Association of clinicopathological characteristics and baseline peripheral blood lymphocyte subsets with efficacy of first-line immunotherapy in advanced gastric cancer
摘要
Immunotherapy has revolutionized treatment for advanced gastric/gastroesophageal junction adenocarcinoma (G/GEJC). However, identifying convenient biomarkers for predicting therapeutic efficacy remains challenging. This study investigated the association between clinicopathological characteristics and baseline peripheral blood lymphocyte subsets with efficacy of first-line chemotherapy combined with immune checkpoint inhibitors (ICIs) in proficient mismatch repair (pMMR) human epidermal growth factor receptor 2 (HER2)-negative advanced G/GEJC.
MethodsThis retrospective study enrolled 97 patients with pMMR HER2-negative advanced G/GEJC receiving first-line chemotherapy combined with ICIs. Clinicopathological characteristics and peripheral blood lymphocyte subsets were collected. Overall survival (OS) and progression-free survival (PFS) were used to evaluate efficacy. The univariate and multivariate analyses were conducted using Cox regression analysis.
ResultsMedian PFS and OS were 5.9 and 15.2 months, respectively. Tumor location, Lauren classification, tumor differentiation, peritoneal metastases, neutrophil to lymphocyte ratio (NLR), and regulatory T cells (Tregs) as significantly associated with PFS. Well-differentiated tumor and higher Tregs independently predicted longer PFS. For OS, only higher NLR was an independent risk factor. Optimal cut-offs for NLR (3.5) and Tregs (10.1) stratified patients with significantly different PFS. A nomogram combining Tregs, NLR, peritoneal metastases, and tumor differentiation achieved superior predictive performance compared to PD-L1 CPS alone, with PFS AUC of 0.68–0.77 and OS AUC of 0.69–0.75.
ConclusionsClinicopathological characteristics and baseline peripheral lymphocyte subsets were significantly associated with efficacy of first-line chemotherapy combined with ICIs in pMMR HER2-negative advanced G/GEJC, highlighting the potential utility of integrating these accessible parameters for efficacy prediction.