Expression and prognostic importance of lymphocyte activation gene 3 and CD73 in advanced or metastatic hepatocellular carcinoma

Abstract

Objective

In this study, we aimed to investigate the prognostic significance of the expression of lymphocyte activation gene 3 and CD73 in advanced or metastatic hepatocellular carcinoma as well as its predictive effect on disease control rates in patients receiving sorafenib.

Methods

Data from 79 patients diagnosed with hepatocellular carcinoma in 3 different oncology centers between 2012 and 2021 were analyzed. Of these patients, 67 were included in this study based on the inclusion and exclusion criteria. The correlation between the expression of lymphocyte activation gene 3 and CD73 and clinical features was analyzed.

Results

Of the 67 patients included in the study, 80.6% were males, and the median age at diagnosis was 65 (55–73) years. A baseline alpha-fetoprotein level of <400 ng/mL and the presence of lymphocyte activation gene 3 expression were correlated with better survival (p = 0.001 and p = 0.049, respectively). CD73 expression was observed in 45.8% of patients whose disease was under control with sorafenib, while 80% of patients who did not respond to sorafenib showed CD73 expression (p = 0.02).

Conclusions

Positive lymphocyte activation gene 3 expression was correlated with better survival in patients with advanced or metastatic hepatocellular carcinoma. In addition, CD73 expression in patients with advanced or metastatic hepatocellular carcinoma was a negative predictive factor in those receiving sorafenib.

Keywords

Hepatocellular carcinoma lymphocyte activation gene 3 expression CD73 expression sorafenib disease control rate

Introduction

Hepatocellular carcinoma (HCC) constitutes 90% of primary liver cancers. HCC is one of the most common causes of cancer-related death globally.^1–3 Despite surveillance programs and advances in imaging, most patients with HCC consult a physician at an advanced stage, and the 5-year overall survival (OS) rates remain poor—approximately 10% for locally advanced disease and 3% for metastatic disease.^4–7

Over the past decade, the therapeutic landscape of HCC has evolved significantly. Sorafenib, a multikinase inhibitor, was the first systemic agent to demonstrate an OS benefit, establishing targeted therapy as the standard of care in advanced HCC. Subsequently, other tyrosine kinase inhibitors (TKIs), such as lenvatinib, regorafenib, cabozantinib, and ramucirumab, have expanded the treatment options.^8–10 HCC is among the solid cancers with the fewest somatic mutations that can be targeted with molecular therapies, and no mutation has been identified to predict a therapeutic response in clinical practice.¹

Most recently, immune checkpoint inhibitors (ICIs) have revolutionized the treatment of advanced HCC. The IMbrave150 trial demonstrated that the combination of atezolizumab and bevacizumab significantly improved OS and progression-free survival (PFS) compared with sorafenib, establishing a new standard of care in the first-line setting.¹¹ Furthermore, the HIMALAYA trial showed that durvalumab plus tremelimumab improved outcomes, highlighting the potential of ICI-based combinations.¹² Ongoing investigations are exploring additional targets, including lymphocyte activation gene (LAG)-3, TIGIT, and the adenosine pathway regulator CD73, further underscoring the rapidly evolving HCC treatment landscape.

Understanding the interaction between the cancer cell and its microenvironment is crucial for developing new treatments and identifying biomarkers.^1,13,14 Clinically relevant immune checkpoint proteins include cytotoxic T lymphocyte–associated antigen (CTLA)-4, programmed cell death protein (PD)-1, and programmed cell death ligand (PD-L)-1.¹⁵ LAG-3 is an another important ICI that has a synergistic effect with PD-1/PD-L1 on T cell activation in the tumor microenvironment, thereby downregulating T cell proliferation and activation.^16,17 LAG-3 expression is significantly correlated with prognosis and clinicopathological features in various cancer types.¹⁸

CD73, an adenosine monophosphate (AMP) hydrolyzing enzyme that regulates the conversion of extracellular adenosine triphosphate (ATP) to adenosine, is a potent immunosuppressor that maintains tissue homeostasis and prevents immune responses during inflammation.¹⁹ In cancer, CD73 is expressed by many cell subsets that populate the tumoral space, including tumor cells, stromal cells, and endothelial cells, as well as infiltrating immune cells.²⁰ High expression of CD73 has been correlated with shorter OS and poor prognosis in certain cancer types such as melanoma and breast and ovarian cancers.^21,22

In this study, we aimed to investigate the prognostic significance of the expression of LAG-3 and CD73 in advanced or metastatic HCC as well as its predictive effect on disease control rates (DCRs) in patients receiving sorafenib.

Patient and methods

Study participants

Data from 79 patients diagnosed with HCC in 3 different oncology centers between 2012 and 2021 were analyzed. The study included patients with locally advanced or metastatic HCC and a histopathological diagnosis, while patients with no recurrence after resection or transplantation and those with only a radiological diagnosis of HCC were excluded. The study included 67 patients whose tissue or resection blocks were located in the pathology laboratories of three different centers (Figure 1). Demographic and patient data, including age, sex, Eastern Cooperative Oncology Group (ECOG) performance score (PS), date of diagnosis, Barcelona Clinic of Liver Cancer (BCLC) score, extrahepatic metastasis, macrovascular invasion, cirrhosis, alpha-fetoprotein (AFP) level (AFP, <400 vs. ≥400 ng/mL), first-line chemotherapy or molecular-targeted therapies, date of recurrence, and date of last assessment were obtained from archived patient files. The study was conducted based on the principles of the Declaration of Helsinki (as revised in 2024). This multicenter study was approved by the ethics committee of our hospital (approval number: 514/196/2). All patients provided their informed consent.

Figure 1.

Flow chart of patient selection in our observational study.

PFS was defined as the time from the start of the first series of therapy to the date of progression or death from any cause. OS was calculated as the time from the start of the first series of therapy to the date of death from any cause or withdrawal from follow-up assessment. PFS and OS values were estimated using the Kaplan–Meier method, and comparisons between survival curves were performed using the log-rank test.

The DCR was defined as the sum of the proportions of patients with advanced HCC who achieved a partial response (PR) and stable disease (SD) with treatment (DCR = PR + SD).

Immunohistochemical examination

The protein expression levels of LAG-3 and CD73 were detected via immunohistochemical examination. For immunohistochemical examination, 4-µm thick sections prepared from formalin-fixed, paraffin-embedded tissues were used. Histological sections were placed on electrostatically charged slides (TOMO, Japan) and dried at 70°C for at least 1 h. The entire immunohistochemical staining process, including deparaffinization and antigen retrieval, was conducted on a fully automated immunohistochemistry stainer (Ventana BenchMark XT; Ventana Medical Systems, Tucson, AZ). A ready-made kit (ultraView Universal DAB Detection Kit; Catalog number 760–500; Ventana Medical Systems) suitable for the instrument—containing biotin-free, horseradish peroxidase (HRP) multimer-based hydrogen peroxide substrate and 3,3′-diaminobenzidine tetrahydrochloride (DAB) chromogen—was used. Antibodies against LAG-3 (dilution: 1:500; Abcam, MA, USA) and CD73 (dilution: 1:200; Cell Signaling, MA, USA) were used. Although the contrast staining was performed using a staining device, the process was completed by manually performing dehydration and xylene clearing of coverslipped sections.

The cases were evaluated by two pathologists (KB/SK) using an Olympus BX53 microscope (WHN10X/22). Cytoplasmic/membranous staining of tumor cells with CD73 expression was considered a positive result. Cases showing no expression were scored as 0, those with mild expression as 1, and those with strong expression as 2. Cytoplasmic/membranous staining of lymphocytes with LAG3 expression was considered a positive result. Stained lymphocytes in a 1-mm² hotspot area were assessed.

Statistical analysis

Statistical analyses were performed using SPSS 22.0 (SPSS Inc., Chicago, IL, USA). Descriptive statistics were presented as mean ± SD or median (minimum–maximum) for numerical variables and as frequency (percentage) for categorical variables. Normality was assessed using the Kolmogorov–Smirnov or Shapiro–Wilk test. Comparisons between two independent numerical variables were conducted using Student’s t-test for normally distributed data and Mann–Whitney U test for non-normally distributed data. Categorical variables were compared using the chi-square or Fisher’s exact test.

Survival analyses were performed using the Kaplan–Meier method, and comparisons between survival curves were evaluated using the log-rank test. The DCR was defined as the proportion of patients achieving PR or SD with treatment. Prognostic factors associated with PFS and OS were examined using Cox regression models, with variables showing p < 0.20 in the univariate analysis included in the multivariate model through stepwise backward elimination. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated. A p value of <0.05 was considered statistically significant.

Results

Clinical characteristics of the patients

Of the 67 patients included in the study, 80.6% were males and 19.4% were females; the median age at diagnosis was 65 (55–73) years. The median follow-up period was 10.6 (range, 1.18–68.99) months. With a rate of 61.2%, hepatitis B was the most common risk factor. The baseline AFP level was ≥400 ng/mL in 34.3% of the patients. Extrahepatic disease was present in 40.3% of the patients, and 40.3% of the patients had macrovascular invasion. Forty-four (65.7%) patients received sorafenib, ten (14.9%) received gemcitabine–oxaliplatin, six (9.0%) received anthracycline, and 1 (1.5%) received capecitabine regimens as the first-line chemotherapy. Clinical and demographic characteristics of the patients are shown in Table 1.

Table 1.

Baseline characteristics of patients (N = 67).

Characteristic	Value
Age (years), median (interquartile range)	65 (55–73)
Sex, n (%)
Female	13 (19.4)
Male	54 (80.6)
ECOG performance score, n (%)
0	25 (37.3)
1	32 (47.8)
2	10 (14.9)
Cause of disease, n (%)
Hepatitis B	41 (61.2)
Hepatitis C	6 (9.0)
NASH	6 (9.0)
Unknown	14 (20.8)
Comorbidity, n (%)
Hypertension	24 (25.8)
Diabetes mellitus	14 (20.9)
Coronary artery disease	7 (10.4)
Other	4 (6.0)
Extrahepatic disease, n (%)	27 (40.3)
Cirrhosis, n (%)	42 (62.7)
BCLC stage, n (%)
A	31(46.3)
B	15 (22.4)
C	17 (25.4)
D	1 (1.5)
Previous TACE therapy, n (%)	19 (28.4)
Baseline serum AFP level, median (interquartile range)	37 (8.3–1246.5)
Baseline AFP concentration group, n (%)
<400	44 (65.7)
≥400	23 (34.3)
Child-Pugh class, n (%)
A	51 (76.1)
B	12 (17.9)
Missing	3 (6.0)
Extrahepatic disease, n (%)	27 (40.3)
Lung	10 (14.9)
Lymph node	8 (11.9)
Bone	4 (6.0)
Other	5 (7.5)
Macrovascular invasion, n (%)	29 (43.3)
First-line therapy option, n (%)
Sorafenib	44 (65.7)
Gemcitabine–oxaliplatin	10 (14.9)
Anthracycline	6 (9.0)
Capecitabine	1 (1.5)
Missing	5 (7.5)

AFP: alpha-fetoprotein; BCLC: Barcelona Clinic of Liver Cancer; ECOG: Eastern Cooperative Oncology Group; NASH: nonalcoholic steatohepatitis; TACE: transarterial chemoembolization.

Expression patterns of LAG-3 and CD73

Positive LAG-3 expression was observed in 41.8% of the patients, while no expression was observed in 58.2%. The positive expression rate of CD73 was 62.7% (42/67) (Table 2). CD73 staining pattern of the patients is shown in Figure 2 (no staining in tumor cells ((Figure 2(a)) and diffuse membranous staining in tumor cells (Figure 2(b)). LAG-3 staining pattern is displayed in Figure 3 (no staining of lymphocytes infiltrating the tumor cells with LAG-3 expression (Figure 3(a)) and staining of lymphocytes infiltrating the tumor cells with LAG-3 expression (Figure 3(b)).

Table 2.

Histopathological findings of the study participants (N = 67).

Findings	Value, n (%)
CD73 expression
Negative	25 (37.3)
Positive	42 (62.7)
LAG-3 expression
Negative	39 (58.2)
Positive	28 (41.8)

LAG-3: lymphocyte activation gene-3.

Figure 2.

Staining in tumor cells with CD73 expression (scale bar = 50 μm).

Figure 3.

Lymphocytes infiltrating the tumor cells with lymphocyte activation gene 3 expression (scale bar = 50 μm).

Predictive value of LAG-3 and CD73 expression for sorafenib response

Considering the correlation between LAG-3 and CD73 expression and DCR, LAG-3 expression was observed in 33.3% of the patients whose disease was controlled with sorafenib, while LAG-3 expression was observed in 50% of the patients who showed progression with sorafenib treatment, and the difference was not statistically significant (p = 0.35). CD73 expression was observed in 45.8% of the patients whose disease was under control with sorafenib, while 80% of the patients who did not respond to sorafenib showed CD73 expression. CD73 expression was found to be a negative predictive factor for sorafenib response (p = 0.02) (Table 3).

Table 3.

Association between CD73 and LAG-3 expression and sorafenib with regard to disease control rate (n = 44).

	DCR (+), n = 24	DCR (−), n = 20	p
LAG-3 expression, n (%)	8 (33.3)	10 (50.0)	0.35
CD73 expression, n (%)	11 (45.8)	16 (80.0)	0.02

Data in bold indicate statistically significant results.

DCR: disease control rate; LAG-3: lymphocyte activation gene-3.

Prognostic factors for OS and PFS

In the univariate survival analysis via the Kaplan–Meier method, a baseline AFP level of <400 ng/mL (p < 0.001), being ranked as Child-Pugh class A (p = 0.006), and absence of extrahepatic disease (p = 0.01) were found to be the most important independent factors affecting OS. In addition, the presence of LAG-3 expression in the univariate analysis was found to be a significant factor for survival (p = 0.05). The median OS times of patients with the identified risk factors are shown in Table 4. Based on the survival curve, patients with LAG-3 expression exhibited a trend toward better survival compared with those without (p = 0.050) (Figure 4).

Table 4.

Univariate analysis of potential prognostic factors for overall survival.

	Median (month)	95% CI	p
Age (years)
<60	10.6	4.5–16.4	0.74
≥60	10.5	4.2–16.8	0.74
Sex
Female	20.2	8.0–32.3	0.19
Male	9.2	5.6–12.8	0.19
ECOG performance score
0–1	12.9	8.5–17.3	0.31
2	5.2	3.7–6.7	0.31
Cause of disease
Viral hepatitis	11.5	5.3–17.7	0.89
Other	10.5	7.1–14.0	0.89
Cirrhosis
Present	9.6	5.2–14.1	0.12
Absent	13.9	6.4–21.4	0.12
Previous TACE therapy
Present	14.1	13.3–14.8	0.19
Absent	8.9	6.6–11.1	0.19
Baseline AFP concentration group (ng/mL)
<400	14.4	11.1–17.7	<0.001
≥400	7.5	4.9–10.1	<0.001
Child-Pugh class
A	13.6	9.2–18.0	0.006
B	5.7	3.2–8.2	0.006
Extrahepatic disease
Present	8.0	2.1–13.9	0.01
Absent	14.0	8.8–19.2	0.01
Macrovascular invasion
Present	9.2	5.4–13.0	0.20
Absent	14.0	8.5–19.6	0.20
First-line therapy option
Sorafenib	9.2	6.1–12.3	0.59
Other	13.6	2.2–25.0	0.59
CD73 expression
Present	8.9	6.1–11.6	0.12
Absent	14.0	13.3–14.8	0.12
LAG-3
Present	17.0	1.0–33.0	0.05
Absent	10.5	7.4–13.7	0.05

Kaplan–Meier, Log-rank test, p < 0.05 indicates statistically significant results. Data in bold indicate statistically significant results.

AFP: alpha-fetoprotein; ECOG: Eastern Cooperative Oncology Group; LAG-3: lymphocyte activation gene-3; HR: hazard ratio; TACE: transarterial chemoembolization.

Figure 4.

The association between lymphocyte activation gene (LAG)-3 expression and survival.

In the univariate Cox regression analysis, a baseline AFP level of <400 ng/mL, being ranked as Child-Pugh class A, and absence of extrahepatic disease were significantly correlated with better survival (p < 0.001, p = 0.007, and p = 0.013, respectively). The variables cirrhosis, CD73 expression, and presence of LAG-3 were included in the multivariate model based on the threshold of p < 0.200. According to the results of the multivariate model, the presence of cirrhosis increased the risk of death by 1.98-fold (HR: 1.98; 95% CI: 1.02–3.85; p = 0.043), and the presence of CD73 expression increased the risk of death by 2.31-fold (HR: 2.31; 95% CI: 1.23–4.34; p = 0.009). However, having a baseline AFP level of <400 ng/mL (HR: 0.36; 95% CI: 0.18–0.73; p = 0.005) and the presence of LAG-3 (HR: 0.63; 95% CI: 0.32–1.22; p = 0.048) were found to decrease the risk of death (Table 5).

Table 5.

Univariate and multivariate Cox regression analysis of overall survival.

Variable, n (%)	Univariate analysis			Multivariate analysis
Variable, n (%)	HR	95% CI	p	HR	95% CI	p
Age (years)
<60	ref
≥60	0.91	0.52–1.58	0.747
Sex
Female, 13 (19.4)	0.62	0.30–1.28	0.201
Male, 54 (80.6)	ref
ECOG performance score
0–1, 57 (85.1)	ref
2, 10 (14.9)	1.46	0.68–3.13	0.320
Cause of disease
Viral hepatitis, 47 (70.2)	1.04	0.57–1.89	0.897
Other, 20 (29.8)	ref
Cirrhosis
Present, 42 (62.7)	1.58	0.88–2.82	0.123	1.98	1.02–3.85	0.043
Absent, 25 (37.3)	ref			ref
Previous TACE therapy
Present, 19 (28.4)	0.67	0.37–1.23	0.202
Absent, 48 (72.6)	ref
Baseline AFP concentration group (ng/mL)
<400, 44 (65.7)	0.31	0.17–0.56	<0.001	0.28	0.13–0.58	0.001
≥400, 23 (34.3)	ref			ref
Child-Pugh class
A, 51 (76.1)	0.40	0.20–0.78	0.007	0.48	0.23–1.02	0.058
B, 12 (17.9)	ref			ref
Extrahepatic disease
Present, 27 (40.3)	2.03	1.16–3.55	0.013	1.04	0.53–2.03	0.902
Absent, 50 (59.7)	ref			ref
Macrovascular invasion
Present, 29 (43.3)	1.45	0.81–2.58	0.209
Absent, 38 (56.7)	ref
First-line therapy option
Sorafenib, 44 (65.7)	1.17	0.64–2.15	0.591
Other, 17 (25.4)	ref
CD73 expression
Present, 42 (62.7)	1.56	0.88–2.76	0.126	2.31	1.23–4.34	0.009
Absent, 25 (37.3)	ref			ref
LAG-3
Present, 28 (41.8)	0.59	0.33–1.05	0.076	0.63	0.32–1.22	0.048
Absent, 39 (58.2)	ref			Ref
				−2 Log likelihood = 309,70, p < 0.001

AFP: alpha-fetoprotein; ECOG: Eastern Cooperative Oncology Group; LAG-3: lymphocyte activation gene-3; HR: hazard ratio.

Data in bold indicate statistically significant results.

In the univariate Cox regression analysis for PFS after the first series of treatments, prior transarterial chemoembolization (TACE) was significantly correlated with better PFS (p = 0.01), and the absence of CD73 expression showed a trend toward better PFS (p = 0.06). The median PFS times after the first series of treatments are shown in Table 6.

Table 6.

Univariate analysis of progression-free survival under first-line therapy setting.

	Median PFS (month)	95% CI	p
Age (years)
<60	4.9	1.7–8.0	0.55
≥60	5.6	3.2–8.0
Sex
Female	8.9	3.9–13.9	0.15
Male	4.3	2.3–6.4
ECOG performance score
0–1	5.8	3.8–7.8	0.17
2	3.3	2.8–3.8
Cause of disease
Viral hepatitis	4.3	2.5–6.2	0.96
Other	6.4	4.9–7.8
Cirrhosis
Present	5.6	2.6–8.6	0.45
Absent	4.3	0.6–8.1
Previous TACE therapy
Present	8.9	5.4–12.3	0.01
Absent	4.0	3.1–4.8
Baseline AFP concentration group (ng/mL)
<400	6.1	3.8–8.4	0.06
≥400	4.0	2.8–5.1
Child-Pugh class
A	5.6	2.3–8.9	0.16
B	3.5	3.1–3.8
Extrahepatic disease
Present	4.9	2.3–7.4	0.25
Absent	6.1	3.2–9.0
Macrovascular invasion
Present	4.9	2.1–7.7	0.40
Absent	6.1	5.2–7.0
First-line therapy option
Sorafenib	6.1	4.2–7.9	0.98
Other	4.1	2.2–6.0
CD73 expression
Present	3.5	2.4–4.6	0.06
Absent	6.8	4.2–9.3
LAG-3
Present	4.0	3.5–4.5	0.62
Absent	6.4	4.7–8.0

Data in bold indicate statistically significant results.

AFP: alpha-fetoprotein; ECOG: Eastern Cooperative Oncology Group; LAG-3: lymphocyte activation gene-3; PFS: progression-free survival; TACE: transarterial chemoembolization.

Discussion

The current study investigated the prognostic significance of the expression of LAG-3 and CD73 in advanced or metastatic HCC as well as its predictive effect on DCRs in patients receiving sorafenib. LAG-3 expression was correlated with better survival, and CD73 expression was found to be a negative predictive factor for sorafenib response.

Activation of the immune system with checkpoint inhibitors has revolutionized the treatment of cancer and is considered important for HCC treatment.¹³ The most studied ex vivo and clinically relevant checkpoint proteins in HCC include CTLA-4, PD-1, and PD-L1.¹⁶ Expression of ICIs may be irregular in the tumor microenvironment, leading to the enhancement of T cell–mediated immune response through cancer immunotherapy.¹⁵ Although the CTLA-4 pathway is primarily involved in the regulation of T cell–mediated immune responses in lymph nodes in the initial stages, a study showed that the PD-1 pathway mainly suppresses T cell activation in peripheral tissues at the final stage.²³ In the HCC tumor microenvironment, PD-L1 is not only mainly expressed on Kupffer cells but also slightly expressed on other antigen-presenting cells (APCs) or HCC tumor cells.²⁴ In many studies, high PD-L1 expression in HCC has been shown to be correlated with worse prognosis. PD-L1 expressed on peritumoural hepatocytes has been shown to significantly increase both the risk of cancer recurrence and cancer-related death in patients with HCC.^24–26 In previous studies, it has been shown that LAG-3, an inhibitory receptor, is upregulated in various tumor types and suppresses the proliferation, activation, and effector functions of T cells.¹⁸ Increasing evidence has shown that patients with high LAG-3 expression (≥1%) tend to respond to immunotherapy.^27,28

Guo et al.²⁹ analyzed 143 patients with HCC and reported high LAG-3 expression in 42% of the patients and low LAG-3 expression in 58%. In another study, Yarchoan et al.³⁰ found that LAG-3 expression was high in 52% of the 29 analyzed patients with HCC. In the current study, we observed positive LAG-3 expression in 41.8% of the patients. Both studies analyzed patients for low or high LAG-3 expression levels. However, in the current study, we scored the staining rate of LAG-3 in tumor cells semiquantitatively.

High LAG-3 expression was correlated with worse OS and disease-free survival in studies evaluating some tumors, such as head and neck squamous cell carcinomas,³¹ melanoma,³² non–small cell lung cancer (NSCLC),³³ and sarcoma.³⁴ In studies evaluating tumors such as breast cancer,³⁵ esophageal squamous cell carcinoma,³⁶ and NSCLC,³⁷ high LAG-3 expression was correlated with better OS. Guo et al.²⁹ found high LAG-3 expression levels in HCC tumor tissue as an independent predictive factor for low OS and PFS. Xie et al.,³⁸ on the contrary, found that high or low LAG-3 expression in HCC did not have a prognostic effect on OS and DFS. In our study, LAG-3 expression was identified as an independent prognostic factor for OS in patients with HCC, similar to other established prognostic factors such as Child-Pugh class A and AFP <400 ng/mL in multivariate analysis. In our study, positive LAG-3 expression was correlated with better OS. Tumor microenvironment as well as different tumor subtypes and patient subgroups may have contributed to this difference in the literature. Due to the limited number of studies in the literature on the prognostic importance of LAG-3 expression in HCC, we consider that the current study will contribute to the literature related to this topic during the maturation of the available data.

CD73 plays a crucial role in adenosinergic signaling by catalyzing AMP to adenosine.³⁹ Therefore, CD73 has been studied for immunosuppression functions and has shown promise as a potential immunocheckpoint target in suppressing tumor growth.^40,41

High expression of CD73 has been reported in many epithelial malignancies, and it has been shown that CD73 supports tumor growth and metastasis in these malignancies.^42,43 Studies on CD73 expression in HCC are limited. Shali et al.⁴⁴ found that CD73 upregulated epithelial growth factor receptor expression in HCC and stimulated tumor growth and metastasis in HCC. Ma et al.⁴⁵ observed that high CD73 expression was correlated with shorter OS and higher mortality in patients with HCC. Consistently, the present study demonstrated that positive CD73 expression was associated with increased mortality. The current study showed a potential significant effect of CD73 expression on PFS (p = 0.06). This study would have better predicted CD73-related PFS if the study had been conducted only among patients receiving sorafenib.

Bruix et al.⁴⁶ analyzed the prognostic and predictive factors of sorafenib benefit in patients with HCC by combining patients from two phase 3 studies. In this study, 827 patients were analyzed; the absence of extrahepatic spread and hepatitis C virus positivity and the low neutrophil–lymphocyte ratio were positive predictive factors in those who received sorafenib. Lin et al.⁴⁷ found that the blockade of CD73 may increase the therapeutic efficacy of adjuvant chemotherapy and radiotherapy by increasing APC maturation for T cell activation.⁴⁷ In the current study, the clinical and laboratory findings revealed that high CD73 expression was a negative predictive factor in those treated with sorafenib (p = 0.02).

Limitations

The retrospective design and the relatively small number of patients were the most important limitations of our study. No formal power analysis was conducted as the study was based on available archival tissue samples. In addition, a standardized method for the immunohistochemical evaluation of LAG-3 and CD73 expression has not yet been established, which may have introduced variability in interpretation. Furthermore, external validation in independent cohorts was not performed, and functional in vitro or in vivo analyses to confirm the biological role of these markers were lacking. These factors should be considered when interpreting the results. In addition, a standard has not yet been determined in immunohistochemical evaluation, and data on LAG-3 and CD73 expression levels could not be provided.

Strengths

We consider that this study is important in terms of determining CD73 expression as a predictive factor for sorafenib treatment in patients with HCC. In addition, as LAG-3 and CD73 expression levels in all patients were evaluated by a single investigative pathologist in this study, individual biases and different pathological evaluations were avoided. There are limited studies on this topic in the literature, and our study may provide new insights and guide the evaluation of prognostic and predictive markers with the combined use of clinical pathological findings and other immune system–related findings.

Future perspectives and recommendations

In the context of sustainable approaches in oncology, repurposing existing drugs (e.g. GLP-1–based therapies) or targeting the proteasome as well as utilizing natural compounds such as prodigiosin or hinokitiol for their immunomodulatory effects in a prophylactic setting are considered promising strategies with potential positive impact.^48–50 Such approaches may help overcome resistance mechanisms to immunotherapy and offer more effective personalized treatment options in HCC.

In conclusion, this study suggests that positive LAG-3 expression shows a trend toward better survival in patients with advanced or metastatic HCC. Additionally, CD73 expression showed a trend toward being a potential predictor of shorter duration of sorafenib response in these patients. This finding raises interest regarding its potential predictive role; however, further large-scale studies are needed to validate these findings and explore their potential clinical implications.

Footnotes

Acknowledgements

We used AI-assisted language editing (ChatGPT, OpenAI) for English clarity.

Author contributions

Conceptualization: Murat Ayhan and Sevinç Hallaç Keser; Data curation: Rukiye Arıkan; Formal analysis: Nadiye Akdeniz, Mahmut Yıldırım, and Hatice Odabaş; Investigation: Muhammed Atcı and Nedim Turan; Methodology: Murat Ayhan; Project administration: Rukiye Arıkan and Osman Kostek; Resources: Selma Şengiz Erhan and Osman Kostek; Software: Kayhan Başak; Supervision: Akif Doğan, Şahin Laçin, and Sedat Yıldırım; Validation: Murat Ayhan, Akif Doğan, Nedim Turan, and Sedat Yıldırım; Visualization: Mahmut Yıldırım, Şahin Laçin, and Hatice Odabaş; Writing–original draft: Murat Ayhan; Writing–review & editing: Kayhan Başak and Çigdem Çelikel.

Data availability statement

The data supporting this study’s findings are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

No specific funding was obtained for this work.

ORCID iD

Murat Ayhan

References

Villanueva

Hepatocellular carcinoma. N Engl J Med 2019; 380: 1450–1462.

Forner

Reig

Bruix

Hepatocellular carcinoma. Lancet 2018; 391: 1301–1314.

Hammad

Aglan

Mohammed

, et al. Cytotoxic T cell expression of leukocyte-associated immunoglobulin-like receptor-1 (LAIR-1) in viral hepatitis C-mediated hepatocellular carcinoma. Int J Mol Sci 2022; 23: 12541.

Arciero

Sigurdson

ER.

Liver-directed therapies for hepatocellular carcinoma. J Natl Compr Canc Netw 2006; 4: 768–774.

Connell

Harding

Abou-Alfa

GK.

Advanced hepatocellular cancer: the current state of future research. Curr Treat Options Oncol 2016; 17: 43.

Rizzo

Ricci

Brandi

Trans-arterial chemoembolization plus systemic treatments for hepatocellular carcinoma: an update. J Pers Med 2022; 12: 1788.

Rizzo

Dadduzio

Ricci

, et al. Lenvatinib plus pembrolizumab: the next frontier for the treatment of hepatocellular carcinoma? Expert Opin Investig Drugs 2022; 31: 371–378.

El Dika

Khalil

Abou-Alfa

GK.

Immune checkpoint inhibitors for hepatocellular carcinoma. Cancer 2019; 125: 3312–3319.

Hamdy

Basalious

El-Sisi

, et al. Advancements in current one-size-fits-all therapies compared to future treatment innovations for better improved chemotherapeutic outcomes: a step-toward personalized medicine. Curr Med Res Opin 2024; 40: 1943–1961.

10.

Rizzo

Ricci

AD.

Challenges and future trends of hepatocellular carcinoma immunotherapy. Int J Mol Sci 2022; 23: 11363.

11.

Carloni

Sabbioni

Rizzo

, et al. Immune-based combination therapies for advanced hepatocellular carcinoma. J Hepatocell Carcinoma 2023; 10: 1445–1463.

12.

Vitale

Rizzo

Santa

, et al. Associations between “cancer risk”, “inflammation” and “metabolic syndrome”: a scoping review. Biology (Basel) 2024; 13: 352.

13.

Hamdy

Zaki

Rizk

, et al. Unraveling the ncRNA landscape that governs colorectal cancer: a roadmap to personalized therapeutics. Life Sci 2024; 354: 122946.

14.

Sia

Jiao

Martinez-Quetglas

, et al. Identification of an immune-specific class of hepatocellular carcinoma, based on molecular features. Gastroenterology 2017; 153: 812–826.

15.

Philips

Atkins

Therapeutic uses of anti-PD-1 and anti-PD-L1 antibodies. Int Immunol 2015; 27: 39–46.

16.

Jin

Zhu

, et al. Immune checkpoint therapy in liver cancer. J Exp Clin Cancer Res 2018; 37: 110.

17.

Workman

Vignali

DA.

Negative regulation of T cell homeostasis by lymphocyte activation gene-3 (CD223). J Immunol 2005; 174: 688–695.

18.

Long

Zhang

Chen

, et al. The promising immune checkpoint LAG-3: from tumor microenvironment to cancer immunotherapy. Genes Cancer 2018; 9: 176–189.

19.

Antonioli

Pacher

Vizi

, et al. CD39 and CD73 in immunity and inflammation. Trends Mol Med 2013; 19: 355–367.

20.

Vijayan

Young

Teng

MWL

, et al. Targeting immunosuppressive adenosine in cancer. Nat Rev Cancer 2017; 17: 709–724. Erratum in: Nat Rev Cancer. 2017; 17: 765.

21.

Monteiro

Vigano

Faouzi

, et al. CD73 expression and clinical significance in human metastatic melanoma. Oncotarget 2018; 9: 26659–26669.

22.

Jiang

Qiao

, et al. Comprehensive evaluation of NT5E/CD73 expression and its prognostic significance in distinct types of cancers. BMC Cancer 2018; 18: 267.

23.

Buchbinder

Desai

CTLA-4 and PD-1 pathways: similarities, differences, and implications of their inhibition. Am J Clin Oncol 2016; 39: 98–106.

24.

Kryczek

Chen

, et al. Kupffer cell suppression of CD8+ T cells in human hepatocellular carcinoma is mediated by B7-H1/programmed death-1 interactions. Cancer Res 2009; 69: 8067–8075.

25.

Calderaro

Rousseau

Amaddeo

, et al. Programmed death ligand 1 expression in hepatocellular carcinoma: relationship with clinical and pathological features. Hepatology 2016; 64: 2038–2046.

26.

Dai

Xue

, et al. Positive expression of programmed death ligand 1 in Peritumoral liver tissue is associated with poor survival after curative resection of hepatocellular carcinoma. Transl Oncol 2017; 10: 511–517.

27.

Ascierto

Bono

Bhatia

, et al. Efficacy of BMS-986016, a monoclonal antibody that targets lymphocyte activation gene-3 (LAG-3), in combination with nivolumab in pts with melanoma who progressed during prior anti–PD-1/PD-L1 therapy (mel prior IO) in all-comer and biomarker-enriched populations. Ann Oncol 2017; 28: V611–V612.

28.

Tawbi

Schadendorf

Lipson

; RELATIVITY-047 Investigatorset al. Relatlimab and nivolumab versus nivolumab in untreated advanced melanoma. N Engl J Med 2022; 386: 24–34.

29.

Guo

Yuan

, et al. Expression and clinical significance of LAG-3, FGL1, PD-L1 and CD8⁺T cells in hepatocellular carcinoma using multiplex quantitative analysis. J Transl Med 2020; 18: 306.

30.

Yarchoan

Xing

Luan

, et al. Characterization of the immune microenvironment in hepatocellular carcinoma. Clin Cancer Res 2017; 23: 7333–7339.

31.

Deng

Mao

, et al. LAG-3 confers poor prognosis and its blockade reshapes antitumor response in head and neck squamous cell carcinoma. Oncoimmunology 2016; 5: e1239005.

32.

Lee

Choi

, et al. Expression of lymphocyte-activating gene 3 and T-cell immunoreceptor with immunoglobulin and ITIM domains in cutaneous melanoma and their correlation with programmed cell death 1 expression in tumor-infiltrating lymphocytes. J Am Acad Dermatol 2019; 81: 219–227.

33.

Rozeboom

, et al. LAG-3 protein expression in non-small cell lung cancer and its relationship with PD-1/PD-L1 and tumor-infiltrating lymphocytes. J Thorac Oncol 2017; 12: 814–823.

34.

Que

Fang

Guan

, et al. LAG-3 expression on tumor-infiltrating T cells in soft tissue sarcoma correlates with poor survival. Cancer Biol Med 2019; 16: 331–340.

35.

Burugu

Gao

Leung

, et al. LAG-3+ tumor infiltrating lymphocytes in breast cancer: clinical correlates and association with PD-1/PD-L1+ tumors. Ann Oncol 2017; 28: 2977–2984.

36.

Zhang

Liu

Luo

, et al. Prognostic value of lymphocyte activation gene-3 (LAG-3) expression in esophageal squamous cell carcinoma. J Cancer 2018; 9: 4287–4293.

37.

Hald

Rakaee

Martinez

, et al. LAG-3 in non-small-cell lung cancer: expression in primary tumors and metastatic lymph nodes is associated with improved survival. Clin Lung Cancer 2018; 19: 249–259.e2.

38.

Xie

, et al. OX40 expression in hepatocellular carcinoma is associated with a distinct immune microenvironment, specific mutation signature, and poor prognosis. Oncoimmunology 2018; 7: e1404214.

39.

Allard

Longhi

Robson

, et al. The ectonucleotidases CD39 and CD73: Novel checkpoint inhibitor targets. Immunol Rev 2017; 276: 121–144.

40.

Beavis

Divisekera

Paget

, et al. Blockade of A2A receptors potently suppresses the metastasis of CD73+ tumors. Proc Natl Acad Sci U S A 2013; 110: 14711–14716.

41.

Kordaß

Osen

Eichmüller

SB.

Controlling the immune suppressor: transcription factors and microRNAs regulating CD73/NT5E. Front Immunol 2018; 9: 813.

42.

Zhang

CD73 promotes tumor growth and metastasis. Oncoimmunology 2012; 1: 67–70.

43.

Wang

Zhou

, et al. Ecto-5'-nucleotidase promotes invasion, migration and adhesion of human breast cancer cells. J Cancer Res Clin Oncol 2008; 134: 365–372.

44.

Shali

Zhang

, et al. Ecto-5′-nucleotidase (CD73) is a potential target of hepatocellular carcinoma. J Cell Physiol 2019; 234: 10248–10259.

45.

Shen

, et al. CD73 promotes hepatocellular carcinoma progression and metastasis via activating PI3K/AKT signaling by inducing Rap1-mediated membrane localization of P110β and predicts poor prognosis. J Hematol Oncol 2019; 12: 37.

46.

Bruix

Cheng

Meinhardt

, et al. Prognostic factors and predictors of sorafenib benefit in patients with hepatocellular carcinoma: analysis of two phase III studies. J Hepatol 2017; 67: 999–1008.

47.

Lin

Chiang

Chen

, et al. Targeting CD73 increases therapeutic response to immunogenic chemotherapy by promoting dendritic cell maturation. Cancer Immunol Immunother 2023; 72: 2283–2297.

48.

Mostafa

Hamdy

El-Mesallamy

, et al. Glucagon-like peptide 1 (GLP-1)-based therapy upregulates LXR-ABCA1/ABCG1 cascade in adipocytes. Biochem Biophys Res Commun 2015; 468: 900–905.

49.

Atta

Alzahaby

Hamdy

, et al. New trends in synthetic drugs and natural products targeting 20S proteasomes in cancers. Bioorg Chem 2023; 133: 106427.

50.

Chiang

Huang

Chen

, et al. Hinokitiol inhibits breast cancer cells in vitro stemness-progression and self-renewal with apoptosis and autophagy modulation via the CD44/Nanog/SOX2/Oct4 pathway. Int J Mol Sci 2024; 25: 3904.