Molecular and Structural Reprogramming of Gastric Cancer Revealed by Systems-Level Transcriptomic Analysis

Gastric cancer (GC) is a major cause of cancer mortality and remains difficult to diagnose early and treat effectively. Although transcriptomic profiling has defined extensive molecular heterogeneity, many studies are not anchored to clinicopathological variables or interpreted in the context of tissue-level pathobiology. We applied an integrative transcriptomic and network-based framework to identify molecular signatures that reflect structural and biochemical reprogramming of gastric tissue during malignant transformation. RNA-seq expression profiles and clinical annotations were analyzed using non-parametric differential expression filtering, functional enrichment, and protein-protein interaction network modeling. Expression patterns were further evaluated across clinicopathological strata (stage, grade, nodal status, and metastasis) and by network-informed clustering. Across clinical strata, GC showed a consistent signature of developmental reactivation and loss of gastric epithelial identity. Developmental regulators, most prominently HOX-cluster genes and the histone variant HIST1H3J, were upregulated, consistent with epigenetic/chromatin reprogramming. In parallel, gastric differentiation and secretory lineage markers (ATP4A, KCNE2, PTF1A, VSTM2A) were persistently downregulated, reflecting suppression of parietal/ductal programs and altered metabolic/secretory function. ADIPOQ demonstrated stage-dependent repression and was associated with poorer survival, supporting a context-dependent prognostic role. Enrichment and network analyses also highlighted FGFR-centered signaling as a dominant oncogenic axis linked to proliferation and invasion. This study identifies a molecular pathology framework in which GC progression involves coordinated chromatin-level developmental reprogramming and sustained loss of gastric differentiation programs, accompanied by FGFR-driven oncogenic signaling and stage-dependent metabolic disruption. These signatures provide candidate diagnostic and prognostic biomarkers and support prioritization of therapeutically actionable pathways in GC.