Cholangiocarcinoma (CCA) displays enhanced glycolysis, pivotal for fulfilling the heightened energy demands intrinsic to its malignant progression. Recent research has indicated that endogenous glycogen rather than exogenous glucose acts as the major carbon source for glycolysis, highlighting the need to better understand the regulation of glycogen homeostasis in CCA. Here, through comprehensive integrative analysis, we identified that glycogen phosphorylase brain form (PYGB), the main enzyme involved in glycogen homeostasis, was markedly upregulated in CCA tissues, serving as an independent prognostic indicator for human patients with CCA. Moreover, elevated PYGB expression potentiated cholangiocarcinogenesis and augmented CCA cell proliferation in both organoid and xenograft models. Hypoxia stimulated PYGB activity in a phosphoglycerate kinase 1–dependent manner, leading to glycogenolysis and the subsequent release of glucose-6-phosphate (G6P) and thereby facilitating aerobic glycolysis. Notably, a virtual screening pinpointed the β-blocker carvedilol as a potent pharmacologic inhibitor of PYGB that could attenuate CCA progression. Collectively, these findings position PYGB as a promising prognostic biomarker and therapeutic target for CCA. Significance: Cholangiocarcinoma cells exhibit high glycogen phosphorylase activity under hypoxic conditions that mediates metabolic reprograming to promote glycolysis and support tumor development.

Objective. Abnormal lipid metabolism is known to influence the malignant behavior of gastric cancer. However, the underlying mechanism remains elusive. In this study, we comprehensively analyzed the biological significance of genes involved in lipid metabolism in advanced gastric cancer (AGC). Methods. We obtained gene expression profiles from The Cancer Genome Atlas (TCGA) database for early and advanced gastric cancer samples and performed differential expression analysis to identify specific lipid metabolism‐related genes in AGC. We then used consensus cluster analysis to classify AGC patients into molecular subtypes based on lipid metabolism and constructed a diagnostic model using least absolute shrinkage and selection operator‐ (LASSO‐) Cox regression analysis and Gene Set Enrichment Analysis (GSEA). We evaluated the discriminative ability and clinical significance of the model using the Kaplan‐Meier (KM) curve, ROC curve, DCA curve, and nomogram. We also estimated immune levels based on immune microenvironment expression, immune checkpoints, and immune cell infiltration and obtained hub genes by weighted gene co‐expression network analysis (WGCNA) of differential genes from the two molecular subtypes. Results. We identified 6 lipid metabolism genes that were associated with the prognosis of AGC and used consistent clustering to classify AGC patients into two subgroups with significantly different overall survival and immune microenvironment. Our risk model successfully classified patients in the training and validation sets into high‐risk and low‐risk groups. The high‐risk score predicted poor prognosis and indicated low degree of immune infiltration. Subgroup analysis showed that the risk model was an independent predictor of prognosis in AGC. Furthermore, our results indicated that most chemotherapeutic agents are more effective for AGC patients in the low‐risk group than in the high‐risk group, and risk scores for AGC are strongly correlated with drug sensitivity. Finally, we performed qRT‐PCR experiments to verify the relevant results. Conclusion. Our findings suggest that lipid metabolism‐related genes play an important role in predicting the prognosis of AGC and regulating immune invasion. These results have important implications for the development of targeted therapies for AGC patients.

Diffuse gastric cancer (DGC) is characterized by high malignancy and metastasis rate, and poorly understood etiology, culminating in dismal patient outcomes. Here, through comprehensive analysis, we identified that glutathione peroxidase 2 (GPX2) plays a pivotal role in the progression of DGC by regulating lipid metabolism. This study demonstrates that GPX2 is markedly upregulated in DGC tissues, establishing its potential as an independent prognostic indicator. Functionally, GPX2 suppression disrupts lipid droplet formation and lipid homeostasis, leading to increased acylcarnitine levels that impair mitochondrial function. This disruption synergizes with endoplasmic reticulum stress to trigger apoptosis in gastric cancer cells. Notably, inhibiting GPX2 enhances the efficacy of cisplatin by sensitizing cancer cells to apoptosis. These insights identify GPX2 not only as a vital prognostic biomarker but also as a promising therapeutic target for overcoming cisplatin resistance in DGC, offering new avenues for treatment strategies.

Radiotherapy has become an indispensable and conventional means for patients with advanced solid tumors including gastrointestinal cancer. However, innate or acquired radiotherapy resistance remains a significant challenge and greatly limits the therapeutic effect, which results in cancer relapse and poor prognosis. Therefore, it is an urgent need to identify novel biomarkers and therapeutic targets for clarify the biological characteristics and mechanism of radiotherapy resistance. Recently, lots of studies have revealed that non-coding RNAs (ncRNAs) are the potential indicators and regulators of radiotherapy resistance via the mediation of various targets/pathways in different cancers. These findings may serve as a potential therapeutic strategy to overcome radiotherapy resistance. In this review, we will shed light on the recent findings regarding the functions and regulatory mechanisms of ncRNAs following radiotherapy, and comprehensively discuss their potential as biomarkers and therapeutic targets in radiotherapy resistance of gastrointestinal cancer.