High expression of SIGLEC7 may promote M2-type macrophage polarization leading to adverse prognosis in glioma patients

Abstract

Introduction: Gliomas are the most common primary intracranial tumors, known for their high invasiveness and destructiveness. Sialic acid-binding immunoglobulin-like lectin 7 (SIGLEC7) is present in various immune cells, especially macrophages, and significantly affects immune homeostasis and cancer cell response. However, research on the role and prognostic impact of SIGLEC7 in glioma patients is currently limited.

Methods: We utilized transcriptomic data from 702 glioma patients in The Cancer Genome Atlas (TCGA) and 693 glioma patients in the Chinese Glioma Genome Atlas (CGGA), along with clinical samples we collected, to comprehensively investigate the impact of SIGLEC7 on glioma expression patterns, biological functions, and prognostic value. We focused on its role in glioma-related immune responses and immune cell infiltration and analyzed its expression at the single-cell level. Finally, we validated the role of SIGLEC7 in gliomas through tissue and cell experiments.

Results: SIGLEC7 expression was significantly increased in glioma patients with malignant characteristics. Survival analysis indicated that glioma patients with high SIGLEC7 expression had significantly lower survival rates. Gene function analysis revealed that SIGLEC7 is primarily involved in immune and inflammatory responses and is strongly negatively correlated with tumor-associated immune regulation. Additionally, the expression of most immune checkpoints was positively correlated with SIGLEC7, and immune cell infiltration analysis clearly demonstrated a significant positive correlation between SIGLEC7 expression and M2 macrophage infiltration levels. Single-cell analysis, along with tissue and cell experiments, confirmed that SIGLEC7 enhances macrophage polarization towards the M2 phenotype, thereby promoting glioma invasiveness through the immunosuppressive effects of M2 macrophages. Cox regression analysis and the establishment of survival prediction models indicated that high SIGLEC7 expression is an unfavorable prognostic factor for glioma patients.

Discussion: High SIGLEC7 expression predicts poor prognosis in glioma patients and is closely associated with M2 macrophages in the tumor environment. In the future, SIGLEC7 may become a promising target for glioma immunotherapy.

Keywords: M2 macrophage; SIGLEC7; glioma; prognostic indicator; tumor immunity.

Figure 1

Correlation of SIGLEC7 with Clinicopathological Features of Gliomas. (A) Overview of the correlation between SIGLEC7 and clinicopathological features of gliomas in the TCGA database. (B) Overview of the correlation between SIGLEC7 and clinicopathological features of gliomas in the CGGA database. (C, D) Expression levels of SIGLEC7 gradually increase with glioma grade escalation in both TCGA and CGGA databases. Significance of differences was assessed using one-way ANOVA. (E, F) Gliomas without 1p/19q chromosomal co-deletion express higher levels of SIGLEC7 in both TCGA and CGGA databases. Significance of differences was assessed using unpaired t-tests. (G, H) Gliomas with O6-methylguanine-DNA methyltransferase (MGMT) promoter non-methylation express higher levels of SIGLEC7 in both TCGA and CGGA databases. Significance of differences was assessed using unpaired t-tests. (I, J) Gliomas without Isocitrate Dehydrogenase (IDH) mutations express higher levels of SIGLEC7 in both TCGA and CGGA databases. Significance of differences was assessed using unpaired t-tests.

Figure 2

Specific Enrichment of SIGLEC7 in the mesenchymal subtype of Gliomas. (A, C) One-way ANOVA detects enrichment of SIGLEC7 in the mesenchymal subtype in the TCGA and CGGA databases. (B, D) Receiver Operating Characteristic (ROC) curves demonstrate the specificity of SIGLEC7 overexpression in the mesenchymal subtype of gliomas in the TCGA and CGGA databases, with the area under the curve (AUC) indicated.

Figure 3

Enrichment Analysis Related to SIGLEC7 Gene. (A-C, E-G) Biological Processes (BP), Cellular Components (CC), and Molecular Functions (MF) most correlated with SIGLEC7 in TCGA and CGGA databases. (D, H) Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis related to SIGLEC7 in TCGA and CGGA databases. (I-N) Positive and negative regulation networks of immune processes associated with SIGLEC7 expression in TCGA and CGGA databases.

Figure 4

Relationship between SIGLEC7 and immune checkpoints and inflammatory responses. (A, B) Pearson correlation analysis between SIGLEC7 and immune checkpoints in TCGA and CGGA databases. The color bands represent the correlation, *** represents P<0.001, and unmarked indicates P>0.05. (C, D) Pearson correlation analysis matrix between SIGLEC7 and inflammation-related proteins in TCGA and CGGA databases. The depth of color in the lower left numerical values and upper right square represents the magnitude of the correlation coefficient.

Figure 5

Impact of SIGLEC7 Expression on Immune Infiltration in Gliomas. (A, B) Comparison of levels of 22 immune cell infiltrations between glioma patients grouped by median SIGLEC7 expression in TCGA and CGGA databases. * represents p < 0.05, ** represents p < 0.01, *** represents p < 0.001, **** represents p < 0.0001.

Figure 6

Relationship of SIGLEC7 with Macrophages and Microglia. (A-C) Relationship between SIGLEC7 and macrophages and microglia predicted based on typical markers CD68, CD163, and TMEM119 in GSE131928, CGGA, and GSE89567 databases.

Figure 7

Tissue and Cellular Experiments Related to SIGLEC7. (A) Immunohistochemical staining of SIGLEC7 in different grades of glioma tissues, scale bar: 50 μm. (B) Western blot analysis of SIGLEC7 and CD163 expression in polarized macrophages after siRNA-mediated SIGLEC7 silencing. (C) Immunofluorescence staining of polarized macrophages. Blue fluorescence represents DAPI-stained cell nuclei, red fluorescence represents CD163 staining, and green fluorescence represents SIGLEC7 staining. The first row shows staining of normal M2 macrophages, while the second and third rows show staining after SIGLEC7 silencing. (D) Bar graph showing the average fluorescence intensity of CD163 and SIGLEC7-positive cells in macrophage immunofluorescence images. (E, I) Results of invasion assays after co-culture of macrophages with tumor cells. **p < 0.01; ***p < 0.001; ****p < 0.0001.

Figure 8

SIGLEC7 Marks Malignant Prognosis of Glioma Patients. (A, B) Impact of high and low expression of SIGLEC7 on the survival of glioma patients. Kaplan-Meier survival analysis was conducted on the TCGA and CGGA databases. (C, D) Univariate and multivariate analyses of parameters affecting clinical prognosis in the TCGA and CGGA databases.

Figure 9

Personalized Prediction Model for Gliomas. (A) Nomogram predicting the 1-year, 2-year, 3-year, and 5-year survival probabilities of patients. (B) Evaluation of the model and predictive effects of individual indicators using the C-index. (C) Calibration plots showing the predicted probabilities of 1-year, 2-year, 3-year, and 5-year survival in TCGA and CGGA databases compared to actual outcomes.