Background: We quantified the pathological spatial intratumor heterogeneity of programmed death-ligand 1 (PD-L1) expression and investigated its relevance to patient outcomes in surgically resected non-small cell lung carcinoma (NSCLC).
Methods: This study enrolled 239 consecutive surgically resected NSCLC specimens of pathological stage IIA-IIIB. To characterize the spatial intratumor heterogeneity of PD-L1 expression in NSCLC tissues, we developed a mathematical model based on texture image analysis and determined the spatial heterogeneity index of PD-L1 for each tumor. The correlation between the spatial heterogeneity index of PD-L1 values and clinicopathological characteristics, including prognosis, was analyzed. Furthermore, an independent cohort of 70 cases was analyzed for model validation.
Results: Clinicopathological analysis showed correlations between high spatial heterogeneity index of PD-L1 values and histological subtype (squamous cell carcinoma; P < .001) and vascular invasion (P = .004). Survival analysis revealed that patients with high spatial heterogeneity index of PD-L1 values presented a significantly worse recurrence-free rate than those with low spatial heterogeneity index of PD-L1 values (5-year recurrence-free survival [RFS] = 26.3% vs 47.1%, P < .005). The impact of spatial heterogeneity index of PD-L1 on cancer survival rates was verified through validation in an independent cohort. Additionally, high spatial heterogeneity index of PD-L1 values were associated with tumor recurrence in squamous cell carcinoma (5-year RFS = 29.2% vs 52.8%, P < .05) and adenocarcinoma (5-year RFS = 19.6% vs 43.0%, P < .01). Moreover, we demonstrated that a high spatial heterogeneity index of PD-L1 value was an independent risk factor for tumor recurrence.
Conclusions: We presented an image analysis model to quantify the spatial intratumor heterogeneity of protein expression in tumor tissues. This model demonstrated that the spatial intratumor heterogeneity of PD-L1 expression in surgically resected NSCLC predicts poor patient outcomes.
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