Abstract 1407P
Background
The use of PD-1 inhibitors improved the clinical outcomes of patients with esophageal squamous cell carcinoma (ESCC). However, reliable biomarkers to predict the prognostic role of immunotherapy are lacking. We aimed to evaluate the prognostic ability of a new comprehensive biomarker, pan-immune-inflammatory value (PIV), in patients with ESCC receiving chemoradiotherapy (CRT) combined with anti-PD-1 immunotherapy, and to explore the underlying mechanisms and dosimetric parameters that affect PIV zenith during CRT.
Methods
In this pooled-analysis, 86 patients were included from two prospective, phase II trials (EC-CRT-001 and NEOCRTECT1901). PIV was calculated as: (neutrophil count × platelet count × monocyte count)/lymphocyte count. The optimum cut-off value was selected by using the receiver-operating characteristics curve. Kaplan-Meier method and Cox hazard regression models were used for survival analyses. Univariate and multivariable logistic regression were used to identify predictors of high PIV zenith. Pre-treatment tumor samples from 47 patients were collected for RNA sequencing to investigate the activation of immune related biological activities.
Results
Patients experienced significant changes in immuno-inflammatory biomarkers during CRT, which gradually recovered after radiotherapy. After a median follow-up of 35.5 months, patients with high PIV zenith during CRT had a worse progression-free survival (PFS) (P=0.007) and overall survival (P=0.015). In multivariable analysis, high PIV zenith remained a significant prognostic factor for PFS. Mean lung dose (MLD) was revealed to be an independent predictor of high PIV zenith. High PIV zenith was associated with higher levels of B cell infiltration, activation, and B cell-mediated immune response.
Conclusions
PIV is a strong predictor for survival outcomes in patients with ESCC treated with anti-PD-1 immunotherapy in combination with CRT. High PIV zenith was correlated to higher MLD and higher levels of B cell-mediated immune response. Prospective trials with large samples are required to validate the value of this new parameter.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
National Natural Science Foundation of China.
Disclosure
All authors have declared no conflicts of interest.
Resources from the same session
1427P - Predicting overall survival and prognostic indicator genes in esophagogastric cancer patients using machine learning and bioinformatics analysis
Presenter: Nguyen-Kieu Viet-Nhi
Session: Poster session 17
1428P - Total neoadjuvant FLOT chemotherapy in oesophagogastric adenocarcinoma: An international cohort study
Presenter: Hollie Clements
Session: Poster session 17
1429P - Differences in esophageal cancer incidence and survival by race/ethnicity: A SEER analysis
Presenter: Ashwin Kulshrestha
Session: Poster session 17
1430P - Impact of menadione supplementation in the treatment of patients with metastatic gastric cancer: A randomized phase II clinical trial
Presenter: Francisco Cezar Moraes
Session: Poster session 17
1431P - Assessing pathological complete response to neoadjuvant chemotherapy combined with immunotherapy in esophageal squamous cell carcinoma: A deep learning approach with voxel-level radiomics
Presenter: Yongling Ji
Session: Poster session 17
1432P - Safety of laparoscopic D2 distal gastrectomy following neoadjuvant chemotherapy for locally advanced gastric cancer patients: A prospective multicenter trial (CLASS-03a)
Presenter: Kun Yang
Session: Poster session 17