Abstract
Programmed death ligand-1 (PD-L1) expression is a key biomarker to screen patients for PD-1/PD-L1-targeted immunotherapy. However, a subjective assessment guide on PD-L1 expression of tumor-infiltrating immune cells (IC) scoring is currently adopted in clinical practice with low concordance. Therefore, a repeatable and quantifiable PD-L1 IC scoring method of breast cancer is desirable. In this study, we propose a deep learning-based artificial intelligence-assisted (AI-assisted) model for PD-L1 IC scoring. Three rounds of ring studies (RSs) involving 31 pathologists from 10 hospitals were carried out, using the current guideline in the first two rounds (RS1, RS2) and our AI scoring model in the last round (RS3). A total of 109 PD-L1 (Ventana SP142) immunohistochemistry (IHC) stained images were assessed and the role of the AI-assisted model was evaluated. With the assistance of AI, the scoring concordance across pathologists was boosted to excellent in RS3 (0.950, 95% confidence interval (CI): 0.936–0.962) from moderate in RS1 (0.674, 95% CI: 0.614–0.735) and RS2 (0.736, 95% CI: 0.683–0.789). The 2- and 4-category scoring accuracy were improved by 4.2% (0.959, 95% CI: 0.953–0.964) and 13% (0.815, 95% CI: 0.803–0.827) (p < 0.001). The AI results were generally accepted by pathologists with 61% “fully accepted” and 91% “almost accepted”. The proposed AI-assisted method can help pathologists at all levels to improve the PD-L1 assay (SP-142) IC assessment in breast cancer in terms of both accuracy and concordance. The AI tool provides a scheme to standardize the PD-L1 IC scoring in clinical practice.
Highlights
Breast cancer is one of the most common malignant tumors for women worldwide[1]
We evaluated the performance of the proposed AIassisted model on the 109 test images using the 2-category and 4category gold standard scores provided by expert pathologists
One case was underestimated on the stain regions, and three cases were falsely over-estimated on stain regions with the slightly underestimated necrotic region
Summary
Breast cancer is one of the most common malignant tumors for women worldwide[1]. Programmed death 1 (PD-1)/programmed death ligand-1 (PD-L1) immunotherapy is one of the most promising treatments for breast cancer, relying on and helping the patient’s immune system to fight cancers[2,3,4], and offering a personalized and less invasive alternative therapy. The Impassion 130 study indicated clinically meaningful prolonged overall survival for PD-L1 positive patients with tumor-infiltrating immune cell (IC) score greater than 1% when atezolizumab combined with nab-paclitaxel were used as first-line treatment for unresectable local advanced or metastatic triple-negative breast cancer (TNBC)[5]. A recent ring study[9] evaluated the concordance of PD-L1 IC scoring on 100 patients with TNBC across 19 pathologists. These reader studies indicate that current PD-L1 scoring protocols suffer from poor reproducibility across multiple pathologists. These studies only evaluated the pathologists’ performances and did not involve AI in the trial
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