AUTHOR=Jin Peng , Ji Xiaoyan , Bai Jingchao , Su Wei , Ke Bin , Liu Yong , Wang Bin 

TITLE=Identification of prognosis and therapy related intratumoral microbiome and immune signatures in gastric cancer

JOURNAL=Frontiers in Immunology

VOLUME=Volume 16 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2025.1622959

DOI=10.3389/fimmu.2025.1622959

ISSN=1664-3224

ABSTRACT=The impact of the intratumoral microbiome (ITM) on the treatment and prognosis of gastric cancer (GC) remains controversial. Our study analyzed the differential ITM in GC tissues and identified nine bacterial genera significantly associated with overall survival (OS), with seven as risk factors and two as protective factors. Three distinct clusters with varying survival outcomes were defined, demonstrating correlations with pathological stage and immune features. An immune-related gene-based RiskScore model incorporating genes such as Apolipoprotein D (APOD), Stanniocalcin 1 (STC1), Coagulation Factor II Thrombin Receptor (F2R), Angiotensinogen (AGT), Fatty Acid Binding Protein 4 (FABP4), Inhibin Subunit Beta A (INHBA), Caspase Recruitment Domain Family Member 11 (CARD11), and Dickkopf WNT Signaling Pathway Inhibitor 1 (DKK1) was established and validated in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. When combined with clinical factors, this RiskScore model formed a Nomogram model achieving Areas Under the Curve (AUCs) of 0.72, 0.76, and 0.79 for 1, 3, and 5-year OS predictions, respectively. This model exhibited robust predictive accuracy over time and correlated with mutation frequency, drug sensitivity, and immunotherapy response. Furthermore, single-cell analysis revealed that tumor-associated fibroblasts may play a pivotal role in immune-microbial interactions. The results were confirmed using quantitative real-time polymerase chain reaction (qPCR) and immunohistochemistry (IHC). In conclusion, the prognostic model incorporating ITM and immune-related genes aids in risk stratification and provides valuable insights and targets for GC treatment.