The Prognostic Value of Natural Killer Cells and Their Receptors/Ligands in Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis

Background: Natural killer (NK) cells play major roles in eliminating tumor cells. Preliminary studies have shown that NK cells and their receptors/ligands have prognostic value in malignant tumors. However, the relevance of NK cells and their receptors/ligands level to the prognosis of hepatocellular carcinoma (HCC) remains unclear.

Methods: Several electronic databases were searched from database inception to November 8, 2021. Random effects were introduced to this meta-analysis. The relevance of NK cells and their receptors/ligands level to the prognosis of HCC was evaluated using hazard ratios (HRs) with 95% confidence interval (95%CI).

Results: 26 studies were included in the analysis. The pooled results showed that high NK cells levels were associated with better overall survival (HR=0.70, 95%CI 0.57–0.86, P=0.001) and disease-free survival (HR=0.61, 95%CI 0.40-0.93, P=0.022) of HCC patients. In subgroup analysis for overall survival, CD57⁺ NK cells (HR=0.70, 95%CI 0.55-0.89, P=0.004) had better prognostic value over CD56⁺ NK cells (HR=0.69, 95%CI 0.38-1.25, P=0.224), and intratumor NK cells had better prognostic value (HR=0.71, 95%CI 0.55-0.90, P=0.005) over peripheral NK cells (HR=0.66, 95%CI 0.41-1.06, P=0.088). In addition, high level of NK cell inhibitory receptors predicted increased recurrence of HCC, while the prognostic role of NK cell activating receptors remained unclear.

Conclusion: NK cells and their inhibitory receptors have prognostic value for HCC. The prognostic role of NK cell activating receptors is unclear and more high-quality prospective studies are essential to evaluate the prognostic value of NK cells and their receptors/ligands for HCC.

Introduction

Hepatocellular carcinoma (HCC) is the sixth most common malignancy worldwide and the third leading cause of cancer-related mortality (1). The major risk factors for HCC involve chronic hepatitis B and hepatitis C infection, alcohol, and metabolic liver disease (2). Natural killer (NK) cells, characterized as CD3^-CD56⁺ lymphocytes, are mainly involved in the early defense against virus infections and play major roles in eliminating tumor cells (3). NK cells account for only about 5–20% of the circulating lymphocytes in the peripheral blood. In contrast, NK cells are abundant in human liver, accounting for almost half of intrahepatic lymphocytes (4), which lays foundation for the powerful role of NK cells in the liver tumor microenvironment.

Human NK cells are divided into two major subpopulations based on the surface density of CD56 antigen (5). CD56^dim NK cells display a mature phenotype, accounting for approximately 90% of all NK cells and mediating the cytolytic response, while immature CD56^bright NK cells account for 5%-15% of total NK cells and are regarded as cytokine producers (6). Another surface marker is CD57, which is a marker for differentiated and highly cytotoxic NK cells, and is described as a phenotypically stable NK cells marker (7).

The regulation of NK cell function is mediated by a series of activated or inhibitory surface receptors. The major activated receptors involved in target cell killing are NK group 2 member D (NKG2D) and natural cytotoxic receptors (NCRs). NCRs mainly consist of NKp44, NKp46 and NKp30 (8), and can recognize ligands from different sources, including viral, parasitic, bacterial, as well as cellular ligands, such as HLA-B-associated transcript 3/Bcl-2-associated athanogene 6 (BAT3/BAG6), mixed lineage leukemia 5 (MLL5), proliferating cell nuclear antigen (PCNA) and B7 homolog 6 (B7-H6) (9, 10). In contrast, NKG2D mainly binds to the major histocompatibility complex class I chain-related protein A and B (MICA and MICB) and UL16-binding proteins (ULBPs). After binding, it can activate NK cells to produce cytotoxic substances to kill harmful and tumor cells (11). Other activated receptors include CD16, NKp88, CD244, CD226 and cytokine receptors such as interleukin (IL)-2R, IL-12R, IL-28R, IL-18R, IL-1R8, IL-15R, IL-10R, interferon receptor (IFNR) and tumor growth factor-β receptor (TGF-βR) (12–14).

The major inhibitory receptors involved in target cell killing are NKG2A, CD96, killer immunoglobulin-like receptors (KIRs), T cell immunoglobulin and immunoreceptor tyrosine-based inhibitory motif domain (TIGIT) and T cell immunoglobulin domain and mucin domain-3 (TIM-3) (12). Other inhibitory receptors include programmed cell death-1 (PD-1), lymphocyte activation gene-3 (LAG3), leukocyte-associated immunoglobulin-like receptors (LAIRs), adenosine 2A receptor (A2AR) and immunoglobulin-like transcripts (ILTs) (15). PD-1 is primarily expressed by activated T lymphocytes, but may also be expressed by NK cells in tumor patients. PD-1/Programmed cell death ligand-1 (PD-L1) interactions can inactivate T cells and NK cells, allowing tumor cells to escape immune surveillance (16). Human histocompatibility leucocyte antigen E (HLA-E) is the main ligand of NKG2A, and is generally upregulated in cancer patients and predicts poor prognosis (17–19). The major histocompatibility complex class I (MHC-I) is the main ligand of KIRs, and is expressed on healthy hepatocytes. It interacts with inhibitory receptors on NK cells to prevent the activation of NK cells (14).

Until now, the correlation of NK cells and their receptors/ligands with the prognosis of HCC remains controversial (20–28). The purpose of this meta-analysis and review is to evaluate the prognostic value of NK cells and their receptors/ligands in HCC.

Materials and Methods

Search Strategy and Study Selection Criteria

This meta-analysis was conducted according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines (supplementary PRISMA Checklist) (29), and inclusion criteria were based on the PICOS model.

Relevant studies were independently searched by two authors (JSX, ZND) from the PubMed, Embase, Web of Science and Cochrane Library literature databases from the beginning of the database until November 8, 2021. Detailed search strategy was as described in the supplement. Additional articles were identified by a manual search of the references of eligible articles.

Studies were included if they met the following criteria. (1) all patients were identified as having HCC; (2) studies revealed the expression of NK cells and their receptors/ligands and obtained their levels by assaying; (3) studies provided adequate information to evaluate the hazard ratio (HR) and 95% confidence interval (95% CI); (4) the prognostic indexes such as overall survival (OS), cancer-specific survival (CSS), disease-free survival (DFS), recurrence-free survival (RFS), time-to recurrence (TTR), and progression-free survival (PFS) were evaluated; (5) Anti-tumor treatments were not conducted; (6) studies must be published in English. Studies were excluded if they met the following criteria. (1) review, meta-analysis and case report; (2) basic experimental researches of HCC and studies unrelated to the NK cells and their receptors/ligands; (3) studies provided inadequate data to evaluate the correlation of NK cells and their receptors/ligands with prognosis. For republished studies, only the studies with the largest sample size were selected; alternatively, the most recent literature and relevant data were collected.

Data Extraction and Quality Assessment

Eligible study data were extracted independently by two investigators (JSX, ZND). Disagreements could be discussed and resolved with a third investigator (GXM). Baseline characteristics were extracted from the included studies. Only one study had outcome indicator for CSS, which we uniformly classified as OS. OS and DFS/RFS/TTR/PFS were used as endpoints for the meta-analysis. The quality of eligible studies was assessed by the Newcastle–Ottawa Scale (NOS) criteria (30).

Statistical Analysis

Most of the relevant data from the studies could be directly collected. However, for those studies that did not provide hazard ratios (HRs) and 95% confidence intervals (95% CIs), we obtained estimates from known information using the method of Altman and Tierney (31, 32). Random effects models were applied. P < 0.05 was considered statistically significant. The pooled HR and 95% CI were used to assess the relevance between NK cell level and prognosis of HCC patients. Cochran’s Q test and Higgins’ I² statistic were used to assess the heterogeneity. P-value of heterogeneity > 0.10 and I² < 50% were considered as no significant heterogeneity. At the same time, subgroup analyses were performed by surface marker, source of NK cell, and outcome of patients. Sensitivity analysis was performed by removing each study to test the stability and reliability of the results. Funnel plots, Egger regression asymmetry tests, and Begg rank correlation tests were conducted to check for potential publication bias (33). Stata 16.0 software analysis was applied to all data in this meta-analysis.

Results

Literature Search

As shown in Figure 1 of the flowchart, a total of 1831 records were initially identified. After removing duplicate studies, 1110 studies were retained. After screening for titles and abstracts, 1052 studies were excluded. After reviewing the remaining 58 studies through full text, 32 studies were excluded due to insufficient data (11), public database (9), measurement of NKT (5), improper detection method including Ficoll separation or radiotaged NK-sensitive K-562 cell separation (2), and treatment of NK cells (5), including intravenous infusion of NK cells alone or combined with other modalities, such as radiofrequency ablation and irreversible electroporation. Finally, 26 studies were included in this analysis, including 13 on classical NK cells, 9 on activating receptors/ligands, 3 on inhibitory receptors/ligands, and 1 on both activating and inhibitory receptors/ligands.

FIGURE 1

Figure 1 Study flow chart of the data extraction process and selection of studies for meta-analysis.

The Basic Characteristics of Included Studies About NK Cells

Table 1 summarized the basic characteristics of the included studies about NK cells. Sample sizes of the eligible studies ranged from 36 to 258, for a total of 1711, and these studies were conducted primarily in two countries: twelve in China and one in Italy. Seven studies reported on CD56⁺ NK cells, 4 on CD57⁺ NK cells, and 2 on NK cells. Among these studies, 5 studies detected NK cells in peripheral blood, and 8 detected intratumor NK cells. In total, 12 studies mentioned the correlation between NK cell levels and OS (20–22, 25–27, 34–37, 39, 40). 9 studies mentioned the correlation between NK cells levels and DFS/RFS/TTR/PFS (20, 25–27, 35, 36, 38–40). NOS score > 6 was defined as high quality, and ≤ 6 was defined as low quality (Supplementary Table 1).

TABLE 1

Table 1 The characteristics of all included eligible studies about NK cells.

Prognostic Value of NK Cells in Patients With HCC

A total of 12 studies, involving 1611 patients, investigated the prognostic value of NK cells for OS. The pooled results from the 12 comparative studies were significant (HR=0.70, 95%CI 0.57-0.86, p=0.001), and the data were not heterogeneous (I^{2 =} 16.0%, P=0.287; Figure 2A). No bias was observed in the funnel plot (Figure 3A). In order to better understand the prognostic value of NK cells, we further performed subgroup analysis according to the marker and source of NK cells (Table 2). In subgroup analysis of CD57⁺ NK cells, the pooled results from 4 comparative studies were significant (HR=0.70, 0.55-0.89, P=0.004), while it was insignificant in CD56⁺ NK cells (HR=0.69, 95%CI 0.38-1.25, P=0.224; Supplementary Figure 1). Compared to peripheral NK cells (HR=0.66, 95%CI 0.41-1.06, P=0.088), the level of intratumor NK cells had better prognostic value (HR=0.71, 95%CI 0.55-0.90, P=0.005) for HCC patients (Supplementary Figure 2).

FIGURE 2

Figure 2 Forest plot of NK cells in HCC. (A) Forest plot of NK cells and OS in HCC. (B) Forest plot of NK cells and DFS/RFS/TTR/PFS in HCC. CI, Confidence interval; HR, Hazard ratio; HCC, Hepatocellular carcinoma; NK, Natural killer; OS, Overall survival; DFS, Disease-free survival; RFS, Recurrence-free survival; TTR, Time-to recurrence; PFS, Progression-free survival.

FIGURE 3

Figure 3 Funnel plots of NK cells in HCC. (A) Funnel plots of HR for OS of NK cells. (B) Funnel plots of HR for DFS/RFS/TTR/PFS of NK cells. CI, Confidence interval; HR, Hazard ratio; HCC, Hepatocellular carcinoma; NK, Natural killer; OS, Overall survival; DFS, Disease-free survival; RFS, Recurrence-free survival; TTR, Time-to recurrence; PFS, Progression-free survival.

TABLE 2

Table 2 Subgroup meta-analysis of the prognostic role of NK cells in HCC.

A total of 9 studies, involving 1313 patients, investigated the prognostic value of NK cells for DFS/RFS/TTR/PFS. The pooled results from the 9 comparative studies were not significant (HR=0.87, 95%CI 0.72-1.06, P=0.164), and the data were not heterogeneous (I^{2 =} 13.4%, P=0.323; Figure 2B). No bias was observed in the funnel plot (Figure 3B). We also performed subgroup analysis to better understand prognostic value of NK cells (Table 2). The pooled HR (95%CI) for CD57⁺ NK cells and CD56⁺ NK cells was 0.76 (0.57-1.01, P=0.059) and 1.09 (0.79-1.50, P=0.602), respectively (Supplementary Figure 3). For NK cells derived from peripheral blood and intratumor, the pooled HR (95%CI) was 0.93 (0.59-1.46, P=0.746) and 0.86 (0.68-1.09, P=0.213), respectively (Supplementary Figure 4). In addition, in subgroup analysis of outcome, we found that high NK cells levels could be a good predictor for DFS (HR=0.61, 95%CI 0.40-0.93, P=0.022), but not for RFS, TTR and PFS (Supplementary Figure 5).

Prognostic Value of Activating Receptors/Ligands on NK Cells

Table 3 summarized the outcomes of 3 studies that reported on NKp30⁺ NK cells. One study mentioned that high NKp30⁺ NK cell level was associated with better survival (41), while another study reported no effect of NKp30⁺ NK cell level on patient outcome (43). Other study suggested that high NKp30⁺ NK cell level was associated with good PFS, but not with OS (42). In addition, one study investigated the prognostic role of NKG2D. They concluded that low frequency of circulating NKG2D⁺CD56^dim NK cells one month after hepatectomy may predict a poor prognosis for patients with HBV-related HCC (23).

TABLE 3

Table 3 The characteristics of included studies about the NK cells activating receptors and their ligands.

A total of 6 studies reported on ligands of NK cell activating receptors, including MICA, MICB, soluble MICA (sMICA), ULBP1 and B7-H6 (28, 44–48). The pooled HR (95%CI) for OS and DFS/RFS/PFS was 0.91 (0.52-1.57, P=0.726; Figure 4A) and 0.68 (0.26-1.75, P=0.422; Figure 4B), respectively.

FIGURE 4

Figure 4 Forest plot of NK cells activating receptors/ligands in HCC. (A) Forest plot of NK cells activating receptors/ligands and OS in HCC. (B) Forest plot of NK cells activating receptors/ligands and DFS/RFS/PFS in HCC. CI, Confidence interval; HR, Hazard ratio; HCC, Hepatocellular carcinoma; NK, Natural killer; OS, Overall survival; DFS, Disease-free survival; RFS, Recurrence-free survival; PFS, Progression-free survival.

Prognostic Value of Inhibitory Receptors/Ligands on NK Cells

Table 4 summarized the outcomes of 4 studies that mentioned NK cell inhibitory receptors, including NKG2A, CD96, CD158b, TIGIT and TIM-3 (24, 42, 49, 50). They all concluded that high level of NK cell inhibitory receptors predicted increased recurrence of HCC patients. Sun and Li et al. suggested that the level of NK cell inhibitory receptors was not associated with survival of HCC patients, while other studies revealed that high NK cell inhibitory receptors level predicted poor survival of HCC patients. One study found that intratumor level of HLA-E was increased, and high HLA-E level was correlated with poor prognosis of HCC patients (Figures 5A, B).

TABLE 4

Table 4 The characteristics of included studies about the NK cells inhibitory receptors and their ligands.

FIGURE 5

Figure 5 Forest plot of NK cells inhibitory receptors/ligands in HCC. (A) Forest plot of NK cells inhibitory receptors/ligands and OS in HCC. (B) Forest plot of NK cells inhibitory receptors/ligands and DFS/PFS in HCC. CI, Confidence interval; HR, Hazard ratio; HCC, Hepatocellular carcinoma; NK, Natural killer; OS, Overall survival; DFS, Disease-free survival; PFS, Progression-free survival.

Assessment of Sensitivity Analysis and Publication Bias

Sensitivity analysis was performed to evaluate the stability of NK cells for predicting survival and recurrence of HCC patients. After removing any of the studies, the results did not exceed the 95% CI range of the pooled results (Figures 6A, B). Begg’s test and Egger’s linear regression test were used to assess whether there was potential publication bias in this meta-analysis. The results showed that no apparent publication bias for the analysis was found between NK cells and OS (Begg’s test: P=0.732, Figure 7A; Egger’s test: P=0.564, Figure 7B). Similarly, no significant publication bias was found for DFS/RFS/TTR/PFS analysis (Begg’s test: P=0.602, Figure 7C; Egger’s test: P=0.401, Figure 7D).

FIGURE 6

Figure 6 Sensitivity analysis of NK cells. (A) Sensitivity analysis for OS of NK cells. (B) Sensitivity analysis for DFS/RFS/TTR/PFS of NK cells. CI, Confidence interval; HR, Hazard ratio; NK, Natural killer; OS, Overall survival; DFS, Disease-free survival; RFS, Recurrence-free survival; TTR, Time-to recurrence; PFS, Progression-free survival.

FIGURE 7

Figure 7 Evaluation of publication bias of NK cells using Begg’s test and Egger’s test. (A) Begg’s test for OS of NK cells, P=0.732. (B) Egger’s test for OS of NK cells, P=0.564. (C) Begg’s test for DFS/RFS/TTR/PFS of NK cells, P=0.602. (D) Egger’s test for DFS/RFS/TTR/PFS of NK cells, P=0.401. lnhr, the ln of HR; s.e., standard error; NK, Natural killer; OS, Overall survival, DFS, Disease-free survival; RFS, Recurrence-free survival; TTR, Time-to recurrence; PFS, Progression-free survival.

Discussion

NK cells are innate lymphocytes that can kill virus-infected or cancer cells, and have a vital role in early hepatocarcinogenesis (51, 52). Different to T cells which require somatic gene rearrangement to produce highly antigen-specific receptors (53), NK cells are innately equipped with germline-encoded activating and inhibitory receptors that can directly determine whether NK cells are activated or inhibited (12, 54). NK cells can deliver cytotoxic granules, secrete effector cytokines, and are involved in death receptor induced apoptosis (55). NK cells can also rapidly produce cytokines with anti-tumor effects, such as IFN-γ, to exert their killing effects in the early stage of disease (56). In addition, NK cells can bind to target cells through surface CD16 and kill them through exerting antibody-dependent cell-mediated cytotoxicity (ADCC) (57). These results imply that NK cells play an essential role in the body’s immune process in the defense against HCC.

In this study, we found that high NK cell level could predict better survival for patients with HCC. Similar results were previously reported in a meta-analysis of solid tumors (58). In subgroup analysis, CD57⁺ NK cells had better prognostic value over CD56⁺ NK cells. On the one hand, it may be that CD56⁺ NK cells, accounting for the majority of circulating NK cells, also expressed inhibitory molecules, which may strive for a dynamic balance between activating and inhibitory molecules. Moreover, lower IFN-γ production was also described in HCC, in accordance with the decreased cytotoxicity of NK cells (59). On the other hand, acquisition of CD57 represents a shift toward a higher cytotoxic capacity, greater responsiveness to signaling via CD16 and natural NCRs (60). The same result was also observed in Hu et al.’s study (61). In addition, compared to peripheral NK cells, NK cells from intratumor had better prognostic value for prognosis of HCC patients, possibly because NK cells are abundant in human liver.

NK cells express activating and inhibitory receptors in order to perceive signals and display their activity. Depending on the received signal, NK cells can be activated or restricted (62). In this study, activating receptors/ligands mainly contain NKG2D, NKp30, and their ligands. NKG2D ligands mainly consist of ULBPs and MICA/B. MICA/B molecules expressed on HCC cells are recognized by NKG2D to induce ubiquitination-mediated endocytosis of the NKG2D-DAP10 complex, thereby activating NK cells to kill HCC (46, 57). NKp30 contains two ligands. One is BAT3, a nuclear protein that induces apoptosis in target cells by interacting with P53. The other is B7-H6, a newly discovered member of the B7 family that is expressed on the surface of tumor cells (45). B7-H6/NKp30 pathway is involved in the NK cell-mediated immune responses, and NK cells can recognize and eliminate B7-H6-expressing tumors, including HCC. However, tumors can also impair NK cell function by shedding B7-H6 membranes or decreasing NKp30 expression, leading to tumor immune escape and tumor progression (63). In addition, hypoxia, some soluble forms of NCRs ligands, or soluble factors produced by tumor/tumor-associated cells, can induce a decrease in both NCR expression and function (10, 64, 65), and protect tumor from NK cell-mediated cytotoxicity (44, 66). Until now, the prognostic value of activating receptors remained inconsistent from different studies and deserved further investigation.

Inhibitory receptors/ligands mainly contain NKG2A, CD96, CD158b, TIGIT and TIM-3, and HLA-E. The NKG2A is expressed approximately in half of the peripheral blood NK cells, and is also expressed on CD8⁺ T cells (67). The inhibitory signals induced by NKG2A engagement can result in decreased capacity of NK cells and CD8⁺ T cells to lyse target cells (68), and enhanced expression of the HLA-E on tumor may result in resistance and immune escape by binding to NKG2A (68). Therefore, blocking the interaction of NKG2A with HLA-E has shown promising therapeutic effects in animal study (69). In addition, there is increasing evidence that PD-1 is also expressed on the surface of NK cells and exerts a suppressive function on T cell responses (16). In this study, though we found that inhibitory receptors of NK cells may be a good predictor for recurrence of HCC, however, their prognostic value in predicting survival was unclear. Therefore, more high-quality prospective studies are needed to explore the prognostic value of NK cells and their receptors/ligands for HCC.

The strength of this study is that it explored for the first time the prognostic value of NK cells and their receptors/ligands in HCC. Almost all relevant articles that could be collected were included and a comprehensive analysis was provided. However, the following limitations should also be considered. First, some of the data were not obtained directly from the included studies. HRs and 95% CIs were calculated using survival curves or 95% CIs were calculated from known P values and HRs, which may result in data inaccuracy to some extent. Second, although most studies used median as the cut-off value for NK cells level, these values were complex and related to the clinicopathological characteristics of the HCC patients. Third, although DFS/RFS/TTR/PFS of HCC patients are considered as composite outcome indicators, there are still slightly difference between them. Fourth, NK cells receptors/ligands are diverse. The pooled results may exist in bias to some extent. Fifth, this was an aggregate data rather than an individual data meta-analysis, and the data were various between studies, which somehow diminished the significance of the study. Finally, some surface markers were expressed not only in NK cells, but also in other immune cells, such as T cells, Dendritic cells (DCs), etc. Moreover, liver NK cells are composed of several subsets including conventional, type 1 innate lymphoid cells (ILC1) like, and liver-resident NK cells. All of them can express similar molecules and potentially be responsible for the clinical benefit observed (70).

Conclusions

In summary, we concluded that NK cells could be a good predictor for survival of HCC. More importantly, CD57⁺ NK cells may have better prognostic value over CD56⁺ NK cells, and intratumor NK cells have better prognostic value over peripheral NK cells. Inhibitory receptors of NK cell may be a good predictor for recurrence of HCC, but the value of activating and inhibitory receptors in predicting the survival of HCC was unclear. More high-quality prospective studies are essential to evaluate the prognostic value of NK cells and their receptors/ligands for HCC.

Data Availability Statement

The original contributions presented in the study are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding author.

Author Contributions

J-SX and TL were responsible for designing the study. J-SX, Z-ND, and G-XM conducted the systematic search and performed the screening. J-SX, Z-ND, G-XM, L-JY, HL, H-CL, S-YY, B-WT, J-GH, Z-RD, Z-QC, and D-XW primarily performed the quality assessment as well as supervision. J-SX analyzed, interpreted the data, and drafted the manuscript. TL revised the manuscript. All data and material analyzed during this study were included in this article. All authors have read and approved the final version of the manuscript.

Funding

This work was supported by the grants from the Taishan Scholars Program for Young Expert of Shandong Province (Grant No. tsqn20161064), National Natural Science Foundation of China (Grant No. 82073200 & 81874178), funds for Independent Cultivation of Innovative Team from Universities in Jinan (Grant No. 2020GXRC023), and Major basic research of Shandong Provincial Natural Science Foundation (Grant No. ZR202105070027).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fimmu.2022.872353/full#supplementary-material

Glossary

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