Automated whole-slide images assessment of immune infiltration in resected non-small-cell lung cancer: towards better risk-stratification

Abstract

Abstract Background High immune infiltration is associated with favourable prognosis in patients with non-small-cell lung cancer (NSCLC), but an automated workflow for characterizing immune infiltration, with high validity and reliability, remains to be developed. Methods We performed a multicentre retrospective study of patients with completely resected NSCLC. We developed an image analysis workflow for automatically evaluating the density of CD3+ and CD8+ T-cells in the tumour regions on immunohistochemistry (IHC)-stained whole-slide images (WSIs), and proposed an immune scoring system “I-score” based on the automated assessed cell density. Results A discovery cohort (n = 145) and a validation cohort (n = 180) were used to assess the prognostic value of the I-score for disease-free survival (DFS). The I-score (two-category) was an independent prognostic factor after adjusting for other clinicopathologic factors. Compared with a low I-score (two-category), a high I-score was associated with significantly superior DFS in the discovery cohort (adjusted hazard ratio [HR], 0.54; 95% confidence interval [CI] 0.33–0.86; P = 0.010) and validation cohort (adjusted HR, 0.57; 95% CI 0.36–0.92; P = 0.022). The I-score improved the prognostic stratification when integrating it into the Cox proportional hazard regression models with other risk factors (discovery cohort, C-index 0.742 vs. 0.728; validation cohort, C-index 0.695 vs. 0.685). Conclusion This automated workflow and immune scoring system would advance the clinical application of immune microenvironment evaluation and support the clinical decision making for patients with resected NSCLC.

Keywords

• Non-small-cell lung cancer (NSCLC)
• Whole-slide image
• Immunohistochemistry (IHC)
• Tumour immune microenvironment
• Prognosis prediction