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July 9, 2026Molecular Biomedicine0 citationsOpen Access

Plasma proteomics-based liquid biopsy for predicting efficacy of PD-1-based immunochemotherapy in advanced gastric cancer: a prospective cohort study

EMEnqing MengXCXu ChengXWXinyi Wu

Key Points

  • This study aims to identify reliable biomarkers for predicting the efficacy of PD-1-based immunochemotherapy in advanced gastric cancer.
  • Performed longitudinal plasma proteomic profiling in 31 patients receiving immunochemotherapy.
  • Analyzed plasma samples at baseline and every two treatment cycles to correlate protein changes with outcomes.
  • Developed a composite risk model integrating baseline IL-15 and dynamic changes in MUC-16 and MMP12.
  • Responders showed significantly lower baseline IL-15 levels (P = 0.01).
  • A 161.9% reduction in plasma MUC-16 after two cycles was linked to better overall survival (HR 7.40, 95% CI 2.22-24.60, P = 0.001).
  • The composite model achieved an AUC of 0.799 for predicting response and was an independent factor for progression-free survival (HR 3.35, 95% 1.56-7.20, P = 0.002).

Abstract

The combination of immune checkpoint inhibitors (ICIs) and chemotherapy has become the standard first-line treatment for advanced gastric cancer and gastroesophageal junction cancer (GC/GEJC), yet reliable biomarkers predicting efficacy remain limited. We performed longitudinal plasma proteomic profiling in 31 patients receiving immunochemotherapy in this prospective observational cohort study. Serial plasma samples collected at baseline and every two treatment cycles were analyzed to identify dynamic protein changes correlated with therapeutic response and survival. The results showed that responders exhibited significantly lower baseline interleukin-15 (IL-15) levels (P = 0.01). After two cycles of treatment, a 161.9% reduction in plasma Mucin-16 (MUC-16), also known as Cancer Antigen-125 (CA-125), was identified as an independent factor for prolonged overall survival (HR 7.40, 95%CI 2.22-24.60, P = 0.001), which was validated by conventional serum CA-125 testing. Integrating baseline IL-15 with dynamic changes in MUC-16 and Matrix Metalloproteinase 12 (MMP12), the constructed composite risk model achieved an Area Under the Curve (AUC) of 0.799 for predicting response, and this model was also an independent factor for progression-free survival (HR 3.35, 95% 1.56-7.20, P = 0.002). In summary, baseline IL-15 helps identify patients likely to benefit from immunochemotherapy, while MUC-16 and the integrated model facilitate dynamic monitoring of therapeutic efficacy. These findings provide new insights into non-invasive blood-based patient stratification and treatment optimization.Trial registration ChiCTR2300078000. Registered 27 November 2023-prospectively registered, https://www.chictr.org.cn/hvshowproject.html?id=241839&v=1.0.

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Cite This Study

Meng et al. (2026) studied this question.

synapsesocial.com/papers/6a4f39e32b81a944af5748c0https://doi.org/10.1186/s43556-026-00510-8
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