Rumei Li , Zhaoxi Li , Wanrong Luo , Xiaotong Zhu , Baoming Luo
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引用次数: 0
Abstract
Accumulation of senescent cells is a recognized feature in hepatocellular carcinoma (HCC), but their specific types and prognostic implications remain under investigation. This study aimed to delineate senescent cell types and their senescent patterns in HCC using publicly available bulk and single-cell mRNA sequencing data. Through gene expression and gene set enrichment analysis, we identified distinct senescent patterns within HCC samples. Notably, unconventional T cells, specifically natural killer T cells and γδT cells, were found to be the predominant senescent cell types. These cells exhibited enriched pathways related to DNA damage, senescence and the negative regulation of lymphocyte activation. Furthermore, we observed upregulation of the mTOR signaling pathway, which correlated positively with the expression of senescence-associated genes. This suggests a potential regulatory role for mTOR in the senescence of HCC. Strikingly, patients with elevated expression of senescence markers, including p16INK4A, p21, and GLB1, demonstrated significantly reduced overall survival rates. Our findings indicate that immunosenescence in unconventional T cells may play a role in HCC progression. The potential therapeutic implications of targeting the mTOR pathway or eliminating senescent unconventional T cells warrant further exploration to improve HCC patient outcomes.
期刊介绍:
Computational Biology and Chemistry publishes original research papers and review articles in all areas of computational life sciences. High quality research contributions with a major computational component in the areas of nucleic acid and protein sequence research, molecular evolution, molecular genetics (functional genomics and proteomics), theory and practice of either biology-specific or chemical-biology-specific modeling, and structural biology of nucleic acids and proteins are particularly welcome. Exceptionally high quality research work in bioinformatics, systems biology, ecology, computational pharmacology, metabolism, biomedical engineering, epidemiology, and statistical genetics will also be considered.
Given their inherent uncertainty, protein modeling and molecular docking studies should be thoroughly validated. In the absence of experimental results for validation, the use of molecular dynamics simulations along with detailed free energy calculations, for example, should be used as complementary techniques to support the major conclusions. Submissions of premature modeling exercises without additional biological insights will not be considered.
Review articles will generally be commissioned by the editors and should not be submitted to the journal without explicit invitation. However prospective authors are welcome to send a brief (one to three pages) synopsis, which will be evaluated by the editors.