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Updated: Jan 17, 2026

Patient-Derived Tumor Explants As a "Live" Preclinical Platform for Predicting Drug Resistance in Patients
Published on: February 7, 2021
Enhanced patient selection with quantitative continuous scoring of PD-L1 expression for IO treatment in metastatic
J Lesniak1, M Schick2, T Kunzke2
1AstraZeneca Computational Pathology GmbH, Munich, Germany. jan.lesniak@astrazeneca.com.
Abstract:
Immune checkpoint inhibitors targeting PD-1/PD-L1 are approved for metastatic non-small-cell lung cancer treatment. In clinical practice, the treatment choice depends on visual scoring of PD-L1, which is subjective and semi-quantitative. In this work, we present PD-L1 Quantitative Continuous Scoring (PD-L1 QCS), a computer vision system for granular cell-level quantification of PD-L1 staining intensity in digitized whole slide images (WSI). We derived a biomarker which captures the percentage of tumor cells (TC) with medium to strong staining intensity (PD-L1 QCS-PMSTC) and classifies patients with ≥0.575% as biomarker positive (BM+). Its effectiveness was examined against visual scoring of %TC ≥ 50 in 768 WSI from the MYSTIC trial (NCT02453282). Considering anti-PD-L1 treatment (N = 256) vs. chemotherapy (N = 246), visual scoring resulted in a hazard ratio (HR) of 0.69 (CI 0.46-1.02) with a 29.7% prevalence of the BM+ group. With PD-L1 QCS-PMSTC, a similar HR of 0.62 (CI 0.46-0.82) with an increased prevalence of 54.3% was obtained.
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