gov ↗

Abstract

METEOR-DST SUMMARY The METEOR Data Synthesis and Transfer (DST) shared resource provides expertise and systems for synthesizing data from across all data sources in METEOR and enabling the ability to transfer the synthesized data into the larger NCI Data ecosystem and repositories. DST addresses the critical issue of aggregating multi- omics data, imaging, radiotherapy, and clinical data as well as enabling these data to be shared in a user-friendly manner. With the successful completion of the aims outlined, we will ensure that the collection and management of patient-derived data is performed in a manner consistent with FAIR and TRUST principles. We will augment CIELO, a HIPAA-secure open science platform for health research, to support the workflows and data types needed for ROBIN. CIELO allows diverse end-users to share, discover, and adapt/adopt “bundles” of health information, such as multi-scale, longitudinally defined phenotypes. This will serve as a comprehensive and “end-to-end” solution for enabling Trans-ROBIN data-centric research collaborations involving multiple ROBIN Centers and beyond. We will add: (1) the capability to ingest the data from multiple sources and then harmonize and integrate the data by creating consistent identifiers for patients, tissues, and sample; (2) API-based interfaces with a number of internal platforms and systems such as REDCap, XNAT OpenSpecimen, and institutional EHR warehouse; (3) addition of support for external data export to other data repositories in the NCI data ecosystem. We will deploy and enhance XNAT to support imaging and radiation therapy data in ROBIN and integrate with CIELO. XNAT is a web-based software platform designed to facilitate common management and productivity tasks for imaging and associated data. It consists of an image repository to store raw and post-processed images, a database to store metadata and non-imaging measures, and user interface tools for accessing, querying, visualizing, and exploring data. We will enhance XNAT to store radiation therapy DICOM formats (RT Structure Set, RT Dose, Segmentation Objects) and to visualize radiation therapy annotations in XNAT’s web- based imaging viewer. We will fully integrate XNAT with CIELO via XNAT’s extensive REST API. We will ensure that the collection and management of patient-derived data is performed in a manner consistent with FAIR and TRUST principles. All METEOR data (eCRFs, biospecimen availability & characterization) will be aggregated into CIELO and XNAT, using REST interfaces, and automated data extraction from our Research Data Core, as well as manual upload capabilities. Processed results of the METEOR-BLST team’s genomics, transcriptomics, proteomics, and metabolomics analyses, including bulk, single-cell, and spatial experiments, will be uploaded into CIELO.

Key facts

NIH application ID
10912710
Project number
5U54CA274318-02
Recipient
WASHINGTON UNIVERSITY
Principal Investigator
ALBERT M LAI
Activity code
U54
Funding institute
NIH
Fiscal year
2024
Award amount
$126,513
Award type
5
Project period
2023-09-01 → 2028-08-31