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. 2023 Dec 1;102(48):e36410. doi: 10.1097/MD.0000000000036410

TREM1 as a novel prognostic biomarker and tumor immune microenvironment evaluator in glioma

Qin Lu a, Yonglin Xie b, Xuchen Qi a, Shuxu Yang a,*
PMCID: PMC10695587  PMID: 38050264

Abstract

Glioma is the most malignant tumor in the central nervous system with a poor prognosis. The tumor immune microenvironment plays a crucial role in glioma formation and progress. TREM1, as a vital immune regulator, has not been investigated in glioma. This study aims to explore the role of TREM1 in prognosis and tumor immune microenvironment of glioma. The mRNA expression level of TREM1 was collected from TCGA and GEO databases. The correlations between the clinic-pathological features and TREM1 expression were analyzed using Cox regression analysis. Kaplan–Meier was used to evaluate the effect of TREM1 on OS. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes were performed to analyze the functional annotations and signaling pathways of the TREM1 coexpression genes. ESTIMATE and TIMER explored the correlations between TREM1 and immune cell infiltration. Spearman correlation analysis was conducted to examine the association between the TREM1 and immune checkpoint expression. The expression level of TREM1 was significantly increased in glioma. TREM1 overexpression was positively related to poor prognosis, higher World Health Organization grade, isocitrate dehydrogenase wildtype, and 1p/19q non-codeletion. TREM1 coexpression genes were mainly related to immunoregulation and inflammatory response. TREM1 participated in the initiation and progression of glioma by regulating immune cell infiltration and expression of immune checkpoints. TREM1 is an effective prognostic and diagnostic biomarker in glioma. It can be adopted as a novel predictor for clinical prognosis, pathological characteristics, and immune microenvironment in glioma patients.

Keywords: glioma, immune infiltration, prognosis, TREM1, tumor microenvironment

1. Introduction

Glioma is the most prevalent malignant tumor in the central nervous system, accounting for about 30% of brain tumors and 80% of primary malignant brain tumors.[1] Glioma is thought to originate from differentiated astrocytes or oligodendrocytes historically, with a high degree of malignancy characterized by a high recurrence rate and short survival time.[2] The most effective treatment for glioma is surgical resection combined with additional radiotherapy and chemotherapy. However, the prognosis for glioma remains very poor, and its median overall survival (OS) is about 12 to 14 months.[3] Therefore, it is urgent to develop novel therapeutic targets for improving the outcome of glioma.

The lack of effective treatment for gliomas can be explained by the immune microenvironment surrounding the glioma cells, which facilitates cancer cells to escape the immune system.[4] Studies have verified immune cells as key regulators in tumor formation, progress, and metastasis.[5,6] Thus, immunotherapy, which utilizes the immune system to recognize and eliminate cancer cells, has emerged as a revolutionary treatment for various tumors, such as immune checkpoint blockade[7] and chimeric antigen receptor T cell immunotherapy.[8] Meanwhile, many biomarkers were reported to recognize and monitor cancer treatment response.[9] However, due to the extremely complex immunosuppressive processes of the microenvironment surrounding the glioma cells, recent studies focusing on PD-1, CTLA-4, or VEGF failed to improve the OS of glioma.[10] Thus, it is crucial to identify more molecules that take part in the immunosuppressive processes microenvironment in glioma.

Triggering receptor expressed on myeloid cells 1 (TREM1) is an immune receptor expressed on the surface of myeloid cells.[11] Although the pathophysiological role of TREM1 was first identified during infectious diseases, increasing studies suggested it participated in no-infectious disorders.[12] Furthermore, recent investigations emphasized the critical role of TREM1 signaling as inflammation-mediated carcinogenesis.[13] Elevated TREM1 expression was found in lung cancer, hepatocellular carcinoma, and pancreatic cancer, and it could be deemed an independent predictor for tumor progression and poor outcomes. Furthermore, TREM1-positive tumor-associated macrophages were reported to result in intestinal tumorigenesis and correlate with reduced disease-free survival in lung cancer.[14,15] In prostate cancer, TREM-1 was also mediated by the androgen receptor signaling pathway in macrophages, increasing prostate cancer cells’ motility and invasive capacity.[16] Although TREM1 has been identified as an oncoprotein, its function in glioma progression and correlation with immune infiltration are poorly understood.

In this study, the expression and biological function of TREM1 in glioma were explored, and its correlation with the clinical characteristics and the prognosis of glioma patients were analyzed. Furthermore, we also investigated the association of TREM1 with the tumor immune microenvironment in glioma.

2. Methods

2.1. Data collection and expression evaluation

The mRNA expression levels of TREM1 in glioma were searched and downloaded from the TCGA (http://cancergenome.nih.gov/) database, while the data of normal samples were obtained from the Genotype-Tissue Expression (GTEx) portal (https://www.gtexportal.org/home/). Both low-grade glioma and glioblastoma multiforme (GBM) patient datasets with gene expression profiles and clinical information were analyzed in this study. Patients with incomplete follow-up data were excluded. The data that do not include TREM1 expression were also excluded. Meanwhile, 3 data series (GSE4290, GSE50161, and GSE16011) were obtained from GEO (https://www.ncbi.nlm.nih.gov/geo/) to verify the expression level of TREM1 in glioma. Furthermore, expression levels of TREM1 in different World Health Organization (WHO) grades were analyzed based on the TCGA data and GEO cohorts (GSE43378, GSE43289, and GSE16011). We also investigated the TREM1 protein expression by immunohistochemical images from the Human Protein Atlas (HPA, https://www.proteinatlas.org/).

2.2. Analysis of the relationship between TREM1 and clinical outcome

Clinical information of glioma was acquired from TCGA. To explore the correlation between TREM1 expression and the OS, the survival curve was performed by R language using Cox regression. GSE43378 was analyzed to verify the relationship between TREM1 and survival prognosis. The diagnostic value of TREM1 was investigated by the ROC curve. Univariate and multivariate COX were used to analyze the association between TREM1 expression and the clinicopathological features. Based on multivariate Cox analysis, a nomogram was established to predict survival probability for 1-, 3-, and 5-year in glioma patients. And the calibration plots were set up to predict the accuracy of the nomogram. The analyses were performed using the R package “rms.”

2.3. Functional enrichment analysis

Pearson correlation analysis was applied to acquire the significant coexpression genes related to TREM1 in the LinkedOmics database (http://www.linkedomics.org/). The top coexpression genes were visualized by volcano plot and heatmap. Then, GO and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed to analyze the functional annotations and signaling pathways of the coexpression genes.

2.4. Immune function analysis

TIMER (https://cistrome.shinyapps.io/timer/), as a platform providing systematical analysis of the immune infiltration across 32 cancer types, was used to investigate the correlation between TREM1 and the infiltration degree of different immune cells. The effects of TREM1 on immune cell infiltration were also analyzed by ESTIMATE and ssGSEA. To further explore the immune role of TREM1, we conducted the correlation between TREM1 and immune checkpoint genes.

2.5. Statistical analysis

Data were analyzed by R language. Student t-test and one-way ANOVA were applied to compare the expressions of TREM1 in different groups. Cox regression was used to analyze the relationship between TREM1 and OS time. Wilcox or Kruskal test was performed to detect the relationship between clinical characteristics and TREM1 expression. Spearman correlation analysis was conducted to examine the correlation analysis. Data were shown by mean ± standard deviation (SD), and P-value < .05 was considered statistically significant (*P < .05, **P < .01, ***P < .001).

3. Results

3.1. The expression level of TREM1 in glioma

Firstly, the TREM1 mRNA level in glioma tissues was collected from TCGA and GTEx databases, including GBM and LLG. Compared with normal tissues, the expression level of TREM1 was significantly upregulated in glioma tissues (Fig. 1A, normal:1157, glioma:689). Meanwhile, we evaluated the TREM1 expression in different tumor grades, and the result demonstrated that the expression of TREM1 increased along with the growth of tumor grade (Fig. 1B). Furthermore, a series of GEO cohorts verified the increased expression level of TREM1 in glioma patients, which is highest in WHO IV grade (Fig. 1A and B).

Figure 1.

Figure 1.

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The expression level of TREM1 increased in glioma. (A) the TREM1 expression between normal and tumor tissues in TCGA and 3 GEO datasets. (B) the expression of TREM1 among different WHO-grade glioma in TCGA and 3 GEO datasets. (C) Representational immunohistochemical images of TREM1 protein expression in normal and glioma tissues from HPA. ***P < .001.

Additionally, the immunohistochemical results of protein expression levels in glioma and normal tissues were obtained from The Human Protein Atlas database, which suggested a higher expression level of TREM1 in glioma (Fig. 1C).

3.2. The clinical value of TREM1 in glioma

Considering the high expression level of TREM1 in glioma, which is positively related to tumor grade, we further explored the clinical value of TREM1. The association between TREM1 expression and clinicopathological features was evaluated by univariate and multivariate COX analyses. As a result, age, tumor grade, isocitrate dehydrogenase (IDH) status, and TREM1 expression could be used as independent factors to predict the prognosis of glioma patients (Table 1). Then, we analyzed the mRNA level of TREM1 in different subgroups, such as age, gender, IDH mutation, and 1p/19q codeletion. And a significantly higher expression of TREM1 was found in older patients (Fig. 2A), IDH wide-type glioma (Fig. 2C), and 1p/19q non-codeletion tissues (Fig. 2D). But, no difference was shown in the gender group (Fig. 2B).

Table 1.

Univariate analysis and multivariate COX analysis of clinical prognostic parameters of glioma.

Variables Univariate Cox regression Multivariate Cox regression
HR (95%CI) P value HR (95%CI) P value
Age
(>60 vs ≤ 60)		 4.668 (3.598–6.056) <.001 1.493 (1.092–2.041) .012
Gender
(female vs male)		 0.793 (0.621–1.012) .062 - –
WHO grade
(IV vs I–III)		 9.496 (7.212–12.503) <.001 2.365 (1.586–3.527) <.001
IDH status
(mutant vs wildtype)		 0.117 (0.090–0.152) <.001 0.248 (0.167–0.367) <.001
1p/19q codeletion
(non-codeletion vs codeletion)		 4.428 (2.885–6.799) <.001 – –
TREM1 expression 1.641 (1.538–1.750) <.001 1.107 (1.002–1.222) .046
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Figure 2.

Figure 2.

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The TREM1 expression in different clinical and pathological features. TREM1 upregulated in old patients (A), IDH wide-type glioma (B), and 1p/19q non-codeletion tissues (C), with no change in gender group (D). ***P < .001.

To further determine the prognostic value of the TREM1 gene in glioma, data from TCGA was divided into 2 groups (high and low) based on the expression level of TREM1. The result of survival analysis indicated that patients with high TREM1 expression presented a significantly shortened OS when compared with low expression (P < .001, Fig. 3A). Meanwhile, a similar result was found in GEO43378, suggesting that TREM1 expression is a risk factor for OS (Fig. 3B). In clinical characteristics, chi-square test results indicated that increased expression of TREM1 was significantly associated with age, WHO grade, IDH status, and 1p/19q codeletion (Table 2). Furthermore, A time-dependent ROC curve was used to assess the predictive power of TREM1. As shown in Figure 3C–F, TREM1 had a remarkable predictive power in glioma diagnosis, IDH mutation, 1p/19q codeletion, and WHO grade with the AUCs 0.710, 0.858,0.830, and 0.936, respectively.

Figure 3.

Figure 3.

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The predictive value of TREM1 in glioma. K-M survival curves comparing the high and low TREM1 expression in glioma patients from TCGA (A) and GEO (B) datasets. ROC curve of TREM1 expression to predict glioma (C), IDH status (D), 1p/19q non-codeletion (E), and WHO grade (F). (G) A nomogram for predicting the probability of 1, 3, and 5-year survival for glioma. (H) Calibration plots of the nomogram.

Table 2.

The correlation between the expression of TREM1 and clinical factors.

Characteristics TREM1 expression level P-value
Low expression High expression
Age, median (IQR) 40.5 (32, 51.25) 52.5 (37, 63) <.001
WHO grade, n (%) <.001
 I–III 298 (47%) 169 (26.6%)
 IV 3 (0.5%) 165 (26%)
IDH status, n (%) <.001
 Wildtype 33 (4.8%) 213 (31%)
 Mutation 314 (45.8%) 126 (18.4%)
1p/19q codeletion, n (%) <.001
 Codeletion, 155 (22.5%) 16 (2.3%)
 Non- codeletion, 193 (28%) 325 (47.2%)
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Furthermore, a nomogram was set up based on the TREM1 expression and independent risk factors for survival. And the nomogram aims to provide a quantitative standard for predicting the prognosis of glioma patients. As shown in Figure 3G, 5 factors were listed and assigned with points in the nomogram (C-index: 0.853). At last, the points of all factors were accumulated with a total score. Then, the 1-year, 3-year, 5-year probability of survival in glioma patients was determined. Additionally, the calibration plots were established to predict the accuracy of the nomogram (Fig. 3H).

All the above results suggest that TREM1 is a sensitive biomarker for predicting the prognosis of glioma patients. High expression of TREM1 is related to poor outcome, worsened WHO grade, IDH wildtype, and 1p/19q non-codeletion.

3.3. Functional enrichment analysis of TREM1 in glioma

To explore the biological function of TREM1 in glioma, TREM1 coexpression genes in glioma were analyzed and collected from the LinkedOmics database. A total of 2384 genes showed significant positive correlations with TREM1 expression, whereas 2077 genes were negative to TREM1 (Fig. 4A, false discovery rate < 0.01). The heat map of the top 50 genes positively and negatively correlated with TREM1 is shown in Figure 4B. Then, GO and KEGG enrichment analyses were performed (Fig. 4C–F). The result suggested that the functions of TREM1 co-expressed genes were mainly located in immune regulation, cell cycle modification, inflammatory response, angiogenesis, and gliogenesis.

Figure 4.

Figure 4.

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The functional analysis of TREM1 coexpression genes. (A) Genes coexpression with TREM1 identified in glioma via LinkedOmics database. (B) The heat map of the top 50 genes positively and negatively correlated with TREM1. The result of Gene ontology analyses of TREM1 coexpression genes in BP (C), CC (D), and MF (E). (F) KEGG enrichment analyses of TREM1 coexpression genes. BP, biological process, CC, cellular component, and MF, molecular function.

3.4. The role of tumor-immune microenvironment in glioma

The tumor immune microenvironment plays a critical role in the growth and metastasis of tumors, including glioma, and it indeed affects the survival of glioma patients. Combined with the functional enrichment of TREM1 coexpression genes and the role of TREM1 serving as an immune regulator, we inferred that TREM1 influences the prognosis of glioma by affecting the immune infiltration levels. Firstly, based on the ESTIMATE algorithm, we found a positive correlation between immune infiltration and the TREM1 expression in glioma stromal score (Fig. 5A, R = 0.759), immune score (Fig. 5B, R = 0.728), and ESTIMATE score (Fig. 5C, R = 0.759). Then, the correlation between 24 immune cell infiltration levels and TREM1 expression was calculated by ssGSEA. As Figure 5D showed, TREM1 expression was positive for various immune cell infiltration, such as macrophages, neutrophils, eosinophils, immature dendritic cells (iDC), activated dendritic cells (aDC), and so on. Meanwhile, some cell infiltrations were negative to TREM1 expression, including plasmacytoid dendritic cells (pDC), T gamma delta cells (Tgd), and T regulate cells. Furthermore, the infiltration scores of different immune cells (|correlation index| > 0.4) were compared between high and low TREM1 expression groups. The infiltration of macrophages, neutrophils, eosinophils, iDC, aDC, T cells, and cytotoxic cells was increased in the high TREM1 expression group, while the score of pDC was reduced (Fig. 5F).

Figure 5.

Figure 5.

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The correlation between TREM1 expression and immune infiltration. The ESTIMATE analysis investigated the association between TREM1 and immune cell infiltration, including stromal scores (A), immune scores (B), and ESTIMATE scores (C). (D) The correlation between TREM1 expression and the infiltration of 24 immune cells by ssGSEA. (F) The infiltration scores of different immune cells between TREM1 high and low expression groups. Adc = activated dendritic cells, Idc = immature dendritic cells, Tcm = T central memory, Tem = T effector memory, TFH = T follicular helper, Tgd = T gamma delta, pDC = plasmacytoid DC. ***P < .001.

We further explore the relationship between mRNA expression of TREM1 and immune cell infiltration via the TIMER database. The results showed that the TREM1 expression was positively correlated with the infiltration of CD4+ T cells (partial cor = 0.06), Neutrophils (partial cor = 0.234), and Dendritic cells (partial cor = 0.575) in GBM tissues (P < .05). While in LLG, the expression level of TREM1 was positive to the infiltration level of all immune cells in Figure 6A.

Figure 6.

Figure 6.

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The effect of TREM1 on immune cell infiltration and immune checkpoints. (A) The analysis of the association between TREM1 expression and purity and 6 types of immune cell infiltrations by TIMER. (B) The relationship between TREM1 expression and immune checkpoints by Spearman correlation analysis.

Considering the dominant role of immune checkpoints in tumor immune escape, we evaluated the relationship between TREM1 expression and immune checkpoint molecular, including PDCD1, CD274, CTLA4, HAVCR2, LAG3, TIGIT, and CD96. The result suggested a positive correlation between the expression level of TREM1 and immune checkpoints (Fig. 6B).

4. Discussion

In clinical and pathological characteristics, overexpression of TREM1 is related to poor prognosis, worsened WHO grade, IDH wildtype, and 1p/19q non-codeletion. Functional enrichment analysis indicated that TREM1 coexpression genes were correlated to immune regulation, cell cycle modification, inflammatory response, angiogenesis, and gliogenesis.

TREM1, as a transmembrane protein on the surface of myeloid cells, plays a vital role in initiating and amplifying the immune-inflammatory response.[17] And various studies have suggested TREM1 as a treatment target for different diseases. In the brain, our previous study indicated that the TREM1 activated rapidly on the surface of microglia and participated in neuroinflammation after intracerebral hemorrhage (ICH), which worsened the outcome of ICH.[18] However, no study explored the role of TREM1 in brain tumors, especially in glioma. Considering the role of immune cells and immune-inflammatory response in tumor formation, progression, and metastasis, we speculated that TREM1 participated in the pathological process of glioma.

This study acquired data from TCGA and GTEx with 689 glioma patients. The result indicated an upregulated TREM1 expression in glioma tissues compared with normal samples, and the expression level of TREM1 increased along with the degree of tumor grade. Glioma was commonly divided into 4 grades, from I to IV, with WHO IV indicating the highest malignancy. In this research, the grades of enrolled gliomas included diffuse astrocytoma (WHO grade II), anaplastic astrocytoma (WHO grade III), and glioblastoma (WHO grade IV).[19] Furthermore, the expression feature of glioma was verified by 5 independent GEO cohorts, suggesting that TREM1 overexpression may be a potential biomarker for malignant phenotypes of gliomas and a predictive factor for outcome. Thus, we collected and analyzed the clinical and pathological characteristics from TCGA. The result of univariate Cox analysis suggested that age, WHO grade, IDH status, 1p/19q codeletion, and TREM1 expression were risk factors for the clinical outcome of glioma. Then, we extracted the mRNA data of TREM1 in age, IDH status, and 1p/19q codeletion, and the data was compared in the different subgroups. We revealed that TREM1 was upregulated in older patients, IDH wide-type group, and 1p/19q non-codeletion group. Gliomas can be classified into IDH1 wildtype and IDH1 mutant based on the IDH mutation status.[20] Compared with IDH mutant gliomas, patients with IDH wildtype tumors tended to have worse outcomes, with OS of about 22 months in grade III and 13 months in grade IV.[21] 1p/19q codeletion is another type of molecular alteration in glioma, which is related to the histologic type of oligodendroglial and chemotherapy sensitivity with alkylating agents.[22] Robert et al reported that the combined 1p and 19q deletion in gliomas are associated with a significantly better prognosis and response to radiation, especially in gliomas with oligodendroglial components.[23] In our study, the expression of TREM1 was raised in glioma with IDH wide-type and 1p/19q non-codeletion, which suggested that TREM1 could be considered as a biomarker for a more malignant phenotype in gliomas. Furthermore, the glioma patients were divided into high and low groups according to the expression level of TREM1. We found a remarkably poorer OS in the TREM1 high expression group, and TREM1overexpression is also positive to WHO grade, IDH wildtype, and 1p/19q non-codeletion.

To investigate the mechanism which TREM1 participates in the formation and progress of glioma, functional annotation and pathway analysis of TREM1 coexpression genes were conducted. The functional annotation analyses indicated that genes were mainly associated with immune-inflammatory response, angiogenesis, and gliogenesis, and the related signal pathways were also inspected by KEGG. Coexpression genes of TREM1 were significantly enriched in the cytokine-cytokine receptor interaction, chemokine signaling pathway, tumor necrosis factor signaling pathway, and NF-kappa B signaling pathway. Nisha et al reported that cytokine-cytokine receptor interaction and chemokine signaling pathway are indispensable in the tumor microenvironment. Cytokine and chemokine can be expressed by tumor cells and other cells and attract different immune cells migrating into the tumor microenvironment and regulating tumor immune responses.[24]

On the other hand, chemokines can directly target nonimmune cells, such as tumor cells and vascular endothelial cells, to further regulate cell proliferation, cancer invasiveness, and metastasis.[25] Over the past decade, activation of NF-kappa B signaling has also been found to promote mesenchymal differentiation of glioma by regulating downstream transcriptional signaling.[26] Numbers of studies suggested that NF-kappa B signaling promotes glioblastoma cell survival and resistance to therapy via acting on Bcl-2, Bcl-xl, survivin, and Cox-2.[27] NF-kappa B signaling can also participate in angiogenesis, invasion, and migration of glioma through different effector molecules.[28,29] A recent study reported that the NF-kB was upregulated in the GBM microenvironment, which is stimulated by inflammatory cells such as macrophages and microglia.[30] Thus, we believe that TREM1 influences the formation and progress of glioma via modulating the immune microenvironment.

To further explore the role of TREM1 in the tumor immune microenvironment, we discussed the relation between TREM1 expression and immune cell infiltration in 672 glioma patients from TCGA. As a dominant component of the tumor immune microenvironment, immune cell infiltration mediates the formation and progression of the tumor, as well as the sensibility to immunotherapy.[31] Our study suggested that macrophages and neutrophils were the 2 primary cells infiltrating into the tumor immune microenvironment in glioma, which is positive for the TREM1 expression. Various studies showed that macrophages, especially those from the peripheral system, were the key factor that regulated glioma growth and migration.[32] In these studies, macrophages released cytokines, such as TGF-β, IL-6, IL-1β, and EGF, and promoted tumor growth.[33] Besides targeting glioma cells, macrophages can also affect angiogenesis by VEGF signaling, indirectly affecting tumor growth.[34]

In contrast, the infiltration of the plasmacytoid dendritic cell was negative to the TREM1 expression in glioma tissue. Plasmacytoid dendritic cells (pDCs) comprise a subset of DCs characterized by their ability to detect pathogen-derived nucleic acids and produce a large amount of IFN-I/α.[35] In cancer, pDCs presented an inadequate response to TLRs activation, decreased IFN-α production and contributed to an immunosuppressive tumor microenvironment. Marianela et al demonstrate that pDCs mediate anti-GBM therapeutic efficacy through the production of IFN-α,[36] and they suggest pDC as a new therapeutic target for the treatment of glioma. Thus, TREM1 induced a specific immune cell infiltration and contributed to a microenvironment that favored glioma formation, growth, and metastasis.

Immune checkpoints are the regulators of the immune system and consist of inhibitory and costimulatory receptors. The main function of immune checkpoints is to maintain immune system homeostasis and avoid autoimmunity.[37] Glioma cells interact with immune cells by expressing some checkpoints, such as CTLA-4, PD-1, TIM-3, and LAG-3, which assist tumor cells in escaping the immune surveillance.[7] In GBM, the binding of PD-1 to its receptor has been demonstrated to induce an immune escape mechanism and to take part in tumor initiation and progression.[38] Encouraging results from inhibiting the PD-1/PD-L1 pathway have validated PD-1 as a target for cancer immunotherapy. A significant improvement in survival was noted in CD73−/− mice treated with anti-PD-1 compared to controls.[39] Furthermore, several clinical trials have been conducted to evaluate the efficacy of anti-PD-1 agents in recurrent and newly diagnosed glioblastoma. In our study, TREM1 was reported positive to various immune checkpoints, including PD-1 and CTL-A. The results emphasized the predictive role of TREM1 on the immunosuppressive microenvironment in glioma.

There were some limitations in this study. Firstly, the analysis was based on the data of mRNA expression and clinical features were acquired from TCGA and GEO databases, relevant animal and cell experiments needed to be carried out to confirm the role of TREM1 in glioma. Secondly, this study did not investigate the extent of surgical resection and chemoradiotherapy, which are key factors to OS. Additionally, the role of TREM1 in the tumor-immune microenvironment was explored on the gene transcription levels, which may reflect all aspects of immune status. And further studies based on pharmacological intervention needed to be conducted, such as inhibition of TREM1 activity by LP17.

5. Conclusion

In summary, we reported that the expression level of TREM1 was significantly increased in glioma, along with the promotion of tumor grade. TREM1 overexpression was positively related to poor outcomes, worsened WHO grade, IDH wildtype, and 1p/19q non-codeletion. TREM participated in the initiation and progression of glioma by regulating immune cell infiltration and expression of immune checkpoints. Hence, TREM1 can be a novel prognostic biomarker and tumor immune microenvironment evaluator in glioma.

Author contributions

Conceptualization: Shuxu Yang.

Data curation: Qin Lu, Yonglin Xie.

Methodology: Qin Lu, Yonglin Xie, Xuchen Qi.

Software: Qin Lu, Yonglin Xie.

Supervision: Xuchen Qi, Shuxu Yang.

Writing – original draft: Qin Lu.

Writing – review & editing: Xuchen Qi, Shuxu Yang.

Abbreviations:

GBM
glioblastoma multiforme
GO
Gene Ontology
GTEx
Genotype-Tissue Expression
IDH
isocitrate dehydrogenase
KEGG
Kyoto Encyclopedia of Genes and Genomes
OS
overall survival
TREM1
triggering receptor expressed on myeloid cells 1
WHO
World Health Organization

This work was supported by the Natural Science Foundation of Zhejiang Province, China (LQ21H090013) and the Medical science and health technology of Zhejiang Province, China (2023KY786).

Ethical review is not applicable in this study because all data comes from public databases.

The authors have no conflicts of interest to disclose.

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

How to cite this article: Lu Q, Xie Y, Qi X, Yang S. TREM1 as a novel prognostic biomarker and tumor immune microenvironment evaluator in glioma. Medicine 2023;102:48(e36410).

Contributor Information

Qin Lu, Email: drluqin1226@zju.edu.cn.

Yonglin Xie, Email: dryonglin@zju.edu.cn.

Xuchen Qi, Email: qixuchen@zju.edu.cn.

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