Sylvester Comprehensive Cancer Center, part of the University of Miami Miller School of Medicine, has developed a novel, cloud-based informatics platform that combines clinical and genomic data from multiple sources into one unified platform.
The Sylvester Data Portal (SDP) enables researchers to study cancer at both the population and individual patient levels by providing access to data across aggregated, de-identified - and under appropriate IRB and data broker approval - identified clinical datasets. These analyses were previously not feasible because Sylvester's integrated real-world clinicogenomic datasets were not available in any single database.
In a poster session to be presented at the American Association for Cancer Research (AACR) annual meeting in San Diego April 17-22, Sylvester researchers will detail the advantages of their data platform.
The portal integrates data from major genomic testing companies, including Caris Life Sciences, Foundation Medicine, NeoGenomics and Guardant Health, and provides secure, role-based access through three major components:
- A clinical dashboard for high-level patient data;
- A clinical browser for exploring de-identified individual records; and
- Clinical collections that link clinical and genomic data for approved research use.
At AACR, Sylvester researchers will describe how SDP first integrates and harmonizes clinical and genomic data from multiple sources into a unified, analysis-ready resource, enabling the study of more than 30,000 tumor samples - almost three times the size of The Cancer Genome Atlas (TCGA), a widely used national dataset. The Sylvester cohort reflects the diversity of its South Florida catchment area, which differs substantially from the national average, with nearly 46% of patients identifying as Hispanic, compared to just over 3% in TCGA.
By integrating clinical and genomic data from a highly diverse patient population into a unified, AI-ready platform, our data portal enables analyses that are both more representative and more translationally relevant. This helps address longstanding gaps in cancer research and allows us to better understand how disease biology varies across real-world populations."
Stephan C. Schürer, Ph.D., senior author and associate director of Data Science at Sylvester
Sylvester's analysis also found differences in key cancer-related mutations. In particular, TP53 is more often mutated in the TCGA cohort, 36.99% vs. 26.72%, whereas KRAS mutations are more prevalent in the SDP cohort --7.5% vs. 9.81%. This disparity highlights how population differences can shape cancer biology.
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