Evidence map›Paper›PMID 42599654›Full record

ArticleCell biochemistry and biophysics2026

Resveratrol Modulates Lung Cancer-Associated Hub Genes Identified by Integrated Bioinformatics, Single-Cell Analysis, Molecular Docking, and Experimental Validation.

Jinghua Yang, Hanxiu Wei, Jie Li, Jun Chen

Abstract read
PubMed Publisher
In one paragraph

Article in Cell biochemistry and biophysics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Jinghua YangDepartment of Pulmonary Diseases, Luzhou Hospital of Traditional Chinese Medicine, Luzhou, 646000, Sichuan Province, China.
Hanxiu WeiDepartment of Cardiology, The Affiliated Hospital of Traditional Chinese Medicine, Southwest Medical University, Luzhou, 646000, Sichuan Province, China.
Jie LiDepartment of Pulmonary Diseases, Luzhou Hospital of Traditional Chinese Medicine, Luzhou, 646000, Sichuan Province, China.
Jun ChenDepartment of Oncology, Luzhou Hospital of Traditional Chinese Medicine, Luzhou, 646000, Sichuan Province, China. RobertMartinez7362@outlook.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Gene Expression Regulation, NeoplasticLung NeoplasmsMolecular Docking SimulationResveratrolA549 CellsApoptosisCell Line, TumorComputational BiologyGene Regulatory NetworksHumansProtein Interaction MapsSingle-Cell AnalysisResveratrolHub genesLung cancerMolecular dockingResveratrolSingle-cell RNA sequencing

Identifiers

PMID42599654

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.