PD-1 and PD-L1 expression predict regression and prognosis following neoadjuvant radiochemotherapy of oesophageal adenocarcinoma

PD-1 和 PD-L1 表达可预测食管腺癌新辅助放化疗后的消退和预后

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Abstract

BACKGROUND AND PURPOSE: PD-1 and PD-L1 are involved in anticancer immunosurveillance, and their expression may be predictive for therapeutic effectiveness of specific antibodies. Their influence on response to neoadjuvant radiochemotherapy (RCT) and prognosis in patients with oesophageal adenocarcinoma (OAC) remains to be defined. MATERIALS AND METHODS: Between 10/2004 and 06/2018, complete pre-RCT biopsy-specimens were available from 76 patients with locally advanced, non-metastatic OAC scheduled for trimodality therapy. We evaluated intra- and peritumoural expression of CD8, PD-1 and PD-L1 in pre-treatment specimens to determine their influence on tumour regression grade and survival. PD-1 and PD-L1 expression were considered positive (+) if ≥1% of all cells were stained positive, otherwise negative (-); densities of CD8+ cells were categorized as being high (Hi) or low (Lo) according to the median. RESULTS: A negative PD-L1 expression in peritumoural cells predicted a poor tumour regression (RD 0.24 [95% CI 0.03-0.44], p = 0.023). A positive PD-1 expression in intra- as well as peritumoural cells was identified as an unfavourable prognostic factor (HR 0.52 [95% CI 0.29-0.93], p = 0.028; HR 0.50 [0.25-0.99], p = 0.047, respectively). With respect to CD8+ infiltration, positive PD-1 and PD-L1 expressions attenuated its favourable prognostic effect in intratumoural area (LoCD8/PD1 + vs. HiCD8/PD1-: HR 0.25 [0.09-0.69], p = 0.007; LoCD8/PDL1+ vs. HiCD8/PDL1-: HR 0.32 [0.12-0.89], p = 0.028) and were associated with negative outcome when seen in peritumoural area (HiCD8/PD1+ vs. LoCD8/PD1-: HR 0.29 [0.11-0.74], p = 0.010); HiCD8/PDL1+ vs. LoCD8/PDL1-: HR 0.33 [0.12-0.90], p = 0.031). CONCLUSIONS: PD-1 and PD-L1 expression were identified to be of predictive and prognostic value in patients with OAC, particularly when considering CD8+ infiltration. Further validation by a large size dataset is required.

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