Chapter 2 36 Results PD-1T TILs as biomarker in NSCLC To assess their predictive potential, we quantified PD-1T TILs in pretreatment samples from 120 patients with advanced stage NSCLC treated with either pembrolizumab (n=26) or nivolumab (n=94). Since the pembrolizumab treated cohort was substantially smaller, we randomized half of the pembrolizumab treated and one third of the nivolumab treated patients in a training set (n=43). The remainder of the patients was included in a validation set (n=77) (Fig. 1A). Each sample set consisted of 30% of patients that obtained disease control (DC) at 6 months of treatment with PD-1 blockade. Clinicopathological characteristics and treatment outcomes are summarized in Table S3. Sample characteristics are shown in Table S4. None of these characteristics differed significantly among the training and validation set. PD-1T TILs are a subpopulation of PD-1+ T cells defined by a bright, tumor-specific PD-1 expression level. To quantify the PD-1T TIL subset in FFPE tissue, we established an automated digital quantification workflow as described previously10, allowing to reliably distinguish these cells from other PD-1+ cells (Fig. 1B, Fig. S1 and methods). Next, we determined the frequency of PD-1T TILs per mm2 tumor area that best discriminated patients with or without DC at 6 months (DC 6m) in the training set (n=43). To minimize the risk of undertreatment due to misclassification of patients with clinical benefit, we aimed for a sensitivity and negative predictive value (NPV) of ≥90%, and a specificity of the biomarker of at least 50% to limit overtreatment. Sensitivity and specificity reflect the predictive accuracy of identifying patients with DC 6m and with PD, respectively. The NPV reflects the probability of having no benefit to PD-1 blockade for patients with a biomarker result below threshold. In the training set, the median number of PD-1T TILs per mm2 was 255 with an interquartile range (IQR) between 86 and 356 in the DC 6m group versus 51 (IQR: 28-84) in the PD group (P<0.01) (Fig. 1C). To select the optimal biomarker cut-off, we performed a receiver operator characteristic (ROC) analysis. The area under the ROC curve (AUC) was 0.79 (95% CI 0.61-0.98), demonstrating a good discriminatory ability of the biomarker (Fig. 1D). As cut-offs reaching the intended sensitivity and NPV ≥90% had a very low specificity (10%), we decided to select the cut-off matching the highest sensitivity as well as a specificity of at least 50% in order to reduce overtreatment. This resulted in a cut-off of 90 PD-1T TILs per mm2, reaching a sensitivity of 79% and a specificity of 83% (Table 1). The chosen cut-off had a high NPV of 89% as indicated by the large fraction of patients with PD in the group with less than 90 PD-1T TILs per mm2 (Fig. 1E).
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