BMB Section Seminar: "Predicting the drug response of cancer cell lines using large-scale mechanistic models"

Dr. Jan Hasenauer, Helmholtz Zentrum München, Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH)

Jan Hansenauer (Photo: Private)

Large-scale studies like The Cancer Genome Atlas revealed that cancers are multi-factorial diseases, which strongly vary between patients. This inter-patient variability poses a challenge for clinicians. A priori it is not clear which drug (combination) will be most beneficial for an individual. In a multi-national collaboration, we approached the problem of drug response prediction. We developed a mechanistic model covering several of cancer associate signaling pathways. This model can be individualized using sequencing data. For statistical inference we develop scalable approach facilitating the study of models with thousands of parameters. To evaluate our model-based approach, we studied data response from the Cancer Cell Line Encyclopaedia for 7 drugs and 120 cell lines originating from five different tissues. On the validation set we achieved a prediction accuracy of roughly 80%. These results demonstrate the potential of large-scale mechanistic modeling for drug selection in personalized therapy.

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Fahri Saatcioglu
Published Mar. 16, 2017 5:31 PM - Last modified Mar. 17, 2017 7:00 PM