Macrophage-associated SLAMF9 is a potential therapeutic target for glioma

Introduction

Glioma is the most common primary intracranial tumor, accounting for approximately 46% of intracranial tumors. Its morbidity and mortality are among the highest among malignant tumors (1,2). After surgical resection, chemoradiotherapy, and even some new treatment methods, such as electric field therapy, the median survival time of glioma patients is still less than 21 months. During the progression of glioma, the generation of new mutations and new antigens is limited, resulting in a “cold tumor”, but the heterogeneity of genetic variation within the tumor is high (3). Studies indicate that standard radiotherapy and chemotherapy regimens are unable to achieve a cure in patients with gliomas harboring specific genetic alterations, such as isocitrate dehydrogenase (IDH) mutations (4). Therefore, there is a critical need to further investigate specific gene mutations associated with glioma to facilitate the development of targeted therapies. Over the past 20 years, advances in the research on biomarkers and molecular subtypes of major cancers and breakthroughs in the development of small-molecule compounds and antibody drugs have ushered in the era of precision medicine for cancer treatment. In the field of glioma treatment, the explosion of clinical trials related to targeted therapy and immunotherapy in recent years has revealed that the precise treatment of glioma has entered a period of vigorous research and exploration (5,6). However, due to the unique anatomical location of glioma and the reduced generation of new mutations and neoantigens during disease progression, the exploration of new precision treatment approaches for glioma has encountered more obstacles than those for other tumors. Glioma-associated macrophages (GAMs) are important factors affecting the progression of glioma and immunotherapy resistance (7). Revealing the key drivers of gene mutations in the origin and malignant progression of glioma through genomics research and providing targeted inhibition may represent a promising approach for reducing the burden of glioma and benefiting patients in the future (8-10).

The signaling lymphocytic activation molecule family (SLAMF) members 1–9 (SLAMF1–9) have recently been regarded as potential immunotherapeutic targets (11,12). SLAMF members, such as SLAMF7, are considered immunotherapy targets in various tumors, and anti-SLAMF7 antibodies have entered clinical trials in hematological tumors (13). In this study, we determined that SLAMF9 expression was significantly upregulated in tumor tissues compared with normal tissues. In addition, high SLAMF9 expression was significantly correlated with poor overall survival (OS) and disease-free survival (DFS) in glioma patients, suggesting that SLAMF9 may be a potential antitumor therapeutic target in glioma and may promote tumor progression by regulating the function of GAMs. We present this article in accordance with the MDAR reporting checklist (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1963/rc).

Methods

Patient samples

The datasets from The Cancer Genome Atlas (TCGA), including the clinical information and SLAMF9 expression data of a total of 672 glioma patients, were used to compare the different expression levels of SLAMF9 between glioma tissues and normal tissues and evaluate the relationship between SLAMF9 expression and the OS of glioma patients. For further verification, we downloaded the GSE83300 glioma dataset from the Gene Expression Omnibus (GEO) database, which contains clinical information and the SLAMF9 messenger RNA (mRNA) expression level of 50 glioma patients. We analyzed the relationship between SLAMF9 mRNA expression levels and the OS of glioma patients. In addition, we purchased a glioma tissue chip from Shanghai Outdo Biotech Company (Shanghai, China), which contains tumor tissues from 139 glioma patients. We analyzed the relationship between SLAMF9 protein expression and the prognosis of glioma in patients. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Committee of Shanghai Outdo Biotech Company (No. SHYJS-CP-1801021), and informed consent was waived due to the retrospective nature of this study.

Survival analysis

Patients were followed up until death or until July 2017. OS was defined as the time interval from surgery to death from any cause. DFS was defined as the time from surgery to disease recurrence or death due to disease progression.

Bioinformatics analysis

To analyze public databases, we downloaded RNA sequencing and clinical data for 672 glioma patients from the TCGA. The data were normalized using the “limma” package in R software, and immune cell infiltration was assessed using the “cibersort” package. For validation, we downloaded the GEO (https://www.ncbi.nlm.nih.gov/geo/) cohort with accession number GSE83300, which includes RNA sequencing and clinical data for 50 glioma patients. Using Gene Set Enrichment Analysis (GSEA) software (v4.0.3, UC San Diego and Broad Institute, Cambridge, MA, USA), we compared the enrichment results of SLAMF9 expression (high vs. low expression) in glioma tissues. The samples in this study from the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (CPTAC) were used to compare the protein expression levels of SLAMF9, CD68, and CD163 in 150 glioma tissues.

Immunohistochemistry (IHC) and IHC scoring

We performed IHC analysis with a rabbit monoclonal anti-human SLAMF9 antibody (1:200, PA5-21103, Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s instructions. The staining area and relative staining intensity of SLAMF9 were calculated using Image-Pro Plus 6.2 software. SLAMF9 expression was quantitatively analyzed according to the methods of Zhu et al. (14).

Multiplex immunofluorescence

Multiplex immunofluorescence was used to characterize the location of the SLAMF9 protein with a rabbit polyclonal antihuman SLAMF9 antibody (1:100, ab221703, Abcam, Cambridgeshire, England), a rabbit monoclonal antihuman CD68 antibody (1:100, ab303565, Abcam), and a rabbit polyclonal antihuman GFAP antibody (1:100, MA5-31969, Invitrogen).

Cell culture and construction of SLAMF9-knockdown macrophages

The human monocyte-macrophage lines THP-1, SW480, MKN45, and U87MG were obtained from the Cell Bank of the Chinese Academy of Sciences (Shanghai, China). All the cells were cultured according to the manufacturer’s instructions. Macrophages transfected with small interfering RNA (siRNA) were obtained from Hanyi Biologicals (Shanghai, China) according to the manufacturer’s instructions. The siRNA sequences used were as follows: SLAMF9F: CACAAAAUGCCAAGGAUGAUU; SLAMF9R: UCAUCCUUGGCAUUUUGUGUC. siRNA was obtained from Hanyi Biologicals.

Flow cytometry analysis

Flow cytometry was used to detect the number of molecules on the surface of RAW264.7 macrophages subjected to different treatments. One hundred microliters of cell suspension were stained with 1 µL of monoclonal antibody (mAb) in the dark at 4 ℃ for 30 min with specific antibodies, followed by washing, and then collected and analyzed by flow cytometry using FlowJo X (FlowJo, Ashland, USA). The following mAbs were used for flow cytometry: phycoerythrin (PE) anti-human CD163 (333605, Biolegend, Biolegend, San Diego, USA); allophycocyanin (APC) anti-human CD80 (305219, Biolegend); PE-cyanine7 (PC-7) anti-human CD86 (374209, Biolegend).

Quantitative real-time polymerase chain reaction (qRT-PCR)

For qRT-PCR, total RNA was extracted and reverse transcribed into cDNA with a Transcriptor First Strand cDNA Synthesis Kit (Roche, Basel, Switzerland) according to the manufacturer’s instructions. qRT-PCR was performed using an ABI 7900 system (Thermo Fisher Scientific, Waltham, MA, USA). The primers used were synthesized by Kingsley Biotechnology Ltd. (Guangzhou, China), and the sequences of the primers used were as follows: human GAPDH-forward (F): ACAACTTTGGTATCGTGGAAGG; human GAPDH-reverse (R): GCCATCACGCCACAGTTTC; human SLAMF9-F: TCTGGTCCTCTCACAAAAGTCT; human SLAMF9-R: CCTGGTAGTGTGGATTGGTCA. GAPDH was used as the endogenous control.

Statistical analysis

Survival curves were generated using the Kaplan-Meier method, and the log-rank test was used to determine differences in survival curves. All the experiments were repeated three times, and the results are presented as mean ± standard error of the mean (SEM). Comparisons were made on the basis of statistical significance using Student’s t-test and one-way analysis of variance (ANOVA). A two-tailed P<0.05 was used to determine whether the differences in the data were statistically significant. SPSS 23.0 software and GraphPad 9.5 software were used for analysis.

Results

High SLAMF9 mRNA expression is associated with poor prognosis of glioma

First, we downloaded and analyzed the glioma dataset, including 672 glioma tissues in the TCGA database. The expression level of SLAMF9 mRNA in many solid tumors was greater than that in normal tissues, and the difference was particularly obvious in glioma tissues (Figure 1A,1B). To further explore the expression of SLAMF9 mRNA and the OS of glioma patients, we downloaded the clinical information of the glioma patients mentioned above. Our results revealed that high SLAMF9 mRNA expression was significantly associated with poor prognosis (Figure 1C, P<0.001). To further evaluate this finding, we downloaded the GEO database GSE83300 glioma dataset, and Kaplan-Meier survival analysis revealed that high SLAMF9 expression was significantly associated with poor OS (Figure 1D, P<0.001). These findings suggest that the increased expression of SLAMF9 mRNA was significantly related to the decreased survival of glioma patients, which is worthy of further investigation.

Figure 1 The expression level of SLAMF9 in the TCGA and GEO glioma datasets is significantly correlated with the prognosis of glioma in patients. (A) The expression levels of SLAMF9 in tumor tissues and normal tissues of various solid tumors in the TCGA dataset. The green box delineates the differential expression of SLAMF9 between glioma and matched normal tissues. The full name of the TCGA abbreviations sees the website: https://gdc.cancer.gov/resources-tcga-users/tcga-code-tables/tcga-study-abbreviations. (B) Differences in the expression levels of SLAMF9 in glioma tumor tissues and normal tissues in the TCGA glioma dataset. (C) Relationships between SLAMF9 mRNA expression levels and the survival of glioma patients in the TCGA glioma dataset. (D) Relationships between SLAMF9 mRNA expression levels and the OS of glioma patients in the GSE83300 glioma dataset. *, P<0.05. GEO, Gene Expression Omnibus; mRNA, messenger RNA; OS, overall survival; SLAMF9, signaling lymphocytic activation molecule family member 9; TCGA, The Cancer Genome Atlas; TPM, transcripts per million.

Correlations between the expression of SLAMF9 and the expression of other genes associated with glioma prognosis

Using Tumor Immune Single Cell Hub (TISCH) (http://TISCH.comp-genomics.org/), a single-cell database of the tumor microenvironment, we found that the expression level of SLAMF9 in glioma patients was significantly positively correlated with the expression levels of multiple genes associated with glioma prognosis, such as FBP1, MARCO, and CXCL3 (Figure 2A). To better understand the relationship between SLAMF9 and these other genes associated with glioma prognosis, we used the glioma dataset from the TCGA database for analysis. Similar to previous results, the mRNA expression level of SLAMF9 was significantly positively correlated with the mRNA expression levels of MARCO, PLIN2, FBP1, and CXCL3 (Figure 2B). The high expression of these genes has been confirmed to be closely related to the poor prognosis of glioma and is considered to be an independent prognostic factor of glioma (15-17). Given these findings, further clarification of the value of SLAMF9 in glioma prognosis in the real world is crucial.

Figure 2 The expression level of SLAMF9 is correlated with the expression levels of multiple genes associated with glioma prognosis. (A) The gene set in the TISCH glioma dataset showed a significant positive correlation with the expression level of SLAMF9. (B) The expression levels of SLAMF9 were significantly positively correlated with those of MARCO, PLIN2, FBP1, and CXCL3 in the TCGA glioma dataset. SLAMF9, signaling lymphocytic activation molecule family member 9; TCGA, The Cancer Genome Atlas; TISCH, Tumor Immune Single Cell Hub.

Relationships between SLAMF9 protein expression levels and clinicopathological characteristics of patients with glioma

To investigate the relationship between SLAMF9 protein expression and the prognosis of glioma in patients, we performed an IHC assay to detect SLAMF9 protein expression using a glioma tissue microarray with 139 glioma tissues. We also collected the pathological information and follow-up data of the 139 patients. Among these 139 patients, 91 were male, and 48 were female. The average patient age was 43.1 years (range, 3–80 years). In terms of tumor histological type, 106 patients had astrocytoma (76.3%), 12 patients had ependymal glioma (8.6%), 19 patients had glioblastoma (13.7%), and 2 patients had other types of tumors (1.4%). All patients with gliomas had primary lesions and were confirmed to have gliomas by pathology. Furthermore, we analyzed the relationships between the protein expression level of SLAMF9 and patient age, sex, histological type, and number of tumors. We found that there was no significant difference in the expression level of SLAMF9 according to patient age, sex, or number of tumors; however, in terms of histological type, the expression level of SLAMF9 in glioblastoma was significantly greater than that in other histological types (P<0.001). Glioblastoma has the worst prognosis among all glioma histological types; therefore, SLAMF9 is likely to be a potential glioma prognostic factor. However, due to the prolonged storage of glioma tissue samples, IDH mutation-related genetic testing could not be performed. Consequently, tumor classification in this study was based solely on morphological features, which introduces certain limitations.

In addition, studies have shown that the S100 protein can be used for evaluating the prognosis of glioma in patients and that the survival time of patients with increased S100 protein expression is significantly shorter. Therefore, we also compared the relationships between the protein expression levels of S100 and SLAMF9. We found that SLAMF9 expression levels were slightly lower in patients with S100 scores of 0 to 1 than in patients with S100 scores of 2 to 3, but the difference was not statistically significant (Table 1).

High SLAMF9 protein expression is associated with poor prognosis of glioma in patients

As mentioned above, we used an IHC assay to detect the protein expression levels of SLAMF9, and representative images of high and low SLAMF9 protein expression are shown in Figure 3A. We found that the higher the tumor grade was, the greater the protein expression of SLAMF9 in glioma patients (Figure 3B, P<0.001). Moreover, we divided the 139 glioma patients into two groups based on recurrence or nonrecurrence status, and SLAMF9 protein expression was significantly higher in the recurrence group compared to the nonrecurrence group (Figure 3C, P<0.001).

Figure 3 Association between the expression level of SLAMF9 and clinicopathological features and prognosis was verified by IHC detection of a glioma tissue microarray. (A) Representative IHC images of glioma tissues with high and low SLAMF9 expression (scale bar =300 μm and 200 μm). (B) Relationship between SLAMF9 protein expression level and tumor grade in gliomas. (C) Correlation between SLAMF9 protein expression level and tumor recurrence in glioma. (D) Relationships between SLAMF9 protein expression levels and OS in 139 glioma patients. (E) Relationships between SLAMF9 protein expression levels and DFS in 139 glioma patients. ****, P<0.0001. DFS, disease-free survival; IHC, immunohistochemistry; OS, overall survival; SLAMF9, signaling lymphocytic activation molecule family member 9.

Furthermore, we retrospectively collected follow-up data from the 139 glioma patients from February 2008 to July 2017. Our results indicated that higher SLAMF9 protein expression predicts shorter OS (Figure 3D, P<0.001) and DFS (Figure 3E, P<0.001). These data suggest that the expression level of SLAMF9 is significantly related to the prognosis of glioma in patients; that is, the higher the expression level of SLAMF9, the worse the prognosis of glioma in patients. Thus, more in-depth investigations are needed to explore the potential value of SLAMF9 in glioma patients.

Cellular localization of SLAMF9 in the glioma tumor microenvironment

To further clarify the role of SLAMF9 in the glioma tumor microenvironment, we first analyzed SLAMF9 expression in the main cell types via TISCH. SLAMF9 is expressed mainly in monocytes/macrophages (Figure 4A). We extracted the data from the four most representative datasets, namely, GSE148842, GSE162631, GSE84465, and GSE139448. The data from these four datasets revealed that SLAMF9 is expressed mainly on the surface of monocytes/macrophages (Figure 4B). Therefore, we believe that SLAMF9 is expressed mainly on the surface of monocytes/macrophages in glioma tissues.

Figure 4 Cellular localization of SLAMF9 expression in the TISCH glioma dataset. (A) Cellular localization of SLAMF9 in 12 glioma datasets in the TISCH database. (B) SLAMF9 was highly expressed in tumor-associated macrophages in glioma according to a single-cell sequencing dataset from the TISCH database (http://tisch.comp-genomic.org//). (C) The mRNA expression levels of SLAMF9 in the gastric cancer cell line MKN45, the colorectal cancer cell line SW480, and the glioma cell line U87MG were detected by qRT-PCR. The expression levels of SLAMF9 mRNA in glioma U87MG cells, U87MG + TPH1 macrophages, and TPH1 macrophages. (D) Cellular localization of the SLAMF9 protein in human glioma tissue was detected by multiplex immunofluorescence (scale bar =50 μm). ***, P<0.001; ****, P<0.0001; ns, not significant (P>0.05). AC, astrocyte cell; DAPI, 4',6-diamidino-2-phenylindole; MES, mesenchymal; mRNA, messenger RNA; NPC, neural progenitor cell; OC, oligodendrocyte cell; OPC, oligodendrocyte progenitor cell; qRT-PCR, quantitative real-time polymerase chain reaction; SLAMF9, signaling lymphocytic activation molecule family member 9; TISCH, Tumor Immune Single Cell Hub; TPM, transcripts per million.

To further demonstrate this, the expression levels of SLAMF9 mRNA in TPH1 human macrophages and human cancer cells were detected by qRT-PCR. The results revealed that the expression level of SLAMF9 in the human glioma cell line U87MG was significantly greater than that in other human cancer cells, such as the gastric cancer cell line MKN45 and the colorectal cancer cell line SW480 (Figure 4C, P<0.001). However, compared with that in human THP-1 macrophages, the expression of SLAMF9 in human glioma cells was significantly lower than that in macrophages. More surprisingly, the expression level of SLAMF9 was the highest when human THP-1 macrophages were cocultured with human U87MG glioma cells (Figure 4C, P<0.001).

Then, we used a multiplex immunofluorescence assay to detect the protein expression of SLAMF9 in the tumor environment of human glioma tissue. SLAMF9 was abundantly present on the surface of CD68⁺ macrophages (Figure 4D). Glioma is a highly aggressive brain tumor characterized by many GAMs and other cellular and molecular components in its complex tumor microenvironment, which dynamically interact with each other and have a profound impact on tumor progression and treatment. As GAMs play important roles in the tumor immune microenvironment, further exploration of the regulatory effect of SLAMF9 on macrophages and glioma cells in the tumor immune microenvironment is highly important.

Potential effects of SLAMF9 on macrophages in glioma

To explore the clinical value of SLAMF9 in GAMs, we first selected a glioma dataset that contained the expression levels of SLAMF9 and CD68 and had complete follow-up information from the GEO database to analyze the relationships between GAMs with high mRNA expression of both CD68 and SLAMF9 and survival. We found that the prognosis of glioma in patients with high mRNA expression of both CD68 and SLAMF9 was significantly worse than that of other types (Figure 5A, P=0.02). To determine the relationships between SLAMF9 expression and CD68 and CD163 expression at the protein level, we investigated the National Cancer Institute’s CPTAC using 150 glioma tissues. From this analysis, we found that the protein expression level of SLAMF9 was significantly positively related to the M2 macrophage markers CD68 and CD163 (Figure 5B, P<0.0001). In addition, we knocked down SLAMF9 expression in mouse macrophages by siRNA and then analyzed the changes in the expression of M1 and M2 macrophage markers after SLAMF9 knockdown. The results revealed that the M1 macrophage markers CD80 (Figure 5C,5D, P<0.01) and CD86 (Figure 5C,5D, P<0.001) were significantly increased after SLAMF9 knockdown in human macrophages. However, the M2 macrophage marker CD163 (Figure 5C,5D, P<0.001) was significantly decreased (Figure 5C,5D, P<0.01).

Figure 5 Relationships between SLAMF9 and M1 and M2 macrophage markers. (A) Prognosis of glioma in patients with high mRNA expression of both SLAMF9 and CD68 in the GSE83300 glioma dataset. (B) The relationships between the protein expression of SLAMF9, CD68, and CD163 in glioma tissues were detected using the CPTAC database. (C,D) Expression of M1 and M2 markers in SLAMF9-knockdown human macrophages. *, P<0.05; **, P<0.01; ***, P<0.001. CPTAC, Clinical Proteomic Tumor Analysis Consortium; mRNA, messenger RNA; NC, normal control; si, small interfering RNA; SLAMF9, signaling lymphocytic activation molecule family member 9.

To preliminarily explore the possible signaling pathways involved in SLAMF9, we conducted GSEA using the TCGA glioma dataset and revealed that the signaling pathways with high expression and significant enrichment of SLAMF9 were associated with glioma, as were the mitogen-activated protein kinase (MAPK) signaling pathway, which is related to macrophage polarization, and the signaling pathways related to macrophage phagocytosis and cancer. We displayed the signaling pathways with high expression and significant enrichment of SLAMF9 including the MAPK signaling pathway (Figure 6A), glioma (Figure 6B), gamma-R-mediated phagocytosis pathway (Figure 6C), chemokine signaling pathway (Figure 6D), cytokine-cytokine receptor interaction (Figure 6E), apoptosis (Figure 6F), and pathways associated with cancer (Figure 6G). Therefore, SLAMF9 may be a potential therapeutic target in glioma.

Figure 6 Bioinformatics analysis of the potential function of SLAMF9 in glioma. Representative images of the MAPK signaling pathway (A), glioma (B), gamma-R-mediated phagocytosis pathway (C), chemokine signaling pathway (D), cytokine-cytokine receptor interaction (E), apoptosis pathway (F), and cancer pathway (G). KEGG, Kyoto Encyclopedia of Genes and Genomes; MAPK, mitogen-activated protein kinase; SLAMF9, signaling lymphocytic activation molecule family member 9.

Discussion

Glioma is a primary intracranial malignant tumor with insidious onset, rapid disease progression, and a short survival time. The high intratumoral heterogeneity of glioma results in the presence of many tumor cell subclones, making it easy to generate treatment resistance to undifferentiated chemoradiotherapy. Therefore, screening genes associated with glioma prognosis as therapeutic targets is an important research direction. The SLAMF is reported to modulate both adaptive and innate immune responses, and several SLAMF members have been confirmed to be abundantly expressed on the surface of macrophages (18,19). In this study, we found for the first time that SLAMF9 expression was significantly elevated in gliomas and correlated with poor prognosis through bioinformatics analysis of a glioma dataset.

In glioma, GAMs are highly infiltrated and play a key role in promoting tumor progression and drug resistance. GAMs promote angiogenesis, thus promoting the formation of new blood vessels to sustain tumor growth. Additionally, GAMs form a tumor microenvironment that is favorable for tumor progression and enhances tumor cell proliferation and metabolism, further promoting the aggressiveness of glioma (20,21). In our study, we demonstrated that SLAMF9 was expressed mainly on the surface of macrophages. Moreover, we found that SLAMF9 knockdown significantly promoted the elevation of M1 macrophage markers and decreased the expression of M2 macrophage markers in vitro, suggesting that SLAMF9 may affect macrophage polarization. M1 GAMs are immune cells with antitumor activity and are generally considered to have some antitumor ability in the early stages of tumor development, whereas M2 GAMs can promote tumor metastasis and immune escape (22). Therefore, we hypothesized that SLAMF9 might contribute to the formation of an immunosuppressive tumor microenvironment by promoting M2 macrophage polarization, leading to a poor prognosis.

Multiple studies have shown that the reason why GAMs have become popular targets for antitumor immunotherapy is their negative immunoregulatory functions in the tumor microenvironment. For example, both the M2 polarization of tumor-associated macrophages and changes in phagocytic function can lead to the formation of an immunosuppressive tumor microenvironment (23). Studies have shown that the MAPK signaling pathway promotes polarization in macrophages, thereby regulating tumor growth (24). Our recent research confirmed that another member of the SLAMF, SLAMF8, is involved in the regulation of the phagocytic function of macrophages in colorectal cancer (25). In this study, our GSEA results suggest that SLAMF9 is closely related to immune response pathways and pathways in cancer, including gamma-R-mediated phagocytosis and chemokine signaling pathways. These results indicate that SLAMF9-related genes are involved mainly in the immune response of glioma.

Conclusions

In summary, our study demonstrates for the first time that SLAMF9 may be a glioma prognostic factor and is associated with M2 polarization of GAMs, but more in-depth studies are still needed to further explore the mechanism of its regulatory role in the tumor immune microenvironment.

Acknowledgments

We sincerely thank all editors and reviewers for their helpful comments on this article. We thank the Jiangsu Health International Exchange Program for supporting the corresponding author, Zhang Qun, during her academic exchange in Italy, where she contributed to the revision of this manuscript.

Footnote

Reporting Checklist: The authors have completed the MDAR reporting checklist. Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1963/rc

Data Sharing Statement: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1963/dss

Peer Review File: Available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1963/prf

Funding: This research was supported by the National Natural Science Foundation of China (No. 82303970).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tcr.amegroups.com/article/view/10.21037/tcr-2025-1963/coif). The 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 and its subsequent amendments. The study was approved by the Ethics Committee of Shanghai Outdo Biotech Company (No. SHYJS-CP-1801021), and informed consent was waived due to the retrospective nature of this study.

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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