A Bioinformatics Investigation of Hub Genes Involved in Treg Migration and Its Synergistic Effects, Using Immune Checkpoint Inhibitors for Immunotherapies
Abstract
:1. Introduction
2. Results
2.1. GEO Dataset Selection
2.2. Identification of DEGs
2.3. GO, KEGG and Reactome Pathway Enrichment Analysis
2.4. Hub Gene Identification from the PPI Network
2.5. Synergistic Effects of CCR8 and Immune Checkpoint Inhibitors
2.5.1. Correlation Analysis between CCR8 Expression and Immune Checkpoint Proteins
2.5.2. TMB, MSI Correlation Analysis
2.6. Comprehensive Integration of Multiple Analysis
3. Discussion
4. Materials and Methods
4.1. GEO Dataset Collection
4.2. Identification of DEGs in GEO Datasets
4.3. GO, KEGG and Reactome Pathway Enrichment Analysis
4.4. Hub Gene Identification from the PPI Network
4.5. Synergistic Effects of CCR8 and Immune Checkpoint Inhibitors
4.6. Comprehensive Integration of Multiple Analysis
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Accession No. | Platform | Total Samples | Case (Treg Group) | Control (Non-Treg Group) | Species | Disease/Condition | Pubmed ID |
---|---|---|---|---|---|---|---|
GSE128822 | GPL18573 | 10 | 5 | 5 | Homo sapiens | Lung adenocarcinoma | 32125291, 34552178 |
GSE116347 | GPL18573 | 18 | 12 | 6 | Homo sapiens | Colorectal carcinoma | 30348759 |
GSE120280 | GPL19057 | 12 | 6 | 6 | Mus musculus | Lung cancer | 32878747 |
Pathway ID | Description | p-Value | Count |
---|---|---|---|
R-HSA-5669034 | TNFs bind their physiological receptors | 4.00 × 10−6 | 4 |
R-HSA-5668541 | TNFR2 non-canonical NF-kB pathway | 4.00 × 10−5 | 5 |
R-HSA-449147 | Signaling by Interleukins | 5.80 × 10−5 | 9 |
R-HSA-8877330 | RUNX1 and FOXP3 control the development of regulatory T lymphocytes (Tregs) | 6.27 × 10−4 | 2 |
R-HSA-8984722 | Interleukin-35 Signaling | 9.15 × 10−4 | 2 |
Degree Centrality | Betweenness Centrality | Closeness Centrality | Clustering Coefficient | |
---|---|---|---|---|
IL2RA | 11 | 0.29 | 0.76 | 0.47 |
TRAF1 | 8 | 0.13 | 0.62 | 0.57 |
IL1R2 | 4 | 0.13 | 0.53 | 0.33 |
BATF | 4 | 0.13 | 0.52 | 0.50 |
IL12RB2 | 4 | 0.13 | 0.50 | 0.53 |
CD80 | 9 | 0.12 | 0.64 | 0.69 |
TNFRSF4 | 9 | 0.06 | 0.64 | 0.69 |
TNFRSF18 | 9 | 0.06 | 0.64 | 0.69 |
TRAF3 | 6 | 0.03 | 0.50 | 0.73 |
CCR8 | 7 | 0.03 | 0.57 | 0.81 |
Classification | Gene Symbol | Function |
---|---|---|
Immune Regulation | IL2RA | IL2RA (Interleukin-2 Receptor Alpha) is crucial for the development and function of Treg cells [46]. It plays a role in the high-affinity IL-2 receptor, which is important for Treg cell proliferation and survival [47]. |
TNFRSF4 | TNFRSF4 (Tumor Necrosis Factor Receptor Superfamily, Member 4), also known as OX40, is involved in the activation, survival, and migration of Treg cells. It enhances Treg cell proliferation and function [48]. | |
TNFRSF18 | TNFRSF18 (Tumor Necrosis Factor Receptor Superfamily, Member 18), also known as GITR, is important for Treg cell function and immune regulation. It contributes to Treg cell-mediated suppression and enhances their survival [49]. | |
Cytokine Signaling | CD80 | CD80 (Cluster of Differentiation 80) is involved in costimulatory signaling essential for T cell activation. It provides necessary second signals for T cell activation and survival through interaction with CD28 and CTLA-4 [50]. |
TRAF1 | TRAF1 (TNF Receptor-Associated Factor 1) plays roles in the downstream signaling of TNFRSF members, contributing to immune-response regulation and inflammation [51]. | |
TRAF3 | TRAF3 (TNF Receptor-Associated Factor 3) is involved in various signaling pathways, including those triggered by TNF receptors, contributing to immune-response regulation and apoptosis [52]. | |
IL1R2 | IL1R2 (Interleukin 1 Receptor Type 2) acts as a decoy receptor for IL-1, modulating immune and inflammatory responses by sequestering IL-1 and preventing it from interacting with the IL1 signaling receptor [53]. | |
IL12RB2 | IL12RB2 (Interleukin 12 Receptor Beta 2) is involved in cytokine receptor activity and plays a role in the differentiation of Th1 cells, impacting immune cell signaling and response to infections [54]. | |
Chemokine Signaling and Treg Migration | CCR8 | CCR8 (C-C Chemokine Receptor Type 8) has a significant role in chemokine signaling, crucial for the migration and positioning of Treg cells within the tumor microenvironment [55]. Its high clustering coefficient (0.81) highlights its role in chemokine-mediated processes that guide Treg cells to their functional sites (Table 3). |
Transcription Factors | BATF | BATF (Basic Leucine Zipper ATF-Like Transcription Factor) is involved in T cell differentiation [56]. It functions as a transcription factor that regulates the expression of genes essential for the development and function of various T cell subsets, including Tregs. |
Correlation with CCR8 Expression | Treg Infiltration Correlation | TMB | MSI | Clinical Status of ICIs | Final Score | |||
---|---|---|---|---|---|---|---|---|
PDCD1 | CD274 | CTLA4 | ||||||
BRCA | 3 | 3 | 3 | 3 | 9 | 6 | 3 | 30 |
HNSC | 2 | 2 | 2 | 3 | 6 | 6 | 3 | 24 |
COAD | 2 | 2 | 2 | 2 | 6 | 6 | 3 | 23 |
STAD | 2 | 2 | 2 | 3 | 6 | 5 | 3 | 23 |
THCA | 2 | 0 | 2 | 3 | 4 | 3 | 0 | 14 |
READ | 0 | 0 | 1 | 1 | 6 | 5 | 0 | 13 |
Criteria | Score | Significance Level | Description |
---|---|---|---|
Correlation (p-Value) | |||
p-value < 1 × 10−50 | 3 | Highly significant correlation | Calculated the correlation coefficients and p-values for the relationships between CCR8 and PD-1, PD-L1, and CTLA-4 |
1 × 10−50 ≤ p-value < 1 × 10−30 | 2 | Very significant correlation | |
1 × 10−30 ≤ p-value < 1 × 10−10 | 1 | Significant correlation | |
p-value ≥ 1 × 10−10 | 0 | Not significant | |
TMB & MSI Correlation | |||
Correlation > 0.3 | 3 | Strong positive correlation | Correlations between TMB, MSI, and hub gene to measure genetic instability and mutational burden within the cancer types |
0.2 < Correlation ≤ 0.3 | 2 | Moderate positive correlation | |
0.1 < Correlation ≤ 0.2 | 1 | Weak positive correlation | |
Correlation ≤ 0.1 | 0 | No correlation |
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Kim, N.; Na, S.; Pyo, J.; Jang, J.; Lee, S.-M.; Kim, K. A Bioinformatics Investigation of Hub Genes Involved in Treg Migration and Its Synergistic Effects, Using Immune Checkpoint Inhibitors for Immunotherapies. Int. J. Mol. Sci. 2024, 25, 9341. https://doi.org/10.3390/ijms25179341
Kim N, Na S, Pyo J, Jang J, Lee S-M, Kim K. A Bioinformatics Investigation of Hub Genes Involved in Treg Migration and Its Synergistic Effects, Using Immune Checkpoint Inhibitors for Immunotherapies. International Journal of Molecular Sciences. 2024; 25(17):9341. https://doi.org/10.3390/ijms25179341
Chicago/Turabian StyleKim, Nari, Seoungwon Na, Junhee Pyo, Jisung Jang, Soo-Min Lee, and Kyungwon Kim. 2024. "A Bioinformatics Investigation of Hub Genes Involved in Treg Migration and Its Synergistic Effects, Using Immune Checkpoint Inhibitors for Immunotherapies" International Journal of Molecular Sciences 25, no. 17: 9341. https://doi.org/10.3390/ijms25179341