CD8+ tumor-infiltrating T cells can be regarded as one of the most relevant predictive biomarkers in immune-oncology.,Highly infiltrated tumors, referred to as inflamed (clinically “hot”), show the most favorable response to immune checkpoint inhibitors in contrast to tumors with a scarce immune infiltrate called immune desert or excluded (clinically “cold”).,Nevertheless, quantitative and reproducible methods examining their prevalence within tumors are lacking.,We therefore established a computational diagnostic algorithm to quantitatively measure spatial densities of tumor-infiltrating CD8+ T cells by digital pathology within the three known tumor compartments as recommended by the International Immuno-Oncology Biomarker Working Group in 116 prospective metastatic melanomas of the Swiss Tumor Profiler cohort.,Workflow robustness was confirmed in 33 samples of an independent retrospective validation cohort.,The introduction of the intratumoral tumor center compartment proved to be most relevant for establishing an immune diagnosis in metastatic disease, independent of metastatic site.,Cut-off values for reproducible classification were defined and successfully assigned densities into the respective immune diagnostic category in the validation cohort with high sensitivity, specificity, and precision.,We provide a robust diagnostic algorithm based on intratumoral and stromal CD8+ T-cell densities in the tumor center compartment that translates spatial densities of tumor-infiltrating CD8+ T cells into the clinically relevant immune diagnostic categories “inflamed”, “excluded”, and “desert”.,The consideration of the intratumoral tumor center compartment allows immune phenotyping in the clinically highly relevant setting of metastatic lesions, even if the invasive margin compartment is not captured in biopsy material.,The authors present a robust diagnostic algorithm based on digital pathology and image analysis that quantifies intratumoral and stromal CD8+ T-cell densities in the tumor center and invasive margin compartment in metastatic melanoma.,Spatial CD8+ T-cell densities are translated into the clinically relevant immune diagnostic categories “inflamed”, “excluded”, and “desert”.,Their approach also allows efficient immune phenotyping of metastatic lesions, on biopsy material or even in the absence of material from the invasive margin.
Treatment with programmed death receptor-1 (PD-1) antibodies is associated with high response rates in patients with advanced melanoma.,Reliable markers for early response and outcome are still sparse.,We evaluated 66 consecutive patients with advanced/metastatic melanoma treated with nivolumab or pembrolizumab between 2013 and 2014.,The main objectives of this study were to investigate whether, first, serum lactate dehydrogenase (LDH) at baseline (normal vs above the upper limit of normal) correlates with overall survival (OS), and, second, whether the change of LDH during treatment predicts response before the first scan and OS in patients with an elevated baseline LDH.,After a median follow-up of 9 months, patients with an elevated baseline LDH (N=34) had a significantly shorter OS compared with patients with normal LDH (N=32; 6-month OS: 60.8% vs 81.6% and 12-month OS: 44.2% vs 71.5% (log-rank P=0.0292).,In those 34 patients with elevated baseline LDH, the relative change during treatment was significantly associated with an objective response on the first scan: the 11 (32%) patients with partial remission had a mean reduction of −27.3% from elevated baseline LDH.,In contrast, patients with progressive disease (N=15) had a mean increase of +39%.,Patients with a relative increase over 10% from elevated baseline LDH had a significantly shorter OS compared with patients with ⩽10% change (4.3 vs 15.7 months, log-rank P<0.00623).,LDH could be a useful marker at baseline and during treatment to predict early response or progression in patients with advanced melanoma who receive anti-PD-1 therapy.