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Identification of CAV1 and CDH5 as potential diagnostic and prognostic biomarkers in lung adenocarcinoma

  • Authors:
    • Lin Zhang
    • Yunpeng Wang
    • Yuan Liu
    • Yantao Li
    • Lei Wang
    • Can Wang
  • View Affiliations / Copyright

    Affiliations: Department of Intensive Care Medicine, Hebei Provincial Hospital of Traditional Chinese Medicine, Shijiazhuang, Hebei 050011, P.R. China, Department of Internal Medicine III, Xingtai Traditional Chinese Medicine Hospital, Xingtai, Hebei 054001, P.R. China
    Copyright: © Zhang et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Article Number: 241
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    Published online on: October 9, 2025
       https://doi.org/10.3892/etm.2025.12991
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Abstract

Lung adenocarcinoma (LUAD) is the most prevalent and lethal subtype of lung cancer worldwide and despite advances in diagnostic and therapeutic strategies, its prognosis remains poor. The present study aimed to identify key genes in LUAD through bioinformatics approaches. Transcriptomic data from the Gene Expression Omnibus and The Cancer Genome Atlas databases were analyzed using differential expression analysis, weighted gene co‑expression network analysis, protein‑protein interaction network construction and machine learning algorithms, and were validated using reverse transcription‑quantitative PCR. Gene set enrichment analysis (GSEA) was performed to explore potential mechanisms associated with the involvement of key genes in LUAD, and single‑cell transcriptomic data, collected from the Tumor Immune Single‑cell Hub database, were used to validate cell‑specific gene expression patterns. The results demonstrated that caveolin‑1 (CAV1) and cadherin 5 (CDH5) are potential key genes in LUAD, both of which were significantly downregulated in tumor tissues compared with normal lung tissues. GSEA suggested that these genes are involved in the MAPK, Wnt and TGF‑β signaling pathways, which are implicated in tumor progression. Furthermore, single‑cell analysis revealed that CAV1 and CDH5 are predominantly expressed in endothelial cells, indicating a possible role in angiogenesis and tumor microenvironment regulation. In conclusion, CAV1 and CDH5 were systematically identified as potential tumor suppressor genes in LUAD, exhibiting robust diagnostic value confirmed by ROC analyses (GSE31210: CAV1 AUC=0.979; CDH5 AUC=0.969; GSE68465: 0.963 and 0.999; TCGA: 0.994 and 0.984). Therefore, CAV1 and CDH5 may serve as promising molecular targets for future therapeutic interventions, warranting further functional and clinical investigations.
View Figures

Figure 1

Expression and prognostic analysis of
key genes. Expression of CAV1 and CDH5 in the (A) GSE31210, (B)
GSE68465 and (C) TCGA datasets. (D) Paired expression analysis of
CAV1 and CDH5 in TCGA samples. (E) RT-qPCR validation in tissues
from patients with LUAD (n=50). (F) Kaplan-Meier survival curves
for CAV1 and CDH5, comparing patients with high expression and low
expression (grouped according to the median expression level).
P-values were calculated using the log-rank test. (G) Diagnostic
nomogram based on CAV1 and CDH5. (H) Calibration curve evaluating
nomogram accuracy. (I) Receiver operating characteristic curve
analysis in the GSE31210, GSE68465 and TCGA datasets.
***P<0.001 and ****P<0.0001. CAV1,
caveolin-1; CDH5, cadherin 5; TCGA, The Cancer Genome Atlas;
RT-qPCR, reverse transcription-quantitative PCR; LUAD, lung
adenocarcinoma; AUC, area under the curve; TRP, true positive rate;
FRP, false positive rate.

Figure 2

Integrated analysis of DEGs and key
WGCNA modules. (A) Volcano plot of DEGs from the GSE31210 dataset
(x-axis: log2 fold change; y-axis: -log10 adjusted
P-value). (B) Gene clustering dendrogram. ‘Dynamic Tree Cut’
indicates modules initially defined by hierarchical clustering, and
‘Merge Dynamic’ represents merging of highly similar modules. (C)
Heatmap of module-trait correlations. (D) Scatter plot of gene
significance vs. module membership in the brown module. (E) Venn
diagram of overlapping genes between DEGs and the key brown module.
(F) Gene Ontology enrichment analysis of overlapping genes (x-axis:
gene counts; y-axis: enrichment score with adjusted P-values). (G)
Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis
of overlapping genes (x-axis: gene counts; y-axis: enrichment score
with adjusted P-values). Gene counts and the corresponding adjusted
P-value levels are shown for each enriched term or pathway.
**P<0.01 and ***P<0.001. DEG,
differentially expressed gene; WGCNA, weighted gene co-expression
network analysis; LUAD, lung adenocarcinoma; MF, molecular
function; CC, cellular component; BP, biological process; sig,
significant.

Figure 3

Screening of lung adenocarcinoma key
genes based on PPI network and machine learning. (A) PPI network of
overlapping genes. PPI subnetworks ranked by (B) Degree and (C)
Betweenness. (D) Venn diagram of overlapping hub genes from both
algorithms. Top-ranked genes from the (E) RF and (F) SVM-RFE
algorithms. (G) Venn diagram identifying shared genes from the RF
and SVM-RFE algorithms. GSEA results for (H) CAV1 and (I) CDH5.
Feature importance and GSEA significance were determined based on
model-specific thresholds. PPI, protein-protein interaction; RF,
Random Forest; SVM-RFE, Support Vector Machine-Recursive Feature
Elimination; GSEA, gene set enrichment analysis; CAV1, caveolin-1;
CDH5, cadherin 5; ES, enrichment score; NP, normalized P-value; NS,
normalized score.

Figure 4

Single-cell expression features of
CAV1 and CDH5 in lung adenocarcinoma. (A) Heatmaps of gene
expression across immune cell types for CAV1 (left) and CDH5
(right). (B) t-distributed stochastic neighbor embedding
visualization of spatial gene expression patterns. (C) Violin plots
of expression heterogeneity across immune subpopulations. Data were
retrieved from the Tumor Immune Single Cell Hub database. Cell type
annotations were based on original dataset classifications. TPM,
transcripts per million. Cell type abbreviations: Tconv,
conventional CD4+ T cells; Treg, regulatory T cells; T
Tex, exhausted CD8+ T cells; DC, dendritic cells;
Mono/Macro, monocytes/macrophages; NK, natural killer cells. CAV1,
caveolin-1; CDH5, cadherin 5.
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Copy and paste a formatted citation
Spandidos Publications style
Zhang L, Wang Y, Liu Y, Li Y, Wang L and Wang C: Identification of CAV1 and CDH5 as potential diagnostic and prognostic biomarkers in lung adenocarcinoma. Exp Ther Med 30: 241, 2025.
APA
Zhang, L., Wang, Y., Liu, Y., Li, Y., Wang, L., & Wang, C. (2025). Identification of CAV1 and CDH5 as potential diagnostic and prognostic biomarkers in lung adenocarcinoma. Experimental and Therapeutic Medicine, 30, 241. https://doi.org/10.3892/etm.2025.12991
MLA
Zhang, L., Wang, Y., Liu, Y., Li, Y., Wang, L., Wang, C."Identification of CAV1 and CDH5 as potential diagnostic and prognostic biomarkers in lung adenocarcinoma". Experimental and Therapeutic Medicine 30.6 (2025): 241.
Chicago
Zhang, L., Wang, Y., Liu, Y., Li, Y., Wang, L., Wang, C."Identification of CAV1 and CDH5 as potential diagnostic and prognostic biomarkers in lung adenocarcinoma". Experimental and Therapeutic Medicine 30, no. 6 (2025): 241. https://doi.org/10.3892/etm.2025.12991
Copy and paste a formatted citation
x
Spandidos Publications style
Zhang L, Wang Y, Liu Y, Li Y, Wang L and Wang C: Identification of CAV1 and CDH5 as potential diagnostic and prognostic biomarkers in lung adenocarcinoma. Exp Ther Med 30: 241, 2025.
APA
Zhang, L., Wang, Y., Liu, Y., Li, Y., Wang, L., & Wang, C. (2025). Identification of CAV1 and CDH5 as potential diagnostic and prognostic biomarkers in lung adenocarcinoma. Experimental and Therapeutic Medicine, 30, 241. https://doi.org/10.3892/etm.2025.12991
MLA
Zhang, L., Wang, Y., Liu, Y., Li, Y., Wang, L., Wang, C."Identification of CAV1 and CDH5 as potential diagnostic and prognostic biomarkers in lung adenocarcinoma". Experimental and Therapeutic Medicine 30.6 (2025): 241.
Chicago
Zhang, L., Wang, Y., Liu, Y., Li, Y., Wang, L., Wang, C."Identification of CAV1 and CDH5 as potential diagnostic and prognostic biomarkers in lung adenocarcinoma". Experimental and Therapeutic Medicine 30, no. 6 (2025): 241. https://doi.org/10.3892/etm.2025.12991
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