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  • Heterogeneity of PD-L1 expr...
    Haragan, Alexander; Field, John K.; Davies, Michael P.A.; Escriu, Carles; Gruver, Aaron; Gosney, John R.

    Lung cancer (Amsterdam, Netherlands), August 2019, 2019-08-00, 20190801, Letnik: 134
    Journal Article

    •PD-L1 expression was assessed for heterogeneity in 107 NSCLC patients.•Intra-tumoural heterogeneity was observed in 78% of cases.•Inter-tumoural heterogeneity was observed in 53% of cases.•23% of cases had clinically relevant changes between primary and secondary tumours.•Sample site selection is an important consideration for testing PD-L1. PD-L1 expression on tumour cells can guide the use of anti-PD-1/PD-L1 immune modulators to treat patients with non-small cell lung cancer (NSCLC). Heterogeneity of PD-L1 expression both within and between tumour sites is a well-documented phenomenon that compromises its predictive power. Our aim was to better characterise the pattern and extent of PD-L1 heterogeneity with a view to optimising tumour sampling and improve its accuracy as a biomarker. Expression of PD-L1 was assessed by immunochemistry using the SP263 clone in 107 resected primary NSCLCs and their nodal metastases. Intra-tumoural heterogeneity, defined as ‘small-scale’ (mm²), ‘medium-scale’ (cm²) and ‘large-scale’ (between tumour blocks), was assessed by digital imaging using a novel ‘squares method’. Inter-tumoural heterogeneity between the primary tumours and their nodal metastases and between N1 and N2 nodal stages was also assessed. The majority of tumours demonstrated intra-tumoural heterogeneity (small-scale 78%, medium-scale 50%, large-scale 46%). Inter-tumoural heterogeneity between the primary and nodal metastases was present in 53% of cases and, in 17%, between N1 and N2 disease. These differences were occasionally sufficient to lead to discrepancy across the ≥1%, ≥25% and ≥50% cut-offs used to guide therapy. Heterogeneity of PD-L1 expression is common, variable in scale and extent, and carries significant implications for its accuracy as a predictive biomarker. Extensive sampling reduces, but cannot eliminate, this inaccuracy.