Integrative proteogenomics maps multifactorial aetiology, progression and therapeutic vulnerabilities in gastric cancer

Background Gastric cancer, with disproportionately higher incidence in East Asia, arises from complex host–microbiome–environment interactions beyond Helicobacter pylori (HP) infection. However, the molecular architecture linking environmental carcinogens, microbial succession and host response remains unclear. Objective To delineate multifactorial aetiologies and clinically actionable subtypes/biomarkers of gastric cancer through integrative proteogenomic, microbial and environmental exposure profiling. Design We established a multiomics atlas of paired tumour, adjacent mucosa tissues and blood from 154 treatment-naïve Taiwanese patients, integrating whole-exome sequencing, RNA-seq, proteome and phosphoproteome profiling with carcinogen signatures, HP status, microbiome composition and refined anatomical mapping. Cell-based functional assays tested carcinogen effects. Microbial subtype was assessed in an independent cohort. Results A polycyclic-aromatic-hydrocarbon signature, dibenz[a,h]acridine, emerged as a high-risk exposure promoting invasion, immune suppression and poor survival, significantly exceeding nitrosamine-linked risk in this cohort. Multilayer integration defined three initiation ecologies: HP-driven inflammatory, non-HP microbiome-enriched immune-silent and HP-free microbially depleted states. Among HP-negative tumours, a Streptococcus -enriched subtype associated with tight-junction (CLDN18.2/ZO-1/OCLN) disruption and epithelial–mesenchymal transition, whereas a subset of clinically aggressive cases retained CLDN18.2-high epithelial-stable subtype for therapeutic accessibility. An independent cohort revealed gastric juice-derived Streptococcus anginosus abundance inversely correlated with tight-junction proteins. Anatomical mapping reveals location-specific, sex-specific, subtype-specific oncogenic networks and kinase activity, including CDK4 activation in clinical biomarker-negative tumours. Decision-tree models combining exposure and proteome–immune states refined recurrence and survival prediction beyond stage. Conclusion This proteogenomic framework defines exposure-informed and microbiome-informed gastric cancer subtypes, providing a molecular schema for patient stratification, prevention and actionable therapeutic vulnerabilities.