Karlijn Hummelink

Chapter 2 62 Figure S5. Combination of PD-1T TILs and PD-L1 to predict clinical benefit. (A) Correlation of PD-1T TILs and PD-L1 TPS. R2 and P-values were calculated using linear regression analysis. (B) IHC analysis of PD-1T TILs and PD-L1. Examples of tumors that are PD-1T high (≥90 per mm2)+PD-L1 high (≥50%), PD-1T high+PD-L1 low (<50%), PD-1T low (<90 per mm2)+PD-L1 high and PD-1T low+PD-L1 low. (C) Number of patients in the validation set (n=77) with either DC 6m or PD in the following subgroups: (1) PD-L1 low (<50%)+PD-1T low (n=38), (2) PD-L1 low+PD1T high (n=31), (3) PD-L1 high (≥50%)+PD-1T low (n=4), and (4) PD-L1 high+PD-1T high (n=4). (D) Same plot as in C for DC 12m and PD. (E) Number of patients in the validation set (n=77) with either DC 6m or PD in the following subgroups: (1) PD-L1 low (<1%)+PD-1T low (n=30), (2) PD-L1 low+PD-1T high (n=20), (3) PD-L1 high (≥1%)+PD-1T low (n=12) and (4) PD-L1 high+PD-1T high (n=15). (F) Same plot as in E for DC 12m. (G) Sensitivity and specificity of composite biomarkers PD-1T 90 per mm2 + PD-L1 at either 50% or 1% cut-off for DC 6m and 12m using samples from the validation set (n=77). Results are compared to PD-1T 90 per mm2 as univariate biomarker.

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