Hosted by Cardiff University's School of Medicine

Precision oncology has made significant advances, mainly by targeting actionable mutations and fusion events involving cancer driver genes. I will describe four new approaches for predicting patients response to cancer treatments that have been recently developed in my lab. I will start by reviewing our work on predicting patients response to targeted therapies from the tumor bulk transcriptome. Second, I will discuss our work on robustly predicting response to checkpoint immunotherapy from simple routine lab tests and the tumor mutational burden. Thirdly, I will describe a new approach that considers tumor heterogeneity in predicting response, based on single cell RNA sequencing of the patients tumors. Last but not least, I will describe deep learning approaches for predicting patients response to cancer therapies and classifying tumors directly from tumor histopathological images without requiring any sequencing. Finally, I will discuss the challenges and the road ahead.

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Bio: Eytan Ruppin has served as a professor of Computer Science & Medicine since 1995 at Tel Aviv University, conducting computational multi-disciplinary research spanning computational neuroscience, natural language processing, machine learning and systems biology. In 2014, he joined the University of Maryland as director of its center for bioinformatics and computational biology (CBCB). In 2018, he moved to the National Cancer Institute (NCI) where he founded and is chief of its Cancer Data Science Lab/Branch (CDSL). His research is focused on developing new computational approaches for advancing precision oncology, leading to a few ongoing innovative clinical trials. Eytan is a member of the editorial board of Molecular Systems Biology, a fellow of the International Society for Computational Biology (ISCB), a recipient of the DeLano award for computational biosciences from the American Society for Biochemistry and Molecular Biology for his work on synthetic lethality. He is a member of the SAB of GSK Oncology and a co-founder of a few precision medicine startup companies.