PD-1/PD-L1 Expression and Predictive Value of Efficacy in HCC Patients with Anti-PD1 Therapy: A Real-World Study

PD-1/PD-L1 Expression and Predictive Value of Efficacy in HCC Patients with Anti-PD1 Therapy: A Real-World Study | 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 PD-1/PD-L1 Expression and Predictive Value of Efficacy in HCC Patients with Anti-PD1 Therapy: A Real-World Study Huili Wu, Hui Liu, Yang Wang, Lin Sun, Mei Liu, Jun Lv This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6640195/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 Background/Objectives The conclusions regarding PD-1/PD-L1 expression and its role as a predictive biomarker for treatment efficacy had been inconsistent in previous clinical trials of PD-1 monoclonal antibodies therapy for hepatocellular carcinoma (HCC). Therefore, this study aimed to analyze the expression of PD-1/PD-L1 in HCC patients treated with PD-1 in real-world settings and to evaluate its predictive value for treatment outcomes. Methods : A retrospective study was conducted on 59 pathologically confirmed HCC patients. PD-1/PD-L1 expression in tumor tissues was assessed via immunohistochemical staining. Clinical characteristics, laboratory parameters, pathological features, and therapeutic outcomes were compared between two groups. Results : Among 59 patients, 12 (20.33%) were PD-1-positive and 18 (30.51%) were PD-L1-positive. The PD-1-positive group exhibited a higher incidence of lymph node metastasis (41.7% vs. 14.9%, P = 0.040) and lower neutrophil counts (3.32 ± 1.19 vs. 4.02 ± 2.22, P = 0.020) compared to the negative group. The PD-L1-positive group showed increased lymph node metastasis (41.2% vs. 14.3%, P = 0.024), reduced platelet counts (136.41 ± 38.18 vs. 148.17 ± 64.13, P = 0.020), higher proportions of poorly differentiated histology (91.7% vs. 44.7%, P = 0.002), and elevated Ki67 expression (54.2 ± 29.3 vs. 37.8 ± 22.4, P = 0.039). However, no significant differences were observed in objective response rate or progression-free survival between PD-1/PD-L1 positive and negative groups(P>0.05). Conclusions : PD-1/PD-L1 expression in HCC tissues is associated with distinct clinicopathological features but demonstrates no significant predictive value for anti-PD-1 therapy efficacy. Hepatocellular carcinoma Immunotherapy Programmed death deceptor-1 Efficacy prediction Figures Figure 1 Figure 2 1. Introduction Primary Liver Cancer (PLC), which includes malignancies originating from hepatocytes or intrahepatic bile duct epithelial cells, ranks as the sixth most common cancer globally and the fourth leading cause of cancer-related deaths. In 2020, there were over 900,000 new cases and more than 830,000 deaths worldwide, with nearly half of these cases occurring in China, where PLC has the highest incidence and mortality rates globally[ 1 ]. PLC is characterized by its insidious onset, high malignancy, rapid progression, and challenging treatment. Recent statistics indicate that the 5-year survival rate for PLC patients in China is only 14.4%[ 2 ]. Hepatocellular Carcinoma (HCC) accounts for 75–85% of PLC cases, and most patients are diagnosed at an advanced stage, losing the opportunity for surgical intervention. Consequently, HCC patients generally have a short overall survival and poor prognosis.In recent years, the application of immune checkpoint inhibitors, particularly Programmed Death Receptor-1 (PD-1) monoclonal antibodies, has brought new breakthroughs in the treatment of advanced PLC. However, the efficacy of PD-1 monoclonal antibody therapy varies significantly among patients, with only a portion (15–40%) benefiting from the treatment. A significant proportion (approximately 20–30%) of patients experience disease progression, and about 25% suffer from grade 3–4 immune-related adverse events[ 3 ]. Thus, patients who do not benefit face substantial risks of immune-related adverse events and tumor progression. With the advent of personalized precision medicine, identifying predictive biomarkers to select patients who are more likely to benefit from immunotherapy is crucial, considering both the efficacy and economic aspects of drug therapy[ 4 , 5 ]. Programmed Death Ligand/Receptor 1 (PD-1/PD-L1) was initially considered a biomarker for predicting the efficacy of PD-1 monoclonal antibody therapy in HCC. Previous clinical studies on PD-1 monoclonal antibodies often used PD-1/PD-L1 as a predictive biomarker, but the conclusions were inconsistent and even contradictory [ 6 – 10 ]. With the widespread clinical use of PD-1 inhibitors, there is limited clinical data on the expression of PD-1/PD-L1 in HCC patients in real-world settings and its predictive value for PD-1 monoclonal antibody therapy. Therefore, this study aims to detect the expression of PD-1/PD-L1 in HCC tissues using immunohistochemistry and analyze its correlation with clinical indicators, pathological characteristics, and treatment efficacy, providing a reference for HCC treatment and prognosis evaluation. 2. Materials and Methods 2.1Research subjects A retrospective analysis was conducted on patients diagnosed with HCC via pathological examination at our center from December 2020 to December 2022. Inclusion criteria: (1) Patients had comprehensive serological and imaging examinations before obtaining pathological specimens; (2) Complete clinical data without omissions or missing information, and uncontaminated pathological tissues; (3) Patients had a history of PD-1 monoclonal antibody monotherapy (Tislelizumab, Sintilimab, or Camrelizumab). Exclusion criteria: (1) Patients with other malignant tumors; (2) Patients who received other anti-tumor treatments for HCC, such as targeted drugs, chemotherapy, radiotherapy, or local/systemic interventions like ablation; (3) Patients treated with systemic corticosteroids (equivalent to or higher than 10 mg/day of prednisone) or other immunosuppressive drugs; (4) Patients with a history of HIV infection, other acquired or congenital immunodeficiency diseases, or organ transplantation; (5) Patients who received PD-1 monoclonal antibodies for neoadjuvant or postoperative adjuvant therapy; (6) Pregnant patients; (7) Patients with a history of or concurrent other tumors were excluded. Tumor tissue samples were obtained through surgical resection or percutaneous liver biopsy. This study was conducted with the approval of the Ethics Committee and obtained an ethical batch number (LL-2021-184-K). 2.2 Methods 2.2.1Laboratory Tests Blood routine tests were performed using the Sysmex XN-550 automated hematology analyzer. Liver function and blood biochemistry were tested using the SK6100 automatic biochemical analyzer (Shenzhen Shengxinkang Technology Co., Ltd.). Alpha-fetoprotein (AFP) was measured using electrochemiluminescence immunoassay (Roche Cobas e601 automatic electrochemiluminescence immunoassay system, Roche reagents). 2.2.2Pathological examination Immunohistochemical staining (immunoenzymatic method) was used to detect the distribution and expression of PD-1 and PD-L1 (using PD-1 antibody [CAL20] and PD-L1 [SP142] antibody from Abcam). Paraffin-embedded HCC tissue samples were sectioned into 5–7 µm slices, transferred to clean slides, and dewaxed to water. Antigen retrieval was performed using microwave treatment for 15–20 minutes, followed by cooling to room temperature. Endogenous peroxidase was blocked with PBS, and sections were incubated with rabbit serum. Primary antibodies were added and incubated overnight at 4°C, followed by secondary antibodies at 37°C for 30 minutes. Horseradish peroxidase-labeled streptavidin was added and incubated at room temperature for 20 minutes. Staining was observed under a microscope, and sections were counterstained with hematoxylin and mounted with glycerol. Positive staining was defined as the presence of yellow-brown to brown staining on the cell membrane or cytoplasm. Based on the expression level, samples were divided into positive (TPS ≥ 1%) and negative (TPS < 1%) groups. Normal tonsil tissues (10 cases) and positive/negative control slides from the kit were used as controls. Other pathological data, including tumor differentiation, Glypican-3 (GPC-3), Hepatocyte Specific Antigen, CD34, Cytokeratin 7 and 19, p53, and Ki-67, were collected using the BOND-MAX automatic staining machine (Leica, Germany). Pathological diagnosis followed the "Primary Liver Cancer Standardized Pathological Diagnosis Guidelines (2015 Edition)" and was evaluated by two pathologists blinded to the patients' clinical and pathological data. 2.2.3Imaging examination Imaging examinations, including abdominal enhanced MRI, enhanced CT, ultrasound, PET-CT, and hepatic artery angiography, performed within 14 days before PD-1 monoclonal antibody treatment, were used for baseline tumor staging. 2.2.4Tumor staging and efficacy evaluation Tumor staging was based on imaging examinations according to the Barcelona Clinic Liver Cancer (BCLC) staging system[ 11 ]. Efficacy was evaluated using the Response Evaluation Criteria in Solid Tumors (RECIST 1.1): (1) Complete Response (CR): Disappearance of all target lesions, except for nodal disease, which must have a short axis < 10 mm; (2) Partial Response (PR): At least a 30% decrease in the sum of diameters of target lesions, using the shortest diameter for nodal lesions and the longest diameter for non-nodal lesions; (3) Progressive Disease (PD): At least a 20% increase in the sum of diameters of target lesions, with an absolute increase of at least 5 mm, or the appearance of new lesions; (4) Stable Disease (SD): Neither sufficient shrinkage to qualify for PR nor sufficient increase to qualify for PD. In this study, CR, PR, and SD were considered effective treatment, while PD was considered ineffective. 2.3 Statistical analysis Statistical analysis was performed using IBM SPSS Statistics 19. Normally distributed data were compared using t-tests or Kruskal-Wallis analysis of variance, expressed as mean ± standard deviation. Non-normally distributed data were compared using the Mann-Whitney U test, expressed as median. Categorical data were compared using the chi-square test or Fisher's exact test. Survival analysis was performed by Kaplan-Meier method. A P-value < 0.05 was considered statistically significant. 3. Results 3.1General clinical sata of patients From December 2020 to December 2022, 858 HCC patients treated with PD-1 monoclonal antibodies were collected, of which 59 patients with pre-treatment HCC pathological tissue samples were included in this study. Among the 59 patients, 52 were male (88.1%) and 7 were female (11.9%), with mean ages of 57.2 ± 9.0 and 60.1 ± 9.7 years, respectively, showing no significant difference (P = 0.428). PD-1 positivity was observed in 12 patients (20.33%), all of whom were male, but there was no significant gender difference (P = 0.065). The mean ages of PD-1 positive and negative groups were 53.7 ± 7.3 and 58.6 ± 9.2 years, respectively, with no significant difference (P = 0.093). PD-L1 positivity was observed in 18 patients (30.5%), including 17 males (94.4%) and 1 female (5.6%), with no significant gender difference (P = 0.578). The mean ages of PD-L1 positive and negative groups were 55.4 ± 9.4 and 58.5 ± 8.8 years, respectively, with no significant difference (P = 0.233). Six patients (10.2%) were positive for both PD-1 and PD-L1. All 59 patients were classified as BCLC stage B or C, and all had liver cirrhosis, with 91.5% being compensated cirrhosis. Forty-four patients (91.5%) had hepatitis B or C virus infection, 13 patients (22.0%) had high AFP levels (≥ 400 µg/mL), and 15 patients (25.4%) had tumors larger than 10 cm. Additionally, 13 patients (22%) had lymph node metastasis, 29 patients (49.2%) had a history of surgical resection, 11 patients (18.6%) had a history of hepatic artery catheter intervention, 38 patients (64.4%) had a history of targeted therapy, and 7 patients (11.9%) had a history of tumor ablation. PD-1 monoclonal antibodies were used as second-line therapy in 37 patients (62.7%) and as third-line or later therapy in 22 patients (37.3%). 3.2PD-1/PD-L1 expression in HCC patients with different clinical characteristics Among the 12 PD-1 positive patients, 5 (41.7%) had lymph node metastasis, while 7 (58.3%) did not. In the PD-1 negative group, 7 patients (14.9%) had lymph node metastasis, while 40 (85.1%) did not. Among the 18 PD-L1 positive patients, 7 (41.2%) had lymph node metastasis, while 10 (58.8%) did not. In the PD-L1 negative group, 6 patients (14.3%) had lymph node metastasis, while 36 (85.7%) did not. There were significant differences in lymph node metastasis between PD-1/PD-L1 positive and negative groups (P = 0.040, 0.024). However, no significant differences were observed in BCLC staging, compensated or decompensated cirrhosis, hepatitis B or C virus infection, high AFP levels, tumor size > 10 cm, or distant metastasis between PD-1/PD-L1 positive and negative groups (all P > 0.05). (Tables 1 and 2 ) Table 1 Expression of PD-1 in hepatocellular carcinoma tissues in patients with different clinical characteristics (N=59) Characteristics N PD-1 positive PD-1 negative P t / x 2 Gender( n,%) 0.065 3.417 Male 52 12(100.0) 40(85.1) Female 7 0(0.0) 7(14.9) Age (years, x±s ) 53.7±7.3 58.6±9.2 0.093 1.707 BCLC stage( n,%) 1.000 0.000 Stage B 10 2(16.7) 8(17.0) Stage C 49 10(83.3) 39(83.0) Liver cirrhosis( n,%) 1.000 0.000 Compensated 54 11(91.7) 43(91.5) Decompensated 5 1(8.3) 4(8.5) Hepatitis virus infection( n,%) 0.575 0.315 Yes 54 10(83.3) 44(93.6) No 5 2(16.7) 3(6.4) AFP( n,%) 0.853 0.034 ≥400ug/ml 16 3(25.07) 13(27.7) ＜400ug/ml 43 9(75.0) 34(72.3) Tumor diameter( n,%) 0.970 0.001 ≥10cm 15 3(25.0) 12(25.5) ＜10cm 44 9(75.0) 35(74.5) Lymph node metastasis ( n,%) 0.040 4.229 Yes 12 5(41.7) 7(14.9) No 47 7(58.3) 40(85.1) Distant metastasis( n,%) 0.948 0.004 Yes 29 6(50.0) 23(48.9) No 30 6(50.0) 24(51.1) Treatment line( n,%) 1.000 0.000 Second-line 37 9（75.0） 28（75.7） Third line and posterior line 12 3（25.0） 9（24.3） Note: Variables are expressed as the mean ± SD or n (%). Abbreviations: BCLC stage, Barcelona Clinic Liver, Cancer stage; AFP, α-fetoprotei. Table 2 Expression of PD-L1 in Hepatocellular Carcinoma Tissues in Patients with Different Clinical Characteristics (N = 59) N PD-L1 positive PD-L1 negative P t / x 2 Gender ( n,%) 0.578 0.309 Male 52 17(94.4) 35(85.4) Female 7 1(5.6) 6(14.6) Age (years, x ± s ) 55.4 ± 9.4 58.5 ± 8.8 0.233 1.206 BCLC stage ( n,%) 0.735 0.115 stage B 10 4(22.2) 6(14.6) stage C 49 14(77.8) 35(85.4) Liver cirrhosis( n,%) 0.322 0.979 Compensated 54 15(83.3) 39(95.1) Decompensated 5 3(16.7) 2(4.9) Hepatitis virus infection ( n,%) 1.000 0.000 Yes 54 16(88.9) 38(92.7) No 5 2(11.1) 3(7.3) AFP( n,%) 0.178 1.816 ≥400ug/ml 16 7(38.9) 9(22.0) <400ug/ml 43 11(61.1) 32(78.0) Tumor diameter( n,%) 0.355 0.855 ≥10cm 15 6(33.3) 9(22.0) <10cm 44 12(66.7) 32(78.0) Lymph node metastasis (n, %) 0.024 5.094 Yes 13 7(41.2) 6(14.3) No 46 10(58.8) 36(85.7) Distant metastasis( n,%) 2.594 0.107 Yes 30 12(66.7) 18(43.9) No 29 6(33.3) 23(56.1) Treatment line( n,%) 0.677 0.173 Second-line 37 12(66.7) 25(80.6) Third line and posterior line 22 6(33.3) 16(19.4) Note: Variables are expressed as the mean ± SD or n (%). Abbreviations: BCLC stage, Barcelona Clinic Liver, Cancer stage; AFP, α-fetoprotei. 3.3 Relationship between PD-1/PD-L1 expression and laboratory tests The neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) were calculated based on absolute neutrophil count (ANC), absolute lymphocyte count (ALC), and platelet count (PLT). Comparisons between PD-1/PD-L1 positive and negative groups showed that ANC was lower in the PD-1 positive group (3.32±1.19 vs. 4.02±2.22, P=0.020), and PLT was lower in the PD-L1 positive group (136.41±38.18 vs. 148.17±64.13, P=0.020). No significant differences were observed in other indicators(Tables 3 and 4). Table 3 Relationship Between PD-1 Expression and Laboratory Tests in Hepatocellular Car cinoma Tissues (N=59) Laboratory tests PD-1 positive PD-1 negative P t ANC(E+9/L) 3.96±1.94 3.86±2.18 0.583 0.631 ALC(E+9/L) 1.06±0.51 1.12±0.54 0.403 0.698 HB(g/L) 134.94±23.24 132.60±24.22 0.653 0.464 PLT(E+9/L) 136.41±38.18 148.17±64.13 0.020 0.902 NLR 4.37±2.64 4.39±3.58 0.086 0.892 PLR 151.41±66.98 157.17±102.99 0.321 0.714 LDH(U/L) 176.14±32.73 187.26±43.21 0.309 0.735 Note: Variables are expressed as the mean ± SD. Abbreviations: ANC:Absolute Neutrophil Count; ALC:Absolute Lymphocyte Count; HB:Hemoglobin; PLT:Platelet; NLR:Neutrophil-to-Lymphocyte Ratio; PLR:Platelet-to-Lymphocyte Ratio; LDH:Lactate Dehydrogenase. Table 4 Relationship Between PD-L1 Expression and Laboratory Tests in Hepatocellular Carcinoma Tissues (N = 59) Laboratory tests PD-L1 positive PD-L1 negative P t ANC(E + 9/L) 3.32 ± 1.19 4.02 ± 2.22 0.020 0.901 ALC(E + 9/L) 1.23 ± 0.71 1.07 ± 0.48 0.047 0.848 HB(g/L) 138.004 ± 25.82 132.40 ± 23.45 0.852 0.641 PLT(E + 9/L) 145.67 ± 64.19 144.057 ± 56.01 0.975 0.077 NLR 3.72 ± 2.97 4.52 ± 3.36 0.564 0.663 PLR 148.22 ± 80.31 156.77 ± 95.20 0.771 0.251 LDH(U/L) 182.33 ± 27.15 184.52 ± 42.20 0.129 0.087 Note: Variables are expressed as the mean ± SD. Abbreviations: ANC:Absolute Neutrophil Count; ALC:Absolute Lymphocyte Count; HB:Hemoglobin; PLT:Platelet; NLR:Neutrophil-to-Lymphocyte Ratio; PLR: Platelet-to-Lymphocyte Ratio; LDH:Lactate Dehydrogenase. 3.4Relationship between PD-1/PD-L1 expression and pathological characteristics of HCC In terms of tumor differentiation, 91.7% (11/12) of PD-L1 positive patients had undifferentiated/poorly differentiated tumors, compared to 44.7% (21/47) in the PD-L1 negative group, showing a significant difference (P=0.002). Additionally, Ki67 expression was significantly higher in the PD-L1 positive group (54.2±29.3 vs. 37.8±22.4, P=0.039). No significant difference was observed in GPC3 positivity between PD-L1 positive and negative groups (P>0.05). Meanwhile, no significant differences were observed in tumor differentiation, Ki67 expression, or GPC3 positivity between PD-1 positive and negative groups (all P>0.05) (Tables 5 and 6). Table 5 Relationship Between PD-1 Expression and Pathological Characteristics in Hepatocellular Carcinoma Tissues (N = 59) Pathological Characteristics PD-1 positive PD-1 negative P t/ x 2 /Z Differentiation( n,%) 0.204 1.612 Undifferentiated/Low 12(66.7) 20(48.8) Moderate/High 6(33.3) 21(51.2) Ki67( %) 48.1 ± 24.1 38.1 ± 24.5 0.154 1.445 GPC3( n,%) 0.938 0.006 Positive 5(41.7) 19(40.4) negative 7(58.3) 28(59.6) Note: Variables are expressed as the mean ± SD. Abbreviations: Ki67: Ki-67 protein; GPC3: Glypican-3. Table 6 Relationship Between PD-L1 Expression and Pathological Characteristics in Hepatocellular Carcinoma Tissues (N = 59) Pathological Characteristics PD-L1 positive PD-L1 negative P t/ x 2 /Z Differentiation ( n,%) 0.002 9.860 Undifferentiated/Low 11(91.7) 21(44.7) Moderate/High 1(8.3) 26(55.3) Ki67( %) 54.2 ± 29.3 37.8 ± 22.4 0.039 2.117 GPC3( n,%) 0.853 0.034 Positive 7(38.9) 17(41.5) negative 11(61.1) 24(58.5) Note: Variables are expressed as the mean ± SD. Abbreviations: Ki67: Ki-67 protein; GPC3: Glypican-3. 3.5Relationship between PD-1/PD-L1 expression and treatment efficacy Among the 59 patients, 48 had post-treatment efficacy evaluations, with 13 patients (27.1%) showing effective treatment. The effective rates in PD-1 positive and negative groups were 33.3% (3/9) and 25.6% (10/39), respectively, with no significant difference in progression-free survival (3.6±2.4 months vs. 3.6±3.2 months, P>0.05)（Figure1 and 2）. In the PD-L1 positive and negative groups, the effective rates were 16.7% (2/12) and 30.6% (11/36), respectively, with no significant difference in progression-free survival (3.0±2.6 months vs. 3.8±3.2 months, P>0.05) (Tables 7 and 8). Table 7 Relationship Between PD-1 Expression and Efficacy of PD-1 Treatment in Hepatocellular Carcinoma Tissues (N = 48) PD-1 positive PD-1 negative P t/ x 2 /Z Efficacy( n,%) 0.959 0.003 Effective 3(33.3) 10(25.6) Ineffective 6(66.7) 29(74.4) PFS(months) 3.6 ± 2.4 3.6 ± 3.2 0.954 0.058 Note: Variables are expressed as the mean ± SD. Abbreviations: PFS: Progression-Free Survival. Table 8 Relationship Between PD-L1 Expression and Efficacy of PD-1 Treatment in Hepatocellular Carcinoma Tissues (N = 48) PD-L1 positive PD-L1 negative P t/ x 2 /Z Efficacy( n,%) 0.574 0.316 Effective 2(16.7) 11(30.6) Ineffective 10(83.3) 25(69.4) PFS(months) 3.0 ± 2.6 3.8 ± 3.2 0.454 0.755 Note: Variables are expressed as the mean ± SD. Abbreviations: PFS: Progression-Free Survival. Discussion PD-1/PD-L1 is a critical negative regulatory factor in tumor immunity, enabling tumor cells to evade immune surveillance through immune checkpoint mechanisms, thereby promoting tumorigenesis. Previous studies have shown that the PD-1/PD-L1 signaling pathway also plays a role in cell proliferation and differentiation, processes that are markedly abnormal in tumor cells. Thus, this pathway is closely linked to tumor development and progression [12,13]. PD-1 monoclonal antibodies target this pathway, blocking PD-1/PD-L1 interactions to induce tumor cell death. Numerous clinical trials have demonstrated the potent anti-tumor efficacy of PD-1 inhibitors across various cancer types. Since the first approval of PD-1 monoclonal antibodies for second-line HCC treatment in 2017[14], many clinical studies have been conducted. However, the response rates in HCC patients remain unsatisfactory, making the search for predictive biomarkers for PD-1 efficacy a hot topic in recent years. Most studies suggest that PD-L1 expression in tumor tissues has predictive value for treatment efficacy, but this remains controversial. In the CheckMate040 trial of Nivolumab for HCC, 34 out of 174 patients (20.0%) had PD-L1 positive tumors, with only 9 (26%) showing treatment response, slightly higher than the 19% response rate in the negative group[14]. In contrast, the CheckMate459 trial of Nivolumab for HCC showed that 71 out of 366 patients (19.4%) had PD-L1 positive tumors, with a 28% objective response rate (ORR) in the positive group compared to 12% in the negative group, although no differences were observed in progression-free survival or overall survival[6]. Additionally, in a domestic trial (NCT02989922) of Camrelizumab for HCC, 11 out of 30 patients (36.7%) had PD-L1 positive tumors, with a 36% ORR in the positive group compared to 11% in the negative group[10]. These inconsistent and even contradictory results highlight the need for further research. This study observed PD-L1 expression in HCC tissues in a real-world setting, finding a 30.51% positivity rate using TPS ≥1% as the cutoff. The effective rates in PD-L1 positive and negative groups were 16.7% and 30.6%, respectively, with progression-free survival of 3.0±2.6 months and 3.8±3.2 months, respectively. Although no significant differences were observed, possibly due to the small sample size, the data suggest that PD-L1 positive patients may have a worse prognosis.In clinical practice, PD-1 monoclonal antibodies are often combined with other anti-tumor drugs, such as targeted therapies. PD-1 monotherapy is typically used in patients intolerant to targeted therapies, often in advanced stages or as second-line treatment. PD-L1 positive patients may have faster tumor progression, potentially explaining the lower response rates observed in this study compared to previous clinical trials. Additionally, this study found that PD-L1 positivity was associated with poorly differentiated tumors and higher Ki67 expression, consistent with previous findings[15], further explaining the poorer prognosis in PD-L1 positive HCC patients. Compared to PD-L1, there is limited research on PD-1 expression in HCC tissues. Since PD-1 is primarily expressed in inflammatory cells, previous studies have shown [16-18] a high PD-1 positivity rate in HCC tissues (up to 58%), especially in patients with AFP ≥400 μg/L, correlating with tumor differentiation and microvascular formation. However, PD-1 expression in HCC tissues has not been established as a predictive biomarker for PD-1 or PD-L1 monoclonal antibody efficacy, and its significance warrants further exploration. In this study, PD-1 positivity was observed in 20.33% of HCC patients, with 41.7% of PD-1 positive patients having lymph node metastasis, significantly higher than the 14.9% in PD-1 negative patients. Additionally, PD-1 positive patients had lower absolute neutrophil counts (3.32±1.19 vs. 4.02±2.22, P=0.020). In HCC patients, lymph node metastasis is often associated with poor prognosis, and in cirrhotic patients, lower neutrophil counts may indicate worse liver function and immune status, predicting a poorer prognosis. However, in this study, PD-1 positive patients treated with PD-1 monoclonal antibodies did not show the expected worse outcomes, with a 33.3% response rate, higher than the 25.9% in PD-1 negative patients, suggesting that PD-1 positive patients may benefit more from PD-1 monoclonal antibody therapy. This study also found that PD-1/PD-L1 positivity was associated with a higher rate of lymph node metastasis, with 41.2% of PD-L1 positive and 41.7% of PD-1 positive patients having lymph node metastasis, significantly higher than the 14.9% and 14.3% in PD-1/PD-L1 negative patients. HCC typically metastasizes via the bloodstream, with lymph node metastasis being rare, reported in only 1.6%-5.9% of cases during treatment and 25.5% in autopsies[19]. HCC patients with lymph node metastasis have a significantly worse prognosis than those without. The high lymph node metastasis rates in PD-1/PD-L1 positive patients (41.2% and 41.7%) suggest a worse prognosis without treatment. However, after PD-1 monoclonal antibody therapy, these patients achieved similar progression-free survival to PD-1/PD-L1 negative patients, indicating that PD-1/PD-L1 positive patients may be more suitable for PD-1 monoclonal antibody therapy and derive greater benefit. Conclusion In conclusion, in real-world HCC patients treated with PD-1 monoclonal antibodies, PD-1/PD-L1 expression in tumor tissues showed differences in pathology, laboratory tests, and clinical characteristics but did not demonstrate significant predictive value for treatment efficacy. However, given the potentially worse prognosis in PD-1/PD-L1 positive patients, they may be more suitable for PD-1 monoclonal antibody therapy and derive greater benefit. Due to the small sample size in this study, further research with larger cohorts is needed to explore the role of PD-1/PD-L1 in HCC development and progression, providing more insights for HCC prevention and treatment. Declarations Author Contribution Conceptualization, Huili Wu and Jun Lv; methodology, Huili Wu Lin Sun and Hui Liu; software and validation, Yang Wang; data curation, Mei Liu; writing—original draft preparation, Huili Wu; writing—review and editing, Jun Lv; funding acquisition, Huili Wu Yang Wang and Jun Lv. All authors have read and agreed to the published version of the manuscript. References Rumgay H, Arnold M, Ferlay J, et al. Global burden of primary liver cancer in 2020 and predictions to 2040. Journal of hepatology. 2022; 77: 1598-606. DOI:10.1016/ j.jhep. 2022.08.021. Zeng H, Zheng R, Sun K, et al. Cancer survival statistics in China 2019-2021: a multicenter, population-based study. Journal of the National Cancer Center. 2024; 4: 203-13. DOI: 10.1016/j.jncc. Zhang N, Yang X, Piao M, et al. Biomarkers and prognostic factors of PD-1/PD-L1 inhibitor-based therapy in patients with advanced hepatocellular carcinoma. Biomarker research. 2024; 12: 26. DOI: 10.1186/s40364-023-00535-z. Lee CK, Chan SL and Chon HJ. Could We Predict the Response of Immune Checkpoint Inhibitor Treatment in Hepatocellular Carcinoma? Cancers (Basel). 2022 Jun30;14(13):3213. DOI: 10.3390/ cancers14133213. Ji JH, Ha SY, Lee D, et al. Predictive Biomarkers for Immune-Checkpoint Inhibitor Treatment Response in Patients with Hepatocellular Carcinoma. Int J Mol Sci. 2023 Apr 21;24(8):7640. DOI:10.3390/ijms24087640. Yau T, Park JW, Finn RS, et al. Nivolumab versus sorafenib in advanced hepatocellular carcinoma (CheckMate 459): a randomised, multicentre, open-label, phase 3 trial. The Lancet Oncology . 2022; 23: 77-90. DOI: 10.1016/S1470-2045(21)00604-5 Finn RS, Ryoo BY, Merle P, et al. Pembrolizumab As Second-Line Therapy in Patients With Advanced Hepatocellular Carcinoma in KEYNOTE-240: A Randomized, Double-Blind, Phase III Trial. Journal of clinical oncology : official journal of the American Society of Clinical Oncology . 2020; 38: 193-202. DOI: 10.1200/JCO.19.01307 Finn RS, Qin S, Ikeda M, et al. Atezolizumab plus Bevacizumab in Unresectable Hepatocellular Carcinoma. The New England journal of medicine. 2020; 382: 1894-905. DOI: 10.1056/NEJMoa1915745 Ren Z, Xu J, Bai Y, et al. Sintilimab plus a bevacizumab biosimilar (IBI305) versus sorafenib in unresectable hepatocellular carcinoma (ORIENT-32): a randomised, open-label, phase 2-3 study. The Lancet Oncology . 2021; 22: 977-90. DOI: 10.1016/S1470-2045(21)00252-7. Qin S, Ren Z, Meng Z, et al. Camrelizumab in patients with previously treated advanced hepatocellular carcinoma: a multicentre, open-label, parallel-group, randomised, phase 2 trial. The Lancet Oncology. 2020; 21: 571-80. DOI: 10.1016/S1470-2045(20)30011-5 Reig M, Forner A, Rimola J, et al. BCLC strategy for prognosis prediction and treatment recommendation: The 2022 update. Journal of hepatology. 2022; 76: 681-93. Zou W, Wolchok JD and Chen L. PD-L1 (B7-H1) and PD-1 pathway blockade for cancer therapy: Mechanisms, response biomarkers, and combinations. Science translational medicine. 2016; 8: 328rv4. DOI: 10.1016/j.jhep.2021.11.018 Sharma P, Hu-Lieskovan S, Wargo JA and Ribas A. Primary, Adaptive, and Acquired Resistance to Cancer Immunotherapy. Cell. 2017; 168: 707-23. DOI: 10.1016/j.cell.2017.01.017 El-Khoueiry AB, Sangro B, Yau T, et al. Nivolumab in patients with advanced hepatocellular carcinoma (CheckMate 040): an open-label, non-comparative, phase 1/2 dose escalation and expansion trial. Lancet (London, England). 2017; 389: 2492-502. DOI: 10.1016/S0140-6736(17)31046-2 Qiu Xiaoli ZY, Liu Qingmei. Expression and Clinical Significance of PD-1 and PD-L1 in Primary Liver Cancer with Different Degree of Differentiation. Chinese and Foreign Medical Research. 2021; 19: 95-8. Zhou ZA-O, Liu SA-O, Xu LA-O, Liu CA-O and Zhang RA-O. Clinicopathological and Prognostic Value of Programmed Cell Death 1 Expression in Hepatitis B Virus-related Hepatocellular Carcinoma: A Meta-analysis. Clin Transl Hepatol. 2021 Dec 28;9(6):889-897. doi: 10.14218/JCTH. Yang J, Zhang W, Zhang Z, et al. Clinicopathological and Prognostic Roles of the Expression Levels of the Programmed Cell Death-1 Gene in Patients with Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis. Genetic testing and molecular biomarkers. 2020; 24: 641-8. DOI: 10.1089/gtmb.2020.0063. Li XS, Li JW, Li H and Jiang T. Prognostic value of programmed cell death ligand 1 (PD-L1) for hepatocellular carcinoma: a meta-analysis. Bioscience reports. 2020; 40. DOI: 10.1042/BSR20200459. Watanabe J, Nakashima O and Kojiro M. Clinicopathologic study on lymph node metastasis of hepatocellular carcinoma: a retrospective study of 660 consecutive autopsy cases. Japanese journal of clinical oncology. 1994; 24: 37-41. 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-6640195","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":458331185,"identity":"9858cf13-2fee-4839-94f6-183d6aa203f0","order_by":0,"name":"Huili Wu","email":"","orcid":"","institution":"Department of Medicine Oncology, Beijing YouAn Hospital, Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Huili","middleName":"","lastName":"Wu","suffix":""},{"id":458331186,"identity":"e6886356-0a45-4498-9ff6-060fea5df403","order_by":1,"name":"Hui Liu","email":"","orcid":"","institution":"Department of Pathology, Beijing YouAn Hospital, Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Hui","middleName":"","lastName":"Liu","suffix":""},{"id":458331187,"identity":"9563cb61-20bf-461b-b339-a7de5e3b6efd","order_by":2,"name":"Yang Wang","email":"","orcid":"","institution":"Department of Medicine Oncology, Beijing YouAn Hospital, Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yang","middleName":"","lastName":"Wang","suffix":""},{"id":458331188,"identity":"c27c3767-8f6b-4536-93e1-d06879edbada","order_by":3,"name":"Lin Sun","email":"","orcid":"","institution":"Department of Pathology, Beijing YouAn Hospital, Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Lin","middleName":"","lastName":"Sun","suffix":""},{"id":458331189,"identity":"e922771d-cef5-4cb3-8a35-42708434bdfd","order_by":4,"name":"Mei Liu","email":"","orcid":"","institution":"Department of Medicine Oncology, Beijing YouAn Hospital, Capital Medical University","correspondingAuthor":false,"prefix":"","firstName":"Mei","middleName":"","lastName":"Liu","suffix":""},{"id":458331190,"identity":"456f682d-b004-411c-91a8-feb162d9fe31","order_by":5,"name":"Jun Lv","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAx0lEQVRIiWNgGAWjYBACPgaGBAaGChs5KJ+ZsBY2sJYzacYkaWFgYGw7nNhAvBaJhGfShW1p6f3tp9MkGCqsExvYzx4gpCVNesY5m9wZZ3K3STCcSU9s4MlLIKyFpywtd4ME7zYJsAsleAyI0MJ2ON0ArOUf0VraDidAtDQQo4XnQbI1z5k0Q6BfNlskHEs3buPJwa+Fnz0n8TZPhY08f/vZjTc+1FjL9rOfwa+FgYEnAcEGMdkIqAcC9gOE1YyCUTAKRsHIBgDTnjznteoKMgAAAABJRU5ErkJggg==","orcid":"","institution":"Department of Medicine Oncology, Beijing YouAn Hospital, Capital Medical University","correspondingAuthor":true,"prefix":"","firstName":"Jun","middleName":"","lastName":"Lv","suffix":""}],"badges":[],"createdAt":"2025-05-11 14:38:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6640195/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6640195/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83149062,"identity":"d78f55ec-fd11-4c7f-8bdf-9c96afdba58a","added_by":"auto","created_at":"2025-05-20 13:30:53","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":202125,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6640195/v1/d632587c71a7f4a2901306e9.png"},{"id":83149066,"identity":"86201384-83cb-4cf9-9c72-9fcbb5e1ee9d","added_by":"auto","created_at":"2025-05-20 13:30:54","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":231611,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6640195/v1/8281fc30b26d1d4c7b670a70.png"},{"id":84232395,"identity":"7f69e75e-c5f8-4606-ac4b-ab7964bc54b5","added_by":"auto","created_at":"2025-06-09 14:08:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1531249,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6640195/v1/6ed6a55d-0308-4a3f-a0d2-ea92827cd966.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"PD-1/PD-L1 Expression and Predictive Value of Efficacy in HCC Patients with Anti-PD1 Therapy: A Real-World Study","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003ePrimary Liver Cancer (PLC), which includes malignancies originating from hepatocytes or intrahepatic bile duct epithelial cells, ranks as the sixth most common cancer globally and the fourth leading cause of cancer-related deaths. In 2020, there were over 900,000 new cases and more than 830,000 deaths worldwide, with nearly half of these cases occurring in China, where PLC has the highest incidence and mortality rates globally[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. PLC is characterized by its insidious onset, high malignancy, rapid progression, and challenging treatment. Recent statistics indicate that the 5-year survival rate for PLC patients in China is only 14.4%[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Hepatocellular Carcinoma (HCC) accounts for 75\u0026ndash;85% of PLC cases, and most patients are diagnosed at an advanced stage, losing the opportunity for surgical intervention. Consequently, HCC patients generally have a short overall survival and poor prognosis.In recent years, the application of immune checkpoint inhibitors, particularly Programmed Death Receptor-1 (PD-1) monoclonal antibodies, has brought new breakthroughs in the treatment of advanced PLC. However, the efficacy of PD-1 monoclonal antibody therapy varies significantly among patients, with only a portion (15\u0026ndash;40%) benefiting from the treatment. A significant proportion (approximately 20\u0026ndash;30%) of patients experience disease progression, and about 25% suffer from grade 3\u0026ndash;4 immune-related adverse events[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Thus, patients who do not benefit face substantial risks of immune-related adverse events and tumor progression. With the advent of personalized precision medicine, identifying predictive biomarkers to select patients who are more likely to benefit from immunotherapy is crucial, considering both the efficacy and economic aspects of drug therapy[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Programmed Death Ligand/Receptor 1 (PD-1/PD-L1) was initially considered a biomarker for predicting the efficacy of PD-1 monoclonal antibody therapy in HCC. Previous clinical studies on PD-1 monoclonal antibodies often used PD-1/PD-L1 as a predictive biomarker, but the conclusions were inconsistent and even contradictory [\u003cspan additionalcitationids=\"CR7 CR8 CR9\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. With the widespread clinical use of PD-1 inhibitors, there is limited clinical data on the expression of PD-1/PD-L1 in HCC patients in real-world settings and its predictive value for PD-1 monoclonal antibody therapy. Therefore, this study aims to detect the expression of PD-1/PD-L1 in HCC tissues using immunohistochemistry and analyze its correlation with clinical indicators, pathological characteristics, and treatment efficacy, providing a reference for HCC treatment and prognosis evaluation.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1Research subjects\u003c/h2\u003e \u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eA retrospective analysis was conducted on patients diagnosed with HCC via pathological examination at our center from December 2020 to December 2022. Inclusion criteria: (1) Patients had comprehensive serological and imaging examinations before obtaining pathological specimens; (2) Complete clinical data without omissions or missing information, and uncontaminated pathological tissues; (3) Patients had a history of PD-1 monoclonal antibody monotherapy (Tislelizumab, Sintilimab, or Camrelizumab). Exclusion criteria: (1) Patients with other malignant tumors; (2) Patients who received other anti-tumor treatments for HCC, such as targeted drugs, chemotherapy, radiotherapy, or local/systemic interventions like ablation; (3) Patients treated with systemic corticosteroids (equivalent to or higher than 10 mg/day of prednisone) or other immunosuppressive drugs; (4) Patients with a history of HIV infection, other acquired or congenital immunodeficiency diseases, or organ transplantation; (5) Patients who received PD-1 monoclonal antibodies for neoadjuvant or postoperative adjuvant therapy; (6) Pregnant patients; (7) Patients with a history of or concurrent other tumors were excluded. Tumor tissue samples were obtained through surgical resection or percutaneous liver biopsy. This study was conducted with the approval of the Ethics Committee and obtained an ethical batch number (LL-2021-184-K).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Methods\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1Laboratory Tests\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eBlood routine tests were performed using the Sysmex XN-550 automated hematology analyzer. Liver function and blood biochemistry were tested using the SK6100 automatic biochemical analyzer (Shenzhen Shengxinkang Technology Co., Ltd.). Alpha-fetoprotein (AFP) was measured using electrochemiluminescence immunoassay (Roche Cobas e601 automatic electrochemiluminescence immunoassay system, Roche reagents).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2Pathological examination\u003c/h2\u003e \u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eImmunohistochemical staining (immunoenzymatic method) was used to detect the distribution and expression of PD-1 and PD-L1 (using PD-1 antibody [CAL20] and PD-L1 [SP142] antibody from Abcam). Paraffin-embedded HCC tissue samples were sectioned into 5\u0026ndash;7 \u0026micro;m slices, transferred to clean slides, and dewaxed to water. Antigen retrieval was performed using microwave treatment for 15\u0026ndash;20 minutes, followed by cooling to room temperature. Endogenous peroxidase was blocked with PBS, and sections were incubated with rabbit serum. Primary antibodies were added and incubated overnight at 4\u0026deg;C, followed by secondary antibodies at 37\u0026deg;C for 30 minutes. Horseradish peroxidase-labeled streptavidin was added and incubated at room temperature for 20 minutes. Staining was observed under a microscope, and sections were counterstained with hematoxylin and mounted with glycerol. Positive staining was defined as the presence of yellow-brown to brown staining on the cell membrane or cytoplasm. Based on the expression level, samples were divided into positive (TPS\u0026thinsp;\u0026ge;\u0026thinsp;1%) and negative (TPS\u0026thinsp;\u0026lt;\u0026thinsp;1%) groups. Normal tonsil tissues (10 cases) and positive/negative control slides from the kit were used as controls. Other pathological data, including tumor differentiation, Glypican-3 (GPC-3), Hepatocyte Specific Antigen, CD34, Cytokeratin 7 and 19, p53, and Ki-67, were collected using the BOND-MAX automatic staining machine (Leica, Germany). Pathological diagnosis followed the \"Primary Liver Cancer Standardized Pathological Diagnosis Guidelines (2015 Edition)\" and was evaluated by two pathologists blinded to the patients' clinical and pathological data.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.2.3Imaging examination\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eImaging examinations, including abdominal enhanced MRI, enhanced CT, ultrasound, PET-CT, and hepatic artery angiography, performed within 14 days before PD-1 monoclonal antibody treatment, were used for baseline tumor staging.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.2.4Tumor staging and efficacy evaluation\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eTumor staging was based on imaging examinations according to the Barcelona Clinic Liver Cancer (BCLC) staging system[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Efficacy was evaluated using the Response Evaluation Criteria in Solid Tumors (RECIST 1.1): (1) Complete Response (CR): Disappearance of all target lesions, except for nodal disease, which must have a short axis\u0026thinsp;\u0026lt;\u0026thinsp;10 mm; (2) Partial Response (PR): At least a 30% decrease in the sum of diameters of target lesions, using the shortest diameter for nodal lesions and the longest diameter for non-nodal lesions; (3) Progressive Disease (PD): At least a 20% increase in the sum of diameters of target lesions, with an absolute increase of at least 5 mm, or the appearance of new lesions; (4) Stable Disease (SD): Neither sufficient shrinkage to qualify for PR nor sufficient increase to qualify for PD. In this study, CR, PR, and SD were considered effective treatment, while PD was considered ineffective.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Statistical analysis\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eStatistical analysis was performed using IBM SPSS Statistics 19. Normally distributed data were compared using t-tests or Kruskal-Wallis analysis of variance, expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. Non-normally distributed data were compared using the Mann-Whitney U test, expressed as median. Categorical data were compared using the chi-square test or Fisher's exact test. Survival analysis was performed by Kaplan-Meier method. A P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1General clinical sata of patients\u003c/h2\u003e\n \u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003eFrom December 2020 to December 2022, 858 HCC patients treated with PD-1 monoclonal antibodies were collected, of which 59 patients with pre-treatment HCC pathological tissue samples were included in this study. Among the 59 patients, 52 were male (88.1%) and 7 were female (11.9%), with mean ages of 57.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.0 and 60.1\u0026thinsp;\u0026plusmn;\u0026thinsp;9.7 years, respectively, showing no significant difference (P\u0026thinsp;=\u0026thinsp;0.428). PD-1 positivity was observed in 12 patients (20.33%), all of whom were male, but there was no significant gender difference (P\u0026thinsp;=\u0026thinsp;0.065). The mean ages of PD-1 positive and negative groups were 53.7\u0026thinsp;\u0026plusmn;\u0026thinsp;7.3 and 58.6\u0026thinsp;\u0026plusmn;\u0026thinsp;9.2 years, respectively, with no significant difference (P\u0026thinsp;=\u0026thinsp;0.093). PD-L1 positivity was observed in 18 patients (30.5%), including 17 males (94.4%) and 1 female (5.6%), with no significant gender difference (P\u0026thinsp;=\u0026thinsp;0.578). The mean ages of PD-L1 positive and negative groups were 55.4\u0026thinsp;\u0026plusmn;\u0026thinsp;9.4 and 58.5\u0026thinsp;\u0026plusmn;\u0026thinsp;8.8 years, respectively, with no significant difference (P\u0026thinsp;=\u0026thinsp;0.233). Six patients (10.2%) were positive for both PD-1 and PD-L1.\u003c/p\u003e\n \u003cp\u003eAll 59 patients were classified as BCLC stage B or C, and all had liver cirrhosis, with 91.5% being compensated cirrhosis. Forty-four patients (91.5%) had hepatitis B or C virus infection, 13 patients (22.0%) had high AFP levels (\u0026ge;\u0026thinsp;400 \u0026micro;g/mL), and 15 patients (25.4%) had tumors larger than 10 cm. Additionally, 13 patients (22%) had lymph node metastasis, 29 patients (49.2%) had a history of surgical resection, 11 patients (18.6%) had a history of hepatic artery catheter intervention, 38 patients (64.4%) had a history of targeted therapy, and 7 patients (11.9%) had a history of tumor ablation. PD-1 monoclonal antibodies were used as second-line therapy in 37 patients (62.7%) and as third-line or later therapy in 22 patients (37.3%).\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2PD-1/PD-L1 expression in HCC patients with different clinical characteristics\u003c/h2\u003e\n \u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003eAmong the 12 PD-1 positive patients, 5 (41.7%) had lymph node metastasis, while 7 (58.3%) did not. In the PD-1 negative group, 7 patients (14.9%) had lymph node metastasis, while 40 (85.1%) did not. Among the 18 PD-L1 positive patients, 7 (41.2%) had lymph node metastasis, while 10 (58.8%) did not. In the PD-L1 negative group, 6 patients (14.3%) had lymph node metastasis, while 36 (85.7%) did not. There were significant differences in lymph node metastasis between PD-1/PD-L1 positive and negative groups (P\u0026thinsp;=\u0026thinsp;0.040, 0.024). However, no significant differences were observed in BCLC staging, compensated or decompensated cirrhosis, hepatitis B or C virus infection, high AFP levels, tumor size\u0026thinsp;\u0026gt;\u0026thinsp;10 cm, or distant metastasis between PD-1/PD-L1 positive and negative groups (all P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). (Tables \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1 Expression of PD-1 in hepatocellular carcinoma tissues in patients with different clinical characteristics (N=59)\u003c/strong\u003e\u003c/p\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"536\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePD-1\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003epositive\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePD-1\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003enegative\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003et\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e/ \u003cem\u003ex\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eGender( n,%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e3.417\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e12(100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e40(85.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e0(0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e7(14.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eAge (years, \u003cem\u003ex\u0026plusmn;s\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e53.7\u0026plusmn;7.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e58.6\u0026plusmn;9.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e0.093\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e1.707\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eBCLC stage( n,%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Stage B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e2(16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e8(17.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eStage C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e10(83.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e39(83.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eLiver cirrhosis( n,%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Compensated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e11(91.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e43(91.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Decompensated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e1(8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e4(8.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eHepatitis virus infection( n,%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e0.575\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.315\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e10(83.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e44(93.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e2(16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e3(6.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eAFP( n,%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e0.853\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026ge;400ug/ml\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e3(25.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e13(27.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003e＜400ug/ml\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e9(75.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e34(72.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eTumor diameter( n,%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e0.970\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026ge;10cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e3(25.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e12(25.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003e＜10cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e9(75.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e35(74.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eLymph node metastasis ( n,%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e4.229\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e5(41.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e7(14.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e7(58.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e40(85.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eDistant metastasis( n,%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e0.948\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e6(50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e23(48.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e6(50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e24(51.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003eTreatment line( n,%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Second-line\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e9（75.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e28（75.7）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Third line and posterior line\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 45px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e3（25.0）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 87px;\"\u003e\n \u003cp\u003e9（24.3）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 50px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003eNote: Variables are expressed as the mean \u0026plusmn; SD or n (%).\u003c/p\u003e\n \u003cp\u003eAbbreviations: BCLC stage, Barcelona Clinic Liver, Cancer stage; AFP, \u0026alpha;-fetoprotei.\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eExpression of PD-L1 in Hepatocellular Carcinoma Tissues in Patients with Different Clinical Characteristics (N\u0026thinsp;=\u0026thinsp;59)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePD-L1\u003c/p\u003e\n \u003cp\u003epositive\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePD-L1\u003c/p\u003e\n \u003cp\u003enegative\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003et\u003c/em\u003e/ x\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGender ( n,%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.578\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.309\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17(94.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e35(85.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1(5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6(14.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge (years, \u003cem\u003ex\u0026thinsp;\u0026plusmn;\u0026thinsp;s\u003c/em\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e55.4\u0026thinsp;\u0026plusmn;\u0026thinsp;9.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e58.5\u0026thinsp;\u0026plusmn;\u0026thinsp;8.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.233\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.206\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBCLC stage ( n,%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.735\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.115\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003estage B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4(22.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6(14.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003estage C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14(77.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e35(85.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLiver cirrhosis( n,%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.322\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.979\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCompensated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15(83.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e39(95.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecompensated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3(16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2(4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHepatitis virus infection\u003c/p\u003e\n \u003cp\u003e( n,%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16(88.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e38(92.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2(11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3(7.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAFP( n,%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.816\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;400ug/ml\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7(38.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9(22.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;400ug/ml\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11(61.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32(78.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTumor diameter( n,%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.355\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.855\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;10cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6(33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9(22.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;10cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12(66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32(78.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLymph node metastasis\u003c/p\u003e\n \u003cp\u003e(n, %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.094\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7(41.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6(14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10(58.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36(85.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDistant metastasis( n,%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.594\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.107\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12(66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18(43.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6(33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e23(56.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTreatment line( n,%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.677\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.173\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSecond-line\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12(66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e25(80.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThird line and posterior line\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6(33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e16(19.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003eNote: Variables are expressed as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or n (%).\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003eAbbreviations: BCLC stage, Barcelona Clinic Liver, Cancer stage; AFP, \u0026alpha;-fetoprotei.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e3.3 Relationship between PD-1/PD-L1 expression and laboratory tests\u003c/p\u003e\n \u003cp\u003eThe neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) were calculated based on absolute neutrophil count (ANC), absolute lymphocyte count (ALC), and platelet count (PLT). Comparisons between PD-1/PD-L1 positive and negative groups showed that ANC was lower in the PD-1 positive group (3.32\u0026plusmn;1.19 vs. 4.02\u0026plusmn;2.22, P=0.020), and PLT was lower in the PD-L1 positive group (136.41\u0026plusmn;38.18 vs. 148.17\u0026plusmn;64.13, P=0.020). No significant differences were observed in other indicators(Tables 3 and 4).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Relationship Between PD-1 Expression and Laboratory Tests in Hepatocellular Car\u003c/strong\u003e\u003cstrong\u003ecinoma Tissues (N=59)\u003c/strong\u003e\u003c/p\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"511\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLaboratory tests\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePD-1 positive\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePD-1 negative\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003et\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eANC(E+9/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e3.96\u0026plusmn;1.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e3.86\u0026plusmn;2.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.583\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.631\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eALC(E+9/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e1.06\u0026plusmn;0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e1.12\u0026plusmn;0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.403\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.698\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eHB(g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e134.94\u0026plusmn;23.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e132.60\u0026plusmn;24.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.653\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.464\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003ePLT(E+9/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e136.41\u0026plusmn;38.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e148.17\u0026plusmn;64.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.902\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eNLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e4.37\u0026plusmn;2.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e4.39\u0026plusmn;3.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.086\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.892\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003ePLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e151.41\u0026plusmn;66.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e157.17\u0026plusmn;102.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.321\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.714\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 124px;\"\u003e\n \u003cp\u003eLDH(U/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e176.14\u0026plusmn;32.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e187.26\u0026plusmn;43.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.309\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e0.735\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cdiv\u003e\n \u003cp\u003eNote: Variables are expressed as the mean \u0026plusmn; SD.\u003c/p\u003e\n \u003cp\u003eAbbreviations: ANC:Absolute Neutrophil Count; ALC:Absolute Lymphocyte Count; HB:Hemoglobin; PLT:Platelet; NLR:Neutrophil-to-Lymphocyte Ratio; PLR:Platelet-to-Lymphocyte Ratio; LDH:Lactate Dehydrogenase.\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv class=\"BlockQuote\"\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eRelationship Between PD-L1 Expression and Laboratory Tests in Hepatocellular Carcinoma Tissues (N\u0026thinsp;=\u0026thinsp;59)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLaboratory tests\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePD-L1 positive\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePD-L1 negative\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eANC(E\u0026thinsp;+\u0026thinsp;9/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.32\u0026thinsp;\u0026plusmn;\u0026thinsp;1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.02\u0026thinsp;\u0026plusmn;\u0026thinsp;2.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.901\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eALC(E\u0026thinsp;+\u0026thinsp;9/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.23\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.848\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHB(g/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e138.004\u0026thinsp;\u0026plusmn;\u0026thinsp;25.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e132.40\u0026thinsp;\u0026plusmn;\u0026thinsp;23.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.852\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.641\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePLT(E\u0026thinsp;+\u0026thinsp;9/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e145.67\u0026thinsp;\u0026plusmn;\u0026thinsp;64.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e144.057\u0026thinsp;\u0026plusmn;\u0026thinsp;56.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.975\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.077\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.72\u0026thinsp;\u0026plusmn;\u0026thinsp;2.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.52\u0026thinsp;\u0026plusmn;\u0026thinsp;3.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.564\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.663\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e148.22\u0026thinsp;\u0026plusmn;\u0026thinsp;80.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e156.77\u0026thinsp;\u0026plusmn;\u0026thinsp;95.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.771\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.251\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLDH(U/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e182.33\u0026thinsp;\u0026plusmn;\u0026thinsp;27.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e184.52\u0026thinsp;\u0026plusmn;\u0026thinsp;42.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.087\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eNote: Variables are expressed as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eAbbreviations: ANC:Absolute Neutrophil Count; ALC:Absolute Lymphocyte Count; HB:Hemoglobin; PLT:Platelet; NLR:Neutrophil-to-Lymphocyte Ratio; PLR: Platelet-to-Lymphocyte Ratio; LDH:Lactate Dehydrogenase.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e3.4Relationship between PD-1/PD-L1 expression and pathological characteristics of HCC\u003c/p\u003e\n \u003cp\u003eIn terms of tumor differentiation, 91.7% (11/12) of PD-L1 positive patients had undifferentiated/poorly differentiated tumors, compared to 44.7% (21/47) in the PD-L1 negative group, showing a significant difference (P=0.002). Additionally, Ki67 expression was significantly higher in the PD-L1 positive group (54.2\u0026plusmn;29.3 vs. 37.8\u0026plusmn;22.4, P=0.039). No significant difference was observed in GPC3 positivity between PD-L1 positive and negative groups (P\u0026gt;0.05). Meanwhile, no significant differences were observed in tumor differentiation, Ki67 expression, or GPC3 positivity between PD-1 positive and negative groups (all P\u0026gt;0.05) (Tables 5 and 6).\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eRelationship Between PD-1 Expression and Pathological Characteristics in Hepatocellular Carcinoma Tissues (N\u0026thinsp;=\u0026thinsp;59)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePathological Characteristics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePD-1 positive\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePD-1 negative\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003et/ x\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e/Z\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDifferentiation( n,%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.204\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.612\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUndifferentiated/Low\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12(66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20(48.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate/High\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6(33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21(51.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKi67( %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e48.1\u0026thinsp;\u0026plusmn;\u0026thinsp;24.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e38.1\u0026thinsp;\u0026plusmn;\u0026thinsp;24.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e1.445\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGPC3( n,%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.938\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5(41.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19(40.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003enegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7(58.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e28(59.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"1\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003eNote: Variables are expressed as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\"\u003eAbbreviations: Ki67: Ki-67 protein; GPC3: Glypican-3.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab6\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eRelationship Between PD-L1 Expression and Pathological Characteristics in Hepatocellular Carcinoma Tissues (N\u0026thinsp;=\u0026thinsp;59)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePathological Characteristics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePD-L1 positive\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePD-L1 negative\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003et/ x\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e/Z\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDifferentiation\u003c/strong\u003e( n,%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9.860\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUndifferentiated/Low\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11(91.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21(44.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate/High\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1(8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26(55.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKi67( %)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e54.2\u0026thinsp;\u0026plusmn;\u0026thinsp;29.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e37.8\u0026thinsp;\u0026plusmn;\u0026thinsp;22.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.117\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGPC3( n,%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.853\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePositive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7(38.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e17(41.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003enegative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11(61.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24(58.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eNote: Variables are expressed as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eAbbreviations: Ki67: Ki-67 protein; GPC3: Glypican-3.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e3.5Relationship between PD-1/PD-L1 expression and treatment efficacy\u003c/p\u003e\n \u003cp\u003eAmong the 59 patients, 48 had post-treatment efficacy evaluations, with 13 patients (27.1%) showing effective treatment. The effective rates in PD-1 positive and negative groups were 33.3% (3/9) and 25.6% (10/39), respectively, with no significant difference in progression-free survival (3.6\u0026plusmn;2.4 months vs. 3.6\u0026plusmn;3.2 months, P\u0026gt;0.05)（Figure1 and 2）. In the PD-L1 positive and negative groups, the effective rates were 16.7% (2/12) and 30.6% (11/36), respectively, with no significant difference in progression-free survival (3.0\u0026plusmn;2.6 months vs. 3.8\u0026plusmn;3.2 months, P\u0026gt;0.05) (Tables 7 and 8).\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab7\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eRelationship Between PD-1 Expression and Efficacy of PD-1 Treatment in Hepatocellular Carcinoma Tissues (N\u0026thinsp;=\u0026thinsp;48)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePD-1 positive\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePD-1 negative\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003et/ x\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e/Z\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEfficacy( n,%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.959\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEffective\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3(33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10(25.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIneffective\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6(66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e29(74.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePFS(months)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.6\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.954\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eNote: Variables are expressed as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eAbbreviations: PFS: Progression-Free Survival.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab8\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eRelationship Between PD-L1 Expression and Efficacy of PD-1 Treatment in Hepatocellular Carcinoma Tissues (N\u0026thinsp;=\u0026thinsp;48)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePD-L1 positive\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePD-L1 negative\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003et/ x\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e/Z\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEfficacy( n,%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.574\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.316\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEffective\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2(16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11(30.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIneffective\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10(83.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e25(69.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePFS(months)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.454\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.755\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eNote: Variables are expressed as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD.\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eAbbreviations: PFS: Progression-Free Survival.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003ePD-1/PD-L1 is a critical negative regulatory factor in tumor immunity, enabling tumor cells to evade immune surveillance through immune checkpoint mechanisms, thereby promoting tumorigenesis. Previous studies have shown that the PD-1/PD-L1 signaling pathway also plays a role in cell proliferation and differentiation, processes that are markedly abnormal in tumor cells. Thus, this pathway is closely linked to tumor development and progression [12,13]. PD-1 monoclonal antibodies target this pathway, blocking PD-1/PD-L1 interactions to induce tumor cell death. Numerous clinical trials have demonstrated the potent anti-tumor efficacy of PD-1 inhibitors across various cancer types. Since the first approval of PD-1 monoclonal antibodies for second-line HCC treatment in 2017[14], many clinical studies have been conducted. However, the response rates in HCC patients remain unsatisfactory, making the search for predictive biomarkers for PD-1 efficacy a hot topic in recent years.\u003c/p\u003e\n\u003cp\u003eMost studies suggest that PD-L1 expression in tumor tissues has predictive value for treatment efficacy, but this remains controversial. In the CheckMate040 trial of Nivolumab for HCC, 34 out of 174 patients (20.0%) had PD-L1 positive tumors, with only 9 (26%) showing treatment response, slightly higher than the 19% response rate in the negative group[14]. In contrast, the CheckMate459 trial of Nivolumab for HCC showed that 71 out of 366 patients (19.4%) had PD-L1 positive tumors, with a 28% objective response rate (ORR) in the positive group compared to 12% in the negative group, although no differences were observed in progression-free survival or overall survival[6]. Additionally, in a domestic trial (NCT02989922) of Camrelizumab for HCC, 11 out of 30 patients (36.7%) had PD-L1 positive tumors, with a 36% ORR in the positive group compared to 11% in the negative group[10]. These inconsistent and even contradictory results highlight the need for further research. This study observed PD-L1 expression in HCC tissues in a real-world setting, finding a 30.51% positivity rate using TPS \u0026ge;1% as the cutoff. The effective rates in PD-L1 positive and negative groups were 16.7% and 30.6%, respectively, with progression-free survival of 3.0\u0026plusmn;2.6 months and 3.8\u0026plusmn;3.2 months, respectively. Although no significant differences were observed, possibly due to the small sample size, the data suggest that PD-L1 positive patients may have a worse prognosis.In clinical practice, PD-1 monoclonal antibodies are often combined with other anti-tumor drugs, such as targeted therapies. PD-1 monotherapy is typically used in patients intolerant to targeted therapies, often in advanced stages or as second-line treatment. PD-L1 positive patients may have faster tumor progression, potentially explaining the lower response rates observed in this study compared to previous clinical trials. Additionally, this study found that PD-L1 positivity was associated with poorly differentiated tumors and higher Ki67 expression, consistent with previous findings[15], further explaining the poorer prognosis in PD-L1 positive HCC patients.\u003c/p\u003e\n\u003cp\u003eCompared to PD-L1, there is limited research on PD-1 expression in HCC tissues. Since PD-1 is primarily expressed in inflammatory cells, previous studies have shown [16-18] a high PD-1 positivity rate in HCC tissues (up to 58%), especially in patients with AFP \u0026ge;400 \u0026mu;g/L, correlating with tumor differentiation and microvascular formation. However, PD-1 expression in HCC tissues has not been established as a predictive biomarker for PD-1 or PD-L1 monoclonal antibody efficacy, and its significance warrants further exploration. In this study, PD-1 positivity was observed in 20.33% of HCC patients, with 41.7% of PD-1 positive patients having lymph node metastasis, significantly higher than the 14.9% in PD-1 negative patients. Additionally, PD-1 positive patients had lower absolute neutrophil counts (3.32\u0026plusmn;1.19 vs. 4.02\u0026plusmn;2.22, P=0.020). In HCC patients, lymph node metastasis is often associated with poor prognosis, and in cirrhotic patients, lower neutrophil counts may indicate worse liver function and immune status, predicting a poorer prognosis. However, in this study, PD-1 positive patients treated with PD-1 monoclonal antibodies did not show the expected worse outcomes, with a 33.3% response rate, higher than the 25.9% in PD-1 negative patients, suggesting that PD-1 positive patients may benefit more from PD-1 monoclonal antibody therapy.\u003c/p\u003e\n\u003cp\u003eThis study also found that PD-1/PD-L1 positivity was associated with a higher rate of lymph node metastasis, with 41.2% of PD-L1 positive and 41.7% of PD-1 positive patients having lymph node metastasis, significantly higher than the 14.9% and 14.3% in PD-1/PD-L1 negative patients. HCC typically metastasizes via the bloodstream, with lymph node metastasis being rare, reported in only 1.6%-5.9% of cases during treatment and 25.5% in autopsies[19]. HCC patients with lymph node metastasis have a significantly worse prognosis than those without. The high lymph node metastasis rates in PD-1/PD-L1 positive patients (41.2% and 41.7%) suggest a worse prognosis without treatment. However, after PD-1 monoclonal antibody therapy, these patients achieved similar progression-free survival to PD-1/PD-L1 negative patients, indicating that PD-1/PD-L1 positive patients may be more suitable for PD-1 monoclonal antibody therapy and derive greater benefit.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, in real-world HCC patients treated with PD-1 monoclonal antibodies, PD-1/PD-L1 expression in tumor tissues showed differences in pathology, laboratory tests, and clinical characteristics but did not demonstrate significant predictive value for treatment efficacy. However, given the potentially worse prognosis in PD-1/PD-L1 positive patients, they may be more suitable for PD-1 monoclonal antibody therapy and derive greater benefit. Due to the small sample size in this study, further research with larger cohorts is needed to explore the role of PD-1/PD-L1 in HCC development and progression, providing more insights for HCC prevention and treatment.\u003c/p\u003e\n"},{"header":"Declarations","content":"\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization, Huili Wu and Jun Lv; methodology, Huili Wu Lin Sun and Hui Liu; software and validation, Yang Wang; data curation, Mei Liu; writing\u0026mdash;original draft preparation, Huili Wu; writing\u0026mdash;review and editing, Jun Lv; funding acquisition, Huili Wu Yang Wang and Jun Lv. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eRumgay H, Arnold M, Ferlay J, et al. Global burden of primary liver cancer in 2020 and predictions to 2040. \u003cem\u003eJournal of hepatology.\u003c/em\u003e 2022; 77: 1598-606. DOI:10.1016/ j.jhep. 2022.08.021.\u003c/li\u003e\n\u003cli\u003eZeng H, Zheng R, Sun K, et al. Cancer survival statistics in China 2019-2021: a multicenter, population-based study. \u003cem\u003eJournal of the National Cancer Center.\u003c/em\u003e 2024; 4: 203-13. DOI: 10.1016/j.jncc.\u003c/li\u003e\n\u003cli\u003eZhang N, Yang X, Piao M, et al. Biomarkers and prognostic factors of PD-1/PD-L1 inhibitor-based therapy in patients with advanced hepatocellular carcinoma. \u003cem\u003eBiomarker research. \u003c/em\u003e2024; 12: 26. DOI: 10.1186/s40364-023-00535-z.\u003c/li\u003e\n\u003cli\u003eLee CK, Chan SL and Chon HJ. Could We Predict the Response of Immune Checkpoint Inhibitor Treatment in Hepatocellular Carcinoma? \u003cem\u003eCancers (Basel).\u003c/em\u003e 2022 Jun30;14(13):3213. DOI: 10.3390/ cancers14133213.\u003c/li\u003e\n\u003cli\u003eJi JH, Ha SY, Lee D, et al. Predictive Biomarkers for Immune-Checkpoint Inhibitor Treatment Response in Patients with Hepatocellular Carcinoma. \u003cem\u003eInt J Mol Sci. \u003c/em\u003e2023 Apr 21;24(8):7640. DOI:10.3390/ijms24087640.\u003c/li\u003e\n\u003cli\u003eYau T, Park JW, Finn RS, et al. Nivolumab versus sorafenib in advanced hepatocellular carcinoma (CheckMate 459): a randomised, multicentre, open-label, phase 3 trial. \u003cem\u003eThe Lancet Oncology\u003c/em\u003e. 2022; 23: 77-90. DOI: 10.1016/S1470-2045(21)00604-5\u003c/li\u003e\n\u003cli\u003eFinn RS, Ryoo BY, Merle P, et al. Pembrolizumab As Second-Line Therapy in Patients With Advanced Hepatocellular Carcinoma in KEYNOTE-240: A Randomized, Double-Blind, Phase III Trial. \u003cem\u003eJournal of clinical oncology : official journal of the American Society of Clinical Oncology\u003c/em\u003e. 2020; 38: 193-202. DOI: 10.1200/JCO.19.01307\u003c/li\u003e\n\u003cli\u003eFinn RS, Qin S, Ikeda M, et al. Atezolizumab plus Bevacizumab in Unresectable Hepatocellular Carcinoma. \u003cem\u003eThe New England journal of medicine.\u003c/em\u003e 2020; 382: 1894-905. DOI: 10.1056/NEJMoa1915745\u003c/li\u003e\n\u003cli\u003eRen Z, Xu J, Bai Y, et al. Sintilimab plus a bevacizumab biosimilar (IBI305) versus sorafenib in unresectable hepatocellular carcinoma (ORIENT-32): a randomised, open-label, phase 2-3 study. \u003cem\u003eThe Lancet Oncology\u003c/em\u003e. 2021; 22: 977-90. DOI: 10.1016/S1470-2045(21)00252-7.\u003c/li\u003e\n\u003cli\u003eQin S, Ren Z, Meng Z, et al. Camrelizumab in patients with previously treated advanced hepatocellular carcinoma: a multicentre, open-label, parallel-group, randomised, phase 2 trial. \u003cem\u003eThe Lancet Oncology.\u003c/em\u003e 2020; 21: 571-80. DOI: 10.1016/S1470-2045(20)30011-5\u003c/li\u003e\n\u003cli\u003eReig M, Forner A, Rimola J, et al. BCLC strategy for prognosis prediction and treatment recommendation: The 2022 update. \u003cem\u003eJournal of hepatology. \u003c/em\u003e2022; 76: 681-93.\u003c/li\u003e\n\u003cli\u003eZou W, Wolchok JD and Chen L. PD-L1 (B7-H1) and PD-1 pathway blockade for cancer therapy: Mechanisms, response biomarkers, and combinations. \u003cem\u003eScience translational medicine.\u003c/em\u003e 2016; 8: 328rv4. DOI: 10.1016/j.jhep.2021.11.018\u003c/li\u003e\n\u003cli\u003eSharma P, Hu-Lieskovan S, Wargo JA and Ribas A. Primary, Adaptive, and Acquired Resistance to Cancer Immunotherapy. \u003cem\u003eCell.\u003c/em\u003e 2017; 168: 707-23. DOI: 10.1016/j.cell.2017.01.017\u003c/li\u003e\n\u003cli\u003eEl-Khoueiry AB, Sangro B, Yau T, et al. Nivolumab in patients with advanced hepatocellular carcinoma (CheckMate 040): an open-label, non-comparative, phase 1/2 dose escalation and expansion trial. \u003cem\u003eLancet (London, England). \u003c/em\u003e2017; 389: 2492-502. DOI: 10.1016/S0140-6736(17)31046-2\u003c/li\u003e\n\u003cli\u003eQiu Xiaoli ZY, Liu Qingmei. Expression and Clinical Significance of PD-1 and PD-L1 in Primary Liver Cancer with Different Degree of Differentiation. \u003cem\u003eChinese and Foreign Medical Research.\u003c/em\u003e 2021; 19: 95-8.\u003c/li\u003e\n\u003cli\u003eZhou ZA-O, Liu SA-O, Xu LA-O, Liu CA-O and Zhang RA-O. Clinicopathological and Prognostic Value of Programmed Cell Death 1 Expression in Hepatitis B Virus-related Hepatocellular Carcinoma: A Meta-analysis. \u003cem\u003eClin Transl Hepatol.\u003c/em\u003e 2021 Dec 28;9(6):889-897. doi: 10.14218/JCTH.\u003c/li\u003e\n\u003cli\u003eYang J, Zhang W, Zhang Z, et al. Clinicopathological and Prognostic Roles of the Expression Levels of the Programmed Cell Death-1 Gene in Patients with Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis. \u003cem\u003eGenetic testing and molecular biomarkers. \u003c/em\u003e2020; 24: 641-8. DOI: 10.1089/gtmb.2020.0063.\u003c/li\u003e\n\u003cli\u003eLi XS, Li JW, Li H and Jiang T. Prognostic value of programmed cell death ligand 1 (PD-L1) for hepatocellular carcinoma: a meta-analysis. \u003cem\u003eBioscience reports.\u003c/em\u003e 2020; 40. DOI: 10.1042/BSR20200459.\u003c/li\u003e\n\u003cli\u003eWatanabe J, Nakashima O and Kojiro M. Clinicopathologic study on lymph node metastasis of hepatocellular carcinoma: a retrospective study of 660 consecutive autopsy cases.\u003cem\u003e \u003c/em\u003e\u003cem\u003eJapanese journal of clinical oncology. \u003c/em\u003e1994; 24: 37-41.\u003c/li\u003e\n\u003c/ol\u003e\n"}],"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":"Hepatocellular carcinoma, Immunotherapy, Programmed death deceptor-1, Efficacy prediction","lastPublishedDoi":"10.21203/rs.3.rs-6640195/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6640195/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground/Objectives\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe conclusions regarding PD-1/PD-L1 expression and its role as a predictive biomarker for treatment efficacy had been inconsistent in previous clinical trials of PD-1 monoclonal antibodies therapy for hepatocellular carcinoma (HCC). Therefore, this study aimed to analyze the expression of PD-1/PD-L1 in HCC patients treated with PD-1 in real-world settings and to evaluate its predictive value for treatment outcomes.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: A retrospective study was conducted on 59 pathologically confirmed HCC patients. PD-1/PD-L1 expression in tumor tissues was assessed via immunohistochemical staining. Clinical characteristics, laboratory parameters, pathological features, and therapeutic outcomes were compared between two groups.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: Among 59 patients, 12 (20.33%) were PD-1-positive and 18 (30.51%) were PD-L1-positive. The PD-1-positive group exhibited a higher incidence of lymph node metastasis (41.7% vs. 14.9%, P = 0.040) and lower neutrophil counts (3.32 ± 1.19 vs. 4.02 ± 2.22, P = 0.020) compared to the negative group. The PD-L1-positive group showed increased lymph node metastasis (41.2% vs. 14.3%, P = 0.024), reduced platelet counts (136.41 ± 38.18 vs. 148.17 ± 64.13, P = 0.020), higher proportions of poorly differentiated histology (91.7% vs. 44.7%, P = 0.002), and elevated Ki67 expression (54.2 ± 29.3 vs. 37.8 ± 22.4, P = 0.039). However, no significant differences were observed in objective response rate or progression-free survival between PD-1/PD-L1 positive and negative groups(P\u0026gt;0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: PD-1/PD-L1 expression in HCC tissues is associated with distinct clinicopathological features but demonstrates no significant predictive value for anti-PD-1 therapy efficacy.\u003c/p\u003e","manuscriptTitle":"PD-1/PD-L1 Expression and Predictive Value of Efficacy in HCC Patients with Anti-PD1 Therapy: A Real-World Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-20 13:30:49","doi":"10.21203/rs.3.rs-6640195/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":"ae86de97-d5df-4018-89e5-0c766627dbed","owner":[],"postedDate":"May 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-16T10:23:35+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-20 13:30:49","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6640195","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6640195","identity":"rs-6640195","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}