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A multicenter retrospective study is conducted from January 2011 to December 2021 and included 317 AFPGC patients. Using a multivariable logistic regression model, a nomogram for predicting liver metastasis is built. By combining AFP and the neutrophil\u2013lymphocyte ratio (NLR), we developed a novel and easily applicable predictive indicator, termed ANLiM score, for liver metastasis in AFPGC. An integrated multi\u2010omics analysis, including whole\u2010exome sequencing and proteomic analysis, is conducted and revealed an immunosuppressive TME in AFPGC with liver metastasis. Single\u2010cell RNA sequencing and multiplex immunofluorescence identified the potential roles of tumor\u2010associated neutrophils and tertiary lymphoid structures in shaping the immune microenvironment. These findings are validated in a real\u2010world cohort receiving anti\u2010programmed cell death 1 (anti\u2010PD\u20101) therapy, which showed concordant effectiveness. In addition, the ANLiM score is also identified as a promising biomarker for predicting immunotherapy efficacy. Overall, a blood biomarker\u2010based predictive indicator is developed for liver metastasis and immunotherapy response in AFPGC. The findings on immune microenvironmental alterations for AFPGC with liver metastasis provide new insights for optimizing immunotherapy strategies.<\/jats:p>","DOI":"10.1002\/advs.202503499","type":"journal-article","created":{"date-parts":[[2025,5,28]],"date-time":"2025-05-28T07:01:16Z","timestamp":1748415676000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Blood Biomarker\u2010Based Predictive Indicator for Liver Metastasis in Alpha\u2010Fetoprotein\u2010Producing Gastric Cancer and Multi\u2010Omics Tumor Microenvironment Insights"],"prefix":"10.1002","volume":"12","author":[{"given":"Yongfeng","family":"Ding","sequence":"first","affiliation":[{"name":"Department of Medical Oncology The First Affiliated Hospital School of Medicine Zhejiang University  Hangzhou 310000 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