ORIGINAL RESEARCH article

Front. Cell Dev. Biol.

Sec. Cancer Cell Biology

Volume 13 - 2025 | doi: 10.3389/fcell.2025.1636288

This article is part of the Research TopicArtificial Intelligence in Multi-omics: Advancing Tumor Metastasis Prediction and Mechanism AnalysisView all articles

PD-L1 expression predicts the efficacy of PD-1 blockade plus chemotherapy versus chemotherapy alone in treatment-naïve advanced or metastatic gastric cancer: a pooled analysis of reconstructed individual patient-level data from two randomized trials

Provisionally accepted
  • 1Sun Yat-sen University Cancer Center (SYSUCC), Guangzhou, China
  • 2Fourth Affiliated Hospital of China Medical University, Shenyang, China
  • 3Shenyang Kingmed Diagnostics Co, Ltd, Shenyang, China
  • 4Jinan University, Guangzhou, China

The final, formatted version of the article will be published soon.

Background: Chemotherapy alone exhibits suboptimal efficacy in patients with treatment-naïve advanced gastric cancer (GC). Randomized controlled trials (RCTs) have demonstrated that combining Programmed Cell Death Protein-1 (PD-1) blockade with chemotherapy significantly improves overall survival (OS) compared to chemotherapy alone. However, the efficacy of PD-1 inhibitors in patients with low Programmed Cell Death-Ligand 1 (PD-L1) expression remains unclear.Methods: Electronic databases were searched for RCTs comparing PD-1/PD-L1 inhibitors plus chemotherapy to placebo plus chemotherapy or chemotherapy alone in treatment-naïve advanced gastric or gastroesophageal junction adenocarcinoma patients. Individual patient-level data (IPD) for overall survival (OS) and progression-free survival (PFS) were reconstructed. The KMSubtraction algorithm was employed to derive IPD for the PD-L1-low subgroup. Treatment effects in PD-L1-high and PD-L1-low subgroups were evaluated using Cox proportional hazards models with shared frailty to account for between-study heterogeneity. Interaction tests were performed to assess differences in treatment effects between these subgroups.Results: Nine RCTs were included in the qualitative analysis. A combined positive score (CPS) of 5 was selected as the cutoff for analysis, with CheckMate 649 and ORIENT-16 trials included. In the CPS<5 subgroup, OS (CheckMate 649: HR = 0.97, 95% CI 0.81-1.17, P = 0.758; ORIENT-16: HR = 0.94, 95% CI 0.68-1.31, P = 0.725) and PFS (CheckMate 649: HR = 0.95, 95% CI 0.79-1.14, P = 0.580; ORIENT-16: HR = 0.73, 95% CI 0.52-1.01, P = 0.055) did not significantly differ between patients receiving PD-1 blockade plus chemotherapy and those receiving chemotherapy alone.Pooled analysis of reconstructed OS IPD from CheckMate 649 and ORIENT-16 (N = 2,231) revealed that PD-1 blockade significantly improved OS in the CPS≥5 subgroup (HR = 0.69, 95% CI 0.60-0.79, P<0.001), but not in the CPS<5 subgroup (HR = 0.96, 95% CI 0.82-1.13, P = 0.643).Interaction tests showed a significantly attenuated treatment effect on OS in the CPS<5 subgroup compared to the CPS≥5 subgroup (Pinteraction = 0.002). Similar findings were observed in the pooled analysis of PFS data (Pinteraction = 0.011).The addition of PD-1 inhibitors to first-line chemotherapy provides minimal benefit in patients with CPS<5. Therefore, PD-1 inhibitors should be individualized for this patient subset.

Keywords: Advanced gastric cancer, Programmed Cell Death Protein-1 blockade, chemotherapy, Programmed cell death-ligand 1 expression, Combined positive score, randomized controlled trials

Received: 27 May 2025; Accepted: 23 Jun 2025.

Copyright: © 2025 Zhou, Cai, Fan, Zheng and Chen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
Xu Zheng, Shenyang Kingmed Diagnostics Co, Ltd, Shenyang, China
Yu-Tong Chen, Jinan University, Guangzhou, China

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