{"title":"Resveratrol Modulates Lung Cancer-Associated Hub Genes Identified by Integrated Bioinformatics, Single-Cell Analysis, Molecular Docking, and Experimental Validation.","authors":"Jinghua Yang, Hanxiu Wei, Jie Li, Jun Chen","doi":"10.1007/s12013-026-02142-9","DOIUrl":null,"url":null,"abstract":"<p><p>Lung cancer remains a major cause of cancer-related mortality, and reliable molecular targets with therapeutic relevance are still needed. This study aimed to identify key genes associated with lung cancer progression and explore the potential regulatory effect of resveratrol. The GSE43458 dataset, including 80 lung cancer samples and 30 control samples, was used for differential expression analysis and weighted gene co-expression network analysis (WGCNA). Intersecting genes were subjected to protein-protein interaction network construction, Cytoscape-based hub gene screening, functional enrichment analysis, and immune infiltration analysis. Single-cell RNA sequencing data from GSE131907 were further analyzed to characterize cellular heterogeneity and hub gene distribution. Resveratrol was predicted as a candidate compound, followed by molecular docking with hub proteins. Finally, CCK-8, Western blotting, and qRT-PCR assays were performed in BEAS-2B and A549 cells. A total of 1,655 differentially expressed genes were identified, and WGCNA identified the 252-gene turquoise module as the module most strongly associated with the lung cancer phenotype (r = - 0.86, P = 6.0 × 10⁻³⁵). Intersection analysis yielded 250 candidate genes, representing 15.1% of all differentially expressed genes. Five hub genes, CASP3, DDX54, TP53BP1, CDKN2A, and ABT1, were identified and showed significantly increased expression in lung cancer tissues (P < 0.05). Functional enrichment analysis linked the candidate genes to apoptosis, cell-cycle regulation, DNA damage repair, immune responses, and cancer-related pathways, while immune infiltration and single-cell analyses revealed marked remodeling of immune and stromal components. Molecular docking predicted potential interactions between resveratrol and the five hub proteins, with the most favorable docking scores observed for TP53BP1 (- 7.0 kcal/mol) and DDX54 (- 6.9 kcal/mol). In vitro validation further showed that resveratrol treatment significantly reduced the mRNA and protein expression of the identified hub genes in A549 cells (P < 0.05). This study identified five lung cancer-associated hub genes and provided preliminary evidence that resveratrol may modulate their expression. These findings provide a multi-level molecular framework for further investigation of resveratrol-responsive networks in lung cancer.</p>","PeriodicalId":510,"journal":{"name":"Cell Biochemistry and Biophysics","volume":" ","pages":"4495-4522"},"PeriodicalIF":3.0000,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cell Biochemistry and Biophysics","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1007/s12013-026-02142-9","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/8/14 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Lung cancer remains a major cause of cancer-related mortality, and reliable molecular targets with therapeutic relevance are still needed. This study aimed to identify key genes associated with lung cancer progression and explore the potential regulatory effect of resveratrol. The GSE43458 dataset, including 80 lung cancer samples and 30 control samples, was used for differential expression analysis and weighted gene co-expression network analysis (WGCNA). Intersecting genes were subjected to protein-protein interaction network construction, Cytoscape-based hub gene screening, functional enrichment analysis, and immune infiltration analysis. Single-cell RNA sequencing data from GSE131907 were further analyzed to characterize cellular heterogeneity and hub gene distribution. Resveratrol was predicted as a candidate compound, followed by molecular docking with hub proteins. Finally, CCK-8, Western blotting, and qRT-PCR assays were performed in BEAS-2B and A549 cells. A total of 1,655 differentially expressed genes were identified, and WGCNA identified the 252-gene turquoise module as the module most strongly associated with the lung cancer phenotype (r = - 0.86, P = 6.0 × 10⁻³⁵). Intersection analysis yielded 250 candidate genes, representing 15.1% of all differentially expressed genes. Five hub genes, CASP3, DDX54, TP53BP1, CDKN2A, and ABT1, were identified and showed significantly increased expression in lung cancer tissues (P < 0.05). Functional enrichment analysis linked the candidate genes to apoptosis, cell-cycle regulation, DNA damage repair, immune responses, and cancer-related pathways, while immune infiltration and single-cell analyses revealed marked remodeling of immune and stromal components. Molecular docking predicted potential interactions between resveratrol and the five hub proteins, with the most favorable docking scores observed for TP53BP1 (- 7.0 kcal/mol) and DDX54 (- 6.9 kcal/mol). In vitro validation further showed that resveratrol treatment significantly reduced the mRNA and protein expression of the identified hub genes in A549 cells (P < 0.05). This study identified five lung cancer-associated hub genes and provided preliminary evidence that resveratrol may modulate their expression. These findings provide a multi-level molecular framework for further investigation of resveratrol-responsive networks in lung cancer.
期刊介绍:
Cell Biochemistry and Biophysics (CBB) aims to publish papers on the nature of the biochemical and biophysical mechanisms underlying the structure, control and function of cellular systems
The reports should be within the framework of modern biochemistry and chemistry, biophysics and cell physiology, physics and engineering, molecular and structural biology. The relationship between molecular structure and function under investigation is emphasized.
Examples of subject areas that CBB publishes are:
· biochemical and biophysical aspects of cell structure and function;
· interactions of cells and their molecular/macromolecular constituents;
· innovative developments in genetic and biomolecular engineering;
· computer-based analysis of tissues, cells, cell networks, organelles, and molecular/macromolecular assemblies;
· photometric, spectroscopic, microscopic, mechanical, and electrical methodologies/techniques in analytical cytology, cytometry and innovative instrument design
For articles that focus on computational aspects, authors should be clear about which docking and molecular dynamics algorithms or software packages are being used as well as details on the system parameterization, simulations conditions etc. In addition, docking calculations (virtual screening, QSAR, etc.) should be validated either by experimental studies or one or more reliable theoretical cross-validation methods.