Expression and prognostic impact of CD73 in classical Hodgkin lymphoma

Expression and prognostic impact of CD73 in classical Hodgkin lymphoma | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Expression and prognostic impact of CD73 in classical Hodgkin lymphoma Zheng Li, Haisheng Liu, Guangyu Ma, Shuo Zhang, Caili Liu, Kexin Li, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4440165/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Treatment of relapsed or refractory classical Hodgkin lymphoma (cHL) remains clinically challenging. Hence, early identification of high-risk patients is critical for treatment stratification. CD73 may exert an immunosuppressive effect by degrading adenosine monophosphate into adenosine, promoting cancer progression. Although increased CD73 expression is associated with reduced survival rates in various cancers, its role in cHL remains unclear. Therefore, in this retrospective study, we aimed to examine the expression of CD73, CD39, and PD-L1 in cHL and assess their clinical implications and prognostic value. Eighty-four patients with cHL hospitalized in the Hematology Department of the Fourth Hospital of Hebei Medical University between May 2007 and May 2021 were included in this study. Of the 84 patients, 35 were male (41.7%), and the median age was 55 years (range: 16–88 years). Univariate analysis showed that relapsed/refractory disease was associated with advanced stage, low CD73 expression, ≥ 1 extranodal lesion, ≥ 3 nodal areas, and lactate dehydrogenase levels ≥ 240 UL. Patients with low CD73 expression had a higher incidence of relapsed/refractory disease (87.2% vs. 12.8%) and a poorer median progression-free survival (24.2 months vs not reached) than those with high CD73 expression. Low CD73 protein abundance in a multivariate model was identified as an independent negative prognostic indicator for cHL (hazard ratio: 0.413, 95% confidence interval: 0.088–1.94). Collectively, the results of this study suggest that CD73 is an independent prognostic immune biomarker for relapsed or refractory cHL and may serve as a novel therapeutic target. CD73 classical Hodgkin lymphoma immune checkpoint inhibitor prognostic factor relapsed/refractory lymphoma Figures Figure 1 Introduction Classical Hodgkin lymphoma (cHL) originates from B cells and comprises approximately 95% of all Hodgkin lymphoma cases. Epidemiologically, cHL has common characteristics in China and Western nations [ 1 ]. The World Health Organization (WHO) classifies cHL into the following subtypes: nodular sclerosis (NS), mixed cellularity (MC), lymphocyte-rich (LR), and lymphocyte-depleted (LD). Although most patients have favorable prognoses, approximately 20% of patients with refractory or relapsed (r/r) cHL experience negative outcomes [ 2 ]. Patients with this condition typically receive second-line chemotherapy as the initial treatment, with subsequent autologous stem cell transplantation [ 3 ]. However, disease progression occurs in approximately 50% of patients who have undergone transplantation, leading to reduced survival [ 4 ]. Thus, early identification of patients at high risk of disease recurrence or resistance is crucial for developing tailored treatment regimens to enhance therapeutic effectiveness. cHL is distinguished by a complex and heterogeneous tumor microenvironment (TME). Approximately 1–2% of the TME is composed of the distinctive multi-nucleated Reed–Sternberg (RS) tumor cells, which are surrounded by a dense network of diverse immune cells [ 5 ]. Indeed, the immunosuppressive TME of cHL, rather than the tumor cells, influences therapeutic efficacy [ 6 , 7 ]. Accordingly, extensive research has been performed to establish strategies capable of stimulating anti-tumor immunity within the TME, thus enhancing immune function. The programmed cell death protein 1 (PD-1)/programmed death ligand 1 (PD-L1) pathway plays a significant role in cHL development. Chromosome 9p24.1 is frequently altered in RS cells, leading to the overexpression of PD-L1 and programmed death ligand 2, both of which are involved in programmed cell death. Different types of immune cells also overexpress PD-L1, creating an immunosuppressive environment within the tumor [ 8 ]. Meanwhile, blocking the PD-1/PD-L1 pathway effectively boosts T cell activity, exhibiting clinical effectiveness similar to that observed with chemotherapy. Nevertheless, when administered independently, PD-1/PD-L1 inhibitors achieve a complete response (CR) rate of only 17–29% [ 9 , 10 ]. This may be due, in part, to RS cells possessing a high capacity to adapt and utilize multiple mechanisms to facilitate immune escape. CD73—a homodimeric soluble protein located on the cell membrane—is encoded by NT5E and is crucial in adenosine metabolism. CD73 is typically expressed on fibroblasts as well as smooth muscle, endothelial, tumor, and various immune cells [ 11 ]. Extracellular adenosine is primarily generated via two independent pathways. (i) E-NTPDase/CD39 converts extracellular ATP into adenosine diphosphate, AMP, and adenosine. Subsequently, adenosine is broken down into inosine by adenosine deaminase [ 12 ]. (ii) Nicotinamide adenine dinucleotide can be degraded by CD38 and CD203 to form AMP, which is then converted into adenosine by CD73 [ 13 , 14 ]. Accordingly, the increased expression of CD73 and CD39, induced by inflammation and a lack of oxygen, causes adenosine accumulation [ 15 ]. However, unlike CD39, CD73 is essential in the purinergic signaling pathway, serving as the key enzyme responsible for regulating the rate of ATP breakdown into adenosine. Moreover, it is the sole enzyme involved in both adenosine metabolism pathways [ 16 ]. Adenosine performs potent immunosuppressive functions. For example, by increasing intracellular levels of cyclic AMP, adenosine directly suppresses effective T cell activation and proliferation [ 17 ]. Additionally, adenosine can enhance the function of various immunosuppressive cells, including myeloid-derived suppressor cells, macrophages, and regulatory T cells, to suppress T cell immunity [ 18 ]. Thus, adenosine accumulation in the TME is associated with immune escape, tumor progression, and metastasis [ 19 ]. The expression of CD73 on cancer cells can directly enhance the growth and spread of tumors in gastric and breast cancers [ 20 , 21 ]. Accumulating evidence indicates that CD73 upregulation correlates with a worse prognosis and poor survival in a myriad of cancer types [ 22 ]. For instance, elevated CD73 levels in patients with melanoma before and during treatment are associated with resistance to PD-1 blockade therapy [ 23 ]. Moreover, in patients with non-small cell lung cancer, the response rates were found to be higher in the combinatorial CD73 antibody and PD-1 blockade group than in the PD-1 blockade monotherapy group. Progression-free survival (PFS) was nearly double in the CD73 antibody plus PD-1 blockade group compared with that in the PD-1 blockade alone group (62.6% vs 33.9%) [ 24 ]. Therefore, CD73 is regarded as a potent clinical prognostic marker, with several clinical studies underway to assess the efficacy of CD73 blockade therapy (NCT04104672, Registration Date: November 6, 2019. NCT02503774, Registration Date: July 24, 2015 et al.). However, despite numerous studies on solid tumors, the role of CD73 in cHL remains unclear. Accordingly, in the present study, we aimed to examine the expression of CD73 via immunohistochemistry (IHC) in patients with cHL. We further assessed its relationship with two additional immune checkpoints, CD39 and PD-L1. Finally, we investigated its clinical characteristics to determine the impact of CD73 on cHL prognosis. The results of this study could offer innovative approaches for identifying potential prognostic and therapeutic targets to improve the outcomes for patients with r/r cHL. Material and Methods Patients Eighty-four individuals hospitalized in the Hematology Department at the Fourth Hospital of Hebei Medical University for chemotherapy or radiotherapy treatment between May 2007 and May 2021 were enrolled in this study. Each patient was diagnosed with cHL based on pathological confirmation following the WHO classification [ 25 ]. Computed tomography (CT) or positron emission tomography (PET) was performed at the start of therapy, after two cycles of initial therapy, and 6–8 weeks post-therapy. Lymphoma staging was assessed using the Ann Arbor staging system based on imaging and bone marrow biopsy [ 26 ]. Clinical data were retrospectively analyzed for clinical symptoms, basic laboratory results, treatment regimens, and outcomes. Patients were divided into two groups according to the results: patients achieving CR after first-line treatment without relapse until the last follow-up ( n = 37) and patients who experienced relapsed or refractory disease (n = 47). Follow-up assessment The effectiveness of cHL treatment was evaluated using the updated standards of the Response Assessment of Lugano Classification (Table 1 ) [ 27 ]. The overall response rate (ORR) was calculated by adding the CR and partial response (PR) rates. PFS was defined as the period from diagnosis to the occurrence of disease progression, relapse, or death. Overall survival (OS) was defined as the time from diagnosis to death or last follow-up. All patients were followed up until August 2022. Table 1 Response assessment using the Deauville score Response FDG-PET/CT-based response Complete response Score of 1, 2, or 3 in nodal or extranodal sites with or without a residual mass Partial response Score of 4 or 5 with reduced uptake compared with baseline and residual mass(es) of any size Stable disease or no metabolic response Score of 4 or 5 with no obvious change in FDG uptake Progressive disease Score 4 or 5 in any lesion with an increase in intensity of FDG uptake from baseline (and/or new FDG-avid foci consistent with lymphoma) Immunohistochemistry Lymphoma samples were preserved in 10% formalin, paraffinized, and sliced into 4-µm sections. Sections were immersed in water for 2 min and exposed to 3% H 2 O 2 to inhibit endogenous peroxidase activity. Following a 30 min incubation in 3% bovine serum albumin to prevent nonspecific binding, the sections were stained overnight at 4°C using primary antibodies targeting CD73 (ab133582, Abcam, Cambridge, UK, 1:100 dilution), CD39 (ab223842, Abcam, 1:100 dilution), and PD-L1 (SK006, DAKO, Santa Clara, CA, USA, 1:100 dilution). Subsequently, the sections were incubated with a secondary anti-rabbit antibody (1:500, Dako) and detected using 3,3′-diaminobenzidine. After counterstaining with hematoxylin, the slides were dehydrated, cover-slipped, and examined using a light microscope (Axio Observer A1, Zeiss, Oberkochen, Germany). Establishing the cutoff point for CD73 expression In a prior study, we reported an immunoreactive scoring method to assess CD73, CD39, and PD-L1 levels [ 28 ]. Briefly, the immunoreactive score (IRS) was determined by multiplying the proportion of positive cells (PP) (0–4) by the intensity of staining (SI) (0–3). The scale for positive cell percentage was as follows: 0, no positive cells; 1, 80% positive cells. The scale for SI was as follows: 0, no color reaction; 1, mild reaction; 2, moderate reaction; 3, intense reaction. The final IRS ranged from 0 to 12. The cutoff value was determined using the X-tile software (Yale University, New Haven, CT, USA). The threshold for CD73 was set at 3.125. Statistical analysis All statistical analyses were performed using SPSS software (IBM, SPSS Statistics 22, Armonk, NY, USA) and GraphPad Prism 6 (GraphPad Software Inc., Boston, MA, USA). Chi-square test or one-way analysis of variance (ANOVA) was utilized to examine the variations in clinical characteristics and response rates. Survival estimation was conducted using the Kaplan–Meier technique and log-rank analysis. The correlations between CD73, CD39, and PD-L1 expression were assessed using Spearman’s correlation test. Prognostic factors were identified through the analysis of univariate and multivariate Cox regression. The threshold for statistical significance was established as P < 0.05. Results Patient characteristics Of the 84 patients, 35 (41.7%) were male, and the median age was 35 years (range: 16–88 years). Of the histological subtypes of cHL, MC (47.6%) and NS (44%) were the most common, with LR accounting for only 8% of cases. Overall, 29 (34.52%) patients exhibited B symptoms (fever, drenching night sweats, and loss of more than 10% of body weight over 6 months). Imaging examination (CT or fluorodeoxyglucose [FDG] PET/CT) showed that 36 (42.9%) patients had lymph node involvement ≥ 3, and 35 (41.7%) had extranodal involvement. The primary sites of extranodal involvement included the bone marrow, lungs, and liver. At the time of diagnosis, 35 (41.7%) patients were at the local stage, and 49 (58.3%) were at an advanced stage. The baseline information for all patients is presented in Table 2 . Table 2 Clinical characteristics of the 84 patients with cHL Characteristic No. of Cases Proportion (%) Gender Male 35 41.7 Female 49 58.3 Age <45 58 69.0 ≥ 45 26 31.0 B symptoms No 55 65.5 Yes 39 46.4 Nodal areas ≥ 3 No 48 57.1 Yes 36 42.9 Extranodal lesion ≥ 1 No 49 58.3 Yes 35 41.7 Histological subtype MC 40 47.6 NS 37 44.0 LR 7 8.3 Ann Arbor stage I–II 35 41.7 III–IV 49 58.3 No., number; cHL, classical Hodgkin lymphoma; MC, mixed cellularity; NS, nodular sclerosis; LR, lymphocyte-rich; B symptoms, fever, drenching night sweats, and loss of more than 10% of body weight over 6 months. Correlations between surface markers and clinical characteristics Positive IHC staining for PD-L1 was observed in RS cells as well as in different types of immune cells, including lymphocytes, macrophages, and fibroblasts. Positive CD73 and CD39 staining was observed in most immune cells and a small number of tumor cells. Three staining patterns were observed: (i) immune cell staining, (ii) immune cell and tumor cell staining, and (iii) no cell staining. No significant differences were detected between the staining patterns in r/r disease (Table 3 ). Table 3 Correlation among staining patterns of the three protein markers Staining pattern Relapsed/Refractory* Chi-square value P -value No Yes CD39 staining No cell 2 (0.054) 1 (0.021) 0.975 0.614 Immune cells 22 (0.595) 26 (0.553) Immune and RS cells 13 (0.351) 20 (0.426) PD-L1 staining Immune and RS cells 37 (1) 47 (1) – – CD73 staining No cell 3 (0.081) 6 (0.128) 0.906 0.636 Immune cells 14 (0.378) 20 (0.426) Immune and RS cells 20 (0.541) 21 (0.447) *Data are presented as absolute number (percentage). RS cells, Reed–Sternberg cells; PD-L1, programmed death ligand 1. We also employed semi-quantitative scoring methods to assess CD73, CD39, and PD-L1 protein levels. IRS was calculated by multiplying the PP by the SI. No notable relationships were observed among the three surface antigens (Table 4 ). However, in patients with r/r disease, the PP, SI, and IRS of CD73 were notably reduced compared to those in patients who had achieved CR (Table 5 ). Furthermore, while there were no notable variances in the percentage of positive cells and IRS, the intensity of CD39 staining was markedly elevated in the cohort that achieved CR compared to that in the group that did not. Meanwhile, no significant variation was observed in PD-L1 expression between the two groups. Hence, our attention was directed toward the clinical variables potentially associated with CD73 expression. Table 4 Correlation among the IRSs of the three protein markers Protein marker Statistical variable CD39 IRS PD-L1 IRS CD73 IRS CD39 IRS Correlation coefficient 1.000 P- value 1.000 PD-L1 IRS Correlation coefficient 0.070 1.000 P- value 0.530 1.000 CD73 IRS Correlation coefficient 0.098 0.170 1.000 P- value 0.374 0.122 1.000 IRS, immunoreactive score; PD-L1, programmed death ligand 1. Table 5 Correlation of protein marker expression with relapsed/refractory disease Relapsed/Refractory* Z -value P -value No Yes CD39 PP 2 (1.25,2.5) 2 (1.5,2.5) −0.234 0.815 CD39 SI 1 (1,1.75) 2 (1,2) −2.434 0.015 CD39 IRS 3 (2,4) 3 (2,5) −0.711 0.477 PD-L1 PP 1.5 (1.5,2) 2 (1,2.5) −0.34 0.734 PD-L1 SI 2 (1,2.5) 2 (1,2.5) −0.033 0.974 PD-L1 IRS 3 (2,4) 4 (1.5,5) −0.39 0.697 CD73 PP 2 (1.5,3) 1.5 (1.5,2) −3.614 <0.001 CD73 SI 3 (2,4.5) 1.5 (0.5,3) −3.161 0.002 CD73 IRS 3 (1.75,5.5) 1.75 (0.75,2.75) −3.475 0.001 *Data are presented as median (25th percentile; 75th percentile). PP, positive cell proportion; SI, staining intensity; IRS, immunoreactive score; PD-L1, programmed death ligand 1. X-tail software categorized patients, based on their CD73 expression, into high or low expression groups, with an IRS cutoff value of 3.125. The Chi-square test indicated no significant association between high/low CD73 expression and clinical data, such as extranodal lesions, lactate dehydrogenase levels, erythrocyte sedimentation rate, white cell counts, and regimen. However, an observed potential relationship between CD73 levels and the Ann Arbor stage was noted (odds ratio [OR]: 0.393, 95% confidence interval (CI): 0.144–1.074; P < 0.05). Table 6 presents the association between CD73 expression and various clinical features. Dissimilarity analysis revealed no difference in the IRS of CD39 or PD-L1 based on r/r disease. Therefore, subsequent analyses focused primarily on CD73. Table 6 Correlation of CD73 expression with clinical characteristics CD73 expression* Chi-square value P- value Low High Gender Female 26 (0.433) 9 (0.375) 0.240 0.624 Male 34 (0.567) 15 (0.625) Histological subtype MC 29 (0.483) 11 (0.458) 0.766 0.682 NS 27 (0.45) 10 (0.417) LR 4 (0.067) 3 (0.125) ≥ 3 nodal areas No 32 (0.533) 16 (0.667) 1.244 0.265 Yes 28 (0.467) 8 (0.333) Extranodal lesion ≥ 1 No 33 (0.55) 16 (0.667) 0.960 0.327 Yes 27 (0.45) 8 (0.333) Bulk (> 10 cm or MMR > 0.33) No 52 (0.867) 24 (1) 3.537 0.060 Yes 8 (0.133) 0 (0) ESR (≥ 50 mmh) No 34 (0.567) 15 (0.625) 0.240 0.624 Yes 26 (0.433) 9 (0.375) B symptoms No 37 (0.617) 18 (0.75) 1.348 0.246 Yes 23 (0.383) 6 (0.25) Age ≥ 45 No 45 (0.75) 13 (0.542) 3.481 0.062 Yes 15 (0.25) 11 (0.458) Lymphocyte count (< 0.6 × 10 9 /L or LYMPH% 15 × 10 9 /L No 56 (0.933) 19 (0.792) 2.268 0.132 Yes 4 (0.067) 5 (0.208) Serum albumin < 40 g/L No 37 (0.617) 14 (0.583) 0.080 0.777 Yes 23 (0.383) 10 (0.417) Hemoglobin 2.5 (mg/L) No 47 (0.783) 19 (0.792) 0.007 0.933 Yes 13 (0.217) 5 (0.208) LDH ≥ 240 (UL) No 46 (0.767) 22 (0.917) 2.501 0.114 Yes 14 (0.233) 2 (0.083) Regimen ABVD 46 (0.767) 23 (0.958) 3.329 0.286 ABVD + Radiotherapy 4 (0.067) 0 (0) BEACOPP 8 (0.133) 1 (0.042) Tirelizumab + AVD 2 (0.033) 0 (0) Ann Arbor stage I–II 21 (0.35) 14 (0.583) 3.840 0.049 III–IV 39 (0.65) 10 (0.417) *Data are presented as absolute number (percentage). MC, mixed cellularity; NS, nodular sclerosis; LR, lymphocyte-rich; ESR, erythrocyte sedimentation rate; B symptoms, fever, drenching night sweats, and loss of more than 10% of body weight over 6 months; ABVD, adriamycin, bleomycin, vincristine, and dacarbazine; BEACOPP, bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, and prednisone; AVD, adriamycin, vincristine, and dacarbazine; MMR, mediastinal mass ratio. Treatment and outcomes Most patients underwent four to eight cycles of chemotherapy (median: six cycles); 73 patients (86.9%) were treated with adriamycin, bleomycin, vincristine, and dacarbazine (ABVD) or a similar regimen as their initial treatment, while 10 patients (11.9%) received the BEACOPP regimen (bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, and prednisone) (Table 7 ). Radiation was typically administered to patients with bulk or mediastinal masses after chemotherapy; no correlation between the different regimens and clinical outcomes was observed. Table 7 Treatment responses in patients with low/high CD73 expression Regimen No. of cases* Z -value P -value CR PR SD PD ABVD 47 (0.855) 6 (0.857) 4 (0.667) 12 (0.75) 0.125 0.257 ABVD + Radiotherapy 2 (0.036) 0 (0) 1 (0.167) 1 (0.063) BEACOPP 5 (0.091) 1 (0.143) 1 (0.167) 2 (0.125) Tirelizumab + AVD 1 (0.018) 0 (0) 0 (0) 1 (0.063) *Data are presented as absolute number (percentage). CR, complete response; PR, partial response; SD, stable disease; PD, progressive disease; ORR, overall response rate; ABVD, adriamycin, bleomycin, vincristine, and dacarbazine; BEACOPP, bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, and prednisone. Out of the 84 patients, 79.2% (19/24) in the high-CD73 expression group and 60% (36/60) in the low-CD73 expression group successfully achieved CR, with a statistically significant difference ( P < 0.05) between the groups. Likewise, patients exhibiting high CD73 levels had a notably higher ORR than those with lower CD73 levels (91.7% vs. 66.7%, P < 0.05). Nevertheless, no notable distinctions were observed in stable disease or progressive disease between the two groups (Table 8 ). Each patient was monitored for a median duration of 105 months. No notable difference was observed in the 5-year OS rates between the high-CD73 and low-CD73 expression groups (82.5% vs. 81.5%, P = 0.76). Patients with low CD73 expression had a worse PFS than patients with high CD73 expression (Fig. 1 ). Table 8 Treatment responses in patients with low/high CD73 expression Treatment response CD73 expression* Z -value P -value Low High CR 36 (0.6) 19 (0.792) 1.978 0.048 PR 4 (0.067) 3 (0.125) SD 5 (0.083) 1 (0.042) PD 15 (0.250) 1 (0.042) ORR 40 (0.667) 22 (0.917) 5.543 0.019 *Data are presented as absolute number (percentage). CR, complete response; PR, partial response; SD, stable disease; PD, progressive disease; ORR, overall response rate. Prognostic factors of PFS in cHL Results from the Chi-square analysis indicated that the presence of extranodal lesions, involvement of one or more nodal areas, presence of B symptoms, elevated levels of lactate dehydrogenase, advanced disease stage, and low CD73 expression were all associated with disease relapse and treatment resistance (Table 9 ). Single-variable examination indicated that having at least three nodal areas (OR = 1.943, 95% CI: 1.084–3.482), experiencing B symptoms (OR = 2.176, 95% CI: 1.211–3.911), being in an advanced stage of disease (OR = 2.108, 95% CI: 1.108–4.008), and having low CD73 expression (OR = 0.268, 95% CI 0.113–0.635) were associated with a worse PFS outcome ( P < 0.05). Meanwhile, multivariate logistic regression results revealed that low CD73 expression was linked to PFS (OR = 0.301, 95% CI: 0.126–0.723, P < 0.05) after adjusting for confounding variables (Table 10 ). Table 9 Correlation of clinical characteristics with relapsed/refractory disease Characteristic Relapsed/Refractory* Chi-square value P -value No Yes Gender Female 17 (0.459) 18 (0.383) 0.498 0.480 Male 20 (0.541) 29 (0.617) Histological subtype MC 14 (0.378) 26 (0.553) 3.776 0.151 NS 18 (0.486) 19 (0.404) LR 5 (0.135) 2 (0.043) ≥ 3 nodal areas No 26 (0.703) 22 (0.468) 4.653 0.031 Yes 11 (0.297) 25 (0.532) Extranodal lesion ≥ 1 No 26 (0.703) 23 (0.489) 3.877 0.049 Yes 11 (0.297) 24 (0.511) Bulk (> 10 cm or MMR > 0.33) No 36 (0.973) 39 (0.83) 3.066 0.080 Yes 1 (0.027) 8 (0.17) ESR (≥ 50 mmh) No 19 (0.514) 30 (0.638) 1.326 0.249 Yes 18 (0.486) 17 (0.362) B symptoms No 30 (0.811) 25 (0.532) 7.124 0.008 Yes 7 (0.189) 22 (0.468) Age ≥ 45 No 24 (0.649) 34 (0.723) 0.541 0.462 Yes 13 (0.351) 13 (0.277) Lymphocyte count (< 0.6 × 10 9 /L or LYMPH% 15 × 10 9 /L No 33 (0.892) 42 (0.894) 0.001 0.980 Yes 4 (0.108) 5 (0.106) Serum albumin < 40 g/L No 22 (0.595) 29 (0.617) 0.044 0.834 Yes 15 (0.405) 18 (0.383) Hemoglobin 2.5 (mg/L) No 31 (0.838) 35 (0.745) 1.067 0.302 Yes 6 (0.162) 12 (0.255) LDH ≥ 240 (UL) No 34 (0.919) 34 (0.723) 5.132 0.023 Yes 3 (0.081) 13 (0.277) Regimen ABVD 33 (0.892) 36 (0.766) 4.792 0.173 ABVD + Radiotherapy 2 (0.054) 2 (0.043) BEACOPP 1 (0.027) 8 (0.17) Tirelizumab + AVD 1 (0.027) 1 (0.021) Ann Arbor stage I–II 22 (0.595) 13 (0.277) 8.613 0.003 III–IV 15 (0.405) 34 (0.723) CD73 expression Low 19 (0.514) 41 (0.872) 13.061 <0.001 High 18 (0.486) 6 (0.128) *Data are presented as absolute number (percentage). MC, mixed cellularity; NS, nodular sclerosis; LR, lymphocyte-rich; ESR, erythrocyte sedimentation rate; B symptoms, fever, drenching night sweats, and loss of more than 10% of body weight over 6 months; ABVD, adriamycin, bleomycin, vincristine, and dacarbazine; BEACOPP, bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, and prednisone; AVD, adriamycin, vincristine, and dacarbazine; MMR, mediastinal mass ratio. Table 10 Univariate and multivariate Cox regression analysis of PFS Univariate Multivariate HR 95% CI P -value HR 95% CI P -value ≥ 3 nodal areas 1.943 1.084–3.482 0.026 1.442 0.757–2.749 0.266 Extranodal lesion ≥ 1 1.421 0.795–2.54 0.236 B symptoms 2.176 1.211–3.911 0.009 1.554 0.788–3.064 0.203 LDH ≥ 240 (UL) 1.73 0.892–3.355 0.105 CD73 expression 0.268 0.113–0.635 0.003 0.301 0.126–0.723 0.007 Ann Arbor stage 2.108 1.108–4.008 0.023 1.213 0.566–2.597 0.620 PFS, progression-free survival; HR, hazard ratio; CI, confidence interval; B symptoms, fever, drenching night sweats, and loss of more than 10% of body weight over 6 months; LDH, lactate dehydrogenase. Discussion CD73 is a vital metabolic and immune checkpoint highly expressed in many types of malignancies and negatively correlated with patient survival [ 22 , 29 ]. To date, the function and clinical characteristics of CD73 in cHL remain unclear, particularly in r/r cHL. The present study demonstrated that the SI, PP, and IRS for CD73 were notably elevated in patients with non-relapsed/non-refractory cHL compared with those in patients with r/r disease. These results were inconsistent with those of previous studies. However, increased CD73 levels may be associated with a better outcome in specific types of cancer [ 30 , 31 ]. For example, prostate cancer patients with high expression of CD73 on stromal cells tend to not show recurrence for a longer period than patients with low expression of CD73 [ 32 ]. CD73-generated adenosine is pivotal in epithelial integrity in early-stage and well-differentiated endometrial carcinomas [ 33 ]. Elevated levels of inhibitory receptors, such as PD-1 and TIGIT, were observed in CD73 − CD8 + T cells in acute myeloid leukemia, leading to reduced cytokine secretion, excess apoptosis, and T cell exhaustion [ 34 ]. The tumor-promoting effect of CD73 is primarily mediated by CD73-generated extracellular adenosine accumulation. The discrepancy observed in our study could be explained by these aspects of CD73 expression. First, although highly expressed in the TME, CD73 may not be highly expressed on immune cells but on other non-immune cells, such as endothelial cells and microvessels [ 35 , 36 ]. CD73 on endothelial cells typically functions as an adhesion factor mediating lymphocyte adhesion to the endothelium [ 37 ]. Increased lymphocyte infiltration may indicate stronger anti-tumor immunity. Second, RS cells frequently lose major histocompatibility complex (MHC) class I while retaining MHC class II [ 38 , 39 ]. CD4 + T cells release chemokines or cytokines with immunological roles upon recognizing antigens associated with MHC II. In cHL, many CD4 + T cells surround RS cells [ 40 ]. Hence, CD73 expression on CD4 + T cells may be essential for preserving optimal immune function, while its absence is associated with cell exhaustion. Further investigation into the pattern of CD73 expression and T cell function in the TME is necessary to elucidate the specific mechanism(s). Alternatively, our study suggests that despite most patients receiving a similar initial regimen (ABVD or ABVD-like), higher levels of CD73 were more commonly observed in patients with non-relapsed/refractory disease than in patients with r/r disease. This suggests that ABVD or similar regimens may not be sufficient to counteract the negative prognostic influence of low CD73 expression. Hence, individualized therapies should be considered for these patients. Moreover, among numerous clinical factors, CD73 levels were impacted only by the Ann Arbor stage. Furthermore, our survival analyses revealed that cHL patients with low CD73 expression experience shorter PFS and a worse prognosis than those with high CD73 expression. Currently, anti-CD73 monoclonal antibodies have been utilized in numerous clinical studies for solid malignancies. Most of these trials have been phase I, evaluating efficacy and safety. Despite the correlation between low CD73 expression and negative outcomes, CD73 blockade may still offer certain therapeutic benefits in cHL. As CD73 levels were not measured in patients with r/r disease, we are not certain whether the expression is comparable with that observed at initial diagnosis. If a patient is found to have elevated CD73 levels at r/r disease, then monoclonal antibodies or CD73 blockade can be applied. The acquired resistance to treatment may occur via dynamic control of CD73 expression. Increased CD73 expression was observed in the tumor tissue of patients with melanoma receiving anti-PD-1 treatment [ 41 ]. Similarly, individuals treated with MAPK and BRAF inhibitors exhibited reduced CD73 expression, while those not treated with MAPK inhibitors had increased CD73 levels [ 16 ]. Therefore, further investigation is required to validate the potential therapeutic effects of pharmacologically blocking CD73 in cHL. We note that there are some limitations to our study. First, our data are derived from a single-center cohort with a small sample size. The clinical applicability of CD73 as a prognostic marker needs further validation. Second, although CD73 is highly expressed in the TME of non-relapsed/non-refractory cHL, which type of cells exhibit high CD73 expression remains unknown. Uncovering the mechanisms through which CD73 expression positively correlates with clinical outcomes remains to be investigated further. Nevertheless, in conclusion, our findings suggest that CD73 could serve as a prognostic indicator and may provide a novel target for individualized treatment of cHL. Declarations Funding Declaration : This study was supported by the Key Project of Hebei Provincial Health and Family Planning Commission Fund (grant no. 20220133). Competing Interest: The authors have no conflict of interest. Ethics Statement: The study complied with the International Ethical Guidelines for Biomedical Research Involving Human subjects and the 1964 Helsinki Declaration and its later amendments. The study was approved by the Ethics Committee of The Fourth Hospital of Hebei Medical University (protocol code: 2022KY191, date of approval: March 21, 2022). Consent to participate : All participants provided written informed consent before being included in the study. Consent to publish: Patients signed informed consent regarding publishing their data. Author Contributions: Beichen Liu and Cuiying He conceived the study, designed the experiments, interpreted the data, and wrote the manuscript. Zheng Li, Shuo Zhang, Kexin Li, Yunzhe Wang, Caili Liu and Shaoning Yin collected the data. Meng Yue, Chang Liu, Xiaoxiao Wang and Yueping Liu performed IHC. Haisheng Liu and Guangyu Ma participated in research design. All authors read and approved the final manuscript. Data, Material and/or Code availability: The data that support the findings of this study are not openly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request. References Song Y, Gao Q, Zhang H et al (2020) Treatment of relapsed or refractory classical Hodgkin lymphoma with the anti-PD-1, tislelizumab: results of a phase 2, single-arm, multicenter study. Leukemia 34(2):533–542. https://doi.org/10.1038/s41375-019-0545-2 Zhang Y, Xing Z, Mi L et al (2022) Novel agents for relapsed and refractory classical Hodgkin lymphoma: a review. 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Cell Death Dis 11(3):202. https://doi.org/10.1038/s41419-020-2403-6 Zhou P, Zhi X, Zhou T et al (2007) Overexpression of Ecto-5'-nucleotidase (CD73) promotes T-47D human breast cancer cells invasion and adhesion to extracellular matrix. Cancer Biol Ther 6(3):426–431. https://doi.org/10.4161/cbt.6.3.3762 Gao ZW, Dong K, Zhang HZ (2014) The roles of CD73 in cancer. BioMed Res Int 2014:460654. https://doi.org/10.1155/2014/460654 Turiello R, Capone M, Giannarelli D et al (2020) Serum CD73 is a prognostic factor in patients with metastatic melanoma and is associated with response to anti-PD-1 therapy. J Immunother Cancer 8(2):e001689. https://doi.org/10.1136/jitc-2020-001689 Herbst RS, Majem M, Barlesi F et al (2022) COAST: an open-label, phase II, multidrug platform study of durvalumab alone or in combination with oleclumab or monalizumab in patients with unresectable, stage III non–small-cell lung cancer. J Clin Oncol 40(29):3383–3393. https://doi.org/10.1200/JCO.22.00227 Alaggio R, Amador C, Anagnostopoulos I et al (2022) The 5th edition of the World Health Organization Classification of Haematolymphoid Tumours: Lymphoid Neoplasms. Leukemia 36(7):1720–1748. https://doi.org/10.1038/s41375-022-01620-2 DeVita V, Hellman S, Rosenberg A (2001) Cancer. Principles and practice of oncology, 6th edn. Lippincott WW (ed.) Cheson BD, Fisher RI, Barrington SF et al (2014) Recommendations for initial evaluation, staging, and response assessment of Hodgkin and non-Hodgkin lymphoma: the Lugano classification. J Clin Oncol 32(27):3059–3068. https://doi.org/10.1200/JCO.2013.54.8800 Remmele W, Stegner HE (1987) [Recommendation for uniform definition of an immunoreactive score (IRS) for immunohistochemical estrogen receptor detection (ER-ICA) in breast cancer tissue]. Vorschlag zur einheitlichen Definition eines Immunreaktiven Score (IRS) für den immunhistochemischen Ostrogenrezeptor-Nachweis (ER-ICA) im Mammakarzinomgewebe. Pathologe 8(3):138–140 Jiang T, Xu X, Qiao M et al (2018) Comprehensive evaluation of NT5E/CD73 expression and its prognostic significance in distinct types of cancers. BMC Cancer 18(1):267. https://doi.org/10.1186/s12885-018-4073-7 Supernat A, Markiewicz A, Welnicka-Jaskiewicz M et al (2012) CD73 expression as a potential marker of good prognosis in breast carcinoma. Appl Immunohistochem Mol Morphol 20(2):103–107. https://doi.org/10.1097/pai.0b013e3182311d82 Oh HK, Sin J-I, Choi J, Park SH, Lee TS, Choi YSJ (2012) Overexpression of CD73 in epithelial ovarian carcinoma is associated with better prognosis, lower stage, better differentiation and lower regulatory T cell infiltration. J Gynecol Oncol 23(4):274–281. https://doi.org/10.3802/jgo.2012.23.4.274 Leclerc BG, Charlebois R, Chouinard G et al (2016) CD73 expression is an independent prognostic factor in prostate CancerCD73. Clin Cancer Res 22(1):158–166. https://doi.org/10.1158/1078-0432.CCR-15-1181 Bowser JL, Blackburn MR, Shipley GL, Molina JG, Dunner K Jr., Broaddus RR (2016) Loss of CD73-mediated actin polymerization promotes endometrial tumor progression. J Clin Invest 126(1):220–238. https://doi.org/10.1172/JCI79380 Kong Y, Jia B, Zhao C et al (2019) Downregulation of CD73 associates with T cell exhaustion in AML patients. J Hematol Oncol 12(1):40. https://doi.org/10.1186/s13045-019-0728-3 Airas L, Hellman J, Salmi M et al (1995) CD73 is involved in lymphocyte binding to the endothelium: characterization of lymphocyte-vascular adhesion protein 2 identifies it as CD73. J Exp Med 182(5):1603–1608. https://doi.org/10.1084/jem.182.5.1603 Henttinen T, Jalkanen S, Yegutkin GG (2003) Adherent leukocytes prevent adenosine formation and impair endothelial barrier function by Ecto-5'-nucleotidase/CD73-dependent mechanism. J Biol Chem 278(27):24888–24895. https://doi.org/10.1074/jbc.M300779200 Topalian SL, Drake CG, Pardoll DM (2015) Immune checkpoint blockade: A common denominator approach to cancer therapy. Cancer Cell 27(4):450–461. https://doi.org/10.1016/j.ccell.2015.03.001 Roemer MGM, Redd RA, Cader FZ et al (2018) Major histocompatibility complex Class II and programmed death ligand 1 expression predict outcome after programmed death 1 blockade in classic Hodgkin lymphoma. J Clin Oncol 36(10):942–950. https://doi.org/10.1200/JCO.2017.77.3994 Reichel J, Chadburn A, Rubinstein PG et al (2015) Flow sorting and exome sequencing reveal the oncogenome of primary Hodgkin and Reed-Sternberg cells. Blood 125(7):1061–1072. https://doi.org/10.1182/blood-2014-11-610436 Menéndez V, Solórzano JL, Fernández S, Montalbán C, García JF (2022) The Hodgkin lymphoma immune microenvironment: turning bad news into good. Cancers (Basel) 14(5):1360. https://doi.org/10.3390/cancers14051360 Turiello R, Capone M, Morretta E et al (2022) Exosomal CD73 from serum of patients with melanoma suppresses lymphocyte functions and is associated with therapy resistance to anti-PD-1 agents. J Immunother Cancer 10(3):e004043. https://doi.org/10.1136/jitc-2021-004043 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4440165","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":313547650,"identity":"0b86fcf4-136e-45d5-bfbf-0e82deda90ee","order_by":0,"name":"Zheng Li","email":"","orcid":"","institution":"The Fourth Affiliated Hospital of Hebei Medical University","correspondingAuthor":false,"prefix":"","firstName":"Zheng","middleName":"","lastName":"Li","suffix":""},{"id":313547651,"identity":"b091f074-51bc-45cd-afad-c2654efbdbef","order_by":1,"name":"Haisheng Liu","email":"","orcid":"","institution":"The Fourth Affiliated Hospital of Hebei 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University","correspondingAuthor":true,"prefix":"","firstName":"Beichen","middleName":"","lastName":"Liu","suffix":""},{"id":313547663,"identity":"81c94ffa-5ec8-439a-a716-23a13f75fedc","order_by":13,"name":"Cuiying He","email":"","orcid":"","institution":"The Fourth Affiliated Hospital of Hebei Medical University","correspondingAuthor":false,"prefix":"","firstName":"Cuiying","middleName":"","lastName":"He","suffix":""}],"badges":[],"createdAt":"2024-05-18 08:38:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4440165/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4440165/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":58514872,"identity":"773c527a-e9ff-44bf-b319-729ec2c7bf24","added_by":"auto","created_at":"2024-06-17 16:39:27","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":68287,"visible":true,"origin":"","legend":"\u003cp\u003eSurvival of 60 patients with low CD73 expression and 24 patients with high CD73 expression. (\u003cstrong\u003ea\u003c/strong\u003e) Progression-free survival. (\u003cstrong\u003eb\u003c/strong\u003e) Overall survival\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4440165/v1/0467f98465c281801bb57589.png"},{"id":88600248,"identity":"8691c869-93f2-4eb8-b6b2-afc2e3088f2c","added_by":"auto","created_at":"2025-08-08 07:40:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1200918,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4440165/v1/4231ea23-04f0-4e2d-8c14-7e15e6b0ea06.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Expression and prognostic impact of CD73 in classical Hodgkin lymphoma","fulltext":[{"header":"Introduction","content":"\u003cp\u003eClassical Hodgkin lymphoma (cHL) originates from B cells and comprises approximately 95% of all Hodgkin lymphoma cases. Epidemiologically, cHL has common characteristics in China and Western nations [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The World Health Organization (WHO) classifies cHL into the following subtypes: nodular sclerosis (NS), mixed cellularity (MC), lymphocyte-rich (LR), and lymphocyte-depleted (LD). Although most patients have favorable prognoses, approximately 20% of patients with refractory or relapsed (r/r) cHL experience negative outcomes [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Patients with this condition typically receive second-line chemotherapy as the initial treatment, with subsequent autologous stem cell transplantation [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. However, disease progression occurs in approximately 50% of patients who have undergone transplantation, leading to reduced survival [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Thus, early identification of patients at high risk of disease recurrence or resistance is crucial for developing tailored treatment regimens to enhance therapeutic effectiveness.\u003c/p\u003e \u003cp\u003ecHL is distinguished by a complex and heterogeneous tumor microenvironment (TME). Approximately 1\u0026ndash;2% of the TME is composed of the distinctive multi-nucleated Reed\u0026ndash;Sternberg (RS) tumor cells, which are surrounded by a dense network of diverse immune cells [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Indeed, the immunosuppressive TME of cHL, rather than the tumor cells, influences therapeutic efficacy [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Accordingly, extensive research has been performed to establish strategies capable of stimulating anti-tumor immunity within the TME, thus enhancing immune function.\u003c/p\u003e \u003cp\u003eThe programmed cell death protein 1 (PD-1)/programmed death ligand 1 (PD-L1) pathway plays a significant role in cHL development. Chromosome 9p24.1 is frequently altered in RS cells, leading to the overexpression of PD-L1 and programmed death ligand 2, both of which are involved in programmed cell death. Different types of immune cells also overexpress PD-L1, creating an immunosuppressive environment within the tumor [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Meanwhile, blocking the PD-1/PD-L1 pathway effectively boosts T cell activity, exhibiting clinical effectiveness similar to that observed with chemotherapy. Nevertheless, when administered independently, PD-1/PD-L1 inhibitors achieve a complete response (CR) rate of only 17\u0026ndash;29% [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. This may be due, in part, to RS cells possessing a high capacity to adapt and utilize multiple mechanisms to facilitate immune escape.\u003c/p\u003e \u003cp\u003eCD73\u0026mdash;a homodimeric soluble protein located on the cell membrane\u0026mdash;is encoded by \u003cem\u003eNT5E\u003c/em\u003e and is crucial in adenosine metabolism. CD73 is typically expressed on fibroblasts as well as smooth muscle, endothelial, tumor, and various immune cells [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Extracellular adenosine is primarily generated via two independent pathways. (i) E-NTPDase/CD39 converts extracellular ATP into adenosine diphosphate, AMP, and adenosine. Subsequently, adenosine is broken down into inosine by adenosine deaminase [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. (ii) Nicotinamide adenine dinucleotide can be degraded by CD38 and CD203 to form AMP, which is then converted into adenosine by CD73 [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Accordingly, the increased expression of CD73 and CD39, induced by inflammation and a lack of oxygen, causes adenosine accumulation [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. However, unlike CD39, CD73 is essential in the purinergic signaling pathway, serving as the key enzyme responsible for regulating the rate of ATP breakdown into adenosine. Moreover, it is the sole enzyme involved in both adenosine metabolism pathways [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Adenosine performs potent immunosuppressive functions. For example, by increasing intracellular levels of cyclic AMP, adenosine directly suppresses effective T cell activation and proliferation [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Additionally, adenosine can enhance the function of various immunosuppressive cells, including myeloid-derived suppressor cells, macrophages, and regulatory T cells, to suppress T cell immunity [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Thus, adenosine accumulation in the TME is associated with immune escape, tumor progression, and metastasis [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe expression of CD73 on cancer cells can directly enhance the growth and spread of tumors in gastric and breast cancers [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Accumulating evidence indicates that CD73 upregulation correlates with a worse prognosis and poor survival in a myriad of cancer types [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. For instance, elevated CD73 levels in patients with melanoma before and during treatment are associated with resistance to PD-1 blockade therapy [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Moreover, in patients with non-small cell lung cancer, the response rates were found to be higher in the combinatorial CD73 antibody and PD-1 blockade group than in the PD-1 blockade monotherapy group. Progression-free survival (PFS) was nearly double in the CD73 antibody plus PD-1 blockade group compared with that in the PD-1 blockade alone group (62.6% vs 33.9%) [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Therefore, CD73 is regarded as a potent clinical prognostic marker, with several clinical studies underway to assess the efficacy of CD73 blockade therapy (NCT04104672, Registration Date: November 6, 2019. NCT02503774, Registration Date: July 24, 2015 et al.).\u003c/p\u003e \u003cp\u003eHowever, despite numerous studies on solid tumors, the role of CD73 in cHL remains unclear. Accordingly, in the present study, we aimed to examine the expression of CD73 via immunohistochemistry (IHC) in patients with cHL. We further assessed its relationship with two additional immune checkpoints, CD39 and PD-L1. Finally, we investigated its clinical characteristics to determine the impact of CD73 on cHL prognosis. The results of this study could offer innovative approaches for identifying potential prognostic and therapeutic targets to improve the outcomes for patients with r/r cHL.\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003eEighty-four individuals hospitalized in the Hematology Department at the Fourth Hospital of Hebei Medical University for chemotherapy or radiotherapy treatment between May 2007 and May 2021 were enrolled in this study. Each patient was diagnosed with cHL based on pathological confirmation following the WHO classification [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Computed tomography (CT) or positron emission tomography (PET) was performed at the start of therapy, after two cycles of initial therapy, and 6\u0026ndash;8 weeks post-therapy. Lymphoma staging was assessed using the Ann Arbor staging system based on imaging and bone marrow biopsy [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Clinical data were retrospectively analyzed for clinical symptoms, basic laboratory results, treatment regimens, and outcomes. Patients were divided into two groups according to the results: patients achieving CR after first-line treatment without relapse until the last follow-up (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;37) and patients who experienced relapsed or refractory disease \u003cem\u003e(n\u003c/em\u003e\u0026thinsp;=\u0026thinsp;47).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eFollow-up assessment\u003c/h2\u003e \u003cp\u003eThe effectiveness of cHL treatment was evaluated using the updated standards of the Response Assessment of Lugano Classification (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The overall response rate (ORR) was calculated by adding the CR and partial response (PR) rates. PFS was defined as the period from diagnosis to the occurrence of disease progression, relapse, or death. Overall survival (OS) was defined as the time from diagnosis to death or last follow-up. All patients were followed up until August 2022.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResponse assessment using the Deauville score\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResponse\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFDG-PET/CT-based response\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComplete response\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eScore of 1, 2, or 3 in nodal or extranodal sites with or without a residual mass\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePartial response\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eScore of 4 or 5 with reduced uptake compared with baseline and residual mass(es) of any size\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStable disease or no metabolic response\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eScore of 4 or 5 with no obvious change in FDG uptake\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProgressive disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eScore 4 or 5 in any lesion with an increase in intensity of FDG uptake from baseline (and/or new FDG-avid foci consistent with lymphoma)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eImmunohistochemistry\u003c/h2\u003e \u003cp\u003eLymphoma samples were preserved in 10% formalin, paraffinized, and sliced into 4-\u0026micro;m sections. Sections were immersed in water for 2 min and exposed to 3% H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e to inhibit endogenous peroxidase activity. Following a 30 min incubation in 3% bovine serum albumin to prevent nonspecific binding, the sections were stained overnight at 4\u0026deg;C using primary antibodies targeting CD73 (ab133582, Abcam, Cambridge, UK, 1:100 dilution), CD39 (ab223842, Abcam, 1:100 dilution), and PD-L1 (SK006, DAKO, Santa Clara, CA, USA, 1:100 dilution). Subsequently, the sections were incubated with a secondary anti-rabbit antibody (1:500, Dako) and detected using 3,3\u0026prime;-diaminobenzidine. After counterstaining with hematoxylin, the slides were dehydrated, cover-slipped, and examined using a light microscope (Axio Observer A1, Zeiss, Oberkochen, Germany).\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003eEstablishing the cutoff point for CD73 expression\u003c/h2\u003e \u003cp\u003eIn a prior study, we reported an immunoreactive scoring method to assess CD73, CD39, and PD-L1 levels [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Briefly, the immunoreactive score (IRS) was determined by multiplying the proportion of positive cells (PP) (0\u0026ndash;4) by the intensity of staining (SI) (0\u0026ndash;3). The scale for positive cell percentage was as follows: 0, no positive cells; 1, \u0026lt; 10% positive cells; 2, 10\u0026ndash;50% positive cells; 3, 51\u0026ndash;80% positive cells; 4, \u0026gt; 80% positive cells. The scale for SI was as follows: 0, no color reaction; 1, mild reaction; 2, moderate reaction; 3, intense reaction. The final IRS ranged from 0 to 12. The cutoff value was determined using the X-tile software (Yale University, New Haven, CT, USA). The threshold for CD73 was set at 3.125.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAll statistical analyses were performed using SPSS software (IBM, SPSS Statistics 22, Armonk, NY, USA) and GraphPad Prism 6 (GraphPad Software Inc., Boston, MA, USA). Chi-square test or one-way analysis of variance (ANOVA) was utilized to examine the variations in clinical characteristics and response rates. Survival estimation was conducted using the Kaplan\u0026ndash;Meier technique and log-rank analysis. The correlations between CD73, CD39, and PD-L1 expression were assessed using Spearman\u0026rsquo;s correlation test. Prognostic factors were identified through the analysis of univariate and multivariate Cox regression. The threshold for statistical significance was established as \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003ePatient characteristics\u003c/h2\u003e \u003cp\u003eOf the 84 patients, 35 (41.7%) were male, and the median age was 35 years (range: 16\u0026ndash;88 years). Of the histological subtypes of cHL, MC (47.6%) and NS (44%) were the most common, with LR accounting for only 8% of cases. Overall, 29 (34.52%) patients exhibited B symptoms (fever, drenching night sweats, and loss of more than 10% of body weight over 6 months). Imaging examination (CT or fluorodeoxyglucose [FDG] PET/CT) showed that 36 (42.9%) patients had lymph node involvement\u0026thinsp;\u0026ge;\u0026thinsp;3, and 35 (41.7%) had extranodal involvement. The primary sites of extranodal involvement included the bone marrow, lungs, and liver. At the time of diagnosis, 35 (41.7%) patients were at the local stage, and 49 (58.3%) were at an advanced stage. The baseline information for all patients is presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClinical characteristics of the 84 patients with cHL\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo. of Cases\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProportion (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e58.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e69.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eB symptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e65.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNodal areas\u0026thinsp;\u0026ge;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e57.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e42.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eExtranodal lesion\u0026thinsp;\u0026ge;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e58.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eHistological subtype\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e47.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e44.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnn Arbor stage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI\u0026ndash;II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e41.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIII\u0026ndash;IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e58.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eNo., number; cHL, classical Hodgkin lymphoma; MC, mixed cellularity; NS, nodular sclerosis; LR, lymphocyte-rich; B symptoms, fever, drenching night sweats, and loss of more than 10% of body weight over 6 months.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eCorrelations between surface markers and clinical characteristics\u003c/h2\u003e \u003cp\u003ePositive IHC staining for PD-L1 was observed in RS cells as well as in different types of immune cells, including lymphocytes, macrophages, and fibroblasts. Positive CD73 and CD39 staining was observed in most immune cells and a small number of tumor cells. Three staining patterns were observed: (i) immune cell staining, (ii) immune cell and tumor cell staining, and (iii) no cell staining. No significant differences were detected between the staining patterns in r/r disease (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation among staining patterns of the three protein markers\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStaining pattern\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eRelapsed/Refractory*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eChi-square value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCD39 staining\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo cell\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (0.054)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.021)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.975\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.614\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eImmune cells\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (0.595)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26 (0.553)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eImmune and RS cells\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (0.351)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20 (0.426)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePD-L1 staining\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eImmune and RS cells\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026ndash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCD73 staining\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo cell\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (0.081)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (0.128)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.906\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.636\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eImmune cells\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (0.378)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20 (0.426)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eImmune and RS cells\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (0.541)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21 (0.447)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e*Data are presented as absolute number (percentage).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eRS cells, Reed\u0026ndash;Sternberg cells; PD-L1, programmed death ligand 1.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWe also employed semi-quantitative scoring methods to assess CD73, CD39, and PD-L1 protein levels. IRS was calculated by multiplying the PP by the SI. No notable relationships were observed among the three surface antigens (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). However, in patients with r/r disease, the PP, SI, and IRS of CD73 were notably reduced compared to those in patients who had achieved CR (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Furthermore, while there were no notable variances in the percentage of positive cells and IRS, the intensity of CD39 staining was markedly elevated in the cohort that achieved CR compared to that in the group that did not. Meanwhile, no significant variation was observed in PD-L1 expression between the two groups. Hence, our attention was directed toward the clinical variables potentially associated with CD73 expression.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation among the IRSs of the three protein markers\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtein marker\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStatistical variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCD39 IRS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePD-L1 IRS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCD73 IRS\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCD39 IRS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCorrelation coefficient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eP-\u003c/em\u003evalue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePD-L1 IRS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCorrelation coefficient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eP-\u003c/em\u003evalue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.530\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCD73 IRS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCorrelation coefficient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eP-\u003c/em\u003evalue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.374\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eIRS, immunoreactive score; PD-L1, programmed death ligand 1.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation of protein marker expression with relapsed/refractory disease\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eRelapsed/Refractory*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD39 PP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (1.25,2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (1.5,2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;0.234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.815\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD39 SI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1,1.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (1,2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;2.434\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD39 IRS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (2,4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (2,5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;0.711\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.477\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePD-L1 PP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.5 (1.5,2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (1,2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.734\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePD-L1 SI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (1,2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (1,2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.974\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePD-L1 IRS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (2,4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (1.5,5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.697\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD73 PP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (1.5,3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.5 (1.5,2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;3.614\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD73 SI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (2,4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.5 (0.5,3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;3.161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD73 IRS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (1.75,5.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.75 (0.75,2.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;3.475\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*Data are presented as median (25th percentile; 75th percentile).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003ePP, positive cell proportion; SI, staining intensity; IRS, immunoreactive score; PD-L1, programmed death ligand 1.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eX-tail software categorized patients, based on their CD73 expression, into high or low expression groups, with an IRS cutoff value of 3.125. The Chi-square test indicated no significant association between high/low CD73 expression and clinical data, such as extranodal lesions, lactate dehydrogenase levels, erythrocyte sedimentation rate, white cell counts, and regimen. However, an observed potential relationship between CD73 levels and the Ann Arbor stage was noted (odds ratio [OR]: 0.393, 95% confidence interval (CI): 0.144\u0026ndash;1.074; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e presents the association between CD73 expression and various clinical features. Dissimilarity analysis revealed no difference in the IRS of CD39 or PD-L1 based on r/r disease. Therefore, subsequent analyses focused primarily on CD73.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation of CD73 expression with clinical characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eCD73 expression*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eChi-square value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP-\u003c/em\u003e value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (0.433)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (0.375)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.240\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.624\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (0.567)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15 (0.625)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eHistological subtype\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (0.483)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (0.458)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.766\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.682\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 (0.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (0.417)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (0.067)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (0.125)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;3 nodal areas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (0.533)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16 (0.667)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.244\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.265\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (0.467)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (0.333)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eExtranodal lesion\u0026thinsp;\u0026ge;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33 (0.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16 (0.667)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.960\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.327\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 (0.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (0.333)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBulk\u003c/p\u003e \u003cp\u003e(\u0026gt;\u0026thinsp;10 cm or MMR\u0026thinsp;\u0026gt;\u0026thinsp;0.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52 (0.867)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e3.537\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.060\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (0.133)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eESR (\u0026ge;\u0026thinsp;50 mmh)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (0.567)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15 (0.625)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.240\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.624\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (0.433)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (0.375)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eB symptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37 (0.617)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 (0.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.348\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.246\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (0.383)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (0.25)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge\u0026thinsp;\u0026ge;\u0026thinsp;45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45 (0.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (0.542)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e3.481\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.062\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (0.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (0.458)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLymphocyte count\u003c/p\u003e \u003cp\u003e(\u0026lt;\u0026thinsp;0.6 \u0026times; 10\u003csup\u003e9\u003c/sup\u003e/L or LYMPH% \u0026lt;8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50 (0.833)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21 (0.875)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.886\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (0.167)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (0.125)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWhite cell count\u0026thinsp;\u0026gt;\u0026thinsp;15 \u0026times; 10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56 (0.933)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19 (0.792)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2.268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (0.067)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (0.208)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSerum albumin\u0026thinsp;\u0026lt;\u0026thinsp;40 g/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37 (0.617)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14 (0.583)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.080\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.777\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (0.383)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (0.417)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHemoglobin\u0026thinsp;\u0026lt;\u0026thinsp;10\u003csup\u003e5\u003c/sup\u003e (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19 (0.792)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (0.208)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eβ2-Microglobulin\u0026thinsp;\u0026gt;\u0026thinsp;2.5 (mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47 (0.783)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19 (0.792)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.933\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (0.217)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (0.208)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLDH\u0026thinsp;\u0026ge;\u0026thinsp;240 (UL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46 (0.767)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22 (0.917)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2.501\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.114\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (0.233)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (0.083)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eRegimen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eABVD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46 (0.767)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23 (0.958)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e3.329\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.286\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eABVD\u0026thinsp;+\u0026thinsp;Radiotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (0.067)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBEACOPP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (0.133)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.042)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTirelizumab\u0026thinsp;+\u0026thinsp;AVD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (0.033)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAnn Arbor stage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI\u0026ndash;II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (0.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14 (0.583)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e3.840\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIII\u0026ndash;IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39 (0.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (0.417)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e*Data are presented as absolute number (percentage).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eMC, mixed cellularity; NS, nodular sclerosis; LR, lymphocyte-rich; ESR, erythrocyte sedimentation rate; B symptoms, fever, drenching night sweats, and loss of more than 10% of body weight over 6 months; ABVD, adriamycin, bleomycin, vincristine, and dacarbazine; BEACOPP, bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, and prednisone; AVD, adriamycin, vincristine, and dacarbazine; MMR, mediastinal mass ratio.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eTreatment and outcomes\u003c/h2\u003e \u003cp\u003eMost patients underwent four to eight cycles of chemotherapy (median: six cycles); 73 patients (86.9%) were treated with adriamycin, bleomycin, vincristine, and dacarbazine (ABVD) or a similar regimen as their initial treatment, while 10 patients (11.9%) received the BEACOPP regimen (bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, and prednisone) (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). Radiation was typically administered to patients with bulk or mediastinal masses after chemotherapy; no correlation between the different regimens and clinical outcomes was observed.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTreatment responses in patients with low/high CD73 expression\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRegimen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eNo. of cases*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePD\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eABVD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47 (0.855)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (0.857)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (0.667)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12 (0.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.257\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eABVD\u0026thinsp;+\u0026thinsp;Radiotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (0.036)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.167)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (0.063)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBEACOPP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (0.091)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.143)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.167)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (0.125)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTirelizumab\u0026thinsp;+\u0026thinsp;AVD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (0.018)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (0.063)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e*Data are presented as absolute number (percentage).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eCR, complete response; PR, partial response; SD, stable disease; PD, progressive disease; ORR, overall response rate; ABVD, adriamycin, bleomycin, vincristine, and dacarbazine; BEACOPP, bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, and prednisone.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eOut of the 84 patients, 79.2% (19/24) in the high-CD73 expression group and 60% (36/60) in the low-CD73 expression group successfully achieved CR, with a statistically significant difference (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) between the groups. Likewise, patients exhibiting high CD73 levels had a notably higher ORR than those with lower CD73 levels (91.7% vs. 66.7%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Nevertheless, no notable distinctions were observed in stable disease or progressive disease between the two groups (Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). Each patient was monitored for a median duration of 105 months. No notable difference was observed in the 5-year OS rates between the high-CD73 and low-CD73 expression groups (82.5% vs. 81.5%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.76). Patients with low CD73 expression had a worse PFS than patients with high CD73 expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTreatment responses in patients with low/high CD73 expression\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTreatment response\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCD73 expression*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eZ\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19 (0.792)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.978\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.048\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4 (0.067)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3 (0.125)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5 (0.083)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (0.042)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15 (0.250)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (0.042)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eORR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e40 (0.667)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22 (0.917)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.543\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e*Data are presented as absolute number (percentage).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eCR, complete response; PR, partial response; SD, stable disease; PD, progressive disease; ORR, overall response rate.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003ePrognostic factors of PFS in cHL\u003c/h2\u003e \u003cp\u003eResults from the Chi-square analysis indicated that the presence of extranodal lesions, involvement of one or more nodal areas, presence of B symptoms, elevated levels of lactate dehydrogenase, advanced disease stage, and low CD73 expression were all associated with disease relapse and treatment resistance (Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). Single-variable examination indicated that having at least three nodal areas (OR\u0026thinsp;=\u0026thinsp;1.943, 95% CI: 1.084\u0026ndash;3.482), experiencing B symptoms (OR\u0026thinsp;=\u0026thinsp;2.176, 95% CI: 1.211\u0026ndash;3.911), being in an advanced stage of disease (OR\u0026thinsp;=\u0026thinsp;2.108, 95% CI: 1.108\u0026ndash;4.008), and having low CD73 expression (OR\u0026thinsp;=\u0026thinsp;0.268, 95% CI 0.113\u0026ndash;0.635) were associated with a worse PFS outcome (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Meanwhile, multivariate logistic regression results revealed that low CD73 expression was linked to PFS (OR\u0026thinsp;=\u0026thinsp;0.301, 95% CI: 0.126\u0026ndash;0.723, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) after adjusting for confounding variables (Table\u0026nbsp;\u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation of clinical characteristics with relapsed/refractory disease\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eRelapsed/Refractory*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eChi-square value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (0.459)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 (0.383)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.498\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.480\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (0.541)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29 (0.617)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eHistological subtype\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (0.378)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26 (0.553)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.776\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.151\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (0.486)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19 (0.404)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (0.135)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (0.043)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;3 nodal areas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (0.703)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22 (0.468)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.653\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (0.297)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25 (0.532)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eExtranodal lesion\u0026thinsp;\u0026ge;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (0.703)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23 (0.489)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.877\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (0.297)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24 (0.511)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBulk\u003c/p\u003e \u003cp\u003e(\u0026gt;\u0026thinsp;10 cm or MMR\u0026thinsp;\u0026gt;\u0026thinsp;0.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36 (0.973)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39 (0.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.080\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.027)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (0.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eESR (\u0026ge;\u0026thinsp;50 mmh)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (0.514)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30 (0.638)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.249\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (0.486)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17 (0.362)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eB symptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (0.811)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25 (0.532)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (0.189)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22 (0.468)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAge\u0026thinsp;\u0026ge;\u0026thinsp;45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (0.649)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34 (0.723)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.541\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.462\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (0.351)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (0.277)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLymphocyte count\u003c/p\u003e \u003cp\u003e(\u0026lt;\u0026thinsp;0.6 \u0026times; 10\u003csup\u003e9\u003c/sup\u003e/L or LYMPH% \u0026lt;8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (0.865)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39 (0.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.659\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (0.135)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (0.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eWhite cell count\u0026thinsp;\u0026gt;\u0026thinsp;15 \u0026times; 10\u003csup\u003e9\u003c/sup\u003e/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33 (0.892)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42 (0.894)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.980\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (0.108)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (0.106)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSerum albumin\u0026thinsp;\u0026lt;\u0026thinsp;40 g/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (0.595)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29 (0.617)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.044\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.834\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (0.405)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 (0.383)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHemoglobin\u0026thinsp;\u0026lt;\u0026thinsp;10\u003csup\u003e5\u003c/sup\u003e (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (0.838)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36 (0.766)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.663\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.416\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (0.162)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (0.234)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eβ2-Microglobulin\u0026thinsp;\u0026gt;\u0026thinsp;2.5 (mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31 (0.838)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35 (0.745)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.302\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (0.162)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (0.255)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eLDH\u0026thinsp;\u0026ge;\u0026thinsp;240 (UL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (0.919)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34 (0.723)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (0.081)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (0.277)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eRegimen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eABVD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33 (0.892)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36 (0.766)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.792\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.173\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eABVD\u0026thinsp;+\u0026thinsp;Radiotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (0.054)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (0.043)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBEACOPP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.027)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (0.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTirelizumab\u0026thinsp;+\u0026thinsp;AVD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.027)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.021)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAnn Arbor stage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eI\u0026ndash;II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (0.595)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (0.277)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.613\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIII\u0026ndash;IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (0.405)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34 (0.723)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCD73 expression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (0.514)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41 (0.872)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (0.486)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (0.128)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e*Data are presented as absolute number (percentage).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eMC, mixed cellularity; NS, nodular sclerosis; LR, lymphocyte-rich; ESR, erythrocyte sedimentation rate; B symptoms, fever, drenching night sweats, and loss of more than 10% of body weight over 6 months; ABVD, adriamycin, bleomycin, vincristine, and dacarbazine; BEACOPP, bleomycin, etoposide, doxorubicin, cyclophosphamide, vincristine, procarbazine, and prednisone; AVD, adriamycin, vincristine, and dacarbazine; MMR, mediastinal mass ratio.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab10\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate and multivariate Cox regression analysis of PFS\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eUnivariate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eMultivariate\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;3 nodal areas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.943\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.084\u0026ndash;3.482\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.757\u0026ndash;2.749\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.266\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExtranodal lesion\u0026thinsp;\u0026ge;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.421\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.795\u0026ndash;2.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB symptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.176\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.211\u0026ndash;3.911\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.554\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.788\u0026ndash;3.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.203\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDH\u0026thinsp;\u0026ge;\u0026thinsp;240 (UL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.892\u0026ndash;3.355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD73 expression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.113\u0026ndash;0.635\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.301\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.126\u0026ndash;0.723\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnn Arbor stage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.108\u0026ndash;4.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.213\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.566\u0026ndash;2.597\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.620\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003ePFS, progression-free survival; HR, hazard ratio; CI, confidence interval; B symptoms, fever, drenching night sweats, and loss of more than 10% of body weight over 6 months; LDH, lactate dehydrogenase.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eCD73 is a vital metabolic and immune checkpoint highly expressed in many types of malignancies and negatively correlated with patient survival [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. To date, the function and clinical characteristics of CD73 in cHL remain unclear, particularly in r/r cHL. The present study demonstrated that the SI, PP, and IRS for CD73 were notably elevated in patients with non-relapsed/non-refractory cHL compared with those in patients with r/r disease. These results were inconsistent with those of previous studies. However, increased CD73 levels may be associated with a better outcome in specific types of cancer [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. For example, prostate cancer patients with high expression of CD73 on stromal cells tend to not show recurrence for a longer period than patients with low expression of CD73 [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. CD73-generated adenosine is pivotal in epithelial integrity in early-stage and well-differentiated endometrial carcinomas [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Elevated levels of inhibitory receptors, such as PD-1 and TIGIT, were observed in CD73\u003csup\u003e\u0026minus;\u003c/sup\u003eCD8\u003csup\u003e+\u003c/sup\u003e T cells in acute myeloid leukemia, leading to reduced cytokine secretion, excess apoptosis, and T cell exhaustion [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The tumor-promoting effect of CD73 is primarily mediated by CD73-generated extracellular adenosine accumulation. The discrepancy observed in our study could be explained by these aspects of CD73 expression. First, although highly expressed in the TME, CD73 may not be highly expressed on immune cells but on other non-immune cells, such as endothelial cells and microvessels [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. CD73 on endothelial cells typically functions as an adhesion factor mediating lymphocyte adhesion to the endothelium [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Increased lymphocyte infiltration may indicate stronger anti-tumor immunity. Second, RS cells frequently lose major histocompatibility complex (MHC) class I while retaining MHC class II [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. CD4\u003csup\u003e+\u003c/sup\u003e T cells release chemokines or cytokines with immunological roles upon recognizing antigens associated with MHC II. In cHL, many CD4\u003csup\u003e+\u003c/sup\u003e T cells surround RS cells [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Hence, CD73 expression on CD4\u003csup\u003e+\u003c/sup\u003e T cells may be essential for preserving optimal immune function, while its absence is associated with cell exhaustion. Further investigation into the pattern of CD73 expression and T cell function in the TME is necessary to elucidate the specific mechanism(s).\u003c/p\u003e \u003cp\u003eAlternatively, our study suggests that despite most patients receiving a similar initial regimen (ABVD or ABVD-like), higher levels of CD73 were more commonly observed in patients with non-relapsed/refractory disease than in patients with r/r disease. This suggests that ABVD or similar regimens may not be sufficient to counteract the negative prognostic influence of low CD73 expression. Hence, individualized therapies should be considered for these patients. Moreover, among numerous clinical factors, CD73 levels were impacted only by the Ann Arbor stage. Furthermore, our survival analyses revealed that cHL patients with low CD73 expression experience shorter PFS and a worse prognosis than those with high CD73 expression.\u003c/p\u003e \u003cp\u003eCurrently, anti-CD73 monoclonal antibodies have been utilized in numerous clinical studies for solid malignancies. Most of these trials have been phase I, evaluating efficacy and safety. Despite the correlation between low CD73 expression and negative outcomes, CD73 blockade may still offer certain therapeutic benefits in cHL. As CD73 levels were not measured in patients with r/r disease, we are not certain whether the expression is comparable with that observed at initial diagnosis. If a patient is found to have elevated CD73 levels at r/r disease, then monoclonal antibodies or CD73 blockade can be applied. The acquired resistance to treatment may occur via dynamic control of CD73 expression. Increased CD73 expression was observed in the tumor tissue of patients with melanoma receiving anti-PD-1 treatment [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Similarly, individuals treated with MAPK and BRAF inhibitors exhibited reduced CD73 expression, while those not treated with MAPK inhibitors had increased CD73 levels [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Therefore, further investigation is required to validate the potential therapeutic effects of pharmacologically blocking CD73 in cHL.\u003c/p\u003e \u003cp\u003eWe note that there are some limitations to our study. First, our data are derived from a single-center cohort with a small sample size. The clinical applicability of CD73 as a prognostic marker needs further validation. Second, although CD73 is highly expressed in the TME of non-relapsed/non-refractory cHL, which type of cells exhibit high CD73 expression remains unknown. Uncovering the mechanisms through which CD73 expression positively correlates with clinical outcomes remains to be investigated further.\u003c/p\u003e \u003cp\u003eNevertheless, in conclusion, our findings suggest that CD73 could serve as a prognostic indicator and may provide a novel target for individualized treatment of cHL.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding Declaration\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eThis study was supported by the Key Project of Hebei Provincial Health and Family Planning Commission Fund (grant no. 20220133).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interest:\u0026nbsp;\u003c/strong\u003eThe authors have no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Statement:\u0026nbsp;\u003c/strong\u003eThe study complied with the International Ethical Guidelines for Biomedical Research Involving Human subjects and the 1964 Helsinki Declaration and its later amendments.\u0026nbsp;The study was approved by the Ethics Committee of The Fourth Hospital of Hebei Medical University (protocol code: 2022KY191, date of approval: March 21, 2022).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003cstrong\u003e:\u0026nbsp;\u003c/strong\u003eAll participants provided written informed consent before being included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish:\u0026nbsp;\u003c/strong\u003ePatients signed informed consent regarding publishing their data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u0026nbsp;\u003c/strong\u003eBeichen Liu\u0026nbsp;and\u0026nbsp;Cuiying He\u0026nbsp;conceived the study, designed the experiments, interpreted the data, and wrote the manuscript.\u0026nbsp;Zheng Li,\u0026nbsp;Shuo Zhang,\u0026nbsp;Kexin Li, Yunzhe Wang,\u0026nbsp;Caili Liu and Shaoning Yin\u0026nbsp;collected the data. Meng Yue, Chang Liu, Xiaoxiao Wang and Yueping Liu\u0026nbsp;performed IHC. Haisheng Liu and\u0026nbsp;Guangyu Ma participated in research design. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData, Material and/or Code availability:\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe data that support the findings of this study are not openly available due to reasons of sensitivity and are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSong Y, Gao Q, Zhang H et al (2020) Treatment of relapsed or refractory classical Hodgkin lymphoma with the anti-PD-1, tislelizumab: results of a phase 2, single-arm, multicenter study. 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J Immunother Cancer 10(3):e004043. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1136/jitc-2021-004043\u003c/span\u003e\u003cspan address=\"10.1136/jitc-2021-004043\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"CD73, classical Hodgkin lymphoma, immune checkpoint inhibitor, prognostic factor, relapsed/refractory lymphoma","lastPublishedDoi":"10.21203/rs.3.rs-4440165/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4440165/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eTreatment of relapsed or refractory classical Hodgkin lymphoma (cHL) remains clinically challenging. Hence, early identification of high-risk patients is critical for treatment stratification. CD73 may exert an immunosuppressive effect by degrading adenosine monophosphate into adenosine, promoting cancer progression. Although increased CD73 expression is associated with reduced survival rates in various cancers, its role in cHL remains unclear. Therefore, in this retrospective study, we aimed to examine the expression of CD73, CD39, and PD-L1 in cHL and assess their clinical implications and prognostic value. Eighty-four patients with cHL hospitalized in the Hematology Department of the Fourth Hospital of Hebei Medical University between May 2007 and May 2021 were included in this study. Of the 84 patients, 35 were male (41.7%), and the median age was 55 years (range: 16\u0026ndash;88 years). Univariate analysis showed that relapsed/refractory disease was associated with advanced stage, low CD73 expression, \u0026ge; 1 extranodal lesion, \u0026ge; 3 nodal areas, and lactate dehydrogenase levels\u0026thinsp;\u0026ge;\u0026thinsp;240 UL. Patients with low CD73 expression had a higher incidence of relapsed/refractory disease (87.2% vs. 12.8%) and a poorer median progression-free survival (24.2 months vs not reached) than those with high CD73 expression. Low CD73 protein abundance in a multivariate model was identified as an independent negative prognostic indicator for cHL (hazard ratio: 0.413, 95% confidence interval: 0.088\u0026ndash;1.94). Collectively, the results of this study suggest that CD73 is an independent prognostic immune biomarker for relapsed or refractory cHL and may serve as a novel therapeutic target.\u003c/p\u003e","manuscriptTitle":"Expression and prognostic impact of CD73 in classical Hodgkin lymphoma","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-17 16:39:23","doi":"10.21203/rs.3.rs-4440165/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"da9da75e-d488-4a9c-b9e9-a57bec709800","owner":[],"postedDate":"June 17th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-08-08T07:39:49+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-17 16:39:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4440165","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4440165","identity":"rs-4440165","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}