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. 2025 Mar 25;14(4):331.
doi: 10.3390/biology14040331.

Shared Genomic Features Between Lung Adenocarcinoma and Type 2 Diabetes: A Bioinformatics Study

Nuerbiye Nueraihemaiti  1   2   3   4 , Dilihuma Dilimulati  1   2   3   4 , Alhar Baishan  1   2   3   4 , Sendaer Hailati  1   2   3   4 , Nulibiya Maihemuti  1   2   3   4 , Alifeiye Aikebaier  1   2   3   4 , Yipaerguli Paerhati  1   2   3   4 , Wenting Zhou  1   2   3   4
Affiliations

Shared Genomic Features Between Lung Adenocarcinoma and Type 2 Diabetes: A Bioinformatics Study

Nuerbiye Nueraihemaiti et al. Biology (Basel). .

Abstract

Background: Lung adenocarcinoma (LUAD) is a common histopathological variant of non-small cell lung cancer. Individuals with type 2 diabetes (T2DM) face an elevated risk of developing LUAD. We examined the common genomic characteristics between LUAD and T2DM through bioinformatics analysis.

Methods: We acquired the GSE40791, GSE25724, GSE10072, and GSE71416 datasets. Differentially expressed genes (DEGs) were identified through R software, particularly its version 4.1.3 and analyzed via gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Subsequently, we analyzed the relationship between immune cell infiltration and DEGs. we constructed a protein-protein interaction network using STRING and visualized it with Cytoscape. Moreover, gene modules were identified utilizing the MCODE plugin, and hub genes were selected through the CytoHubba plugin. Additionally, we evaluated the predictive significance of hub genes using receiver operating characteristic curves and identified the final central hub genes. Finally, we forecasted the regulatory networks of miRNA and transcription factors for the central hub genes.

Results: A total of 748 DEGs were identified. Analysis of immune infiltration showed a notable accumulation of effector-memory CD8 T cells, T follicular helper cells, type 1 T helper cells, activated B cells, natural killer cells, macrophages, and neutrophils in both LUAD and T2DM. Moreover, these DEGs were predominantly enriched in immune-related pathways, including the positive regulation of I-κB kinase/NF-κB signaling, positive regulation of immunoglobulin production, cellular response to interleukin-7, and cellular response to interleukin-4. The TGF-β signaling pathway was significantly important among them. Additionally, seven hub genes were identified, including ATR, RFC4, MCM2, NUP155, NUP107, NUP85, and NUP37. Among them, ATR, RFC4, and MCM2 were identified as pivotal hub genes. Additionally, hsa-mir147a, hsa-mir16-5p, and hsa-mir-1-3p were associated with LUAD and T2DM. SP1 (specific protein 1) and KDM5A (lysine-specific demethylase 5A) regulated MCM2, ATR, and RFC4.

Conclusions: Our study elucidates the common mechanisms of immune response, TGF-β signaling pathway, and natural killer cells in LUAD and T2DM, and identifies ATR, RFC4, and MCM2 as key potential biomarkers and therapeutic targets for the comorbidity of these two conditions.

Keywords: bioinformatics; genomic features; lung adenocarcinoma (LUAD); type 2 diabetes (T2DM).

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Analysis of DEGs between T2DM and LUAD. (A) Volcano plot showing DEGs of LUAD from GSE40791. (B) Volcano plot showing DEGs of T2DM from GSE25724. (C) Heat map showing DEGs of T2DM from GSE40791. (D) Heat map showing DEGs of LUAD from GSE25724. (E) Venn diagram showing common DEGs between T2DM and LUAD.
Figure 2
Figure 2
Immune infiltration analysis. (A) Correlation between LUAD with immune cells. (B) Correlation between T2DM with immune cells. * represents a p-value < 0.05; ** represents a p-value < 0.01; *** represents a p-value < 0.001; **** represents a p-value < 0.0001.
Figure 3
Figure 3
Enrichment analysis of common DEGs. (A) GO enrichment analysis. Top GO terms in biological process (BF), cellular component (CC), and molecular function (MF) are displayed. (B) KEGG pathway enrichment analysis. Top 9 pathways are presented.
Figure 4
Figure 4
PPI network analysis. (A) PPI network. (B) Significant module 1. (C) Significant module 2. (D) Significant module 3. (E) Venn diagram of MNC, DEGREE, EPC, and MCC.
Figure 5
Figure 5
ROC analysis of hub genes. ROC curve for hub genes from the training set (GSE40791 and GSE25724) and the validation set (GSE10072 and GSE71416) were plotted with the pROC package in R.
Figure 6
Figure 6
Network of central hub genes and miRNAs. miRNA–target gene network was constructed using the NetworkAnalyst dataset. Central hub genes were RFC4, MCM2, and ATR.
Figure 7
Figure 7
Regulatory network of central hub genes and TFs. Hub gene–TF regulatory network was constructed using the NetworkAnalyst. Central hub genes were RFC4, MCM2, and ATR.
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