Author

Xuewei Zheng

1 paper indexed here

Fetches their full publication history.

Not the right person? Other researchers publish under this name.

Open access Jul 2026

Unraveling role of arginine-NO metabolism by targeting HIF-1α signaling in mediating esophageal squamous cell carcinoma

Objective Due to the lack of specific biomarkers, patients with esophageal cancer are often diagnosed at an advanced stage, resulting in poor treatment outcomes. This study aims to identify potential diagnostic and therapeutic biomarkers for esophageal squamous cell carcinoma (ESCC) through metabolomics and to elucidate their mechanisms of action. Methods Untargeted metabolomics was employed to analyze ESCC tissue samples and matched normal esophageal tissue samples. Differentially expressed metabolites were identified using multivariate statistical analysis. MetaboAnalyst 6.0 software was used for pathway analysis. Key molecules were validated via immunohistochemistry (IHC) and Western blot (WB), and their functions were assessed through cellular functional assays. Results A total of 2,850 metabolites were identified, among which 939 were differentially regulated, including 575 upregulated and 364 downregulated metabolites. Pathway enrichment analysis revealed that these differentially expressed metabolites were predominantly enriched in amino acid metabolism-related pathways, Mechanistically, activation of the HIF-1α–iNOS–NO signaling axis drove arginine metabolic reprogramming, leading to profound metabolic disturbances that ultimately enhanced the migratory and invasive capacities of ESCC cells. Conclusion This study confirms that ESCC exhibits significant amino acid metabolic dysregulation, with arginine related metabolic pathways being significantly enriched. This disruption in arginine metabolism may be caused by hypoxia, which activates the iNOS-NO signaling axis mediated by HIF-1α, thereby promoting the migratory and invasive capabilities of ESCC. Finally, the study confirmed that NO can serve as a potential non-invasive biomarker for distinguishing ESCC.

Kaiyuan Yao, Shunshun Zhang, Siya Tang et al. · 0 citations