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Fig. 1 | BMC Cancer

Fig. 1

From: Genomics of NSCLC patients both affirm PD-L1 expression and predict their clinical responses to anti-PD-1 immunotherapy

Fig. 1

The schema for creating predictive computational simulation models to predict molecule responses and identify patients that would respond or not respond to PD-1 immunotherapy treatment using patient SA97V5 as a model example. Exome information from patient SA97V5 (a) contained 1192 total mutations with 36 deleterious mutations. This profile (b) was converted from a mutational profile to a computational format and annotated into the computational workflow to convert (c) a nontransformed model in the cancer network into (d) a patient SA97V5-specific simulation model. The patient SA97V5-specific simulation model was used to predict PD-L1 expression (e.g., 67.0% with respect to control), dendritic cell (DC) infiltration index (e.g., 23.8% with respect to control); and an immunosuppressive molecule expression profile (e.g., range − 1.9% to 56.5% with respect to controls) (e). Predicted expression responses were all used (f) to sort patients into groups that would respond or not respond to PD-1 immunotherapy treatment. SA97V5 was identified as a patient who would respond to PD-1 immunotherapy treatment. Numerous validation checks (g) occurred on the cancer network, the simulation model predictions, and the PD-1 match rates between the predicted responses and the patient clinical responses

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