Discovery of predictive biomarkers for metastatic cancer

Analysis of a Wellness Cohort Identifies Markers of Metastatic Cancer Years Prior to Diagnosis

Speaker: Andrew Magis, PhD, Director of Data Science, Health Science Data Lab, Institute for Systems Biology, Seattle WA

This free webinar discusses a study that sought to identify early biomarkers for cancer by analyzing pre-diagnosis samples from seemingly healthy individuals who were later diagnosed with cancer.

Andrew Magis of the Institute for Systems Biology shares details of the study, which used the Olink platform to analyze 1,196 proteins in longitudinal plasma samples from participants in a commercial wellness program, including samples collected pre-diagnosis from ten cancer patients and 69 controls. The study identified protein biomarkers that predicted the development of metastatic cancer years prior to the actual diagnosis. Dr. Magis will discuss how these results support the value of deep phenotyping seemingly healthy individuals in order to prospectively infer disease transitions.


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Biomarker assays

~475 million

Protein data points generated

662

Publications listed on website

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