Early Detection and Diagnosis
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Researchers at the Institute for Systems Biology argue that combining systems biology, longitudinal multiomics data, and artificial intelligence could transform healthcare from reactive treatment to proactive prevention, enabling scientists and clinicians to detect early molecular signs of disease and intervene before symptoms appear.
Discussing Super Agers, Drs. Eric Topol and Lee Hood connected breakthroughs in genomics, AI, and lifestyle science to the pursuit of longer, healthier lives.
By taking detailed measurements of blood and other biological samples, ISB scientists have shown they can identify markers for cancer years before diagnosis. This was the topic of a recent Research Roundtable presentation delivered by Dr. Andrew Magis, Director of Data Science in ISB’s Health Data Science Lab.
ISB researchers have found that a small, persistent increase in the expression of NOD1 could be responsible for higher cancer risks. The research team found that a slight 1.5-fold uptick in NOD1 expression can activate the protein and downstream signaling pathways in a manner similar to vast (30- to 200-fold) overexpression.
By analyzing blood plasma samples taken at several time points, ISB researchers have identified specific proteins that persistently presented as outliers and signaled metastatic cancer well before patients were diagnosed. The findings were published in the journal Scientific Reports.
By using single-cell analysis to measure metabolic activities in rare disseminated tumor cells taken from non-small cell lung cancer (NSCLC) patients, ISB researchers and their collaborators can accurately predict how patients will respond to various cancer therapies, and how treatments will impact a patient’s physiological performance and survival.