Pan-immune-inflammation value predicts survival of patients with oesophageal squamous cell carcinoma receiving immunotherapy and chemoradiotherapy: a pooled analysis of two phase II trials.
To evaluate the prognostic role of pan-immune-inflammation value (PIV) in patients with oesophageal squamous cell carcinoma (ESCC) receiving chemoradiotherapy (CRT) combined with anti-programmed cell death 1 (PD-1) immunotherapy, and to explore the underlying mechanisms and dosimetric parameters that affect PIV zenith.
In this pooled analysis, 86 patients from two phase II trials who received toripalimab plus CRT were analysed. PIV was calculated as follows: (neutrophil count × platelet count × monocyte count)/lymphocyte count. The optimal cut-off value was determined using the receiver operating characteristic curve. Survival analysis was conducted using the Kaplan-Meier method and Cox regression models. Univariate and multivariable logistic regression analyses identified predictors of high PIV zenith. Pretreatment tumour samples from 46 patients were subjected to RNA and whole-exome sequencing (WES). Gene set enrichment analysis was performed on RNA sequencing (RNA-seq) data, and somatic mutations were assessed using WES to further explore molecular correlates.
Significant changes in immuno-inflammatory biomarkers were observed during CRT, which gradually normalized post-radiotherapy. After a median follow-up of 35.5 months, patients with high PIV zenith during CRT exhibited significantly poorer progression-free survival (p = 0.007) and overall survival (p = 0.015). In multivariable analysis, high PIV zenith remained a significant prognostic indicator for survival. Mean lung dose (MLD) was identified as an independent predictor of high PIV zenith. Patients with high PIV zenith had decreased interferon α response, interferon γ response, transforming growth factor-β signalling and more frequent mutations in the Hippo pathway genes, resulting in pathway downregulation.
High PIV zenith during CRT strongly predicts poorer survival outcomes in patients with ESCC treated with combined immunotherapy and CRT. These peaks are associated with higher MLD, reduced interferon α response, interferon γ response and increased prevalence of Hippo pathway mutations.
In this pooled analysis, 86 patients from two phase II trials who received toripalimab plus CRT were analysed. PIV was calculated as follows: (neutrophil count × platelet count × monocyte count)/lymphocyte count. The optimal cut-off value was determined using the receiver operating characteristic curve. Survival analysis was conducted using the Kaplan-Meier method and Cox regression models. Univariate and multivariable logistic regression analyses identified predictors of high PIV zenith. Pretreatment tumour samples from 46 patients were subjected to RNA and whole-exome sequencing (WES). Gene set enrichment analysis was performed on RNA sequencing (RNA-seq) data, and somatic mutations were assessed using WES to further explore molecular correlates.
Significant changes in immuno-inflammatory biomarkers were observed during CRT, which gradually normalized post-radiotherapy. After a median follow-up of 35.5 months, patients with high PIV zenith during CRT exhibited significantly poorer progression-free survival (p = 0.007) and overall survival (p = 0.015). In multivariable analysis, high PIV zenith remained a significant prognostic indicator for survival. Mean lung dose (MLD) was identified as an independent predictor of high PIV zenith. Patients with high PIV zenith had decreased interferon α response, interferon γ response, transforming growth factor-β signalling and more frequent mutations in the Hippo pathway genes, resulting in pathway downregulation.
High PIV zenith during CRT strongly predicts poorer survival outcomes in patients with ESCC treated with combined immunotherapy and CRT. These peaks are associated with higher MLD, reduced interferon α response, interferon γ response and increased prevalence of Hippo pathway mutations.
Authors
Cheng Cheng, Luo Luo, Gao Gao, Wang Wang, Liu Liu, Li Li, Zhou Zhou, Yang Yang, Chen Chen, Liu Liu, Xi Xi
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