ArticleTranslational cancer research2026
Cysteine suppresses the progression of oral squamous cell carcinoma via regulating
Article in Translational cancer research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Oral cancer is a common malignant tumor of the head and neck, with squamous cell carcinoma being the most common, accounting for over 90% of all cases. In recent years, the incidence rate of oral cancer has increased year by year. Amino acids are the fundamental components of protein synthesis and participate in multiple physiological processes such as cell growth and differentiation. Tumor cells often adapt to harsh microenvironments by altering their amino acid metabolism pathways, promoting tumor growth, metastasis, and immune escape. Therefore, amino acid metabolism plays a crucial role in tumor development, but the potential link between plasma amino acids and the risk of oral squamous cell carcinoma (OSCC) has not been fully explored. Therefore, this study aims to explore the role and mechanism of amino acid metabolism in the progression of oral cancer and explore the clinical application value of targeted amino acid metabolism in the treatment of oral cancer. Methods: In this study, we employed Mendelian randomization (MR) study to assess the association between plasma amino acids and OSCC, and verified the effect by Results: The results revealed a negative correlation between cysteine levels and OSCC. In oral cancer cells, cysteine was shown to inhibit tumor cell proliferation, migration, and invasion. Additionally, in a subcutaneous tumor-bearing nude mouse model, cysteine supplementation effectively suppressed tumor growth. Transcriptome sequencing further indicated that cysteine influences oral cancer progression by regulating the expression of Conclusions: These findings suggest that increasing cysteine intake could potentially improve disease prognosis and may serve as a preventative or therapeutic approach for OSCC.
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