Xiaoli Lei , Feifei Wang , Xinying Zhang , Jiaxi Huang , Yanqin Huang
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Abstract
Background
Thyroid cancer (TC) is the most prevalent endocrine malignancy, with a rising incidence necessitating safer treatment strategies to reduce overtreatment and its side effects. Xiaoyao Powder (XYP), a widely used herbal formula, shows promise in treating TC. This study aims to investigate the mechanisms by which XYP may affect TC.
Methods
The components of XYP were identified through database retrieval, and targets related to TC were collected to construct a target network for key screening. GEO dataset samples analyzed immune cells and identified significantly differentially expressed core genes (SDECGs). Based on SDECG expression and clustering, samples were classified for comparison. WGCNA was employed to identify gene modules linked to clinical characteristics. ML models screened characteristic genes and constructed a nomogram validated using another GEO dataset. MR methods explored causal relationships between genes and TC.
Results
The top ten active components of XYP were identified, along with 27 SDECGs that exhibited significant differences in immune cell infiltration between TC patients and normal controls. The nomogram effectively predicted TC risk, validated through ROC curves. Key characteristic genes included SMIM1, PPP1R16A, KIAA1462, DNAJC22, and EFNA5.
Conclusion
XYP may treat TC by regulating SMIM1, PPP1R16A, KIAA1462, DNAJC22, EFNA5, and associated immune pathways; this provides theoretical support for its potential mechanisms.
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.
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