Assessing the Relevance of Non-molecular Prognostic Systems for Myelodysplastic Syndrome in the Era of Next-Generation Sequencing
2025; 45(1): 44-52
Ann Lab Med 2025; 45(2): 185-198
Published online December 20, 2024 https://doi.org/10.3343/alm.2024.0178
Copyright © Korean Society for Laboratory Medicine.
Yurong Gu , Ph.D.1,*, Yanhua Bi
, B.S.2,*, Zexuan Huang
, B.S.2, Chunhong Liao
, B.S.2, Xiaoyan Li
, Ph.D.1, Hao Hu
, B.M.1, Huaping Xie
, B.M.1, and Yuehua Huang, M.D., Ph.D.1,2
1Department of Infectious Diseases, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China; 2Guangdong Provincial Key Laboratory of Liver Disease Research, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
Correspondence to: Yuehua Huang, M.D., Ph.D.
Department of Infectious Diseases, the Third Affiliated Hospital of Sun Yat-sen University, No. 600, Tianhe Road, Guangzhou 510630, China
E-mail: huangyh53@mail.sysu.edu.cn
* These authors contributed equally to this study as co-first authors.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Background: The function of CD69 expressed on T cells in chronic hepatitis B (CHB) remains unclear. We aimed to elucidate the roles of CD69 on T cells in the disease process and in antiviral therapy for CHB.
Methods: We enrolled 335 treatment-naive patients with CHB and 93 patients with CHB on antiviral therapy. CD69, antiviral cytokine production by T cells, T-helper (Th) cells, and inhibitory molecules of T cells were measured using flow cytometry, and clinical-virological characteristics were examined dynamically during antiviral therapy.
Results: CD69 expression on CD3+, CD4+, and CD8+ T cells was the lowest in the immune-active phase and was negatively correlated with liver transaminase activity, fibrosis features, inflammatory cytokine production by T cells, and Th-cell frequencies but positively with inhibitory molecules on T cells. CD69 expression on CD3+, CD4+, and CD8+ T cells decreased after 48 weeks of antiviral therapy, and patients with hepatitis B e antigen (HBeAg) seroconversion in week 48 showed lower CD69 expression on T cells at baseline and week 48. The area under the ROC curve of CD69 expression on T cells at baseline for predicting HBeAg seroconversion in week 48 was 0.870, the sensitivity was 0.909, and the specificity was 0.714 (P =0.002).
Conclusions: CD69 negatively regulates T-cell immunity during CHB, and its expression decreases with antiviral therapy. CD69 expression predicts HBeAg seroconversion in week 48. CD69 may play an important negative role in regulating T cells and affect the efficacy of antiviral therapy.
Keywords: Antiviral agents, CD69, Chronic hepatitis B, T cell, Therapy
Hepatitis B virus (HBV) infection affects approximately 257 million people worldwide and represents a significant global health challenge [1]. The natural history of CHB is influenced by both viral and host factors, and CHB progression has been classified into four phases: immune-active (IA), inactive CHB (IC), immune-tolerant (IT), and an indeterminate or gray zone (GZ). T-cell immunity is crucial in suppressing HBV replication and virus clearance and acts as the main pathogenic mechanism of liver inflammatory injury. HBV-specific T cells initially induce hepatocellular necroinflammation, which involves a relatively small number of hepatocytes. Subsequently, numerous antigen-non-specific inflammatory cells are recruited to the liver and contribute to the formation of necro-inflammatory foci throughout the liver [2, 3].
CD69 is a calcium-dependent, carbohydrate-binding integral membrane protein with an extracellular C-type lectin domain [4, 5]. It is constitutively expressed in various cells, including monocytes and platelets, and during infection, its expression increases in activated B cells, T cells, eosinophils, and neutrophils [7]. CD69 provides costimulatory signals and promotes cytotoxicity and proliferation [7, 8]. CD69 stimulation, combined with T-cell receptor activation, induces Ca2+ influx, ERK1/2 kinase activation, and cytokine production in T cells, ultimately promoting T-cell proliferation, which is essential for CD69-mediated cell degranulation [9, 10]. Recent studies have reported a negative immune-regulatory role of CD69, which can inhibit T-helper (Th) cell differentiation by promoting the Jak3/STAT5 transcriptional signaling pathway, inhibiting transcription factor RORγt activation, and reducing the production of transforming growth factor-β, interleukin (IL)-17, and other cytokines [11, 12].
T-cell immunity is weaker in patients with CHB—who exhibit persistently high levels of viral replication—than in those with acute HBV infection [13, 14]. The role of CD69 in T-cell immunity during different disease phases and antiviral therapy in patients with CHB remains unclear. Therefore, we examined the expression of CD69, antiviral cytokines, and inhibitory molecules on T cells, along with clinical-virological characteristics in a cohort of 335 treatment-naive patients with CHB. Additionally, we analyzed CD69 expression on T cells in a cohort of 93 patients with CHB who received longitudinal antiviral therapy to elucidate the role of CD69 in chronic HBV infection.
Between December 2015 and December 2017, we recruited two groups of patients with CHB from the hepatitis clinic of the Third Affiliated Hospital of Sun Yat-sen University and 17 healthy controls (HCs) from the physical examination center. The study was approved by the Ethics Committee of the Third Affiliated Hospital of Sun Yat-sen University (approval No. [2014] 2-66), and written informed consent was obtained from all patients.
Three hundred thirty-five treatment-naive patients with CHB were enrolled in the cross-sectional study, and 93 patients with CHB who received antiviral therapy were included in the longitudinal study. Among the latter, 36 received Peg-interferon (Peg-IFN), and 57 received entecavir (ETV).
According to the American Association for the Study of Liver Diseases (AASLD) [15], we classified the treatment-naive CHB patients into four groups: IA, IC, IT, and GZ. The criteria are provided in Supplemental Data Table S1.
Hepatitis B surface antigen (HBsAg) and hepatitis B e antigen (HBeAg) were measured using commercial kits (Roche Diagnostics, Indianapolis, IN, USA). HBV DNA was measured using Roche COBAS AmpliPrep/COBAS TaqMan (Roche Molecular Diagnostics, Branchburg, NJ, USA). Fibrosis was scored based on liver stiffness measurements (Fibroscan; Echosens, Paris, France). Serum ALT, AST, and total bilirubin (TBIL) were measured using a 7600-020 (ISE) Automatic Analyzer (Hitachi, Tokyo, Japan). Blood routine parameters, including white blood cell (WBC) and platelet (PLT) counts, were measured using an XN2000 instrument (Sysmex, Kobe, Japan). The aminotransferase: platelet ratio index (APRI) score was calculated as (AST/upper limit of normal [ULN])×100/platelet count, and the fibrosis-4 index (FIB-4) was calculated as age (yrs)×AST (U/L)/(platelet count [109/L]×ALT [U/L]1/2). The ULN for AST was set to 40 U/L for men and 35 U/L for women.
EDTA-anticoagulated blood was drawn on the day written informed consent was obtained. Peripheral blood mononuclear cells (PBMCs) were isolated from heparinized peripheral blood samples of all patients and healthy volunteers using Ficoll density gradients, as described previously [16]. Flow-cytometric staining and detection were performed on the day written informed consent was obtained to ensure cell integrity and viability. Surface markers were stained using relevant antibodies. For cytokine and Th-cell analyses, PBMCs were stimulated with Leukocyte Activation Cocktail (eBioscience, San Diego, CA, USA) for 4 hrs before intracellular staining. All antibodies and isotype-matched controls for flow staining were purchased from EBioscience. Data were acquired on a Gallios instrument (Beckman Coulter, Brea, CA, USA) and analyzed using the FlowJo software (FlowJo, Ashland, OR, USA). The gating strategy for CD69 is shown in Supplemental Data Fig. S1.
The continuous variables did not conform to a normal distribution according to a Kolmogorov–Smirnov test (P<0.05). Therefore, we used the Mann–Whitney U and Kruskal–Wallis H tests to compare the groups. Dynamic changes in CD69 between baseline and after 48 weeks of antiviral therapy were assessed using the Wilcoxon matched-pairs rank test. Correlations between parameters were tested using Pearson or Spearman correlation. Relationships between CD69 levels and other factors were evaluated using univariate and multivariate linear regression analyses. The ROC curve and area under the ROC curve (AUROC) were examined to determine the predictive value of the CD69 level. GraphPad Prism 7 was used to generate graphs, and statistical analyses were performed using SPSS version 23 (IBM Corp; Armonk; NY). Statistical significance was set to P<0.05.
Baseline demographic and clinical data are shown in Table 1. Among treatment-naive patients, clinical and virological characteristics differed significantly among the four disease phases (P<0.001), which is consistent with the clinical characteristics of patients with CHB in different phases. Among treatment-naive patients, patients in the IT phase were the youngest, and those in the IC phase were the oldest (P=0.001). Patients who received Peg-IFN were younger than those who received ETV (P=0.002).
Characteristic | Treatment-naive | Receiving antiviral therapy | |||||||
---|---|---|---|---|---|---|---|---|---|
IT(N=31) | IA (N=196) | GZ (N=59) | IC (N=49) | P | ETV treatment(N=57) | PEG treatment(N=36) | P | ||
Age, yrs | 26.0 (24.0, 31.0) | 29.5 (25.0, 34.8) | 31.00(27.0, 38.0) | 32.0(27.5, 39.0) | 0.001* | 33.0(28.0, 39.0) | 29.5(26.0, 31.0) | 0.002* | |
Sex | 0.415* | 0.817* | |||||||
Male, N (%) | 19 (61.3) | 148 (75.5) | 43 (72.9) | 35 (71.4) | 47 (82.5) | 29 (80.6) | |||
Female, N (%) | 12 (38.7) | 48 (24.5) | 16 (27.1) | 14 (28.6) | 10 (17.5) | 7 (19.4) | |||
BMI, kg/m2 | 20.6 (18.4, 22.6) | 21.0 (19.3, 23.0) | 21.2 (19.5, 23.3) | 22.1 (20.2, 23.4) | 0.082† | 21.9(19.5, 24.2) | 20.5(19.3, 22.8) | 0.318‡ | |
Fibroscan, Kpa | 4.75 (4.00, 5.63) | 6.82 (5.53, 10.48) | 4.80 (4.15, 5.50) | 4.70 (4.23, 5.58) | <0.001† | 9.00(7.20, 12.05) | 8.30(6.30, 12.13) | 0.275‡ | |
AST, U/L | 25.0 (21.0, 28.0) | 61.0 (36.0, 108.0) | 26.0(22.0, 31.0) | 24.0(21.0, 29.0) | <0.001† | 96.0(62.0, 148.5) | 68.5(52.8, 109.8) | 0.083‡ | |
ALT, U/L | 24.5 (19.3, 28.8) | 101.0(57.0, 174.0) | 25.5(20.0, 32.0) | 24.0(18.0, 30.0) | <0.001† | 153.0(95.5, 246.0) | 135.0(96.8, 222.0) | 0.705‡ | |
Albumin, g/L | 44.8 (44.0, 47.1) | 44.9(42.5, 47.0) | 46.5(45.5, 47.9) | 46.8(45.1, 48.5) | <0.001† | 44.4(41.7, 46.9) | 43.8(42.5, 45.9) | 0.738‡ | |
Globulin, g/L | 29.3 (26.4, 31.5) | 29.0(26.2, 32.1) | 29.3(26.9, 31.4) | 28.6(27.0, 31.1) | 0.924† | 29.0(26.7, 31.9) | 29.0(25.4, 32.8) | 0.994‡ | |
TBIL, μmol/L | 13.1 (9.5, 18.6) | 15.4(11.7, 20.1) | 12.1(9.3, 15.6) | 12.1(9.4, 16.6) | <0.001† | 16.2(11.7, 21.5) | 17.9(14.2, 22.4) | 0.346‡ | |
HBeAg status | <0.001* | 0.146* | |||||||
Negative, N (%) | 0 (0.0) | 44 (22.5) | 49 (83.1) | 46 (93.9) | 8 (14.0) | 1 (2.8) | |||
Positive, N (%) | 31 (100.0) | 152 (77.6) | 10 (17.0) | 3 (6.1) | 49 (86.0) | 35 (97.2) | |||
HBV genotype | <0.001* | NA | |||||||
B, N (%) | 21 (67.7) | 71 (59.2) | 27 (45.8) | 14 (28.6) | 10 (17.5) | 0 (0.0) | |||
C, N (%) | 4 (12.9) | 36 (30.0) | 14 (23.7) | 5 (10.2) | 11 (19.3) | 0 (0.0) | |||
O, N (%) | 3 (9.7) | 5 (4.2) | 3 (5.1) | 2 (4.1) | 0 (0.0) | 0 (0.0) | |||
NA, N (%) | 3 (9.7) | 8 (6.7) | 15 (25.4) | 28 (57.1) | 36 (63.2) | 36 (100.0) | |||
HBV DNA, Log IU/mL | 8.23(8.23, 8.23) | 7.88(6.25, 8.23) | 3.76(3.24, 4.48) | 1.86(1.35, 2.97) | <0.001† | 7.98(7.20, 8.23) | 7.70(6.48, 8.19) | 0.081† | |
HBsAg, IU/mL | 4.63 (4.45, 4.72) | 4.04(3.42, 4.53) | 3.15(2.28, 3.42) | 2.96(2.04, 3.55) | <0.001† | 4.12(3.60, 4.47) | 3.98(3.27, 4.31) | 0.099† |
Data are presented as median (interquartile range) or N (%). All continuous variables did not conform to the normal distribution.
*P-values were calculated using the chi-square test.
†P-values were calculated using the Kruskal–Wallis H test.
‡P-values were calculated using the Mann–Whitney U test.
Abbreviations: IT, immune-tolerant; IA, immune-active; GZ, gray zone; IC, inactive carrier; ETV, entecavir; PEG: Peg-interferon; BMI: body mass index; TBIL: total bilirubin; HBeAg: hepatitis B e antigen; NA, not available; HBsAg: hepatitis B surface antigen.
We profiled CD69 expression on the CD3+, CD4+, and CD8+ T subsets in treatment-naive patients. Only CD69 expression on CD8+ T cells was lower in patients with CHB than in HCs (P=0.038) (Fig. 1A). CD69 expression on T cells did not significantly differ between patients in the IT, GZ, and IC phases and HCs but was the lowest in patients in the IA phase (Fig. 1B and 1C). The mean fluorescence intensity (MFI) of CD69 on T cells also differed between patients in the different phases and HCs (Fig. 1D and 1E).
We next explored the correlation between CD69 levels on T cells and liver inflammation and fibrosis. The CD69 levels on T cells and their subsets were negatively correlated with ALT, AST, and TBIL (P<0.001), as well as with the Fibroscan value, APRI, FIB-4, and ALB level (P<0.05) (Supplemental Data Fig. S2A). Univariate linear regression analysis revealed that CD69 levels on CD3+, CD4+, and CD8+ T cells were negatively correlated with the above liver inflammation and fibrosis features (all P<0.05), whereas multivariate linear regression analysis showed that CD69 levels on T cells were negatively correlated only with ALT (Supplemental Data Table S2). In addition, the results corroborated that the MFIs of CD69 levels on T cells were negatively correlated with the above liver inflammation and fibrosis features (all P<0.05) (Supplemental Data Fig. S2B).
We further analyzed the correlations between CD69 expression and five inflammatory cytokines produced by T cells in treatment-naive patients with CHB. Patients were divided into CD69high and CD69low groups based on the median CD69 expression level on T cells and their subsets. CD69high patients had significantly lower levels of IL-2 (all P<0.001 for CD3+, CD4+, and CD8+ T cells), IFN-γ (P<0.001, P=0.001, and P<0.001, respectively), TNF-α (all P<0.001), granzyme B (P=0.009 on CD4+ T cells), and IL-6 (P<0.001 on CD3+ and CD8+ T cells) produced by T cells and their subsets than CD69low patients (Fig. 2). Spearman correlation analysis revealed that all these cytokines were negatively correlated with CD69 levels on T cells and their subsets (P<0.05) (Fig. 2). Uni- and multivariate linear regression analyses showed that IL-2 and TNF-α levels were negatively correlated with CD69 expression on T cells and their subsets (Supplemental Data Table S3). CD69MFIhigh patients had higher inflammatory cytokine levels than CD69MFIlow patients (Supplemental Data Fig. S3). Linear regression analysis showed that the levels of TNF-α produced by CD3+ T cells, granzyme B produced by CD4+ T cells, and IL-6 produced by CD8+ T cells were negatively correlated with CD69 MFI (Supplemental Data Table S4).
In a similar manner, we explored the correlations between CD69 levels and Th cells, including Th1, Th2, Th17, Th22, and T follicular helper (Tfh) cells. CD69high patients had significantly lower frequencies of all these Th cells than CD69low patients (P<0.05) (Fig. 3). CD69 levels on T cells were negatively correlated with Th-cell frequencies (Fig. 3). Univariate linear regression analysis showed that CD69 levels on T cells were negatively correlated with Th-cell frequencies. Uni- and multivariate analyses revealed negative correlations between CD69 levels on T cells and Th2 and Tfh cell frequencies (Supplemental Data Table S5). CD69MFIlow patients had higher Th-cell subset frequencies than CD69MFIhigh patients (Supplemental Data Fig. S4). Uni- and multivariate linear regression analyses revealed a correlation between the CD69 MFIs of CD8+ T cells and Th2 cells (Supplemental Data Table S6).
We further explored the correlations between CD69 and inhibitory molecules on CD3+, CD4+, and CD8+ T cells, including programmed death receptor 1 (PD-1), cytotoxic T lymphocyte-associated antigen-4 (CLTA-4), leukocyte-associated Ig-like receptor-1 (LAIR-1), and lymphocyte activation gene-3 (LAG-3). PD-1 (P<0.001, P<0.001, and P=0.007, respectively) and LAG-3 (all P<0.001) levels on T cells were higher in the CD69high group than in the CD69low group. PD-1, LAIR-1, and LAG-3 levels on T cells were positively correlated with CD69 expression (P<0.05). CLTA-4 and LAIR-1 levels on CD3+ and CD4+ T cells did not significantly differ between the CD69high and CD69low groups, and CTLA-4 and LAIR-1 levels did not correlate with CD69 expression on CD3+ and CD4+ T cells, although CD69 expression on CD8+ T cells was negatively correlated with the CTLA-4 level (Fig. 4).
Uni- and multivariate analyses revealed that CD69 levels on T cells and their subsets positively correlated with PD-1 and LAG-3 levels. LAIR-1 expression positively correlated with CD69 levels on CD3+ and CD4+ T cells according to univariate analysis and with CD69 on CD8+ T cells according to uni- and multivariate analyses. No significant correlation between CD69 expression on CD3+ and CD4+ T cells and CTLA-4 expression was found in linear regression analysis, although CD69 expression on CD8+ T cells negatively correlated with CTLA-4 expression (Supplemental Data Table S7).
Inhibitory molecule expression on T cells was higher in CD69MFIhigh patients than in CD69MFIlow patients (Supplemental Data Fig. S5). In uni- and multivariate linear regression analyses, CTLA-4 positively correlated with CD69 MFI on CD4+ T cells. Conversely, based on univariate analysis alone, it correlated with CD69 expression on CD8+ T cells (Supplemental Data Table S8).
The levels of HBsAg, HBV DNA, and ALT decreased significantly after antiviral therapy (P<0.05, Fig. 5A). CD69 levels on T cells and their subsets significantly decreased after ETV and Peg-IFN therapy for 48 weeks (P<0.05) (Fig. 5B and 5C), as did CD69 MFI on T cells and their subsets (Supplemental Data Fig. S6A), particularly in the ETV group (Supplemental Data Fig. S6B).
Among the 57 patients with CHB who received ETV treatment, 49 were HBeAg-positive at baseline, and eight of them reached HBeAg seroconversion at 48 weeks. Interestingly, CD69 levels on T cells and their subsets at baseline and in week 48 were lower in patients who achieved HBeAg seroconversion than in those who did not (Fig. 5D). ROC analysis showed that the combined or solo expression of CD69 on T cells and their subsets at baseline could predict HBeAg seroconversion in week 48 in ETV-treated patients (all P<0.01, Fig. 5E). The AUC of ROC1 (combined CD69 expression on CD3+, CD4+, and CD8+ T cells) was 0.870 (0.741–0.999), with a sensitivity of 0.909 and a specificity of 0.714. However, there was no significant difference in the CD69 MFI between the HBeAg seroconversion and non-seroconversion groups (P>0.05) (Supplemental Data Fig. S6C).
Liver injury in CHB, driven by immune-mediated inflammation and T-cell immunity, plays a crucial role in disease progression; however, the role of CD69 expression on T cells during chronic HBV infection remains understudied. Our observational study involving 335 treatment-naive patients with CHB revealed that CD69 expression on T cells varies across different disease phases. CD69 levels on T cells and their subsets were lower in patients in the IA phase than in those in the IT, IC, and GZ phases, as well as HCs. CD69 expression on T cells negatively correlated with liver inflammation, fibrosis, inflammatory cytokines produced by T cells, and Th-cell frequencies but positively correlated with the levels of inhibitory molecules PD-1, LAIR-1, and LAG-3 on T cells and their subsets. These findings indicate the important negative regulatory role of CD69 in T-cell immunity and liver inflammation during chronic HBV infection.
CD69 is an activation marker that enhances T-cell immunity and promotes cell proliferation and function that is expressed on the surface of activated T cells [17]. CD69 is crucial in generating an effective immune response against bacteria and viruses [18]. Additionally, CD69 is associated with the ability of T cells to produce cytokines such as IFN-γ, TNF-α, and CD107a [19]. However, recent studies have shown that CD69 functions as a brake on T-cell immunity. CD69-knockout mice are more susceptible to inflammatory diseases induced by Th17 cells, and CD69 loss enhances Th1 and Th17 cell recruitment and tissue damage [20, 21]. In vitro, CD69 negatively regulates lymphocyte egress from lymph nodes, leading to lymphocyte retention, whereas CD69–/– cells can easily egress [22]. CD69 binds to its ligand, oxidized low-density lipoprotein (ox-LDL), to increase PD-1 expression in T cells [23]. These findings highlight the negative regulatory function of CD69 in immune and inflammatory responses. However, the role of CD69 in T-cell immunity and its enhancement of chronic inflammation in humans requires further validation.
Consistent with animal model observations, we identified a negative regulatory role of CD69 in T-cell immunity during chronic HBV infection in patients. In CD69high patients, T-cell cytokine production, liver inflammation, and fibrosis levels were significantly lower. The most distinctive feature of patients in the IA phase was a significantly elevated ALT level due to active immune inflammation in the liver. Previous studies have confirmed T-cell activation in IA patients, characterized by increased T-cell frequencies and cytokine secretion, and decreased inhibitory receptor expression [24, 25]. Concordantly, we observed the lowest CD69 expression on T cells in patients in the IA phase, suggesting a potential negative role of CD69 in regulating T-cell immunity. CD69 also supports the immune-suppressive functions of regulatory T cells (Tregs) and induces PD-1 expression, further indicating its negative role in T-cell immunity [26, 27]. Moreover, we observed a negative correlation between CD69 expression on T cells and that on Th2 and Tfh cells, suggesting that Th-cell suppression may be a mechanism through which CD69 negatively regulates immunity in CHB.
Notably, we observed a decrease in CD69 expression on T cells after 48 weeks of antiviral therapy and a correlation between CD69 expression on T cells and HBeAg seroconversion, which supported that the negative effect of CD69 on T-cell immunity was reduced by antiviral therapy. Few studies have focused on CD69 expression on T cells in patients with CHB receiving antiviral therapy based on nucleoside (acid) analogs or Peg-IFN. The decreased expression of CD69 on T cells after antiviral therapy indicates that Peg-IFN promotes the egress of IA CD69low T cells to combat HBV. Given the uncertainty regarding whether the change in CD69 expression results from the decrease in HBV after antiviral therapy, this explanation must be treated with caution.
HBeAg suppresses host T-cell immunity and induces immune tolerance through mechanisms such as promoting monocytic myeloid-derived suppressor cell proliferation [28], aiding T cells in converting to CD4+CD25+Foxp3+ Tregs via transforming growth factor-β [29], increasing PD-1 expression, reducing cytokine production [30], and inducing natural killer cell dysfunction by enhancing NKG2A expression [31]. HBeAg seroconversion, a critical outcome of CHB antiviral therapy, reflects immune recovery. Consistent herewith, our findings revealed lower CD69 levels on T cells in HBeAg seroconversion patients, suggesting that reduced CD69 expression may alleviate T-cell dysfunction. The lower baseline CD69 levels in patients with HBeAg seroconversion further support the negative effect of CD69 on T-cell immunity, which might contribute to seroconversion after antiviral therapy. However, this hypothesis requires further validation.
The relationships between CD69 and inhibitory receptors are well-established, and potential mechanisms have been elucidated. In patients with non-small cell lung cancer, co-expression of PD-1 and LAG-3 correlated positively with CD69 expression on T cells [32]. In nonhuman primate tumors, CD69-expressing CD8+ tumor-infiltrating lymphocytes simultaneously expressed high levels of PD-1 [33]. Jiménez-Fernández, et al. [23] showed that CD69 can induce PD-1 expression in CD4+ T cells by binding to ox-LDL, with PD-1 and CD69 mRNA levels correlating. Cortés, et al. [34] found that CD69+ Tregs, but not CD69– Tregs, express high levels of CTLA-4. Collectively, these findings suggest that CD69 may promote inhibitory receptor expression, warranting further mechanistic studies.
We observed some inconsistencies in our results. First, some antiviral cytokines did not significantly differ between the CD69MFIlow and CD69MFIhigh groups, whereas most antiviral cytokines did significantly differ, and trends between the CD69low and CD69high groups were consistent. These imperfect data may have resulted from the limited sample size, indicating that future studies should include more cases. Second, the correlations observed between PD-1, LAIR-1, and CTLA-4 with CD69 differed (Fig. 4). CTLA-4 is primarily expressed in activated T cells and translocates to the membrane following activation [35, 36], suggesting a positive correlation between CTLA-4 expression and T-cell activation. In our study, CD69 expression was reduced in activated T cells, indicating a negative correlation between CD69 and CLTA-4, differing from findings for PD-1 and LAIR-1. Further experimental verification is required.
This study included more patients in the IA phase than in other phases. All patients were recruited consecutively and randomly from outpatient departments, and we speculate that this number difference may have several causes. First, patients in the IA phase are more likely to visit the hospital because of elevated ALT levels and clinical symptoms than patients in other phases. Second, with the spread of the hepatitis B vaccine in China, fewer young individuals are infected with HBV, resulting in fewer IT patients.
We also observed an age mismatch among patient groups, which may have had various causes. For treatment-naive patients, the age mismatch among phases was because of the natural course of chronic HBV infection, which is strongly associated with age [15]. For patients receiving antiviral therapy, as Peg-IFN has several side effects, older patients tended to select ETV treatment because of its better safety profile and tolerability. Age is an important factor affecting T-cell number and function [37, 38]; therefore, the age mismatch represents a limitation of our study and restricts the generalizability of our findings. Studies have shown that CD69 on T cells exerts immunosuppressive effects through various mechanisms, including the suppression of Th1 and Th17 responses [20, 21], maintenance of Treg function [27], induction of PD-1 expression on T cells [23], and lymphocyte retention via negative regulation of S1P1 [26]. Functional in vivo or in vitro studies are required to validate the role of CD69 in T-cell inhibition.
In conclusion, CD69 expression on T cells in CHB patients is associated with liver inflammation, fibrosis, T-cell immunity, and HBeAg seroconversion after antiviral therapy. Our findings indicate that CD69 plays a negative regulatory role in T-cell immunity in liver injury, contributes to disease progression, and influences the efficacy of antiviral therapy in CHB. These findings suggest that CD69 may serve as an immunotherapeutic target for the treatment of CHB, warranting further study.
None.
Gu YR and Bi YH contributed to the study conception and design and drafted the manuscript; Huang ZX participated in the experiments; Liao CH and Li XY interpreted the results; Hu H and Xie HP performed the statistical analyses; Huang YH supervised the study. All authors read and approved the final manuscript.
None declared.
This study was supported by the Research and Development Planned Project in Key Areas of Guangdong Province (grant No. 2019B110233002), the Guangdong Basic and Applied Basic Research Foundation (No. 2020A1515010052), the Guangzhou Science and Technology Project (grant No. 202002030431), and the Joint Key Projects of City and Hospital of Guangzhou Science and Technology (grant No. 202201020422).
Supplementary materials can be found via https://doi.org/10.3343/alm.2024.0178