IRF5 as a potential immunological biomarker in lung adenocarcinoma

Introduction

Lung cancer is one of the most common causes of cancer-related death, ranking first among cancer-related deaths in men and second among cancer-related deaths in women (1). In China, the incidence rate and mortality rate of non-small cell lung cancer (NSCLC) rank first. NSCLC accounts for about 85–90% of all lung cancer cases, and about 75% of patients are in the late stage (stages III–IV) at the time of diagnosis (2).

The main traditional approaches for the clinical treatment of advanced NSCLC are surgery, radiation therapy, and chemotherapy. In recent years, the emergence of immunotherapy has broadened the scope of treatment options for advanced NSCLC patients. Combining immune checkpoint inhibitors (ICIs) with traditional therapy or other immunotherapies can maximize the clinical benefits for patients; however, currently, only a small number of patients have been found to respond well to ICIs treatments, and overall survival (OS) remains very low. Indeed, the 5-year survival rate of NSCLC patients after radical surgery is only about 50% (3).

In relation to recurrence or distant metastasis (3,4), some prognosis factors are known and have been published, but there is insufficient evidence to incorporate them into routine clinical care. Perhaps cite some to highlight the need of new biomarkers and aid in the selection of drug treatments. The exact mechanism of NSCLC progression requires further exploration, and effective biomarkers need to be identified. The tumor immunosuppressive microenvironment is considered an important factor that hinders the effects of tumor immunotherapy, and affects recurrence and metastasis (5,6). Therefore, the immune regulatory mechanism of NSCLC needs to be investigated.

Transcription factor interferon regulatory factor 5 (IRF5) is a key mediator of innate immunity and adaptive immunity downstream of pathogen recognition receptors. In the past few decades, IRF5 has been frequently reported to be abnormally expressed in various types of tumors (7). Additionally, the loss of IRF5 expression has been found to be associated with tumor initiation in breast cancer, gastric cancer, colorectal cancer, pancreatic cancer, and other tumors, and it is directly related to accelerated growth, an increased metastatic burden, and worse overall prognosis (7). IRF5 has also been reported to regulate the function of immune cells in the tumor microenvironment, mediate immune escape, and participate in pathological processes, such as metastasis (8).

In NSCLC, research has shown that the aberrant expression of IRF5 in the peripheral blood of patients has potential prognostic implications (9), and a study have indicated that IRF5 expression is inhibited in the epithelial to mesenchymal transition of lung cancer cells (10). However, currently, little is known about the expression and prognostic significance of IRF5 in lung cancer tumor tissues. The precise mechanism by which IRF5 contributes to the pathological processes, including recurrence and metastasis, of NSCLC, has yet to be elucidated.

Presently, lung adenocarcinoma (LUAD) is the most common subtype of NSCLC. This study sought to investigate the expression of IRF5 in LUAD and its effect on patient prognosis, and examine the biological function of IRF5. Additionally, the study aimed to examine the association between IRF5 expression and immune cell infiltration, as well as its correlation with key immune checkpoint genes relevant to NSCLC. Finally, the study aimed to examine the signaling pathways in which IRF5 is involved in LUAD. Our findings may extend understandings of the functions of IRF5 in LUAD, and its potential as a marker and novel therapeutic target. We present this article in accordance with the REMARK reporting checklist (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2024-2354/rc).

Methods

Public data collection and preprocessing

A total of 600 LUAD samples were downloaded from The Cancer Genome Atlas (TCGA) database (https://portal.gdc.cancer.gov/) on April 18, 2024. The data were extracted and normalized using R software (version 4.3.1). The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013).

Analysis of public TCGA data

For the publicly available TCGA data, differences in IRF5 expression between the tumor and cancer tissues were examined and plotted using both the DESeq2 (version 1.38.3) and edge R (version 3.42.2) packages. The Limma (version 3.56.2), gpubr (version 0.6.0), and ComplexHeatmap (version 2.16.0) packages in R were used to analyze and visualize the relationship between the characteristics of LUAD and IRF5 expression. A Spearman correlation analyses was conducted to examine the correlation between IRF5 and immune checkpoint genes, respectively, and the relevant graphs were drawn using ggplo2t (version 3.4.2). Kaplan-Meier survival curves were generated using the survminer package (version 0.4.9). The survival package (version 3.5-5) in R was used to assess the ability of IRF5 to predict patient survival using 513 samples with complete clinical data and detailed follow-up information. Log-rank tests were used to assess differences in survival between the low and high IRF5 expression groups.

GSEA

The LUAD samples from TCGA dataset were divided into groups based on the high and low expression of IRF5. The c2.cp.kegg.v7.4.symbols.gmt file and the c5.go.v7.4.symbols.gmt file were downloaded from the Molecular Signatures Database (https://www.gsea-msigdb.org/gsea/msigdb/). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to examine the biological processes (BPs) and signaling pathways related to IRF5.

Correlation analysis of IRF5 expression and immune infiltration

The LUAD samples from TCGA dataset were divided into two groups based on the expression level of IRF5. CIBERSORT (https://cibersort.stanford.edu) was used to estimate the proportions of the 22 immune cell types to quantify the abundance of tumor immune‑infiltrating cells in TCGA-LUAD sample dataset. The following R packages were used to run CIBERSORT: e1071 (version 1.7-13), parallelly (version 1.35.0), and preprocessCore (version 1.62.1). Immune cell infiltration in the low and high IRF5 expression groups was compared and plotted using the ggpubr (version 0.6.0) package in R. A P value <0.05 was considered statistically significant.

LUAD TMA analysis

Commercially available tissue microarray (TMA) slides (LUC1401) with 69 pairs of LUAD samples and corresponding adjacent tissues were obtained from Guilin Fanpu Biotechnology Co. Ltd., Guilin, China. The TMA slides were commercially preconstructed by dot-arrayed tissues in parallel from 69 LUAD patients for whom clinical data and detailed follow-up information, including age, gender, American Joint Committee on Cancer (AJCC) tumor-node-metastasis (TNM) stage, AJCC pathologic stage (II/III/IV), and vital status (dead/alive), were available.

Immunofluorescence staining

For the immunofluorescence staining of the TMA sections, the following primary antibodies were used: IRF5 (1:1,000, Abcam, Cambridge, UK), cluster of differentiation (CD)86 (1:200, Abcam), and CD206 (1:400, Cell Signaling Technology, Danvers, MA, USA). Next, the sections were washed three times with phosphate-buffered saline at room temperature, and then incubated with the appropriate secondary antibodies conjugated to Alexa Fluor (Thermo Fisher Scientific, MA, USA) for 1.5 hours. After washing, the sections were mounted with 4'6-diamidino-2-phenylindole (DAPI) and observed with an Olympus Fluorview-3000 confocal microscope (Olympus Optical, Ltd., Japan). The pathologists used the positive pixel count method provided by Image-Pro Plus (version 6.0) (Media Cybernetics, Bethesda, MD, USA) to quantify and assess the high-resolution digital images. The expression of IRF5 was analyzed based on the integrated optical density. The expression of CD86 and CD206 was analyzed based on the density of the positively expressed cells.

TMA data analysis

The differential gene analysis of IRF5, CD86, and CD206 between the tumor group (n=69) and non-tumor (n=69) group was performed by SPSS 20.0 (IBM, Armonk, NY, USA) using the Mann-Whitney U test. A Spearman correlation analysis was performed to detect the correlation between the expression levels of IRF5, CD86, and CD206, and the clinical variables. Kaplan-Meier survival curves were generated using Graphpad Prism 8 (Graphpad Software, CA, USA). A P value <0.05 was considered significantly significant.

Statistical analysis

All statistical analyses and the plotting of publica TCGA data were performed and visualized with R (version 4.3.1). The statistical analyses of the TMA samples were performed using SPSS 20.0 and Graphpad Prism 8. A P value <0.05 was considered statistically significant.

Results

IRF5 expression in LUAD patients

This study examined the expression IRF5 in LUAD tissues sourced from TCGA dataset, and found that the expression levels of IRF5 were lower in the LUAD tissues than the normal tissues (Figure 1A). To confirm this discrepancy in IRF5 expression, a TMA analysis was then conducted of tumor tissues obtained from 69 LUAD patients. Immunofluorescence detection revealed that IRF5 was expressed on the cytoplasm (Figure 1B), and the results also showed that the expression levels of IRF5 were lower in the LUAD tissues than the corresponding adjacent tissues (Table 1).

Figure 1 IRF5 expression levels in LUAD and normal tissues. (A) Comparison of IRF5 expression between normal and tumor tissues from TCGA dataset. (B) IRF5 immunofluorescence detection in normal and tumor tissues. Scale bar: 50 µm. *, P<0.05. DAPI, 4',6-diamidino-2-phenylindole; IRF5, interferon regulatory factor 5; LUAD, lung adenocarcinoma; TCGA, The Cancer Genome Atlas.

Relationship between characteristics of LUAD and IRF5 expression

We also explored the relationship between IRF5 expression and the clinicopathological characteristics of LUAD patients using TCGA dataset, but no significant correlation was found between IRF5 expression and the clinicopathological features (Figure 2). However, following a correlation analysis of 69 tissue chip samples, a significant correlation between IRF5 expression and lymph node metastasis was found (P=0.009) (Table 2).

Figure 2 IRF5 expression in different clinical feature subgroups. IRF5, interferon regulatory factor 5.

Prognosis analysis of IRF5 expression in LUAD

We preliminarily explored the association between IRF5 expression and the prognosis of LUAD patients. The Kaplan-Meier curve analysis showed that in the LUAD-TCGA patients, IRF5 expression was positively correlated with OS (P=0.009, Figure 3A), while the tissue chip analysis results of 69 cases also showed that IRF5 expression was positively correlated with OS (P=0.009, Figure 3B).

Figure 3 Kaplan-Meier prognostic analysis of the correlation between IRF5 expression and OS. (A) The correlation between the gene expression level of IRF5 and survival prognosis using the LUAD-TCGA dataset. (B) The correlation between the immunofluorescence expression level of IRF5 and survival prognosis using the data of 69 patients with LUAD. IRF5, interferon regulatory factor 5; OS, overall survival; LUAD, lung adenocarcinoma; TCGA, The Cancer Genome Atlas.

Analysis of immune characteristics and IRF5 in LUAD

There were the proportions of the 22 immune cell types (Figure 4A). The immune infiltration analysis revealed significant differences in the presence of nine distinct types of immune cells between the groups with high and low IRF5 expression levels (Figure 4B). These immune cell types included naive B cells, memory B cells, plasma cells, regulatory T cells (Tregs), gamma delta T cells, monocytes, M0 macrophages, M2 macrophages, and resting dendritic cells. Specifically, higher IRF5 expression levels were associated with increased infiltration in memory B cells, Tregs, monocytes, M0 macrophages, M2 macrophages, and resting dendritic cells, while lower levels of IRF5 expression were correlated with decreased infiltration in B cells (Figure 4B). Notably, the major eight immune checkpoint genes were all upregulated in LUAD patients with high IRF5 expression, including CD274, CTLA4, HAVCR2, LAG3, LAIR1, PDCD1, PDCD1LG2, and TIGIT (Figure 4C).

Figure 4 IRF5 expression and immune cells. (A) Proportion of each type of immune cell. (B) Correlation analysis between IRF5 expression level and the immune infiltration cells. (C) Correlation analysis of IRF5 expression and immune checkpoint gene expression. *, P<0.05. **, P<0.01. ***, P<0.001. IRF5, interferon regulatory factor 5; NK, natural killer.

BPs and signaling pathways involved in LUAD by IRF5

IRF5 was found to be mainly associated with the following GO terms: receptor ligand activity; external side of plasma membrane; and collagen-containing extracellular matrix (Figure 5A). IRF5 was found to be mainly associated with the following signaling pathways: cytokine-cytokine receptor interaction; cytoskeleton in muscle cells; and neutrophil extracellular trap formation (Figure 5B). The gene set enrichment analysis (GSEA) results showed that the following BPs were active in the IRF5 high expression group: leukocyte proliferation, regulation of lymphocyte activation, T cell activation, plasma membrane signaling receptor complex, and T cell receptor complex (Figure 5C). The GSEA results also showed that the following signaling pathways were active in the IRF5 high expression group: allograft rejection, cytokine-cytokine receptor interaction, hematopoietic cell lineage, intestinal immune network for immunoglobulin A (IGA) production, and leishmania infection (Figure 5D).

Figure 5 IRF5-related cell immune response pathways. (A) GO analysis of the differential genes from the IRF5 high expression group versus the IRF5 low expression group. (B) BPs, CCs, and MFs of the differential genes from the IRF5 high expression group versus the IRF5 low expression group. (C) GSEA of the GO pathways of the differential genes in the IRF5 high and low expression groups. (D) GSEA of the KEGG pathways of the differential genes in the IRF5 high and low expression groups. ECM, extracellular matrix; IL, interleukin; BP, biological process; CC, cellular component; MF, molecular function; IRF5, interferon regulatory factor 5; GO, Gene Ontology; GESA, gene set enrichment analysis; KEGG, Kyoto Encyclopedia of Genes and Genomes.

The relationship between IRF5 and CD86/CD206

Immunofluorescence detection revealed that CD86 and CD206 were expressed on the cell membrane (Figure 6). A strong negative correlation was observed between IRF5 and CD86/CD206 (Spearman correlation coefficient, r=−0.408) (Table 3).

Figure 6 Immunofluorescence expression of CD86 cells (orange) and CD206 cells (green) in normal and tumor tissues. Scale bar: 50 µm. DAPI, 4',6-diamidino-2-phenylindole.

Discussion

As the most prevalent subtype of NSCLC, LUAD is increasingly impacting patients. It is characterized by recurrence, metastasis, and drug resistance, all of which lead to a poor prognosis and high mortality rates (11,12). Given the lack of reliable biomarkers for predicting prognosis, in-depth studies and research on prognosis-related genes in molecular biology urgently need to be conducted. Our research findings based on TCGA data showed that IRF5 was lowly expressed in LUAD tissues compared to para-cancerous tissues. Similarly, our TMA analysis of 69 patients showed that the expression levels of IRF5 were lower in the LUAD than the corresponding adjacent tissues.

The correlation analysis between IRF5 and clinical data from TCGA database did not reveal any significant relationships between IRF5 and the clinicopathological characteristics in LUAD; however, the findings from the tissue chip samples revealed a close association between IRF5 and lymph node metastasis. This inconsistency in the results may be attributed to the composition of the tissue chip samples, which primarily comprised stage II, III, and IV patients, while TCGA dataset had a higher proportion of stage I patients. Lymph node metastasis often occurs in stage III and IV patients. There were large differences between the different stages in TCGA dataset, which might have led to the absence of positive results from the analysis.

Our subsequent studies, including our TCGA and tissue chip data analyses, revealed that the expression of IRF5 was positively associated with the survival time of LUAD patients. The underlying reason for the positive correlation between the high expression of IRF5 in tumor tissues and prolonged survival time in LUAD patients remains uncertain. From the tissue chip samples, the patients with no lymph node metastases (N0) have a higher proportion of higher expression of IRF5.

We also analyzed the correlation between immune cell infiltration and IRF5 within the LUAD-TCGA dataset, and found that nine types of immune cells were significantly associated with IRF5. Notably, IRF5 expression was positively correlated with several immune cells, including memory B cells, Tregs, monocytes, M0 macrophages, M2 macrophages, and resting dendritic cells. Previous research has shown that IRF5 exhibits immunomodulatory properties and is present in a diverse array of immune cells, including dendritic cells, macrophages, monocytes, B cells, and T cells (13,14). It is generally believed that B cells, monocytes, macrophages, resting dendritic cells, may be associated with immune surveillance, preventing tumor progression and leading to a good prognosis for patients. In addition to its role in regulating interferon-related antiviral responses (15), IRF5 also modulates the secretion of inflammatory cytokines and chemokines, thereby influencing immune cell-mediated inflammatory reactions (16). For example, it plays a role in regulating macrophage polarization. IRF5 has been reported to be involved in macrophage polarization (17), and macrophage polarization has been shown to be involved in various processes of LUAD, including metastasis (18), invasion (19), and drug resistance (20). A further analysis of tissue chip research results from 69 patients also indicated a moderate negative correlation between IRF5 and the expression of the marker ratio (CD86/CD206) of M1 and M2 macrophages. It is consistent with the LUAD-TCGA dataset results that IRF5 is positively correlated with M2 macrophages. These results suggest that IRF5 expression is closely related to tumor immunity in LUAD; thus, IRF5 may be involved in regulating macrophage polarization. Thereby affecting the prognosis of LUAD patients.

In the presence of allergens like house dust mites (HDM), IRF5 may enhance the production of IL-33 and TSLP by epithelial cells, which are critical for activating innate lymphoid cells (ILC2s) and promoting Th2 immunity (21). In conditions like lung infections, IRF5 promotes the secretion of pro-inflammatory cytokines and chemokines that recruit immune cells, including neutrophils, eosinophils, and Th2 cells, to the lung. This helps clear pathogens and promotes lung defense mechanisms. To elucidate the role of IRF5 in lung immunity, future studies should focus on investigating the relationship between IRF5 and the lung’s immune microenvironment, as well as examining the specific signaling pathways that IRF5 utilizes to exert its regulatory functions.

The GO/KEGG analyses and the GESA revealed that the differential genes in the two high and low IRF5 expression groups were involved in the regulation of the immune response and the activation of immune cells, which is consistent with previous findings that IRF5 participates in the regulation of the adaptive immune system, the regulation of cytokine production, and immune cell function (22). A correlation analysis was then conducted to examine the relationship between IRF5 expression and eight major LUAD-related immune checkpoint genes; that is, CD274, CTLA4, HAVCR2, LAG3, LAIR1, PDCD1, PDCD1LG2, and TIGIT. The results revealed that all eight genes were positively correlated with IRF5. Thus, our results suggest that IRF5 expression in LUAD patients may be linked to their prognosis and could potentially influence the effectiveness of immunotherapy. IRF5 plays a crucial role in tumor immunity by influencing the tumor microenvironment and immune cell activation, which may impact ICI treatments. It regulates the production of cytokines and chemokines, crucial for immune cell recruitment and activation, and controls inflammatory responses through pathways like NF-κB and JAK-STAT. IRF5 is also key in inflammatory pathways, particularly in TLR signaling, which is dysregulated in cancers and chronic inflammation, affecting both pro- and anti-inflammatory responses.

This study had a number of limitations. First, the study’s sample sizes varied significantly across different groups. Second, IRF5 expression was only verified at the tissue level and not at the cellular level. Therefore, animal and cellular experiments should be performed in the future. Additionally, to elucidate the role of IRF5 in tumor immunity, the relationship between IRF5 and the tumor immunosuppressive microenvironment, as well as its impact on ICI treatment, needs to be investigated. The specific signaling pathways through which IRF5 functions and contributes to regulation should also be examined.

Conclusions

In summary, we examined the role of IRF5 in LUAD tumor tissues and provided important insights into its biological role. This study found that IFR5 can be used to indicative of prognosis in LUAD patients, and further research is essential to confirm in a more representative population. In addition, this study found that IRF5 was closely related to immunotherapy in LUAD patients.

Acknowledgments

Funding: This work was supported by Guangzhou Municipal Health Commission (No. 20221A011015).

Footnote

Reporting Checklist: The authors have completed the REMARK reporting checklist. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2024-2354/rc

Data Sharing Statement: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2024-2354/dss

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2024-2354/prf

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2024-2354/coif). A.M. receives payment from Amgen for symposium, from Oseus for educational meeting and from Viatris as speaker; receives support from BMS for congress invitation (national) and Takeda for congress invitation (ESMO); participates on medical board of Takeda and AstraZeneca, on expert meeting of Pfizer, and on commercial board of Amgen, outside the submitted work. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013).

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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(English Language Editor: L. Huleatt)