Patient-derived xenografts (PDXs) are a powerful model system for assessing drug efficacy of anti-cancer agents and understanding molecular mechanisms of drug resistance. However, results from individual research groups have been difficult to validate due to the lack of standardized PDX procedures, lack of scale for adequately powered PDX studies and the inability to efficiently share PDX specimens. A key contributor to this challenge is the lack of well-managed resources for community sharing and large-scale analysis of integrated, standardized datasets from PDX models. The JAX-Seven Bridges PDX Data Commons and Coordination Center (PDCCC) seeks to address this challenge and unite the efforts of the component data- generating (PDX Development and Trial Centers/PDTCs) and PDX model sharing (NCI?s Patient-Derived Model Repository/PDMR) parts of the PDX Development and Trials Centers Research Network (PDXNet) into a cohesive, trans-Network whole. Using innovative cloud computing and bioinformatic approaches, our PDCCC will provide administrative and computational infrastructure for PDXNet to enable PDX method standardization, model sharing, data sharing, and massive-scale data analysis. We will build a data storage, sharing, and analysis platform that harmonizes PDXNet data with other large datasets and analysis workflows available in the NCI Cancer Genomics Cloud. Simultaneously, we will administer planning meetings, training activities, and research pilots to build synergies within the PDXNet, enhancing the ability of the PDXNet to develop clinical trials from PDX studies.
Our Specific Aims are to 1) establish a leadership and administration unit to manage and coordinate activities within PDXNet, including annual meetings, regular conference calls, training activities, trans-Network pilot projects, and outreach; 2) develop a cloud- integrated PDXnet Data Commons that integrates PDXNet data with the existing cloud-based data analysis platform - the Seven Bridges Cancer Genomics Cloud (SB-CGC); and 3) build analysis workflows and data sharing practices to optimize PDXNet research and enable PDXNet data to facilitate clinical trial design. To accomplish these Aims we have assembled a team with unique expertise in PDXs, cancer treatment, genomic analysis, data coordination, and project management from The Jackson Laboratory and Seven Bridges. Our combined institutional strengths include a history of leadership in (and commitment) to PDX, data resource, analytic and consensus standards development and application; practical expertise in PDX model sharing and collaborative community efforts; a broad array of statistical, bioinformatic, and software-related PDX resources; leadership expertise in large-scale, cloud-based biomedical data projects, notably the SB-CGC; and deep experience in high-performance database engineering and development. Our goal is to build an innovative, systematically organized PDCCC that will advance the efforts of PDXNet to improve the validity?and expand use?of the PDX system as a preclinical platform for precision oncology.
To realize the full promise of patient-derived xenografts (PDXs) to advance precision therapies for cancer, standardized PDX procedures and coordinated sharing of PDX specimens is needed to validate results across research groups and determine which results may be robust for cancer patients. To address this need, we will build and administer a PDX Data Commons and Coordination Center that will unify the activities of NIH- supported PDX Development and Trial Centers and the National Cancer Institute?s Patient-Derived Models Repository. Our Data Commons and Coordination Center will use innovative administrative, cloud computing and bioinformatic approaches to enable PDX method standardization, model sharing, data sharing, and massive-scale data analysis.
| Kim, Hyunsoo; Kumar, Pooja; Menghi, Francesca et al. (2018) High-resolution deconstruction of evolution induced by chemotherapy treatments in breast cancer xenografts. Sci Rep 8:17937 |
| Cho, Sung-Yup; Sung, Chang Ohk; Chae, Jeesoo et al. (2018) Alterations in the Rho pathway contribute to Epstein-Barr virus-induced lymphomagenesis in immunosuppressed environments. Blood 131:1931-1941 |
| Noorbakhsh, Javad; Kim, Hyunsoo; Namburi, Sandeep et al. (2018) Distribution-based measures of tumor heterogeneity are sensitive to mutation calling and lack strong clinical predictive power. Sci Rep 8:11445 |
