Department of Bioinformatics
Semmelweis University, Hungary
Utilizing transcriptomic data to uncover robust cancer biomarkers
In the last two decades, gene array, RNAseq, and WGS based projects have produced a vast amount of data available for translational oncology. However, the utilization of these data is limited due to scattered studies, divergent platforms, and insufficient clinical data. We established databases and developed web-based tools for the real-time mining and discovery of new cancer biomarkers. The lecture will show how diagnostic (www.tnmplot.com), predictive (www.rocplot.com), and prognostic biomarkers (www.kmplot.com) can be uncovered using integrated databases of different layers of biological information. A sample application will be demonstrated by uncovering the most robust biomarkers of immunotherapy resistance using a cohort of more than 1500 ICI-treated patients.