Abstract PS11-14: Advanced precision health resources in the Susan G Komen tissue bank at the IU simon comprehensive cancer center
Authors: Bray Steven M , Wong Swee Seong , Parikh Baiju G , Wood Kevin C , Rysdyk Samuel T , Henry Jill E , Marino Natascia , Radovich Milan , Storniolo Anna Maria V 
Published: February 2021

Background: Understanding how hereditary, lifestyle and demographic risk factors influence the development of breast cancer is critical for its prevention and treatment. For this purpose, the Susan G. Komen Tissue Bank at the IU Simon Comprehensive Cancer Center (KTB) serves as the world’s primary repository for normal breast tissue and blood samples from healthy women (~5,500 tissue + blood donors and ~4,500 blood-only donors). In addition, KTB has received mammograms, H&E images and additional longitudinal health and wellness data from its donors via ongoing annual surveys. Whole genome sequencing has also recently been completed on a subset of 500 donors, including ~125 initially healthy donors who later went on to develop breast cancer. To make these disparate, multi-modal data accessible to the larger research community and add advanced precision health analytics capabilities to the KTB database, LifeOmic's Precision Health Cloud (PHC), a secure healthcare-compliant cloud platform, was chosen to host the KTB data moving forward. The PHC provides browsing and querying capabilities across all data including genomic, demographic, histology, donor surveys, and scanned images. Data from donors can be viewed individually as well as analyzed across cohorts of interest. Computation resources, such as informatics workflows and machine learning infrastructure, are available on the same secure environment to leverage the power of cloud computing without having to download large files. This is in addition to visual and custom analytics using Jupyter Notebooks accessible to collaborators.

Methods: We loaded all available KTB data from ~10,000 donors into the PHC. Donor-reported data collected at the time of donation and subsequent follow-up questionnaire responses were loaded as FHIR Observations and Medications in the PHC. Additional imaging and genomic data loaded into the PHC include approximately 12,000 mammogram images, 5,000 H&E images, 5,000 ancestry-informative genotypes and 500 VCF and BAM files from whole genome sequencing. A timeline view of each donor shows data collected from each donation and follow-up surveys. All genetic variants were annotated upon ingestion into the PHC with functional effect on genes, population allele frequency, ClinVar clinical significance and in silico predictions for functional impact.

Results: To demonstrate the utility of KTB data hosted in the PHC, we will show how the PHC can be used to directly analyze genomic and donor-reported data, specifically focusing on the recent whole genome sequencing data from 500 donors. Whole genome sequencing data will be used to calculate the genetic ancestry of each donor compared to their self-reported ancestry and previously predicted ancestry from a 41-SNP ancestry panel. Additionally, we will calculate genomewide breast cancer polygenic risk scores and compare these with the survey-based Tyrer-Cuzick and Gail score risk measures. We will assess how the polygenic risk score further stratifies the donors that have germline pathogenic variants in a known breast cancer gene. For the ~125 sequenced donors that went on to develop breast cancer we will also investigate correlations between family history of cancer, age of diagnosis, prior gynecological history and lifestyle differences. All generated results will remain in the PHC for access by future KTB collaborators to continue to build the utility and value of the KTB data.

Conclusions: We have shown how hosting KTB data in the PHC opens new opportunities for advanced precision health research for breast cancer researchers worldwide. As more specimens and diverse data sets including genomic, longitudinal and imaging information are being tracked and deposited into KTB, this resource will continue to grow to enable diverse research needs.

Citation Format: Steven M Bray, Swee Seong Wong, Baiju G Parikh, Kevin C Wood, Samuel T Rysdyk, Jill E Henry, Natascia Marino, Milan Radovich, Anna Maria V Storniolo. Advanced precision health resources in the Susan G Komen tissue bank at the IU simon comprehensive cancer center [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS11-14.