PD-1T TILs as precision biomarker in NSCLC 33 2 0.24 per µm2 using a 3DHistech P1000 scanner. For manual scoring, PD-L1 and CD68 IHC images were uploaded on Slidescore, a digital pathology slide web platform that integrates a slide viewer with a scoring sheet (https://www.slidescore.com). PD-1T TILs, CD20 and TLS were digitally scored as described below. Digital quantification of PD-1T TILs PD-1T TILs are a subset of PD-1+ T cells in the tumor tissue that can be identified both by flow cytometry and by immunohistochemistry (IHC). To quantify PD-1T TILs in FFPE tissue, a digital workflow using a PD-1T IHC scoring algorithm was previously established10. For the current study, the automated detection of PD-1T TILs was recalibrated using the Multiplex IHC v1.2 module of the HALO™ software, v2.3.2089.69 (Indica Labs). To this end, an independent set of 16 NSCLC tumor samples was used to perform flow cytometry and IHC analysis in parallel. PD-1T TILs are defined by bright, tumor-associated PD-1 expression at levels that exceed those observed on peripheral blood T cells10. Hence, to determine the frequency of PD-1T TILs in the NSCLC samples, PD-1 expression on intratumoral lymphocytes was assessed by flow cytometry and compared to peripheral blood T cells as external reference to establish the threshold for tumor-associated PD-1 expression (Fig. S1A). Next, a digital IHC algorithm to quantify PD-1+ lymphocytes in matched FFPE samples was generated (Fig. S1B). The optical density (OD) measured by this approach is reflective of staining intensity and thereby PD-1 levels. To identify the optimal OD cut-off resulting in similar frequencies of PD-1T TILs by IHC as by flow cytometry, Pearson correlation coefficients were determined using thresholds varying from 0.2 to 0.5 OD. The percentage PD-1 bright lymphocytes obtained for each OD threshold in FFPE samples were normalized to total lymphocyte counts and compared to the flow cytometry-guided annotation of PD-1T lymphocytes. An OD of 0.25 showed the highest Pearson correlation coefficient (R2=0.615, P<0.001) (Fig. S1C,D) and was selected as the threshold for further automated PD-1T quantification in FFPE tumor tissue. For prediction of clinical benefit to PD-1 blockade, the tumor areas were measured and the number of PD-1T TILs per mm2 tumor area was determined (Table S2). To this end, tumor areas were annotated with a 0.5 mm margin from the tumor border and necrotic areas were excluded with a 0.5 mm margin. Digital image analysis was carried out by a trained MD (K.H.) and supervised by an experienced pathologist (K.M.), blinded for clinical outcome. Receiver operator characteristic (ROC) curves were used in the training set to establish an optimal cut-off of 90 PD-1T TILs per mm2 for discriminating patients with and without clinical benefit (see Results).
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