MCP-1-CCR2-M2 macrophages axis contributes to diffuse large B-cell lymphoma progression and inhibits antitumor immune response

MCP-1-CCR2-M2 macrophages axis contributes to diffuse large B-cell lymphoma progression and inhibits antitumor immune response | 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 Article MCP-1-CCR2-M2 macrophages axis contributes to diffuse large B-cell lymphoma progression and inhibits antitumor immune response Zhao-Feng Wen, Qi-Tang Huang, Feng-Ya Nan, Zhi-Min Zhai, Yan-Li Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6219553/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Diffuse large B-cell lymphoma (DLBCL) is an aggressive hematological malignancy with restricted effective therapy choices. The MCP-1/CCR2 axis is required for the recruitment of monocytes and polarization of macrophages. We investigated the feasibility of treatment targeting MCP-1-CCR2-macrophages axis in DLBCL. MCP-1, CD68, CD163 expression was analyzed by immunohistochemistry in 143 DLBCL patients tissues, and MCP-1 concentration and CD14+CCR2+ monocytes in peripheral blood were analyzed in another cohort by enzyme linked immunosorbent assay or flow cytometry. THP-1 or U937 cells were used to mimic macrophages polarization with or without the blockade of MCP-1/CCR2 axis in vitro. BALB/C mice subcutaneous tumors were evaluated and detected after blocking MCP-1/CCR2 axis with CCR2 antagonist. MCP-1, CD68, CD163 expression and proportion of CD14+CCR2+ monocytes in peripheral blood are prognostic for DLBCL patients. MCP-1 expression is positively associated with CD68 or CD163 expression in DLBCL. Blockade of MCP-1/CCR2 axis with CCR2 antagonist inhibits monocytes recruitment and M2 macrophages polarization in vitro and concomitantly increases the number of CD8 T-cells, which can lead to inhibition of subcutaneous tumour growth. MCP-1-CCR2-M2 macrophages polarization plays vital roles in DLBCL progression. The results demonstrate the translational potential of MCP-1/CCR2 blockade for treatment of DLBCL. Biological sciences/Cancer/Haematological cancer Biological sciences/Cancer/Cancer microenvironment diffuse large B-cell lymphoma MCP-1/CCR2 axis M2 macrophages polarization progression antitumor immune response Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Introduction Diffuse large B-cell lymphoma (DLBCL) is the aggressive hematological malignancy originated from B cells, also known as the most common adult non-Hodgkin lymphoma (NHL), accounting for about 30-40%. It’s standard chemotherapy CHOP (cyclophosphamide, doxorubicin, vincristine and prednisone) or R-CHOP (rituximab+ CHOP) has greatly improved the cure rate up to 60-70% 1 . However, 30-40% patients eventually develop refractory or recurrence. Therefore, it is urgent to explore more targeted and effective therapeutic methods for these patients 2 . In DLBCL, the tumor stromal component consists of a wide range of cells, including kinds of infiltrating inflammatory cells, endothelial cells, fibroblasts and so on. These cells create a special environment to influence tumor initiation, development or response to treatment 3 . Among these infiltrating inflammatory cells, tumor-associated macrophages (TAMs) as one of the main components, has been confirmed to exert vital roles in tumors. For example, the amount of TAMs could predict patients prognosis in hepatocellular carcinoma, lung cancer and DLBCL 4-6 . As known, TAMs are primarily derived from blood monocytes via the chemotaxis of MCP-1/CCR2 axis 7 . Chemokines are small and secreted proteins that play their roles by binding to the specific receptors expressed on cell surface in disease involving inflammation, including tumors 8,9 . Monocyte chemoattractant protein-1 (MCP-1), also known as C-C motif ligand 2 (CCL2), was first discovered and well understood CC chemokine and its primary receptor is CC chemokine receptor 2 (CCR2) 10 . MCP-1 can be secreted by different types of cells, including tumor cells, epithelial cells, fibroblasts, endothelial cells and others 11 . As the main receptor of MCP-1, CCR2 is expressed by kinds of cells such as monocytes 12 , endothelial cells 13 , dendritic cells 14 and tumor cells. Now, the role of MCP-1/CCR2 axis in chemotaxis has been well understood, and moreover, the non-chemotactic role has also attracted more and more attention. For example, Liat Izhak 15 et al determined MCP-1/CCR2 axis promoted tumor survival/growth in an autocrine manner by in vivo experiment, and Yang 16 et al found MCP-1/CCR2 axis promoted tumor metastasis by activating ERK1/2-MMP2/9 pathway in nasopharyngeal carcinoma. Additionally, MCP-1/CCR2 axis has been confirmed to participate in TAMs polarization such as MCP-1 and IL-6 could promote CD206 expression 17 , and MCP-1 increased M2 polarization of TAMs by granulocyte- macrophage colony-stimulating factor (GM-CSF) and granulocyte colony- stimulating factor (G-CSF) in vitro 18 . In some preclinical studies, treatment targeting MCP-1/CCR2 axis has achieved encouraging results. However, the role of MCP-1/CCR2 axis in DLBCL remains little understood and this inspires us to explore the potential of targeting MCP-1/CCR2 axis in DLBCL. In this study, we analyzed MCP-1, CD68 and CD163 expression in DLBCL tissues, the MCP-1 concentration and amount of CD14+CCR2+ monocytes in DLBCL patients’ peripheral blood, and further investigated the correlation between MCP-1 and CD68, CD163 expression. Additionally, we used THP-1 cells and A20 cells to investigate the function of MCP-1/CCR2 axis in M2 macrophages polarization by in vitro and in vivo experiments. Results Immunohistochemical MCP-1, CD68 and CD163 staining in DLBCL patients Immunohistochemistry was performed to analyze the expression of MCP-1, CD68 and CD163 in 143 DLBCL patients’ tissue samples. As results, MCP-1 positive staining was observed in cytoplasm of tumor cells (Fig.1A,B), and 75.5% (108/143) cases showed high MCP-1 expression. CD68 positive staining was observed in cytoplasm of macrophages (Fig.1C,D), and 42.7% (61/143) cases showed high CD68 expression. CD163 positive staining was observed in the membrane of macrophages (Fig.1E,F), and 46.2% (66/143) cases showed high CD163 expression. Clinicopathological characteristics according to MCP-1, CD68 or CD163 expression and the correlation of MCP-1 and CD68 or CD163 in DLBCL patients The clinicopathological characteristics are showed in Table 1. As is shown, high CD68 expression was related with poor ECOG-PS (P=0.050), more extranodal sites of disease (P=0.003), Ⅲ/Ⅳ Ann Arbor stage (P=0.002), elevated LDH level (P=0.001), 3-5 IPI score (P＜0.001), worse response (P＜0.001), high AMC (P＜0.001) and ABC type (P＜0.001), high CD163 expression was correlated with more extranodal sites of disease (P=0.004), Ⅲ/Ⅳ Ann Arbor stage (P=0.001), elevated LDH level (P＜0.001), 3-5 IPI score (P＜0.001), worse response (P＜0.001), high AMC (P＜0.001) and ABC type (P＜0.001), and high MCP-1 expression was correlated with poor ECOG-PS (P=0.018), more extranodal sites of disease (P=0.024), Ⅲ/Ⅳ Ann Arbor stage (P=0.002), elevated LDH level (P＜0.001), 3-5 IPI score (P＜0.001), worse response (P＜0.001), high AMC (P＜0.001) and ABC type (P＜0.001) (Table 1). Further, Spearman analysis showed the expression level of MCP-1 was significantly positively associated with CD68 (r=0.458, P ＜0.001); at the same time, a significant positive correlation also existed between the expression of MCP-1 and CD163 (r=0.494, P ＜0.001) (Table 2). Table 1 Patient ’ s demographics according to CD68, CD163 and MCP-1 expression Characteristics Patients CD68 expression CD163 expression MCP-1 expression NO % Low High P Low High P Low High P Gender male 80 55.9 43 37 0.328 41 39 0.483 20 60 0.869 female 63 44.1 39 24 36 27 15 48 Age ＜60 87 60.8 51 36 0.700 47 40 0.958 21 66 0.907 ≥60 56 39.2 31 25 30 26 14 42 ECOG-PS ≤1 86 60.1 55 31 0.050 52 34 0.051 27 59 0.018 ＞1 57 39.9 27 30 25 32 8 49 Extranodal sites of disease ≤1 111 77.6 71 40 0.003 67 44 0.004 32 79 0.024 ＞1 32 22.4 11 21 10 22 3 29 Ann Arbor stage Ⅰ/Ⅱ 73 51.0 51 22 0.002 49 24 0.001 26 47 0.002 Ⅲ/Ⅳ 70 49.0 31 39 28 42 9 61 LDH ≤245 100 69.9 66 34 0.001 64 36 ＜0.001 34 66 ＜0.001 ＞245 43 30.1 16 27 13 30 1 42 IPI score 0-2 93 65.0 65 28 ＜0.001 62 31 ＜0.001 32 61 ＜0.001 3-5 50 35.0 17 33 15 35 3 47 Treatment R-CHOP 39 27.3 27 12 0.078 26 13 0.060 14 25 0.052 CHOP 104 72.7 55 49 51 53 21 83 Evaluation CR PR uCR 58 40.6 17 41 ＜0.001 16 42 ＜0.001 1 57 ＜0.001 PD 85 59.4 65 20 61 24 34 51 AMC ＜460 75 52.4 54 21 ＜0.001 55 20 <0.001 30 45 ＜0.001 ≥460 68 47.6 28 40 22 46 5 63 GCB/ABC GCB 64 44.8 55 9 ＜0.001 54 10 ＜0.001 32 32 ＜0.001 ABC 79 55.2 27 52 23 56 3 76 Abbreviations: ECOG-PS Eastern Cooperative Oncology Group performance status, LDH lactate dehydrogenase, IPI International Prognostic Index, CR Complete response, PR Partial response, uCR complete response, PD Progressive disease, AMC absolute monocyte count, CHOP cyclophosphamide hydroxydaunorubicin vincristine prednisone, R-CHOP rituximab- cyclophosphamide hydroxydaunorubicin vincristine prednisone. Table 2 Spearman analysis of MCP-1 and CD68 or CD163 in DLBCL staining MCP-1 expression total r P Low High CD68 Low 34 48 82 0.458 ＜0.001 High 1 60 61 CD163 Low 34 43 77 0.494 ＜0.001 High 1 65 66 High MCP-1 and CD163 expression are independent prognostic factors for survival and the prognostic value of MCP-1, CD68 and CD163 expression in DLBCL patients Multivariate analyses was used to explore whether MCP-1 or CD68 or CD163 was the independent prognostic factor for DLBCL patients’ survival. By multivariate analyses, we found MCP-1 expression and the subtypes of DLBCL were independent prognostic factors for overall survival (OS, HR 11.1145, 95% CI 3.416-18.813, P＜0.001 and HR 3.2055, 95% CI 1.352-5.059) and progression-free survival (PFS, HR 15.507, 95% CI 3.446-27.568, P＜0.001 and HR 10.747, 95% CI 3.544-17.950, P＜0.001). Besides, CD163 expression and LDH level were independent prognostic factors for PFS (HR 3.178, 95% CI 1.027-5.329, P=0.043 and HR 2.635, 95% CI 1.156-4.113, P=0.016) (Table 3). For more detailed exploration, Kaplan-Meier analysis was performed to compare the OS and PFS according to the expression of MCP-1 or CD68 or CD163. The results indicated DLBCL patients with high expression of MCP-1 (n=108) or CD68 (n=61) or CD163 (n=66) owned worse OS (Fig.2A-C, P＜0.001) and PFS (Fig.2D-F, P＜0.001) than those with low expression. To exclude the effect of treatment modality, we analyzed patients in the R-CHOP treatment group separately, which again showed that DLBCL patients with high expression of MCP-1 (n=25) or CD68 (n=12) or CD163 (n=13) had poorer OS (Fig.3A-C, P＜0.001) and PFS (Fig.3D-F, P＜0.001) than those with low expression. We further analyzed whether MCP-1 or CD68 or CD163 expression could stratify different risks R-CHOP treatment group that first stratified as low risk (IPI score=0-1, n=19), immediate risk (IPI score=2-3, n=13 and high risk (IPI score=4-5, n=6) by International Prognostic Index (IPI). The results showed better PFS and OS in low-risk patients (IPI score= 0-1, n=19) with low expression of MCP-1 (Fig.4A,B) , better PFS and OS in intermediate-risk patients (IPI score=2-3, n=13) with low expression of CD68, CD163 (Fig.4C-F) , and in high-risk (IPI score=4-5, n=6) patients with MCP-1, CD68 and CD163 expression had no statistically significant PFS and OS (Supplementary Fig.1A-L). Table 3 Multivariate Cox regression analyses of potential prognostic factors for OS and PFS Variables OS PFS HR(95%CI) P HR(95%CI) P Gender male 0.719(0.411-1.027) 0.065 0.867(0.505-1.229) 0.294 female Age ＜60 1.0715(0.59-1.553) 0.859 1.284(0.693-1.875) 0.606 ≥60 ECOG-PS ≤1 1.364(0.681-2.047) 0.555 1.064(0.534-1.593) 0.773 ＞1 Extranodal sites of disease ≤1 1.154(0.533-1.775) 0.927 1.641(0.758-2.523) 0.291 ＞1 Ann Arbor stage Ⅰ/Ⅱ 1.06(0.485-1.635) 0.709 1.525(0.692-2.357) 0.435 Ⅲ/Ⅳ LDH ≤245 2.0275(0.936-3.119) 0.081 2.635(1.156-4.113) 0.016 ＞245 IPI score 0-2 1.791(0.534-3.048) 0.583 1.248(0.357-2.138) 0.767 3-5 Treatment R-CHOP 1.2535(0.657-1.85) 0.712 1.494(0.786-2.201) 0.297 CHOP Evaluation CR PR uCR 0.6325(0.287-0.978) 0.042 0.336(0.136-0.535) ＜0.001 PD CD68 Low 1.384(0.481-2.287) 0.905 0.985(0.329-1.641) 0.452 High CD163 Low 3.0395(0.968-5.111) 0.060 3.178(1.027-5.329) 0.043 High MCP-1 Low 11.1145(3.416-18.813) ＜0.001 15.507(3.446-27.568) ＜0.001 High GCB/ABC GCB 3.2055(1.352-5.059) 0.004 10.747(3.544-17.950) ＜0.001 ABC Abbreviations: OS overall survival, PFS progression-free survival, HR hazard ratio, CI confidence interval, ECOG-PS Eastern Cooperative Oncology Group performance status, LDH lactate dehydrogenase, IPI International Prognostic Index, CR Complete response, PR Partial response, uCR complete response, PD Progressive disease, CHOP cyclophosphamide hydroxydaunorubicin vincristine prednisone, R-CHOP rituximab-cyclophosphamide hydroxydaunorubicin vincristine prednisone. The proportion of CD14+CCR2+ monocytes of PBMC s in DLBCL patients is higher than healthy volunteers and MCP-1 concentration is positively associated with CD14+CCR2+ monocytes of PBMC s in newly diagnosed DLBCL patients Our FC analysis presented in another cohort, including 30 healthy volunteers, 32 newly diagnosed (ND) DLBCL patients, 29 remission (Rem) DLBCL patients, 21 relapsed (Rel) DLBCL patients, CD14+CCR2+ monocytes proportion of PBMCs in ND, Rem and Rel groups were statistically higher than healthy volunteers, and proportion in Rel group was the highest. Besides, proportion in Rem-DLBCL group was lower than ND-DLBCL and Rel-DLBCL group (Fig.5A,B). Moreover, we further analyzed ND group. By analyzing the CD14+CCR2+ monocytes proportion of PBMCs before and after standard chemotherapy, we found the proportion statistically decreased after standard chemotherapy (Fig.5C). Additionally, in ND group, we found MCP-1 concentration of plasma was positively associated with CD14+CCR2+ monocytes proportion of PBMCs by Spearman analysis. MCP-1/CCR2 axis is necessary for monocytes recruitment We first detected MCP-1 secretion of different DLBCL cell lines by ELISA, including SUDHL-2, SUDHL-4, SUDHL-6 and OCI-Ly8, and found they all secret MCP-1 at similar level (Fig.6A). Meanwhile, we examined whether THP-1 or U937 monocytes expressed CCR2 by WB as we expected, THP-1 and U937 cells expressed CCR2 (Fig. 6B). Having confirmed the establishment of MCP1/CCR2 axis, we next explored the role of the axis in monocytes recruitment. 8-μm pore size transwell chambers were used to mimic the process of chemotaxis, THP-1 or U937 cells were cultured in upper of the chambers and SUDHL-4 cells were cultured in bottom of the 6-well plates containing 1640 medium with or without treatment of 50μM CCR2 antagonist. Finally, we observed significantly reduced amount of THP-1 or U937 cells migrating to the underside of membrane in CCR2 antagonist treated group (Fig.6C, D). MCP-1/CCR2 axis induces M2 macrophages polarization Reacting with different tumor microenvironment, macrophages can convert to different types, including M1 macrophages and M2 macrophages. To explore whether DLBCL cell-derived MCP-1 regulates macrophages polarization by MCP-1/CCR2 axis, THP-1 cells was employed to mimic macrophages polarization in response to DLBCL microenvironment in vitro. THP-1 cells were treated with 100ng/ml PMA for 24 h to induce THP-1 cells to differentiate into M0 macrophages. Then, we examined the effects of DLBCL cell-derived MCP-1 on M2 polarization of macrophages. To mimic the real DLBCL microenvironment, we collected the conditioned medium (CM) of SUDHL-4, and then cultured THP-1-derived M0 macrophages with the CM. To further confirm the effects of MCP-1, we used CCR2 antagonist to block MCP-1/ CCR2 axis, in other words, to block the way MCP-1 playing roles and observe M2 macrophages polarization. As results, FC analysis showed M2 marker CD206 was increased after being cultured with the CM , while CCR2 antagonist significantly reversed the CD206 improvement of the CM (Fig.7A). Meanwhile, M1 marker CD86 showed almost no difference by FC analysis in CM or CCR2 antagonist treated group (Fig.7B), so there may be other factors to regulate M1 macrophages polarization. Next, qPCR and WB were performed to confirm the M2 polarization induced by CM and the inhibition by CCR2 antagonist. As shown in Fig.6C, by qPCR, M2 macrophages secreted more interleukin (IL)-10, CD163 and transforming growth factor-β(TGF-β)than the other two groups. Consistent with the results of FC and qPCR, WB showed the signaling pathway proteins that related with M2 polarization activation increased, including p-Stat3, p-Stat6, p-Akt (Fig.7D). Blockade of MCP-1/CCR2 axis with a CCR2 antagonist suppresses BALB/C subcutaneous tumor growth As known, MCP-1/CCR2 axis contributed to tumor initiation, progression and response to treatment, so we next explored whether the CCR2 antagonist could inhibit DLBCL tumor growth by performing in vivo experiments. 1×10 7 A20 cells, mouse-derived B lymphoma cells, were subcutaneously injected into the right armpits of immunocompetent female BALB/C mice. When the diameter reached about 5mm, mice were randomly divided into two groups, including control group (n=5) and CCR2 antagonist treated group (n=6), and CCR2 antagonist started to be given intraperitoneally at a dose of 20mg/kg every other day. Tumor volume and mice weight were recorded every other day, and once tumor appeared ulcer, all mice were euthanized. As results, the tumor volume of CCR2 antagonist treated group were significantly smaller than control group (Fig.8A-C), while mice weight showed no significantly difference (Fig.8D). Blockade of MCP-1/CCR2 axis with CCR2 antagonist reduces M2 macrophages while increases CD8+ T cells of the tumor microenvironment to suppress tumor growth We have validated blockade of MCP-1/CCR2 axis with CCR2 antagonist did suppress tumor growth in vivo, while whether relating to M2 macrophages polarization needs further exploration. For further exploration, we analyzed the subcutaneous tumors microenvironment by FC and immunohistochemistry. We took the same quality tumor of each mice and digested the tumors into single cell suspension by collagenase and DNAse for FC. Anti-mouse CD20 antibody was first used to exclude B lymphoma cells, and then the proportion of natural killer (NK) cells, Regulatory T (Treg) cells, CD4+ T cells, CD8+ T cells and M2 macrophages were analyzed among those non-tumor cells (Fig.9A). As expected, compared to control group, M2 macrophages were less in CCR2 antagonist treated group (Fig.9B). To our surprise, we found CD8+ T cells were more in CCR2 antagonist group than control group, while the other cells did not show significantly difference between two groups (Fig.9C), For further analysis, we concluded M2 macrophages were negatively correlated with CD8+ T cells. Immunohistochemistry analysis also showed reduced M2 macrophages and increased CD8+ T cells (Fig.10). So blockade of MCP-1/CCR2 axis suppressed tumor growth may via inhibiting M2 macrophages polarization and increasing CD8+ T cells. Discussion The tumor-derived chemotactic protein MCP-1 and its receptor CCR2 have been found to be involved in the metastatic progression of tumors in a variety of tumors and are expected to be new targets for tumor therapy. Meanwhile about one-third of patients with diffuse large B-cell lymphoma are suffering from disease due to insensitivity to R-CHOP regimens, and they are in urgent need of novel therapeutic agents or treatments. Previous experiments by our group have demonstrated that CCR2 expression promotes DLBCL survival and invasion 21 . In this study, we further investigated the role of MCP-1/CCR2 axis in DLBCL and explored the therapeutic mechanism of CCR2 antagonists. First, we determined the cut-off values of MCP-1, CD68, CD163 expression based on previously published articles 6,20 , and found that high MCP-1 expression was associated with poor prognosis in DLBCL patients, while MCP-1 expression was positively correlated with the expression of CD68 and CD163 expression. Wang et al got the same conclusion that high MCP-1 expression was correlated with poor prognosis of DLBCL patients based on different cut off value with ours (Expression of MCP-1 and CCR2 in Newly Diagnosed Diffuse Large B-Cell Lymphoma and Clinical Significance). Other researches also demostrated CD68 and CD163 expressions were correlated with poor prognosis of DLBCL patients based on different cut-off values 59 . However, we first explored the relation of MCP-1 and TAMs in DLBCL, so more works were needed to validate our results, including appropriate cut-off values and the relationship between MCP-1 expression and CD68, CD163 expression. Then,we found the blockage of MCP-1/CCR2 by CCR2 antagonist inhibited the polarization of TAMs towards M2 and increased the proportion of CD8+ T cells in a mouse transplantation tumor model together inhibiting DLBCL progression in our in vitro and in vivo experiments. The cancer microenvironment has been identified as one of the hallmark drivers of cancer 22 , and chemokines are central regulators of the cancer microenvironment. Chemokines can direct various immune cells to the site of tumourigenesis and subsequently lead to inflammatory/immune responses 23 and have been found to play a role in the progression, migration, angiogenesis and metastasis of many cancer types 24 . Among these, signalling between CCR2 and its ligand MCP-1 has been found to promote cancer progression by directly stimulating tumour cell proliferation and down-regulating the expression of apoptotic proteins 25-30 . But more striking is the ability of tumor-derived MCP-1 to drive recruitment of circulating CCR2+ monocytes and to predispose monocytes to differentiate into TAMs 31 . In esophageal cancer the MCP-1/CCR2 axis polarizes TAMs to the immunosuppressive M2 phenotype and significantly increases PD-L2 expression, thereby depleting antitumor effector T cells and effectively mediating immune escape of tumor cells 32 . In hepatocellular carcinomas (HCCs), high MCP-1 expression was associated with more tumor-infiltrating TAMs and fewer CD8+ T cells. Blocking the MCP-1/CCR2 axis reduces monocytes/TAMs recruitment and M2 phenotype polarisation, thereby reducing immunosuppression of CD8+ T cells and directly enhancing tumor immunotherapy 33 . High expression of MCP-1 in breast cancer is similarly associated with infiltration of M2-type macrophages 34 . We have identified for the first time the ability of the MCP-1/CCR2 axis to recruit monocytes and induce polarization of TAMs in lymphohematopoietic tumors, and have also demonstrated for the first time the therapeutic mechanism by which CCR2 antagonists block the MCP-1/CCR2 axis and thereby inhibit immune escape from tumors in DLBCL. Clinical data from 143 patients with new-diagnosed non-specific DLBCL demonstrate that high expression of CD68 , CD163 and MCP-1 is highly correlated with a variety of poor prognostic signs that have been shown to be associated with DLBCL, such as IPI score, AMC 35 and high expression of MCP-1 is positively correlated with expression of CD68 and CD163, which further demonstrates the close relationship between MCP-1 and M2 type macrophages. The correlations between MCP-1 expression and CD68, CD163 expression are statistically significant, but these are moderate. So more representative, larger samples, and appropriate cut-off values are needed to obtain more obvious evidence. We also found that DLBCL patients with high expression of CD68, CD163 and MCP-1 had shorter survival and CD163 and MCP-1 were independent risk factors for DLBCL patients, which is consistent with studies in other tumors 36-42 . Moreover, low-risk patients could be further identified by the expression of MCP-1 expression, intermediate-risk patients could be further identified by the expression of CD68 or CD163 expression.However, the above indicators were not statistically significant in high-risk patients, which may be related to the bias caused by the small sample of high-risk patients, which was left for us to collect more samples for the next analysis to determine. The proportion of CD14+CCR2+ monocytes of PBMCs in DLBCL patients is higher than healthy volunteers and MCP-1 concentration is positively associated with CD14+CCR2+ monocytes of PBMCs in newly diagnosed DLBCL patients. Although previous studies have found that chemotherapy received by relapsed patients leads to a reduction in the total number of monocytes and a lower proportion of mononuclear myeloid-derived suppressor cells (M-MDSCs, CD14+HLA-DR low ) in DLBCL 43 , the relapsed group showed a statistically significant higher proportion of CD14+CCR2+ monocytes compared to the remission group in spite of the chemotherapy interruption. CCR2+ monocytes in the relapse group compared to the remission group, which was more statistically significant. Together, these clinical data reflect the importance of the MCP-1/CCR2 axis in the progression of DLBCL and the relationship with M2 macrophages. In vitro, we first demonstrated the role of MCP-1 secretion of DLBCL cell lines by ELISA, with no significant differences between these cell lines, which allowed it to exert a chemotactic effect in combination with CCR2 expressed on monocytes. As reported, MCP-1 was also secreted by breast cancer cells, lung cancer cells, ovarian cancer cells, ect 44,45 . However, the secretion levels by ELISA between these tumor cells and DLBCL tumor cells needed to be further explored. It is well known that monocytes recruited to the tumor can differentiate into macrophages, and then polarized into different types TAMs in response to various factors, thereby promoting or inhibiting tumor progression 46,47 . Thus there are four main strategies for TAMs-based anti-tumor therapy: inhibition of macrophages recruitment, inhibition of TAMs survival, enhancement of the M1 killing activity of TAMs and blocking the M2 tumor-promoting activity of TAMs 48,49 . In DLBCL, we found that monocytes mediating chemotaxis via the MCP-1/CCR2 axis were polarized towards M2 TAMs, and the proportion of M2 TAMs in the tumor supernatant mock co-culture system increased significantly, while the proportion of M2 TAMs blocked by CCR2 antagonists in the MCP-1/CCR2 axis decreased. This finding is also consistent with hepatocellular carcinoma and other tumors 33,34,50 . We also found that although the proportion of M1 type macrophages increased in the tumor supernatant mock co-culture system, the CCR2 antagonist did not block or promote this effect, suggesting that there are other factors involved in the tumor supernatant that control the polarization of M1 type macrophages. In vivo, we have not only demonstrated that CCR2 antagonists can inhibit tumor progression by blocking the MCP-1/CCR2 axis between monocytes and tumor cells, but also further demonstrated that tumor-derived MCP-1 induces polarization of TAMs towards M2 macrophages via the MCP-1/CCR2 axis. Even more promising was the discovery of a link between M2-type macrophages and CD8+ T cells, which may show a reciprocal pattern. CD8+ cytotoxic T lymphocytes (CTLs) as the immune cells of choice against cancer 51,52 , and their immunosuppression correlated with the drug-resistant properties of tumors 53 . M2 macrophages have been shown to create an immune barrier to CD8+ T cell-mediated anti-tumor immune responses 54 . Our results demonstrate that blocking the MCP-1/CCR2 axis can further exert anti-tumor effects by reducing the proportion of M2-type macrophages and increasing CD8+ T cells. It must be emphasized that our research only confirmed a negative correlation between the number of M2 macrophages and CD8+ T cells in DLBCL microenvironment of mice, and the mechanisms of how M2 macrophages interact with CD8 T cells need further exploration. As known, the application of rituximab that direct against human CD20 antigen has significantly improved the survival of DLBCL patients 1 . Rituximab mainly exerts its effect through antibody-dependent cellular cytotoxicity (ADCC) 55 . Rituximab- mediated ADCC contains different types of effector cells, such as neutrophils, M2 macrophages and NK cells, and NK cells play the most vital roles 56-58 . Our results showed significantly decreased M2 macrophages while slightly increased NK cells. Further researches are needed to determine whether M2 macrophages can synergize with rituximab immunotherapy by regulating NK cells. In summary, we have identified a novel therapeutic strategy for DLBCL and further investigated its mechanism of action. In vitro and in vivo experiments and clinical data together confirm that tumor-derived MCP-1 can induce the polarization of M2 macrophages via the MCP-1/CCR2 axis in DLBCL, thereby promoting tumor progression, and that this effect can be blocked by CCR2 antagonists. Meanwhile, we infer CD8+ T cells may be the dowmstream target of M2 macrophages and this needs further confirmation. In brief, our findings offer the possibility of further development of targeted therapies for the MCP-1/CCR2 axis in DLBCL. Materials and methods Patients samples 143 newly diagnosed non specific DLBCL patients were recruited for the immunohistochemistry and another cohort including 30 healthy volunteers and 82 DLBCL patients (32 newly diagnosed cases (ND) with a median age of 57.9 years; 29 remission cases (REM) with a median age of 56.3 years; 21 relapse cases (Rel) with a median age of 58.6 years) were also recruited. These patients were all diagnosed, treated and followed from 2004 to 2016 at the First Affiliated Hospital and the Second Affiliated Hospital of Anhui Medical University. Each patient was given the informed consent. The diagnosis and prognosis criteria were based on the Word Health Organization (WHO) classification and International Prognostic Index (IPI) 19 . All patients were pathologically proved to be diffuse large B-cell lymphoma, and had no history of malignancy, transplantation or immunodeficiency. In addition, they all had complete clinical data and follow-up information. The study followed the Helsinki Declaration and was approved by the ethics committee of Anhui Medical University. Cell lines and cultures The human originated DLBCL cell lines SUDHL-2 and SUDHL-4 were kindly gifted by Dr. Ding Kaiyang (The first affiliated hospital of USTC, China), SUDHL-6 and OCI-Ly8 were generously favored by Prof. Zhai Zhimin (The second affiliated hospital Of Anhui Medical University, China). The human monocyte cell lines THP-1 and U937 were separately liberally given by Dr. He and Dr. Shen (The school of basic medical science, Anhui Medical University, China). The murine B lymphoma cell line A20 was purchased from the American Type Culture Collection (ATCC, Manassas, Virginia, USA). All cells were cultured with RPMI 1640 (Hyclone, Utah, USA) medium consisted 10% fetal bovine serum (FBS) (Gibco, NY, USA) and 1% penicillin-streptomycin (Beyotime, Shanghai, China) at 37℃ and 5% CO 2 incubator. Enzyme linked immunosorbent assay (ELISA) ELISA was performed to detect the secretion of MCP-1 by different DLBCL cell lines and the secretion in 32 newly diagnosed DLBCL patients’peripheral blood. DLBCL cell lines SUDHL-2, SUDHL-4, SUDHL-6 and OCI-Ly8 were cultivated in FBS free 1640 for 48 hours. Subsequently, we collected the medium of these cell lines to centrifuge at 3000rpm for 20 min and gathered the supernatant. Besides, the peripheral blood of the DLBCL patients was centrifugated at 500g for 15min to get the upper plasma. Finally, the ELISA kit (Mlbio, Shanghai, China) was used according to the manufacture instructions. Western blotting (WB) The cells were lysed by RIPA lysis reagent (Beyotime, Shanghai, China) on ice and the total cellular protein was extrated by centrifugation at 12,000rpm for 20 min at 4℃. BCA reagent kit (Beyotime, Shanghai, China) was used to detect the protein concentration. Then, equal quality proteins were separated by 10% SDS-PAGE (Beyotime, Shanghai, China) and transferred onto activated PVDF membranes (Millipore, Massachusetts, USA). Followed blocking with 5% skim milk for 2 h at room temperature, the PVDF membranes were incubated with primary antibodies against CCR2 (1:1000, Bioworld Technology Inc., Minnesota, USA), p-Stat3, p-Stat6, p-Akt (1:1000, all from Cell Signaling Technology, Boston, USA) at 4℃ overnight. β-actin (1:2000, ZSGB-Bio, Beijing, China) was used as control. Next day, the membranes were incubated with HRP-conjugated secondary antibody (1:5000, ZSGB -Bio, Beijing, China) for 1 h at room temperature, and then the blots were visualized by chemiluminescence imaging system (Tanon5200, Shanghai, China). Finally, image J was used to analyze and calculate the protein expression levels. Chemotaxis assays THP-1 or U937 cells were seeded in the upper of 8-μm pore size transwell chambers (Corning Costar, NY, USA) and DLBCL cell lines cells were cultured in the bottom of 6-well plates with 1640 medium containing 50μM CCR2 antagonist for blocking CCL2/CCR2 axis. After 48h, cells migrating to the underside of the membrane were fixed with methanol and stained with crystal violet. Finally, the migrated cells were observed and counted with the light microscope (ZEISS, Germany). Preparation of the conditioned medium (CM) of DLBCL cell lines cells DLBCL cell lines (SUDHL-4) cells were first cultured with 1640 medium with 10% FBS normally. When tumor cells grew up about 50% of the culture flask,1640 medium without FBS was used to culture these cells continuously for 48h. Then, the supernatant was collected after being centrifugated at 2000 rpm for 10 min. Finally, we mixed the supernatant and 1640 (1:1), and the mixture was conditioned medium (CM). Macrophages generation and culture with CM 1×10 6 THP-1 cells were cultured in each well of 6-well plates with 1640 media containing 10% FBS. Firstly, these THP-1 cells were treated with 100ng/ml Phorbol 12-myristate 13-acetate (PMA) (TQ0198, Target Mol, USA) for 24 h, and then were incubated in FBS-free 1640 medium for 24 h to obtain M0 macrophages. To mimic the real tumor microenvironment, the THP-1-derived M0 macrophages were cultured in the mixture media CM for 48h with or without pre-treatment of 100μM CCR2 antagonist for 1h. Quantitative real time polymerase chain reaction (qPCR) Total RNA was extracted with TRIzol reagent (Cat No:15596026, Thermo Fisher) and cDNA was synthesized by a reverse transcription kit (Vazyme Biotech Co., Ltd, Nanjing, China) according to its instructions. qPCR was processed in the reaction mixture containing 10μl 2×AceQ qPCR SYBR Green Master Mix, 0.4μl 50×ROX Reference Dye 1, 0.4μl 10μM Primer1, 0.4μl 10μM Primer2, 7.8μl ddH2O (all from Vazyme Biotech Co., Ltd, Nanjing, China) and 1μl cDNA on LC480 Ⅱ machine (Roche). The mRNA relative expression level was calculated by using the 2−ΔΔCt method. The sequences of the primers are listed as follows: β-actin, forward primer, 5’-CAGGAGGCATTGCTGATGAT-3’, reverse primer, 5’-GAAGGCTGGGGCTCATTT-3’, IL-10, forward primer, 5’-TCTCCGAGATGCCTTCAGGAGA-3’, reverse primer, 5’-TCAGACAAGGCTTGGCAACCCA-3’, CD163, forward primer, 5’-CCAGAAGGAACTTGTAGCCACAG-3’, reverse primer, 5’-CAGGCACCAAGCGTTTTGAGCT-3’, TGF-β, forward primer, 5’-CGGAGAGCCCTGGATACCACCTA-3’, reverse primer, 5’-GCCGCACACAGCAGTTCTTCTCT-3’ Animal ethics declarations A statement to confirm that all experimental protocols were approved by the Ethics Committee of the The Second Affiliated Hospital of Anhui Medical University and Anhui Medical University. A statement to confirm that all methods were carried out in accordance with relevant guidelines and regulations. A statement to confirm that all methods are reported in accordance with ARRIVE guidelines. After all experimental studies were completed, mice were euthanized with 100% carbon dioxide (CO 2 ) inhalation. Animal models 6 weeks old immunocompetent BALB/C female mice were purchased from Animal center of Anhui Province and fed at the SPF environment of the Animal center of Anhui Medical University. 1×10 7 A20 cells were resuspended in 200ul PBS and then injected subcutaneously into the right armpit of mice. When subcutaneous tumor path reached around 5mm, all mice were divided into two groups randomly, 20mg/kg CCR2 antagonist was injected intraperitonealy into the CCR2 antagonist group mice every other day and the control group mice were injected intraperitoneally equivalent dose of placebo. The tumor volume and mice weight were also recorded every other day. Once the tumor appeared ulcer, all mice were euthanized and the subcutaneous tumors were removed for FCM and immunohistochemistry. The tumor volume was calculated as (length×width×width)/2. Flow cytometry (FC) analysis 4-5ml DLBCL patients’ peripheral blood was collected and then extracted peripheral blood mononuclear cells (PBMCs) for FC to detect CD14+CCR2+ monocytes. FITC anti-human CD14 and PE anti-human CCR2 antibodies were used in this process and they were purchased from Beckman Coulter company. THP-1-derived macrophages co-cultured with the supernatant of DLBCL lines were collected from 6-well plates, washed 3 times with PBS and then made into single-cell suspension and adjusted its concentration into 1×10 6 /ml. After being incubated with PE mouse anti-human CD206 for 30 min at 4℃,the stained cells were detected by FACS Calibur flow cytometer (BD) and then analyzed by FlowJo software. The same quality of each mice’fresh subcutaneous tumors were cut, and then placed in 6-well plates on ice to wash with PBS, and then cut into pieces to digest single cells with collagenase and DNAse for 1h at 37℃. After digesting, the single cells were filtered with 100μM filter and centrifugated at 1500rpm for 10 min. Followed by lysis red blood cells, single cells were centrifugated at 1500rpm for 10 min and resuspended in PBS at concentration of 1×10 6 , then the single cell suspensions were stained with antibodies for 30 min at 4℃. Finally, the stained cells were detected by FACS Calibur flow cytometer (BD) and then analyzed by FlowJo software. For detection of different cells, we used the following antibodies: Brilliant Violet 421 anti-mouse CD20, PE anti-mouse NK1.1, FITC anti-mouse CD4, PE anti-mouse CD25, AF 647 anti-mouse Foxp 3, PerCP-cy5.5 anti-mouse CD8, FITC anti-mouse CD11b, PE anti-mouse F4/80, AF 647 anti-mouse CD206. All antibodies were purchased from BD Pharmingen. Immunohistochemistry Human samples and mice subcutaneous tumors were formalin-fixed, paraffin- embedded and then cut into 3um specimen sections. Antibodies aganist human MCP-1 (1:100, Santa Cruz, Biotechnology, USA), CD68 (1:200, Abcam, USA), CD163 (1:200, Abcam, USA), against mouse F4/80 (1:200, Abcam, USA), CD206 (1:200, Abcam, USA), CD8 (1:100, Abcam, USA) were used. All sections were deparaffinized and rehydrated and then repaired antigens in citric acid antigen repair solution (PH 6.0). After blocking endogenous peroxidase with 3% hydrogen peroxide, the sections were incubated respectively with anti-MCP-1, CD68, CD163, F4/80, CD206 and CD8 antibodies at 4℃ overnight. The sections were then incubated with HRP-conjugated goat anti-mouse and rabbit IgG secondary antibody (ZSGB-Bio, Beijing, China) for 15 minutes at room temperature. Finally, DAB solution (ZSGB- Bio, Beijing, China) and haematoxylin (ZSGB-Bio, Beijing, China) were used to visualize the staining. All the finished staining sections were analysed by our two professional pathologists who knew nothing about patients. They evaluated the adequacy of immunostaining and selected the representative tumor areas for counting and recording. Semi-quantitative analysis of immunostaining in MCP-1 was judged as grade 0,1,2 or 3. Grade 0＜1% tumor staining, grade 1＜1-33%, grade 2＜34-66%, and grade 3＞67%. Grade 0 represented low expression and grade 1-3 represented high expression 6,19,20 . The cut-off values were selected at 33% for CD68 and 19% for CD163 6 . Statistical analysis SPSS software (version 25) was used. All data were recorded as the mean±SEM from three independent experiments. The chi-square test or Fisher’s exact test was used to compare categorical values between two groups. Cox proportional hazard model was used to analyze the factors of progression-free survival (PFS) and overall survival (OS). Kaplan-Meier method and log-rank tests were used to compare differences between groups. For cell culture trials and in vivo experiments, we used two-tailed Student’s t-tests to determine statistical significance. P＜0.05 was indicated a statistically significant. Declarations Data availability statement All data generated or analysed during this study are included in this published article. Author Contribution Z.W. and Q.H. performed the research and wrote the paper. Y.L. and Z.Z. designed the research study. F.N., Q.H. and Z.W. analyzed the data and contributed to the data collection. All authors finally approved the manuscript. Funding This work was supported by National Natural Science Foundation of China (81700194) and College Natural Science Foundation of Anhui Province (KJ2021A0214). Competing interests Te authors declare no competing interests. References Grimm KE, O'Malley DP. Aggressive B cell lymphomas in the 2017 revised WHO classification of tumors of hematopoietic and lymphoid tissues. Ann Diagn Pathol. 2019;38:6-10. Sarkozy C, Sehn LH. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6219553","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":457847389,"identity":"7d249f18-057f-4e20-be77-5b07effbe22d","order_by":0,"name":"Zhao-Feng Wen","email":"","orcid":"","institution":"Anhui Medical University","correspondingAuthor":false,"prefix":"","firstName":"Zhao-Feng","middleName":"","lastName":"Wen","suffix":""},{"id":457847390,"identity":"6ad87a72-10e0-4b6a-bc2e-93a55b17d123","order_by":1,"name":"Qi-Tang Huang","email":"","orcid":"","institution":"Anhui Medical University","correspondingAuthor":false,"prefix":"","firstName":"Qi-Tang","middleName":"","lastName":"Huang","suffix":""},{"id":457847391,"identity":"d41ab74a-8623-4c10-a823-9b58231f8b01","order_by":2,"name":"Feng-Ya Nan","email":"","orcid":"","institution":"The Second Affiliated Hospital of Anhui Medical University","correspondingAuthor":false,"prefix":"","firstName":"Feng-Ya","middleName":"","lastName":"Nan","suffix":""},{"id":457847392,"identity":"5890ced0-00c8-4279-87e8-06df3cae0db0","order_by":3,"name":"Zhi-Min Zhai","email":"","orcid":"","institution":"The Second Affiliated Hospital of Anhui Medical University","correspondingAuthor":false,"prefix":"","firstName":"Zhi-Min","middleName":"","lastName":"Zhai","suffix":""},{"id":457847393,"identity":"ba0a99c0-4d1a-4303-b5d6-3db8f8064094","order_by":4,"name":"Yan-Li Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEUlEQVRIiWNgGAWjYBACPmYQWSABJBgbQGwefvbmAwc+/MCthQ2sxQChRUay51jiwZk9eLSASQMIB6TFxuCGj/FhDjY8Wth5DD8XGFgwmLcfbntcUHGYh+EGz4fDDDwM8vxiB3A4jMdYegbQYTJnEtuNZ5w5zMM4u3fD4QILBsOZsxNwaTGQ5gFqkWBIbJPmbbvNwyxzdsPhGTwMCQa3cWox/g3Wwv8QooVNIufBYR42vFrMILZIQG3hkchhIKCFrcwaogVoy4wz/3kkeI4ZAANZAqdf+PkPb77NU1EHdFj6M+mCijR7++PNjz98+GEjzy+NXQsDAwc4Uuob0IQlcCgHAfYHeCRHwSgYBaNgFAABABxiUehXEraGAAAAAElFTkSuQmCC","orcid":"","institution":"The Second Affiliated Hospital of Anhui Medical University","correspondingAuthor":true,"prefix":"","firstName":"Yan-Li","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2025-03-13 11:23:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6219553/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6219553/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83158288,"identity":"aee3ee4c-7e46-4a20-939a-67eeb95b34d9","added_by":"auto","created_at":"2025-05-20 14:54:45","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2613844,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMCP-1、CD68 and CD163 expression in DLBCL tissues (×400). (A) \u003c/strong\u003eLow MCP-1 expression, \u003cstrong\u003e(D) \u003c/strong\u003eHigh MCP-1 expression, \u003cstrong\u003e(B) \u003c/strong\u003eLow CD68 expression, \u003cstrong\u003e(E) \u003c/strong\u003eHigh CD68 expression, \u003cstrong\u003e(C) \u003c/strong\u003eLow CD163 expression,\u003cstrong\u003e(F) \u003c/strong\u003eHigh CD163 expression.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6219553/v1/2a754d8e2f893976c2410dc6.jpeg"},{"id":83158281,"identity":"350214ff-167c-407d-b0f8-63f3eecf3319","added_by":"auto","created_at":"2025-05-20 14:54:44","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":480107,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKaplan-Meier analysis of OS and PFS according to the expression of MCP-1, CD68 and CD163 expression in DLBCL patients. (A,D) \u003c/strong\u003ethe OS and PFS according to MCP-1 expression, \u003cstrong\u003e(B,E)\u003c/strong\u003e the OS and PFS according to CD68 expression, \u003cstrong\u003e(C,F)\u003c/strong\u003e the OS and PFS according to CD163 expression. P value was calculated by log-rank test.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6219553/v1/38421667df031352d2b1afaf.jpeg"},{"id":83159483,"identity":"8f266f9b-4b77-4636-a670-22062b09e264","added_by":"auto","created_at":"2025-05-20 15:02:44","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":406806,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKaplan-Meier analysis of OS and PFS according to the expression of MCP-1, CD68 and CD163 expression in patients treated with R-CHOP. (A,D) \u003c/strong\u003ethe OS and PFS according to MCP-1 expression,\u003cstrong\u003e (B,E) \u003c/strong\u003ethe OS and PFS according to CD68 expression, \u003cstrong\u003e(C,F) \u003c/strong\u003ethe OS and PFS according to CD163 expression. P value was calculated by log-rank test.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6219553/v1/befb8738d79e9a9d5237fede.jpeg"},{"id":83159484,"identity":"077ca137-5a71-487e-b380-65ec2b5bf3be","added_by":"auto","created_at":"2025-05-20 15:02:44","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":579451,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKaplan-Meier analysis of OS and PFS was performed according to the expression of MCP-1, CD68, and CD163 in different levels of risk.\u003c/strong\u003e OS and PFS in IPI score = 0-1\u003cstrong\u003e(A,B)\u003c/strong\u003e,\u003c/p\u003e\n\u003cp\u003eOS and PFS in IPI score = 2-3 \u003cstrong\u003e(C-F)\u003c/strong\u003e; P value was calculated by log-rank test.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6219553/v1/c266a6f9573e9efa20cbf2e3.jpeg"},{"id":83158277,"identity":"06ea09f8-57be-4b54-a600-4888e43de18c","added_by":"auto","created_at":"2025-05-20 14:54:44","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":159811,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFC analysis of CD14+CCR2+ monocytes in healthy volunteers and different DLBCL patients groups. (A) \u003c/strong\u003eThe representative FC image of gate of CD14+CCR2+ monocytes.\u003cstrong\u003e (B) \u003c/strong\u003eCD14+CCR2+ monocytes proportion in different groups (healthy volunteers group, ND-DLBCL group, Rem-DLBCL group, Rel-DLBCL group). \u003cstrong\u003e(C) \u003c/strong\u003eCD14+CCR2+ monocytes proportion before and after standard chemotherapy in ND-DLBCL group. \u003cstrong\u003e(D) \u003c/strong\u003eSpearman analysis of CD14+CCR2+ monocytes proportion of PBMCs and MCP-1 concentration in plasma. *P＜0.05, **P＜0.01, ***P＜0.001.\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6219553/v1/0af04d3adfca58fbf978549b.jpeg"},{"id":83158307,"identity":"b7f70d81-a451-4edb-a297-651b64dcd857","added_by":"auto","created_at":"2025-05-20 14:54:46","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":135786,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBlockade of MCP-1/CCR2 axis with CCR2 antagonist reduces monocytes recruitment.\u003c/strong\u003e \u003cstrong\u003e(A)\u003c/strong\u003eLevels of chemokine MCP-1 secreted by DLBCL cell lines SUDHL-2, SUDHL-4, SUDHL-6 and OCI-Ly8 were quantified in the supernatants by ELISA. \u003cstrong\u003e(B)\u003c/strong\u003e By western blots, the expression of CCR2 was analyzed in two monocytes THP-1 and U937. The migration of monocytes was analyzed by chemotaxis assays. THP-1 or U937 cells were added in the upper of chambers, and SUDHL-4 cells were cultured in the lower chambers with or without treatment of 50μM CCR2 antagonist. \u003cstrong\u003e(C) \u003c/strong\u003eThe amount of THP-1 cells migrating to underside of membrane in control group (DMSO treated) and CCR2 antagonist treated group. \u003cstrong\u003e(D)\u003c/strong\u003e The amount of U937 cells migrating to underside of membrane in control group (DMSO treated) and CCR2 antagonist treated group. Data are means±SEM. *P＜0.05, **P＜0.01, ***P＜0.001.\u003c/p\u003e","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6219553/v1/64f9edaad2b4924ea47a41b2.jpeg"},{"id":83160641,"identity":"c179849f-5efa-4228-b7e7-83e000e5c5cc","added_by":"auto","created_at":"2025-05-20 15:10:44","extension":"jpeg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":345953,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMCP-1/CCR2 axis induces M2 macrophages polarization. \u003c/strong\u003eTo mimic M2 macrophages polarization, THP-1 derived M0 macrophages were cultured with CM or CM+CCR2 antagonist. \u003cstrong\u003e(A) \u003c/strong\u003eFC analysis of CD206 expression in three groups. \u003cstrong\u003e(B)\u003c/strong\u003eFC analysis of CD86 expression in three groups. \u003cstrong\u003e(C)\u003c/strong\u003e qPCR analysis of M2 macrophages markers, including IL10, CD163 and TGF-β. \u003cstrong\u003e(D)\u003c/strong\u003e WB analysis of signaling pathway proteins about M2 macrophages polarization activation (p-Stat3, p-Stat6, p-Akt). Data are means±SEM. *P＜0.05, **P＜0.01, ***P＜0.001.\u003c/p\u003e","description":"","filename":"floatimage7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6219553/v1/f103621e1e04cb329765c590.jpeg"},{"id":83158299,"identity":"5dd87d66-a8f9-4bb1-9208-95d07db803a8","added_by":"auto","created_at":"2025-05-20 14:54:46","extension":"jpeg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":162052,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBlockade of MCP-1/CCR2 axis with CCR2 antagonist suppresses BALB/C subcutaneous tumor growth.\u003c/strong\u003e 1×10\u003csup\u003e7 \u003c/sup\u003eA20 cells, mouse-derived B lymphoma cells, were subcutaneously injected into the right armpits of immunocompetent female BALB/C mice. When the diameter reached about 5mm, mice were randomly divided into two groups, including control group (n=5) and CCR2 antagonist treated group (n=6), and CCR2 antagonist started to be given intraperitoneally at a dose of 20mg/kg every other day. Tumor volume and mice weight were recorded every other day. \u003cstrong\u003e(A)\u003c/strong\u003e The mice image with their subcutaneous tumors of control group and CCR2 antagonist treated group. \u003cstrong\u003e(B) \u003c/strong\u003eTumor curve of two groups. \u003cstrong\u003e(C)\u003c/strong\u003e Representative image of removed tumors in two groups. \u003cstrong\u003e(D)\u003c/strong\u003e Curve of mice weight in two groups. Data are means±SEM. *P＜0.05, **P＜0.01, ***P＜0.001.\u003c/p\u003e","description":"","filename":"floatimage8.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6219553/v1/5c33e8682fac2422763695d3.jpeg"},{"id":83158287,"identity":"58a272c8-5b44-47e5-a69a-27366ec32e96","added_by":"auto","created_at":"2025-05-20 14:54:45","extension":"jpeg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":354074,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBlockade of MCP-1/CCR2 axis with CCR2 antagonist reduces M2 macrophages while increases CD8+ T cells in the tumor microenvironment to suppress tumor growth. \u003c/strong\u003eThe same quality tumor of each mice was cut and digested into single cell suspension by collagenase and DNAse for FC. \u003cstrong\u003e(A)\u003c/strong\u003e The proportion of a variety of cells among non-tumor cells , including NK cells (NK1.1+), Treg cells (CD4+CD25+Foxp3+), CD4 T cells (CD4+), CD8 T cells (CD8+), M2 macrophages (CD11b+F4/80+CD206+). \u003cstrong\u003e(B)\u003c/strong\u003eThe representative FC image of M2 macrophages. \u003cstrong\u003e(C)\u003c/strong\u003e The representative FC image of CD8+ T and CD4+ T cells. *P＜0.05, ** P＜0.01, ***P＜0.001.\u003c/p\u003e","description":"","filename":"floatimage9.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6219553/v1/6019efd445abc86cdac048a6.jpeg"},{"id":83158298,"identity":"f5547378-1d50-4e2e-85ff-2337db23313d","added_by":"auto","created_at":"2025-05-20 14:54:45","extension":"jpeg","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":1207258,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eImmunohistochemical staining of subcutaneous tumors\u003c/strong\u003e (TAMs: F4/80, M2 macrophages: CD206, CD8+ T cells: CD8, ×200).\u003c/p\u003e","description":"","filename":"floatimage10.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6219553/v1/0ab7b1439aa34c0ee79d72a2.jpeg"},{"id":83161645,"identity":"a77d80e2-5542-460b-8696-aa8fe63492f4","added_by":"auto","created_at":"2025-05-20 15:18:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":8441473,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6219553/v1/e1693d62-5c2a-4ef9-888f-b238401f9f11.pdf"},{"id":83158275,"identity":"00d1d092-b880-45d0-92f8-5372a8b57157","added_by":"auto","created_at":"2025-05-20 14:54:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":256789,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementary.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6219553/v1/7025097eeefb07035cbbd256.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"MCP-1-CCR2-M2 macrophages axis contributes to diffuse large B-cell lymphoma progression and inhibits antitumor immune response","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDiffuse large B-cell lymphoma (DLBCL) is the aggressive hematological malignancy originated from B cells, also known as the most common adult non-Hodgkin lymphoma (NHL), accounting for about 30-40%. It\u0026rsquo;s standard chemotherapy CHOP (cyclophosphamide, doxorubicin, vincristine and prednisone) or R-CHOP (rituximab+ CHOP) has greatly improved the cure rate up to 60-70%\u003csup\u003e1\u003c/sup\u003e. However, 30-40% patients eventually develop refractory or recurrence. Therefore, it is urgent to explore more targeted and effective therapeutic methods for these patients\u003csup\u003e2\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eIn DLBCL, the tumor stromal component consists of a wide range of cells, including kinds of infiltrating inflammatory cells, endothelial cells, fibroblasts and so on. These cells create a special environment to influence tumor initiation, development or response to treatment\u003csup\u003e3\u003c/sup\u003e. Among these infiltrating inflammatory cells, tumor-associated macrophages (TAMs) as one of the main components, has been confirmed to exert vital roles in tumors. For example, the amount of TAMs could predict patients prognosis in hepatocellular carcinoma, lung cancer and DLBCL\u003csup\u003e4-6\u003c/sup\u003e. As known, TAMs are primarily derived from blood monocytes via the chemotaxis of MCP-1/CCR2 axis\u003csup\u003e7\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eChemokines are small and secreted proteins that play their roles by binding to the specific receptors expressed on cell surface in disease involving inflammation, including tumors\u003csup\u003e8,9\u003c/sup\u003e. Monocyte chemoattractant protein-1 (MCP-1), also known as C-C motif ligand 2 (CCL2), was first discovered and well understood CC chemokine and its primary receptor is CC chemokine receptor 2 (CCR2)\u003csup\u003e10\u003c/sup\u003e. MCP-1 can be secreted by different types of cells, including tumor cells, epithelial cells, fibroblasts, endothelial cells and others\u003csup\u003e11\u003c/sup\u003e. As the main receptor of MCP-1, CCR2 is expressed by kinds of cells such as monocytes\u003csup\u003e12\u003c/sup\u003e, endothelial cells\u003csup\u003e13\u003c/sup\u003e, dendritic cells\u003csup\u003e14\u003c/sup\u003e and tumor cells. Now, the role of MCP-1/CCR2 axis in chemotaxis has been well understood, and moreover, the non-chemotactic role has also attracted more and more attention. For example, Liat Izhak\u003csup\u003e15\u003c/sup\u003e et al determined MCP-1/CCR2 axis promoted tumor survival/growth in an autocrine manner by in vivo experiment, and Yang\u003csup\u003e16\u003c/sup\u003e et al found MCP-1/CCR2 axis promoted tumor metastasis by activating ERK1/2-MMP2/9 pathway in nasopharyngeal carcinoma. Additionally, MCP-1/CCR2 axis has been confirmed to participate in TAMs polarization such as MCP-1 and IL-6 could promote CD206 expression\u003csup\u003e17\u003c/sup\u003e, and MCP-1 increased M2 polarization of TAMs by granulocyte- macrophage colony-stimulating factor (GM-CSF) and granulocyte colony- stimulating factor (G-CSF) in vitro\u003csup\u003e18\u003c/sup\u003e. In some preclinical studies, treatment targeting MCP-1/CCR2 axis has achieved encouraging results. However, the role of MCP-1/CCR2 axis in DLBCL remains little understood and this inspires us to explore the potential of targeting MCP-1/CCR2 axis in DLBCL.\u003c/p\u003e\n\u003cp\u003eIn this study, we analyzed MCP-1, CD68 and CD163 expression in DLBCL tissues, the MCP-1 concentration and amount of CD14+CCR2+ monocytes in DLBCL patients\u0026rsquo; peripheral blood, and further investigated the correlation between MCP-1 and CD68, CD163 expression. Additionally, we used THP-1 cells and A20 cells to investigate the function of MCP-1/CCR2 axis in M2 macrophages polarization by in vitro and in vivo experiments.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eImmunohistochemical MCP-1, CD68 and CD163 staining in DLBCL patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eImmunohistochemistry was performed to analyze the expression of MCP-1, CD68 and CD163 in 143 DLBCL patients\u0026rsquo; tissue samples. As results, MCP-1 positive staining was observed in cytoplasm of tumor cells (Fig.1A,B), and 75.5% (108/143) cases showed high MCP-1 expression. CD68 positive staining was observed in cytoplasm of macrophages (Fig.1C,D), and 42.7% (61/143) cases showed high CD68 expression. CD163 positive staining was observed in the membrane of macrophages (Fig.1E,F), and 46.2% (66/143) cases showed high CD163 expression. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinicopathological characteristics according to MCP-1, CD68 or CD163 expression and the correlation of MCP-1 and CD68 or CD163 in DLBCL patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe clinicopathological characteristics are showed in Table 1. As is shown, high CD68 expression was related with poor ECOG-PS (P=0.050), more extranodal sites of disease (P=0.003), Ⅲ/Ⅳ Ann Arbor stage (P=0.002), elevated LDH level (P=0.001), 3-5 IPI score (P＜0.001), worse response (P＜0.001), high AMC (P＜0.001) and ABC type (P＜0.001), high CD163 expression was correlated with more extranodal sites of disease (P=0.004), Ⅲ/Ⅳ Ann Arbor stage (P=0.001), elevated LDH level (P＜0.001), 3-5 IPI score (P＜0.001), worse response (P＜0.001), high AMC (P＜0.001) and ABC type (P＜0.001), and high MCP-1 expression was correlated with poor ECOG-PS (P=0.018), more extranodal sites of disease (P=0.024), Ⅲ/Ⅳ Ann Arbor stage (P=0.002), elevated LDH level (P＜0.001), 3-5 IPI score (P＜0.001), worse response (P＜0.001), high AMC (P＜0.001) and ABC type (P＜0.001) (Table 1). Further, Spearman analysis showed the expression level of MCP-1 was significantly positively associated with CD68 (r=0.458, \u003cem\u003eP\u003c/em\u003e＜0.001); at the same time, a significant positive correlation also existed between the expression of MCP-1 and CD163 (r=0.494, \u003cem\u003eP\u003c/em\u003e＜0.001) (Table 2). \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1 Patient\u003c/strong\u003e\u003cstrong\u003e\u0026rsquo;\u003c/strong\u003e\u003cstrong\u003es demographics according to CD68, CD163 and MCP-1 expression\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"556\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003ePatients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"bottom\" style=\"width: 109px;\"\u003e\n \u003cp\u003eCD68 expression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"bottom\" style=\"width: 109px;\"\u003e\n \u003cp\u003eCD163 expression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"bottom\" style=\"width: 109px;\"\u003e\n \u003cp\u003eMCP-1 expression\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eNO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003emale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e55.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.328\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.483\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.869\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003efemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e44.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e＜60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e60.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.700\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.958\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.907\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026ge;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eECOG-PS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026le;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e60.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.051\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e＞1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\"\u003e\n \u003cp\u003eExtranodal sites of disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026le;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e77.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e＞1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAnn Arbor stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eⅠ/Ⅱ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e51.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eⅢ/Ⅳ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e49.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eLDH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026le;245\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e69.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e＞245\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIPI score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0-2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e65.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e3-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eTreatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eR-CHOP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e27.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eCHOP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e72.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eEvaluation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eCR PR uCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e40.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003ePD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e59.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAMC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e＜460\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e52.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026ge;460\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e47.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eGCB/ABC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eGCB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e44.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eABC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e55.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u0026nbsp;\u003c/strong\u003eECOG-PS Eastern Cooperative Oncology Group performance status, LDH lactate dehydrogenase, IPI International Prognostic Index, CR Complete response, PR Partial response, uCR complete response, PD Progressive disease, AMC absolute monocyte count, CHOP cyclophosphamide hydroxydaunorubicin vincristine prednisone, R-CHOP rituximab- cyclophosphamide hydroxydaunorubicin vincristine prednisone.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2 Spearman analysis of MCP-1 and CD68 or CD163 in DLBCL\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"504\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003estaining\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 144px;\"\u003e\n \u003cp\u003eMCP-1 expression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003etotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003er\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003eCD68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.458\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"bottom\"\u003e\n \u003cp\u003eCD163\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.494\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eHigh MCP-1 and CD163 expression are independent prognostic factors for survival and the prognostic value of MCP-1, CD68 and CD163 expression in DLBCL patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMultivariate analyses was used to explore whether MCP-1 or CD68 or CD163 was the independent prognostic factor for DLBCL patients\u0026rsquo; survival. By multivariate analyses, we found MCP-1 expression and the subtypes of DLBCL were independent prognostic factors for overall survival (OS, HR 11.1145, 95% CI 3.416-18.813, P＜0.001 and HR 3.2055, 95% CI 1.352-5.059) and progression-free survival (PFS, HR 15.507, 95% CI 3.446-27.568, P＜0.001 and HR 10.747, 95% CI 3.544-17.950, P＜0.001). Besides, CD163 expression and LDH level were independent prognostic factors for PFS (HR 3.178, 95% CI 1.027-5.329, P=0.043 and HR 2.635, 95% CI 1.156-4.113, P=0.016) (Table 3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor more detailed exploration, Kaplan-Meier analysis was performed to compare the OS and PFS according to the expression of MCP-1 or CD68 or CD163. The results indicated DLBCL patients with high expression of MCP-1 (n=108) or CD68 (n=61) or CD163 (n=66) owned worse OS (Fig.2A-C, P＜0.001) and PFS (Fig.2D-F, P＜0.001) than those with low expression. To exclude the effect of treatment modality, we analyzed patients in the R-CHOP treatment group separately, which again showed that DLBCL patients with high expression of MCP-1 (n=25) or CD68 (n=12) or CD163 (n=13) had poorer OS (Fig.3A-C, P＜0.001) and PFS (Fig.3D-F, P＜0.001) than those with low expression. We further analyzed whether MCP-1 or CD68 or CD163 expression could stratify different risks R-CHOP treatment group that first stratified as low risk (IPI score=0-1, n=19), immediate risk (IPI score=2-3, n=13 and high risk (IPI score=4-5, n=6) by International Prognostic Index (IPI). The results showed better PFS and OS in low-risk patients (IPI score= 0-1, n=19) with low expression of MCP-1 (Fig.4A,B) , better PFS and OS in intermediate-risk patients (IPI score=2-3, n=13) with low expression of CD68, CD163 (Fig.4C-F) , and in high-risk (IPI score=4-5, n=6) patients with MCP-1, CD68 and CD163 expression had no statistically significant PFS and OS (Supplementary Fig.1A-L). \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3 Multivariate Cox regression analyses of potential prognostic factors for OS and PFS\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"561\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 162px;\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 192px;\"\u003e\n \u003cp\u003eOS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 191px;\"\u003e\n \u003cp\u003ePFS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003eHR(95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003eHR(95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003emale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e0.719(0.411-1.027)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e0.867(0.505-1.229)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.294\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003efemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e＜60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e1.0715(0.59-1.553)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.859\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e1.284(0.693-1.875)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.606\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e\u0026ge;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003eECOG-PS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e\u0026le;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e1.364(0.681-2.047)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.555\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e1.064(0.534-1.593)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.773\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e＞1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003eExtranodal sites of disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e\u0026le;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e1.154(0.533-1.775)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.927\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e1.641(0.758-2.523)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.291\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e＞1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003eAnn Arbor stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003eⅠ/Ⅱ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e1.06(0.485-1.635)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.709\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e1.525(0.692-2.357)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.435\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003eⅢ/Ⅳ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003eLDH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e\u0026le;245\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e2.0275(0.936-3.119)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e2.635(1.156-4.113)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e＞245\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003eIPI score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e0-2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e1.791(0.534-3.048)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.583\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e1.248(0.357-2.138)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.767\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003e3-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003eTreatment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003eR-CHOP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e1.2535(0.657-1.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.712\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e1.494(0.786-2.201)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.297\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003eCHOP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003eEvaluation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003eCR PR uCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e0.6325(0.287-0.978)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e0.336(0.136-0.535)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 48px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003ePD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003eCD68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e1.384(0.481-2.287)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.905\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e0.985(0.329-1.641)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.452\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003eCD163\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e3.0395(0.968-5.111)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e3.178(1.027-5.329)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003eMCP-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e11.1145(3.416-18.813)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 46px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e15.507(3.446-27.568)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 48px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003eGCB/ABC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003eGCB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e3.2055(1.352-5.059)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e10.747(3.544-17.950)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 48px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 162px;\"\u003e\n \u003cp\u003eABC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 146px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 46px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 143px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e OS overall survival, PFS progression-free survival, HR hazard ratio, CI confidence interval, ECOG-PS Eastern Cooperative Oncology Group performance status, LDH lactate dehydrogenase, IPI International Prognostic Index, CR Complete response, PR Partial response, uCR complete response, PD Progressive disease, CHOP cyclophosphamide hydroxydaunorubicin vincristine prednisone, R-CHOP rituximab-cyclophosphamide hydroxydaunorubicin vincristine prednisone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe proportion of CD14+CCR2+ monocytes of\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ePBMC\u003c/strong\u003e\u003cstrong\u003es in DLBCL patients is higher than healthy volunteers and MCP-1 concentration is positively associated with CD14+CCR2+ monocytes of\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ePBMC\u003c/strong\u003e\u003cstrong\u003es in newly diagnosed DLBCL patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur FC analysis presented in another cohort, including 30 healthy volunteers, 32 newly diagnosed (ND) DLBCL patients, 29 remission (Rem) DLBCL patients, 21 relapsed (Rel) DLBCL patients, CD14+CCR2+ monocytes proportion of PBMCs in ND, Rem and Rel groups were statistically higher than healthy volunteers, and proportion in Rel group was the highest. Besides, proportion in Rem-DLBCL group was lower than ND-DLBCL and Rel-DLBCL group (Fig.5A,B). Moreover, we further analyzed ND group. By analyzing the CD14+CCR2+ monocytes proportion of PBMCs before and after standard chemotherapy, we found the proportion statistically decreased after standard chemotherapy (Fig.5C). Additionally, in ND group, we found MCP-1 concentration of plasma was positively associated with CD14+CCR2+ monocytes proportion of PBMCs by Spearman analysis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMCP-1/CCR2 axis is necessary for monocytes recruitment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe first detected MCP-1 secretion of different DLBCL cell lines by ELISA, including SUDHL-2, SUDHL-4, SUDHL-6 and OCI-Ly8, and found they all secret MCP-1 at similar level (Fig.6A). Meanwhile, we examined whether THP-1 or U937 monocytes expressed CCR2 by WB as we expected, THP-1 and U937 cells expressed CCR2 (Fig. 6B). Having confirmed the establishment of MCP1/CCR2 axis, we next explored the role of the axis in monocytes recruitment. 8-\u0026mu;m pore size transwell chambers were used to mimic the process of chemotaxis, THP-1 or U937 cells were cultured in upper of the chambers and SUDHL-4 cells were cultured in bottom of the 6-well plates containing 1640 medium with or without treatment of 50\u0026mu;M CCR2 antagonist. Finally, we observed significantly reduced amount of THP-1 or U937 cells migrating to the underside of membrane in CCR2 antagonist treated group (Fig.6C, D). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMCP-1/CCR2 axis induces M2 macrophages polarization \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eReacting with different tumor microenvironment, macrophages can convert to different types, including M1 macrophages and M2 macrophages. To explore whether DLBCL cell-derived MCP-1 regulates macrophages polarization by MCP-1/CCR2 axis, THP-1 cells was employed to mimic macrophages polarization in response to DLBCL microenvironment in vitro. THP-1 cells were treated with 100ng/ml PMA for 24 h to induce THP-1 cells to differentiate into M0 macrophages. Then, we examined the effects of DLBCL cell-derived MCP-1 on M2 polarization of macrophages. To mimic the real DLBCL microenvironment, we collected the conditioned medium (CM) of SUDHL-4, and then cultured THP-1-derived M0 macrophages with the CM. To further confirm the effects of MCP-1, we used CCR2 antagonist to block MCP-1/ CCR2 axis, in other words, to block the way MCP-1 playing roles and observe M2 macrophages polarization. As results, FC analysis showed M2 marker CD206 was increased after being cultured with the CM , while CCR2 antagonist significantly reversed the CD206 improvement of the CM (Fig.7A). Meanwhile, M1 marker CD86 showed almost no difference by FC analysis in CM or CCR2 antagonist treated group (Fig.7B), so there may be other factors to regulate M1 macrophages polarization.\u003c/p\u003e\n\u003cp\u003eNext, qPCR and WB were performed to confirm the M2 polarization induced by CM and the inhibition by CCR2 antagonist. As shown in Fig.6C, by qPCR, M2 macrophages secreted more interleukin (IL)-10, CD163 and transforming growth factor-\u0026beta;(TGF-\u0026beta;)than the other two groups. Consistent with the results of FC and qPCR, WB showed the signaling pathway proteins that related with M2 polarization activation increased, including p-Stat3, p-Stat6, p-Akt (Fig.7D).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBlockade of MCP-1/CCR2 axis with a CCR2 antagonist suppresses BALB/C subcutaneous tumor growth \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs known, MCP-1/CCR2 axis contributed to tumor initiation, progression and response to treatment, so we next explored whether the CCR2 antagonist could inhibit DLBCL tumor growth by performing in vivo experiments. 1\u0026times;10\u003csup\u003e7\u003c/sup\u003e A20 cells, mouse-derived B lymphoma cells, were subcutaneously injected into the right armpits of immunocompetent female BALB/C mice. When the diameter reached about 5mm, mice were randomly divided into two groups, including control group (n=5) and CCR2 antagonist treated group (n=6), and CCR2 antagonist started to be given intraperitoneally at a dose of 20mg/kg every other day. Tumor volume and mice weight were recorded every other day, and once tumor appeared ulcer, all mice were euthanized. As results, the tumor volume of CCR2 antagonist treated group were significantly smaller than control group (Fig.8A-C), while mice weight showed no significantly difference (Fig.8D).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBlockade of MCP-1/CCR2 axis with CCR2 antagonist reduces M2 macrophages while increases CD8+ T cells of the tumor microenvironment to suppress tumor growth\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe have validated blockade of MCP-1/CCR2 axis with CCR2 antagonist did suppress tumor growth in vivo, while whether relating to M2 macrophages polarization needs further exploration. For further exploration, we analyzed the subcutaneous tumors microenvironment by FC and immunohistochemistry. We took the same quality tumor of each mice and digested the tumors into single cell suspension by collagenase and DNAse for FC. Anti-mouse CD20 antibody was first used to exclude B lymphoma cells, and then the proportion of natural killer (NK) cells, Regulatory T (Treg) cells, CD4+ T cells, CD8+ T cells and M2 macrophages were analyzed among those non-tumor cells (Fig.9A). As expected, compared to control group, M2 macrophages were less in CCR2 antagonist treated group (Fig.9B). To our surprise, we found CD8+ T cells were more in CCR2 antagonist group than control group, while the other cells did not show significantly difference between two groups (Fig.9C), For further analysis, we concluded M2 macrophages were negatively correlated with CD8+ T cells. Immunohistochemistry analysis also showed reduced M2 macrophages and increased CD8+ T cells (Fig.10). So blockade of MCP-1/CCR2 axis suppressed tumor growth may via inhibiting M2 macrophages polarization and increasing CD8+ T cells. \u0026nbsp; \u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe tumor-derived chemotactic protein MCP-1 and its receptor CCR2 have been found to be involved in the metastatic progression of tumors in a variety of tumors and are expected to be new targets for tumor therapy. Meanwhile about one-third of patients with diffuse large B-cell lymphoma are suffering from disease due to insensitivity to R-CHOP regimens, and they are in urgent need of novel therapeutic agents or treatments. Previous experiments by our group have demonstrated that CCR2 expression promotes DLBCL survival and invasion\u003csup\u003e21\u003c/sup\u003e. In this study, we further investigated the role of MCP-1/CCR2 axis in DLBCL and explored the therapeutic mechanism of CCR2 antagonists. First, we determined the cut-off values of MCP-1, CD68, CD163 expression based on previously published articles\u003csup\u003e6,20\u003c/sup\u003e, and found that high MCP-1 expression was associated with poor prognosis in DLBCL patients, while MCP-1 expression was positively correlated with the expression of CD68 and CD163 expression. Wang et al got the same conclusion that high MCP-1 expression was correlated with poor prognosis of DLBCL patients based on different cut off value with ours (Expression of MCP-1 and CCR2 in Newly Diagnosed Diffuse Large B-Cell Lymphoma and Clinical Significance). Other researches also demostrated CD68 and CD163 expressions were correlated with poor prognosis of DLBCL patients based on different cut-off values\u003csup\u003e59\u003c/sup\u003e. However, we first explored the relation of MCP-1 and TAMs in DLBCL, so more works were needed to validate our results, including appropriate cut-off values and the relationship between MCP-1 expression and CD68, CD163 expression. Then,we found the blockage of MCP-1/CCR2 by CCR2 antagonist inhibited the polarization of TAMs towards M2 and increased the proportion of CD8+ T cells in a mouse transplantation tumor model together inhibiting DLBCL progression in our in vitro and in vivo experiments.\u003c/p\u003e\n\u003cp\u003eThe cancer microenvironment has been identified as one of the hallmark drivers of cancer\u003csup\u003e22\u003c/sup\u003e, and chemokines are central regulators of the cancer microenvironment. Chemokines can direct various immune cells to the site of tumourigenesis and subsequently lead to inflammatory/immune responses\u003csup\u003e23\u003c/sup\u003e and have been found to play a role in the progression, migration, angiogenesis and metastasis of many cancer types\u003csup\u003e24\u003c/sup\u003e. Among these, signalling between CCR2 and its ligand MCP-1 has been found to promote cancer progression by directly stimulating tumour cell proliferation and down-regulating the expression of apoptotic proteins\u003csup\u003e25-30\u003c/sup\u003e. But more striking is the ability of tumor-derived MCP-1 to drive recruitment of circulating CCR2+ monocytes and to predispose monocytes to differentiate into TAMs\u003csup\u003e31\u003c/sup\u003e. In esophageal cancer the MCP-1/CCR2 axis polarizes TAMs to the immunosuppressive M2 phenotype and significantly increases PD-L2 expression, thereby depleting antitumor effector T cells and effectively mediating immune escape of tumor cells\u003csup\u003e32\u003c/sup\u003e. In hepatocellular carcinomas (HCCs), high MCP-1 expression was associated with more tumor-infiltrating TAMs and fewer CD8+ T cells. Blocking the MCP-1/CCR2 axis reduces monocytes/TAMs recruitment and M2 phenotype polarisation, thereby reducing immunosuppression of CD8+ T cells and directly enhancing tumor immunotherapy\u003csup\u003e33\u003c/sup\u003e. High expression of MCP-1 in breast cancer is similarly associated with infiltration of M2-type macrophages\u003csup\u003e34\u003c/sup\u003e. We have identified for the first time the ability of the MCP-1/CCR2 axis to recruit monocytes and induce polarization of TAMs in lymphohematopoietic tumors, and have also demonstrated for the first time the therapeutic mechanism by which CCR2 antagonists block the MCP-1/CCR2 axis and thereby inhibit immune escape from tumors in DLBCL.\u003c/p\u003e\n\u003cp\u003eClinical data from 143 patients with new-diagnosed non-specific DLBCL demonstrate that high expression of CD68 , CD163 and MCP-1 is highly correlated with a variety of poor prognostic signs that have been shown to be associated with DLBCL, such as IPI score, AMC\u003csup\u003e35\u003c/sup\u003e and high expression of MCP-1 is positively correlated with expression of CD68 and CD163, which further demonstrates the close relationship between MCP-1 and M2 type macrophages. The correlations between MCP-1 expression and CD68, CD163 expression are statistically significant, but these are moderate. So more representative, larger samples, and appropriate cut-off values are needed to obtain more obvious evidence. We also found that DLBCL patients with high expression of CD68, CD163 and MCP-1 had shorter survival and CD163 and MCP-1 were independent risk factors for DLBCL patients, which is consistent with studies in other tumors\u003csup\u003e36-42\u003c/sup\u003e. Moreover, low-risk patients could be further identified by the expression of MCP-1 expression, intermediate-risk patients could be further identified by the expression of CD68 or CD163 expression.However, the above indicators were not statistically significant in high-risk patients, which may be related to the bias caused by the small sample of high-risk patients, which was left for us to collect more samples for the next analysis to determine. The proportion of CD14+CCR2+ monocytes of PBMCs in DLBCL patients is higher than healthy volunteers and MCP-1 concentration is positively associated with CD14+CCR2+ monocytes of PBMCs in newly diagnosed DLBCL patients. Although previous studies have found that chemotherapy received by relapsed patients leads to a reduction in the total number of monocytes and a lower proportion of mononuclear myeloid-derived suppressor cells (M-MDSCs, CD14+HLA-DR\u003csub\u003elow\u003c/sub\u003e) in DLBCL\u003csup\u003e43\u003c/sup\u003e, the relapsed group showed a statistically significant higher proportion of CD14+CCR2+ monocytes compared to the remission group in spite of the chemotherapy interruption. CCR2+ monocytes in the relapse group compared to the remission group, which was more statistically significant. Together, these clinical data reflect the importance of the MCP-1/CCR2 axis in the progression of DLBCL and the relationship with M2 macrophages.\u003c/p\u003e\n\u003cp\u003eIn vitro, we first demonstrated the role of MCP-1 secretion of DLBCL cell lines by ELISA, with no significant differences between these cell lines, which allowed it to exert a chemotactic effect in combination with CCR2 expressed on monocytes. As reported, MCP-1 was also secreted by breast cancer cells, lung cancer cells, ovarian cancer cells, ect\u003csup\u003e44,45\u003c/sup\u003e. However, the secretion levels by ELISA between these tumor cells and DLBCL tumor cells needed to be further explored. It is well known that monocytes recruited to the tumor can differentiate into macrophages, and then polarized into different types TAMs in response to various factors, thereby promoting or inhibiting tumor progression\u003csup\u003e46,47\u003c/sup\u003e. Thus there are four main strategies for TAMs-based anti-tumor therapy: inhibition of macrophages recruitment, inhibition of TAMs survival, enhancement of the M1 killing activity of TAMs and blocking the M2 tumor-promoting activity of TAMs\u003csup\u003e48,49\u003c/sup\u003e. In DLBCL, we found that monocytes mediating chemotaxis via the MCP-1/CCR2 axis were polarized towards M2 TAMs, and the proportion of M2 TAMs in the tumor supernatant mock co-culture system increased significantly, while the proportion of M2 TAMs blocked by CCR2 antagonists in the MCP-1/CCR2 axis decreased. This finding is also consistent with hepatocellular carcinoma and other tumors\u003csup\u003e33,34,50\u003c/sup\u003e. We also found that although the proportion of M1 type macrophages increased in the tumor supernatant mock co-culture system, the CCR2 antagonist did not block or promote this effect, suggesting that there are other factors involved in the tumor supernatant that control the polarization of M1 type macrophages.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn vivo, we have not only demonstrated that CCR2 antagonists can inhibit tumor progression by blocking the MCP-1/CCR2 axis between monocytes and tumor cells, but also further demonstrated that tumor-derived MCP-1 induces polarization of TAMs towards M2 macrophages via the MCP-1/CCR2 axis. Even more promising was the discovery of a link between M2-type macrophages and CD8+ T cells, which may show a reciprocal pattern. CD8+ cytotoxic T lymphocytes (CTLs) as the immune cells of choice against cancer\u003csup\u003e51,52\u003c/sup\u003e, and their immunosuppression correlated with the drug-resistant properties of tumors\u003csup\u003e53\u003c/sup\u003e. M2 macrophages have been shown to create an immune barrier to CD8+ T cell-mediated anti-tumor immune responses\u003csup\u003e54\u003c/sup\u003e. Our results demonstrate that blocking the MCP-1/CCR2 axis can further exert anti-tumor effects by reducing the proportion of M2-type macrophages and increasing CD8+ T cells. It must be emphasized that our research only confirmed a negative correlation between the number of M2 macrophages and CD8+ T cells in DLBCL microenvironment of mice, and the mechanisms of how M2 macrophages interact with CD8 T cells need further exploration.\u003c/p\u003e\n\u003cp\u003eAs known, the application of rituximab that direct against human CD20 antigen has significantly improved the survival of DLBCL patients\u003csup\u003e1\u003c/sup\u003e. Rituximab mainly exerts its effect through antibody-dependent cellular cytotoxicity (ADCC)\u003csup\u003e55\u003c/sup\u003e. Rituximab- mediated ADCC contains different types of effector cells, such as neutrophils, M2 macrophages and NK cells, and NK cells play the most vital roles\u003csup\u003e56-58\u003c/sup\u003e. Our results showed significantly decreased M2 macrophages while slightly increased NK cells. Further researches are needed to determine whether M2 macrophages can synergize with rituximab immunotherapy by regulating NK cells.\u003c/p\u003e\n\u003cp\u003eIn summary, we have identified a novel therapeutic strategy for DLBCL and further investigated its mechanism of action. In vitro and in vivo experiments and clinical data together confirm that tumor-derived MCP-1 can induce the polarization of M2 macrophages via the MCP-1/CCR2 axis in DLBCL, thereby promoting tumor progression, and that this effect can be blocked by CCR2 antagonists. Meanwhile, we infer CD8+ T cells may be the dowmstream target of M2 macrophages and this needs further confirmation. In brief, our findings offer the possibility of further development of targeted therapies for the MCP-1/CCR2 axis in DLBCL.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cstrong\u003ePatients samples\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e143 newly diagnosed non specific DLBCL patients were recruited for the immunohistochemistry and another cohort including 30 healthy volunteers and 82 DLBCL patients (32 newly diagnosed cases (ND) with a median age of 57.9 years; 29 remission cases (REM) with a median age of 56.3 years; 21 relapse cases (Rel) with a median age of 58.6 years) were also recruited. These patients were all diagnosed, treated and followed from 2004 to 2016 at the First Affiliated Hospital and the Second Affiliated Hospital of Anhui Medical University. Each patient was given the informed consent. The diagnosis and prognosis criteria were based on the Word Health Organization (WHO) classification and International Prognostic Index (IPI)\u003csup\u003e19\u003c/sup\u003e. All patients were pathologically proved to be diffuse large B-cell lymphoma, and had no history of malignancy, transplantation or immunodeficiency. In addition, they all had complete clinical data and follow-up information. The study followed the Helsinki Declaration and was approved by the ethics committee of Anhui Medical University.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCell lines and cultures\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe human originated DLBCL cell lines SUDHL-2 and SUDHL-4 were kindly gifted by Dr. Ding Kaiyang (The first affiliated hospital of USTC, China), SUDHL-6 and OCI-Ly8 were generously favored by Prof. Zhai Zhimin (The second affiliated hospital Of Anhui Medical University, China). The human monocyte cell lines THP-1 and U937 were separately liberally given by Dr. He and Dr. Shen (The school of basic medical science, Anhui Medical University, China). The murine B lymphoma cell line A20 was purchased from the American Type Culture Collection (ATCC, Manassas, Virginia, USA). All cells were cultured with RPMI 1640 (Hyclone, Utah, USA) medium consisted 10% fetal bovine serum (FBS) (Gibco, NY, USA) and 1% penicillin-streptomycin (Beyotime, Shanghai, China) at 37℃ and 5% CO\u003csub\u003e2\u003c/sub\u003e incubator.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEnzyme linked immunosorbent assay (ELISA)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eELISA was performed to detect the secretion of MCP-1 by different DLBCL cell lines and the secretion in 32 newly diagnosed DLBCL patients’peripheral blood. DLBCL cell lines SUDHL-2, SUDHL-4, SUDHL-6 and OCI-Ly8 were cultivated in FBS free 1640 for 48 hours. Subsequently, we collected the medium of these cell lines to centrifuge at 3000rpm for 20 min and gathered the supernatant. Besides, the peripheral blood of the DLBCL patients was centrifugated at 500g for 15min to get the upper plasma. Finally, the ELISA kit (Mlbio, Shanghai, China) was used according to the manufacture instructions.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWestern blotting (WB)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe cells were lysed by RIPA lysis reagent (Beyotime, Shanghai, China) on ice and the total cellular protein was extrated by centrifugation at 12,000rpm for 20 min at 4℃. BCA reagent kit (Beyotime, Shanghai, China) was used to detect the protein concentration. Then, equal quality proteins were separated by 10% SDS-PAGE (Beyotime, Shanghai, China) and transferred onto activated PVDF membranes (Millipore, Massachusetts, USA). Followed blocking with 5% skim milk for 2 h at room temperature, the PVDF membranes were incubated with primary antibodies against CCR2 (1:1000, Bioworld Technology Inc., Minnesota, USA), p-Stat3, p-Stat6, p-Akt (1:1000, all from Cell Signaling Technology, Boston, USA) at 4℃\u0026nbsp;overnight.\u0026nbsp;β-actin (1:2000, ZSGB-Bio, Beijing, China) was used as control. Next day, the membranes were incubated with HRP-conjugated secondary antibody (1:5000, ZSGB -Bio, Beijing, China) for 1 h at room temperature, and then the blots were visualized by chemiluminescence imaging system (Tanon5200, Shanghai, China). Finally, image J was used to analyze and calculate the protein expression levels.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eChemotaxis assays\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTHP-1 or U937 cells were seeded in the upper of 8-μm pore size transwell chambers (Corning Costar, NY, USA) and DLBCL cell lines cells were cultured in the bottom of 6-well plates with 1640 medium containing 50μM CCR2 antagonist for blocking CCL2/CCR2 axis. After 48h, cells migrating to the underside of the membrane were fixed with methanol and stained with crystal violet. Finally, the migrated cells were observed and counted with the light microscope (ZEISS, Germany). Preparation of the conditioned medium (CM) of DLBCL cell lines cells DLBCL cell lines (SUDHL-4) cells were first cultured with 1640 medium with 10% FBS normally. When tumor cells grew up about 50% of the culture flask,1640 medium without FBS was used to culture these cells continuously for 48h. Then, the supernatant was collected after being centrifugated at 2000 rpm for 10 min. Finally, we mixed the supernatant and 1640 (1:1), and the mixture was conditioned medium (CM).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMacrophages generation and culture with CM\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e1×10\u003csup\u003e6\u003c/sup\u003e THP-1 cells were cultured in each well of 6-well plates with 1640 media containing 10% FBS. Firstly, these THP-1 cells were treated with 100ng/ml Phorbol 12-myristate 13-acetate (PMA) (TQ0198, Target Mol, USA) for 24 h, and then were incubated in FBS-free 1640 medium for 24 h to obtain M0 macrophages. To mimic the real tumor microenvironment, the THP-1-derived M0 macrophages were cultured in the mixture media CM for 48h with or without pre-treatment of 100μM CCR2 antagonist for 1h.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQuantitative real time polymerase chain reaction (qPCR)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTotal RNA was extracted with TRIzol reagent (Cat No:15596026, Thermo Fisher) and cDNA was synthesized by a reverse transcription kit (Vazyme Biotech Co., Ltd, Nanjing, China) according to its instructions. qPCR was processed in the reaction mixture containing 10μl 2×AceQ qPCR SYBR Green Master Mix, 0.4μl 50×ROX Reference Dye 1, 0.4μl 10μM Primer1, 0.4μl 10μM Primer2, 7.8μl ddH2O (all from Vazyme Biotech Co., Ltd, Nanjing, China) and 1μl cDNA on LC480\u0026nbsp;Ⅱ\u0026nbsp;machine (Roche). The mRNA relative expression level was calculated by using the 2−ΔΔCt method. The sequences of the primers are listed as follows:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eβ-actin, forward primer, 5’-CAGGAGGCATTGCTGATGAT-3’, reverse primer, 5’-GAAGGCTGGGGCTCATTT-3’,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIL-10, forward primer, 5’-TCTCCGAGATGCCTTCAGGAGA-3’, reverse primer, 5’-TCAGACAAGGCTTGGCAACCCA-3’,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCD163, forward primer, 5’-CCAGAAGGAACTTGTAGCCACAG-3’, reverse primer, 5’-CAGGCACCAAGCGTTTTGAGCT-3’,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTGF-β, forward primer, 5’-CGGAGAGCCCTGGATACCACCTA-3’, reverse primer, 5’-GCCGCACACAGCAGTTCTTCTCT-3’\u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnimal ethics declarations \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA statement to confirm that all experimental protocols were approved by the Ethics Committee of the The Second Affiliated Hospital of Anhui Medical University and Anhui Medical University. A statement to confirm that all methods were carried out in accordance with relevant guidelines and regulations. A statement to confirm that all methods are reported in accordance with ARRIVE guidelines. After all experimental studies were completed, mice were euthanized with 100% carbon dioxide (CO\u003csub\u003e2\u003c/sub\u003e) inhalation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnimal models\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e6 weeks old immunocompetent BALB/C female mice were purchased from Animal center of Anhui Province and fed at the SPF environment of the Animal center of Anhui Medical University. 1×10\u003csup\u003e7\u003c/sup\u003e A20 cells were resuspended in 200ul PBS and then injected subcutaneously into the right armpit of mice. When subcutaneous tumor path reached around 5mm, all mice were divided into two groups randomly, 20mg/kg CCR2 antagonist was injected intraperitonealy into the CCR2 antagonist group mice every other day and the control group mice were injected intraperitoneally equivalent dose of placebo. The tumor volume and mice weight were also recorded every other day. Once the tumor appeared ulcer, all mice were euthanized and the subcutaneous tumors were removed for FCM and immunohistochemistry. The tumor volume was calculated as (length×width×width)/2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFlow cytometry (FC) analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e4-5ml DLBCL patients’\u0026nbsp;peripheral blood was collected and then extracted peripheral blood mononuclear cells (PBMCs) for FC to detect CD14+CCR2+ monocytes. FITC anti-human CD14 and PE anti-human CCR2 antibodies were used in this process and they were purchased from Beckman Coulter company. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTHP-1-derived macrophages co-cultured with the supernatant of DLBCL lines were collected from 6-well plates, washed 3 times with PBS and then made into single-cell suspension and adjusted its concentration into 1×10\u003csup\u003e6\u003c/sup\u003e/ml. After being incubated with PE mouse anti-human CD206 for 30 min at 4℃,the stained cells were detected by FACS Calibur flow cytometer (BD) and then analyzed by FlowJo software. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe same quality of each mice’fresh subcutaneous tumors were cut, and then placed in 6-well plates on ice to wash with PBS, and then cut into pieces to digest single cells with collagenase and DNAse for 1h at 37℃. After digesting, the single cells were filtered with 100μM filter and centrifugated at 1500rpm for 10 min. Followed by lysis red blood cells, single cells were centrifugated at 1500rpm for 10 min and resuspended in PBS at concentration of 1×10\u003csup\u003e6\u003c/sup\u003e, then the single cell suspensions were stained with antibodies for 30 min at 4℃. Finally, the stained cells were detected by FACS Calibur flow cytometer (BD) and then analyzed by FlowJo software. For detection of different cells, we used the following antibodies: Brilliant Violet 421 anti-mouse CD20, PE anti-mouse NK1.1, FITC anti-mouse CD4, PE anti-mouse CD25, AF 647 anti-mouse Foxp 3, PerCP-cy5.5 anti-mouse CD8, FITC anti-mouse CD11b, PE anti-mouse F4/80, AF 647 anti-mouse CD206. All antibodies were purchased from BD Pharmingen.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImmunohistochemistry\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHuman samples and mice subcutaneous tumors were formalin-fixed, paraffin- embedded and then cut into 3um specimen sections. Antibodies aganist human MCP-1 (1:100, Santa Cruz, Biotechnology, USA), CD68 (1:200, Abcam, USA), CD163 (1:200, Abcam, USA), against mouse F4/80 (1:200, Abcam, USA), CD206 (1:200, Abcam, USA), CD8 (1:100, Abcam, USA) were used. All sections were deparaffinized and rehydrated and then repaired antigens in citric acid antigen repair solution (PH 6.0). After blocking endogenous peroxidase with 3% hydrogen peroxide, the sections were incubated respectively with anti-MCP-1, CD68, CD163, F4/80, CD206 and CD8 antibodies at 4℃ overnight. The sections were then incubated with \u0026nbsp;HRP-conjugated goat anti-mouse and rabbit IgG secondary antibody (ZSGB-Bio, Beijing, China) for 15 minutes at room temperature. Finally, DAB solution (ZSGB- Bio, Beijing, China) and haematoxylin (ZSGB-Bio, Beijing, China) were used to visualize the staining. All the finished staining sections were analysed by our two professional pathologists who knew nothing about patients. They evaluated the adequacy of immunostaining and selected the representative tumor areas for counting and recording. Semi-quantitative analysis of immunostaining in MCP-1 was judged as grade 0,1,2 or 3. Grade 0＜1% tumor staining, grade 1＜1-33%, grade 2＜34-66%, and grade 3＞67%. Grade 0 represented low expression and grade 1-3 represented high expression\u003csup\u003e6,19,20\u003c/sup\u003e. The cut-off values were selected at 33% for CD68 and 19% for CD163\u003csup\u003e6\u003c/sup\u003e. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSPSS software (version 25) was used. All data were recorded as the mean±SEM from three independent experiments. The chi-square test or Fisher’s exact test was used to compare categorical values between two groups. Cox proportional hazard model was used to analyze the factors of progression-free survival (PFS) and overall survival (OS). Kaplan-Meier method and log-rank tests were used to compare differences between groups. For cell culture trials and in vivo experiments, we used two-tailed Student’s t-tests to determine statistical significance. P＜0.05 was indicated a statistically significant.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp skip=\"true\"\u003eAll data generated or analysed during this study are included in this published article.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eAuthor Contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZ.W. and Q.H. performed the research and wrote the paper. Y.L. and Z.Z. designed the research study. F.N., Q.H. and Z.W. analyzed the data and contributed to the data collection. All authors finally approved the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by National Natural Science Foundation of China (81700194) and College Natural Science Foundation of Anhui Province (KJ2021A0214).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGrimm KE, O\u0026apos;Malley DP. Aggressive B cell lymphomas in the 2017 revised WHO classification of tumors of hematopoietic and lymphoid tissues. Ann Diagn Pathol. 2019;38:6-10.\u003c/li\u003e\n\u003cli\u003eSarkozy C, Sehn LH. Management of relapsed/refractory DLBCL. Best PractRes Clin Haematol. 2018;31(3):209-216.\u003c/li\u003e\n\u003cli\u003eHanahan D, Coussens LM. 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Histopathology. 2012;60(2):313-319.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"diffuse large B-cell lymphoma, MCP-1/CCR2 axis, M2 macrophages polarization, progression, antitumor immune response ","lastPublishedDoi":"10.21203/rs.3.rs-6219553/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6219553/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Diffuse large B-cell lymphoma (DLBCL) is an aggressive hematological malignancy with restricted effective therapy choices. The MCP-1/CCR2 axis is required for the recruitment of monocytes and polarization of macrophages. We investigated the feasibility of treatment targeting MCP-1-CCR2-macrophages axis in DLBCL. MCP-1, CD68, CD163 expression was analyzed by immunohistochemistry in 143 DLBCL patients tissues, and MCP-1 concentration and CD14+CCR2+ monocytes in peripheral blood were analyzed in another cohort by enzyme linked immunosorbent assay or flow cytometry. THP-1 or U937 cells were used to mimic macrophages polarization with or without the blockade of MCP-1/CCR2 axis in vitro. BALB/C mice subcutaneous tumors were evaluated and detected after blocking MCP-1/CCR2 axis with CCR2 antagonist. MCP-1, CD68, CD163 expression and proportion of CD14+CCR2+ monocytes in peripheral blood are prognostic for DLBCL patients. MCP-1 expression is positively associated with CD68 or CD163 expression in DLBCL. Blockade of MCP-1/CCR2 axis with CCR2 antagonist inhibits monocytes recruitment and M2 macrophages polarization in vitro and concomitantly increases the number of CD8 T-cells, which can lead to inhibition of subcutaneous tumour growth. MCP-1-CCR2-M2 macrophages polarization plays vital roles in DLBCL progression. The results demonstrate the translational potential of MCP-1/CCR2 blockade for treatment of DLBCL.","manuscriptTitle":"MCP-1-CCR2-M2 macrophages axis contributes to diffuse large B-cell lymphoma progression and inhibits antitumor immune response","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-20 14:54:39","doi":"10.21203/rs.3.rs-6219553/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-28T14:14:20+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-22T09:30:06+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-22T02:20:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"276334693401215953083109956007495703488","date":"2025-05-17T01:56:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"294269941304661630954124434866993793865","date":"2025-05-15T06:06:35+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-15T01:46:14+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-05-02T05:25:40+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-09T18:29:49+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-08T06:44:20+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-04-08T06:43:14+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2f69dc04-ac6a-4eec-ac9e-182334f36f37","owner":[],"postedDate":"May 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":48659618,"name":"Biological sciences/Cancer/Haematological cancer"},{"id":48659619,"name":"Biological sciences/Cancer/Cancer microenvironment"}],"tags":[],"updatedAt":"2025-07-31T12:53:46+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-20 14:54:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6219553","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6219553","identity":"rs-6219553","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}