The Promise and Potential of Genomic Data for the Future of Precision Medicine

Precision medicine in cancer care is the product of a transformative change in our collective thinking, driven by a deepening understanding of genomics and the biology of disease.  But that transformation requires us to evolve our approach to research in tandem. The American Society of Clinical Oncology Annual Meeting (ASCO) 2021 provided us with a global platform to demonstrate the power, broad utility and value of harnessing the potential of real-world genomic data.

Together with our partners, we brought more than a dozen studies to ASCO that showcased how genomic data can be leveraged to further understand the disease, optimize treatment, and advance patient care.

These studies relied heavily on data from our two comprehensive databases: our genomic database, FoundationCore®, with over 440,000 de-identified research samples, representing over 550 tumor types and subtypes, and a diverse population; and our joint clinico-genomic database (CGDB), built in partnership with Flatiron Health, that delivers a real-world, de-identified data source of over 74,000 patient samples, linking Foundation Medicine’s comprehensive genomic profiling (CGP) data with Flatiron’s clinical data from electronic health records.

For genomic data resources like these to function and deliver meaningful results, they must contain high quality, reliable and accurate multimodal data that is organized within a structured and well curated framework. And as FoundationCore® and CGDB continue to expand and mature, their value and potential to shape the future of precision medicine grows in parallel. Reflecting on ASCO 2021, I would like to take some time to explore how the studies we presented this year reinforce the role comprehensive genomic data plays in advancing our understanding of cancer and how to treat it.

The CGDB is delivering insights that are transforming our understanding of cancer. It was designed to provide a comprehensive picture of real-world patient cases and outcomes by linking genomic profiling data with longitudinal clinical data, spanning the entire patient journey. With over 74,000 samples across 21+ tumor type cohorts, the CGDB gives us the ability to better understand the influence and interplay of the many factors involved in treatment choices and response in a diverse set of patients.

For all its promise to help the oncology community chart the future path of cancer care, the CGDB is also delivering insights that are shaping care today. In metastatic castration-resistant prostate cancer (mCRPC) for example, the ability to predict response and optimize treatment sequencing could play a significant role in delaying progression. We mined the CGDB and analyzed data from over 300 mCRPC patients, uncovering a number of promising genomic biomarkers associated with poorer response to novel hormone therapy (NHT) but not to the current alternative, taxane chemotherapy.

Key to the success of the study was the completeness of the CGDB itself, which includes baseline patient clinical and pathological features, treatment histories and multiple outcomes measures. We were able to use this rich data to create more balanced cohorts for assessments and comparisons between patient groups, essential for then evaluating the relative outcomes on standard of care drugs in standard of care settings related to genomic biomarkers assessed with CGP. While initial insights are promising, we will continue to invest in growing longitudinal datasets that allow us to more robustly address these important questions via larger cohorts and more robust outcomes data.

Testing for these biomarkers in the clinic could inform the decisions of when non-hormonal modalities might be considered via better anticipation of the efficacy and degree of benefit of NHT.

Insights from the CGDB also contribute to a much wider change in the oncology landscape. Access to population-level genomic data from resources like FoundationCore® and the CGDB has given us a much deeper understanding of the genomic basis of cancer. The identification of novel driver mutations, pathways and biomarkers across different tumor types is fueling the trend towards a pan-tumor approach to the classification, diagnosis, and treatment of the disease.

There are significant advantages to this approach from a research perspective, particularly in rarer cancers where pan-tumor clinical trials would allow for higher participation and stimulate research into new treatments. But for this approach to be embraced in the clinic, it needs to provide defined benefits from a clinical and patient care perspective. Accurate assessment of disease severity and risk of progression are fundamental to the decision-making process in treatment selection.

Our databases are being used across the entire oncology landscape to expand our knowledge and provide new directions for research. But I’d like to finish by highlighting the important role they are playing in supporting efforts of equity and true personalization of treatment for all patients.

Never have we had the opportunity to analyze data of this magnitude, and caliber—it is already helping to build the knowledge we need to work toward more equity in cancer care. The genetic landscape of cancer with respect to ancestry is still poorly understood and we will never achieve treatment equity until we can fully understand the role of all factors that influence cancer progression and treatment response.

The diversity and comprehensive nature of the data within FoundationCore® and the CGDB, will help us to achieve this goal. The cultivation of these resources will continue to be foundational in our partnerships with the oncology community, and we are committed to a future where personalized medicine is the reality for every person with cancer.