Fig. 4
From: Personalized cancer therapy prioritization based on driver alteration co-occurrence patterns
Specific contribution of driver co-occurrences to the prediction of drug response. a Summary plot of the local feature’s contribution (SHAP values) attributed to individual genes when predicting response to treatment with TCT4U. Each point represents the contribution of a driver gene to the prediction of response in a given PDX. The color of the points indicates whether the given driver gene was altered or not in each PDX. The three examples represent the five most explanatory genes when predicting response to three approved targeted therapies with biomarker-specific indications. b SHAP interaction plots and driver co-occurrence (DCO) networks representing the oncogenic alterations and pairs of alterations that are overrepresented in responder and non-responder PDXs. SHAP interaction plots show the effect of having driver alteration in gene A on the distribution of SHAP values of gene B. Each point represents the average SHAP value of PDXs classified on the basis of the status of the two drivers that tend to be co-altered. The size of the points is proportional to the number of PDXs that belong to each of the four resulting categories. The figure represents feature interactions involving driver genes that are located far apart in the genome. We also show some exemplary DCO networks with the driver co-occurrences represented in the accompanying SHAP interaction plots highlighted in yellow. The size of the nodes represents the average feature importance in the LOOCV, and their color represents the probability of being overrepresented in responder (red) or non-responder (blue) PDXs. Previously known biomarkers detected in the cohort are annotated with diamond shapes