Association of Gene Polymorphisms in Programmed Death Ligand-1 (PD-L1) with susceptibility and prognosis of B-Cell Non-Hodgkin Lymphoma in a Cohort of Egyptians

Association of Gene Polymorphisms in Programmed Death Ligand-1 (PD-L1) with susceptibility and prognosis of B-Cell Non-Hodgkin Lymphoma in a Cohort of Egyptians | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Association of Gene Polymorphisms in Programmed Death Ligand-1 (PD-L1) with susceptibility and prognosis of B-Cell Non-Hodgkin Lymphoma in a Cohort of Egyptians Laila A Hegazi¹, Manal W El-Masry¹, Heba M Gouda¹, Mervat M Matter, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3838300/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose: To investigate the possible relation between polymorphisms of PD-L1 rs4143815 and rs2890658 with the susceptibility and prognosis of B-NHL in a Cohort of Egyptians, we conducted a case-control study. Methods: Genotyping was done using real-time polymerase chain reaction (real-time PCR) for 100 adult B-NHL patients and 100 healthy adults (controls). Results: Our results did not show any significant association between PD-L1 (rs4143815, rs2890658) SNPs and risk of B-NHL occurrence. However, the relationship between allele distribution of rs4143815 (C>G) and rs2890658 (A>C) and adverse clinico-pathological features of B-NHL patients revealed positive results. Conclusions: Our results provided the first evidence that PD-L1 rs4143815 (C>G) and rs2890658 (A>C) are not molecular susceptibility markers for B-NHL in Egyptians, at least in the studied population. However, these polymorphic sites could be candidates for predicting some adverse clinico-pathological features and might have a potential prognostic role in B-NHL. B-NHL- PDL1- rs4143815- rs2890658- SNP- Real-Time PCR Introduction Cancer is considered a highly significant global health problem and worldwide leading cause of death. Thus, the etiology and pathogenesis of malignancy have not been completely elucidated and their understanding is still decisive. During the past decades, several investigators focused their research on the functional role of the immune system in the process of carcinogenesis ( De Visser et al., 2006 ). The results point out that mutations in immune-related genes may alter cancer predisposition and susceptibility ( Kim et al., 2007 ). Human cancers, including hematological malignancies, have developed multiple effective strategies to evade the host immune surveillance. Mechanisms used by tumors for immune evasion have been extensively studied in the last decade ( Parry et al., 2005 ), and a better understanding of these decisive mechanisms has facilitated the development of novel therapies aimed at stopping tumor immune evasion. Tumor cells are capable of evading immune surveillance by over-expressing the ligands of checkpoint receptors, bringing T lymphocytes to a state of anergy or exhaustion ( Wherry and Kurachi 2015 ). Cancer cells can work on a variety of immune checkpoint signaling pathways such as programmed cell death protein 1 (PD-1) and cytotoxic T lymphocyte antigen 4 (CTLA4) to elicit immunosuppressive functions. The PD-1/PD-L1 signaling pathway has an important role in immune tolerance and prevention of occurrence of autoimmune disorders ( Salmaninejad et al., 2019 ). Although many studies on chemical therapy for cancer have generated promising results, a major breakthrough has been made by using immunotherapeutic agents that unleash our ability to recognize and overcome cancer ( Wu et al., 2018 ). During the last decade we have witnessed a remarkable development of immunotherapy targeting numerous checkpoint molecules of the immune system ( Kula et al., 2020 ). Under normal physiological circumstances, the PD-1/PD-L1 checkpoint pathway plays a vital role in maintaining immune homeostasis. PD-L1 is a ligand bound to PD-1 receptor and their interaction down-regulates T cell response for optimal control of the immune system in normal cells. In cancer, tumor cells use PD-L1 to escape from immune surveillance where they overexpress this ligand at a high level to downregulate tumor-specific T lymphocytes and inhibit their proliferation ( Zak et al., 2017 ). Many single-nucleotide polymorphisms (SNPs) that might alter the genetic predisposition of cancer have been reported in PD-L1 genes recently. These polymorphisms might affect tumor growth, behavior, and response to therapy ( Zou et al., 2016 ). Since a limited number of studies have investigated the association between PD-L1 polymorphisms and the risk of lymphoma occurrence, it is necessary to examine the effect of these polymorphisms on the tumor behavior, prognosis, and response to treatment. The Aim of this study was to investigate the possible relation between polymorphisms of PD-L1 rs4143815 and rs2890658 with the susceptibility and prognosis of B-NHL in a Cohort of Egyptians. Materials and Methods 1.1. Study Population One hundred adult Egyptians with B-NHL were recruited from the Department of Hematology and Medical Oncology at Kasr Al-Ainy Hospital, Cairo University, and 100 volunteers with similar ages and sexes from The Checkup Clinic served as the control group in this study. 1.2. Sample collection and DNA extraction Three ml venous blood were withdrawn from all subjects and collected in EDTA tubes and kept frozen at -20˚C till time of DNA extraction. Genomic DNA was isolated using GeneJET Whole Blood Genomic DNA Purification Mini Kit (Cat No: #K0781, Life Technologies Inc., 5781 Van Allen Way, Carlsbad, California) applied by Thermo Fisher according to the manufacturer’s instructions. 1.3. Genotyping of PDL1 rs4143815 (C/G) and rs2890658 (A/C) PD-L1 allelic discrimination was assessed using Sequence-specific primers and Custom allele-specific TaqMan® SNP Genotyping Assays provided from Applied biosystems then consequent analysis was performed on DNA-Technology StepOne ™ Real-Time PCR system. Also, each allele-specific TaqMan probe has a reporter dye at its 5´end (FAM dye is linked to the 5´end of the Allele 1 probe, and VIC dye is linked to the 5´ end of the Allele 2 probe), which allows the allele-specific fixation of each probe. The context sequence for rs4143815 of PDL1 was: TTGCCTCCACTCAATGCCTCAATTT [C/G] TTTTCTGCATGACTGAGAGTCTCAG Variant: G > C, transition substitution, while the context sequence for PDL1 rs2890658 was: CAAGAGGAAGTGAAATAATCAAGGC [A/C] GCCATTTAATAGTGAGCAGCCACTC Variant: C < A, transition substitution. Amplification of DNA was done in a real-time thermocycler. After PCR amplification, an endpoint plate read was performed using an DNA-Technology Real-Time PCR System, The DTMaster Software uses the fluorescence signal measurements which were made during the plate reading to plot fluorescence values based on the signals from each well. Statistical Analysis With the help of the statistical program SPSS version 22, data were coded and examined. Analysis of variance (ANOVA) with multiple comparisons post hoc testing was used to compare the groups. An analysis using the Chi square (2) test was done to compare categorical data. It was determined the odds ratio (OR) and its 95% confidence interval. Statistics were considered significant for P-values under 0.05. The Fisher exact test, the Pearson chi-square test, or the Kruskal-Wallis test were all used to analyze univariate association. The Kaplan-Meier method was used to produce the survival curves, and the log-rank test was used to compare them. Results 3.1. Demographic profile They were 54 males and 46 females with a mean age of 52.7 years for the patients and 52 male and 48 female (with a mean age of 52.5 years for the controls. Clinicopathological data of B-NHL patients at diagnosis are presented in Table 1 . 3.2. Association between PDL-1 polymorphisms and risk of NHL Genotype distribution of PD-L1 rs4143815 GG, GC, and CC genotypes were 62%, 33%, and 5% among B-NHL patients, compared to 58%, 36%, and 6% in the control group, respectively (p = 0.837). Furthermore, the frequency of G and C alleles was 78.5%, 21.5% among patients compared to 76%, 24% in the controls, respectively with no statistical significance (p = 0.551). In PD-L1 rs2890658 polymorphism, the distribution of CC, AC and AA genotypes were 80%, 18% and 2% among B-NHL patients, compared to 77%, 22% and 1% in the control group, respectively. Furthermore, the frequency of C and A alleles was 89% and 11% among patient group compared to 88% and 12% in the control group respectively with no statistical significance (p = 0.787). As a net result, data revealed from analysis of genotype distribution and allele frequencies of PDL-1 rs4143815 (C C) SNPs, did not show any association with the susceptibility of B-NHL (table 2). 3.3. Association between PD-L1 Genotyping and clinicopathological features. Statistical comparison between two studied groups of B-NHL regarding allele frequency of PD-L1 rs4143815 revealed that presence of mediastinal lymphadenopathy, hepatomegaly, extra-nodal involvement ≥ 2 sites and bone marrow infiltration were more prominent in those harboring the G allele and results showed statistical significance (P = 0.001, p = 0.009, p = 0.013, < 0.001), respectively. On multivariate analysis, hepatomegaly retains statistical significance (OR = 2.426, P value = 0.035). Concerning PD-L1 rs2890658 analysis, the presence of nodal involvement, advanced clinical stage III & IV, presence of anemia, presence of bone marrow infiltration and increased level of LDH were more prominent in those harboring the C allele and results showed statistical significance (P = 0.017, p = 0.049, p = 0.012, p = 0.009, 0.002), respectively. By multivariate analysis of the variables, nodal involvement (OR = 4.3, P = 0.037), BM involvement (OR = 6.2, P = 0.017) and high LDH (OR = 4.0, P = 0.004) show statistical significance. Moreover, co-inheritance of the common alleles of both SNPs of PDL1 show very high statistical significance by both univariate and multivariate analysis (OR = 14.086, p = < 0.001). 3.4. Regarding the potential role of these SNPs as molecular prognostic markers The 12 months, 36 months, and 60 months DFS rates were estimated and PDL1 rs4143815 & rs2890658 genetic variants were assessed for their impact on patients’ DFS. The 36 months DFS` rate for the combined genotype (GC & CC) of PD-L1 rs4143815 (C > G) was 63.8% versus 67% for the common genotype (GG), while the 60 months DFS rate for the combined genotype (GC & CC) was 63.8% versus 44.6% for the common genotype (GG) with no statistically significant difference (p = 0.249). While the 36 months` DFS rate for the combined genotype (AA & AC) of rs2890658 (A > C) was 83.3% versus 61.5% for the common genotype (CC), and the 60 months DFS rate for the combined genotype (AA & AC) was 83.3% versus 46.1% for the common genotype (CC), which was statistically insignificant (p = 0.599) , therefore PDL1 rs4143815 & rs2890658 polymorphism have no impact on patients’ DFS. By univariate analysis between clinicopathological factors and DFS; patients with B symptoms, PS ≥ 2, advanced An Arbor stage, presence of anemia and high TLC count were found to have a statistically significant relation with poorer DFS (p = 0.016, p = 0.039, p = 0.023, p = 0.038, p = 0.019), respectively. It was found that An Arbor stage (HR = 7.53, P = 0.053) is independent predictor of DFS by multivariate analysis. Other potential prognostic factors, such as the patients’ age at diagnosis, sex, International Prognostic Index score, extra-nodal involvement, and LDH level did not affect the DFS of our B-NHL patients. Discussion Several SNPs in PD-L1 genes are heavily studied for their contribution to the susceptibility of cancer occurrence, tumor growth, behavior, and response to therapy ( Lee et al., 2017 ) however, the relationship between the PDL-1 genetic variations and B-NHL remains ambiguous ( Hoseini et al., 2020 ). So far, this is considered the first study to address the association between PD-L1 SNPs (rs4143815 and rs2890658) and the susceptibility of NHL in Egypt. Results of PD-L1 rs4143815 demonstrated similar genotype distribution between both patient and control groups with no statistical significance revealed (p = 0.551). These results were in agreement with recent study in 2020, that revealed no significant association between PD-L1 rs4143815 and the risk of NHL incidence ( Hoseini et al., 2020 ), also in agreement with Du (2017)’ study that revealed no significant association between PD-L1 rs4143815 polymorphism and occurrence of Lung cancer ( Du et al., 2017 ). Discordant results from a meta-analysis by Zou (2018) in Asian population revealed that rs4143815 (C > G) is associated with increased cancer susceptibilities, including gastric, bladder cancer and HCC, indicating that this SNP might be used as a genetic biomarker tool to predict the cancer susceptibility. Moreover, GG genotype in rs4143185 (C > G) SNP was found to be related to increased risk of HCC in another study (p < 0.001) ( Xie et al., 2018 ). Hashemi and colleagues , revealed that PDL-1 rs4143815 polymorphism is associated with decreased overall risk of tumour occurrence giving it a protective value against cancer, while no significant association found between rs2890658 SNP and the overall risk of cancer in parallel to our results ( Hashemi et al., 2019 ). Moreover, the pooled analysis from Zou (2019) study did not support an association between PD-L1 rs2890658 polymorphism and the cancer susceptibilities. In the other side, data reported by Hoseini (2020) demonstrated significant association of PD-L1 rs2890685 (A > C) SNP with increased risk of NHL (p < 0.0001), where rs2890685 AA genotype distribution was significantly prevalent in patients with NHL in comparison to controls, although these results conflict with our observation. Moreover, Zhou (2016) reported that PD-L1 rs2890658 SNP is associated with increased risk of oesophageal carcinoma in group of smokers. Since prognostic markers are important clinical tools used in assessing the newly diagnosed patient to help predict the patient’s clinical outlook. For B-NHL patients, many prognostic markers such as age 1, presence of BM involvement, anemia and B symptoms have been used to predict future clinical outcome of patients. Here, we studied the relationship between the allele frequencies of the PD-L1 polymorphisms and adverse clinicopathological factors of the patients which revealed some positive results. Our findings revealed, the presence of mediastinal nodal involvement, hepatomegaly, extra-nodal involvement and BM infiltration were more prominent in patients with G allele of rs4143815 and results showed a statistical significance (P = 0.001, p = 0.009, p = 0.013, < 0.001), respectively. These findings are consistent with Wu (2006)’ study which found significant relation between rs4143815 SNP and clinicopathological features of gastric cancer including tumour size, differentiation grade, depth of tumour infiltration, lymph node metastasis, and TNM stage, and considered this variant might be a potential risk factor for cancer predisposition. Another study done by Du et al. , was in agreement with our findings, which reported that rs4143815 SNP had significant associations with clinicopathological features, including depth of tumor infiltration, distant metastasis, lymph node metastasis and TNM stage in lung cancer; therefore, it might be possible future prognostic tool ( Du et al., 2017 ). So, we can conclude that our results provided the first evidence that PD-L1 rs4143815 and rs2890658 genetic variants are not considered genetic predisposing factors in susceptibility to B-NHL in a cohort of Egyptian population, at least in the studied population. Although the polymorphism at PD-L1 gene has no impact on patients’ survival; rather, there was a significant association between the major alleles of PD-L1 rs4143815 and rs2890658 SNPs and the adverse clinico-pathological features of B-NHL patients. Therefore, these polymorphic sites could be candidates for predicting the adverse clinicopathological features of B-NHL and might be valuable for prognostic values in Egyptian population. Although, validation by a larger prospective study from diverse ethnic population is warranted to confirm our findings. Study Limitations The relatively small sample size of this study is a limitation of the present work. Larger sample size is recommended to validate our results regarding the role of the studied SNPs as molecular risk factors for B-NHL and to clarify their impact on therapeutic response and disease course. Furthermore, serum PD-L1 level should have been examined to conclude the association between the examined variations and B-NHL. Declarations Funding The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Competing Interests The authors have no relevant financial or non-financial interests to disclose. Author Contributions All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by [Marwa T Hassan], [Heba M Gouda] and [Manal W El-Masry]. The first draft of the manuscript was written by [Marwa T Hassan] and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.” Data Availability The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. Ethics approval This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Cairo University, faculty of medicine. Consent to participate. Informed consent was obtained from all individual participants included in the study. Consent to publish. The authors affirm that human research participants provided informed consent for publication of the images in Figure(s) 1a, 1b and 1c. References De Visser KE, Eichten A, and Coussens LM (2006): Paradoxical roles of the immune system during cancer development. Nature Reviews Cancer, 6(1): 24–37. doi: 10.1038/nrc1782 . Du W, Zhu J, Chen Y, et al. (2017): Variant SNPs at the microRNA complementary site in the B7H1 3'untranslated region increase the risk of non-small cell lung cancer. Mol Med Rep, 16(3):2682–90. doi: 10.3892/mmr.2017.6902 . Epub 2017 Jun 30. PMID: 28677815; PMCID: PMC5547930. Hashemi M, Karami S, Sarabandi S, et al. (2019): Association between PD-1 and PD-L1 Polymorphisms and the Risk of Cancer: A Meta-Analysis of Case-Control Studies. Cancers (Basel), 11(8):1150. doi: 10.3390/cancers11081150 . Hoseini H, Yaghmaei P, Bahari G, and Aminzadeh S. (2020): Correlations of PD-1/PD-L1 Gene Polymorphisms with Susceptibility and Prognosis in Non-Hodgkin Lymphoma in Iranian Population. IRANIAN RED CRESCENT MEDICAL JOURNAL (IRCMJ), 22(11), 0–0. SID. https://sid.ir/paper/976152/en . Kim R, Emi M and Tanabe K, (2007): Cancer immunoediting from immune surveillance to immune escape. Immunology, 121 (1): 1–14. https://doi.org/10.1111/j. 1365-2567.2007.02587.x. Kula A, Dawidowicz M, Kiczmer P, Prawdzic Seńkowska A and Świętochowska E (2020): The role of genetic polymorphism within PD-L1 gene in cancer. Review. Experimental and Molecular Pathology, 104–494. doi: 10.1016/j.yexmp.2020.104494 . Lee SY, Jung DK, Choi JE, et al. (2017): Functional polymorphisms in PD-L1 gene are associated with the prognosis of patients with early-stage non-small cell lung cancer. Gene, 599, 28–35. doi: 10.1016/j.gene.2016.11.007 . Parry RV, Chemnitz JM, Frauwirth KA, et al (2005): CTLA-4 and PD-1 receptors inhibit T-cell activation by distinct mechanisms. Mol Cell Biol, 25 (21): 9543–53. doi: 10.1128/mcb.25.21.9543-9553.2005 . Salmaninejad A, Valilou SF, Shabgah AG et al., (2019): PD-1/PD-L1 pathway: Basic biology and role in cancer immunotherapy. J Cell Physiol, 234(10):16824–37. doi: 10.1002/jcp.28358 . Epub 2019 Feb 19. PMID: 30784085. Wherry EJ and Kurachi M. (2015): Molecular and cellular insights into T cell exhaustion. Nat Rev Immunol, 15(8):486–99. Wu C, Zhu Y, Jiang J, et al. (2006): Immunohistochemical localization of programmed death-1 ligand-1 (PD-L1) in gastric carcinoma and its clinical significance. Acta Histochemica, 108(1): 19–24. doi: 10.1016/j.acthis.2006.01.003 . Wu D, Guo M, Min X, et al. (2018): LY2874455 potently inhibits FGFR gatekeeper mutant and overcomes mutation-based resistance. Chem Commun (Camb), 54(85):12089–92. doi: 10.1039/c8cc07546h . Xie Q, Chen Z, Xia L, et al. (2018): Correlations of PD-L1 gene polymorphisms with susceptibility and prognosis in hepatocellular carcinoma in a Chinese Han population. Gene, 674, 188–94. Zak KM, Grudnik P, Magiera K, et al. (2017): Structural Biology of the Immune Checkpoint Receptor PD-1 and Its Ligands PD-L1/PD-L2. Structure, 25(8):1163-74. doi: 10.1016/j.str.2017.06.011 . PMID: 28768162. Zhou RM, Li Y, Wang N, et al., (2016): Association of programmed death-1 polymorphisms with the risk and prognosis of esophageal squamous cell carcinoma. Cancer Genet, 209, 365–75. Zhou RM, Li Y, Liu JH, et al. (2017): Programmed death-1 ligand-1 gene rs2890658 polymorphism associated with the risk of esophageal squamous cell carcinoma in smokers. Cancer Biomark, 21(1):65–71. doi: 10.3233/CBM-170269 . PMID: 29060926. Zou W, Wolchok JD and Chen L, (2016): PD-L1 (B7-H1) and PD-1 pathway blockade for cancer therapy: Mechanisms, response biomarkers, and combinations. Sci Transl Med, 8(328):328rv4. doi: 10.1126/scitranslmed.aad7118 . PMID: 26936508; PMCID: PMC4859220. Zou J, Wu D, Li T, et al. (2019): Association of PD-L1 gene rs4143815 C > G polymorphism and human cancer susceptibility: A systematic review and meta-analysis. Pathol Res Pract, 215(2):229–34. doi: 10.1016/j.prp.2018.12.002 . Statements & Declarations Tables Table (1): Clinicopathological data of B-cell non-Hodgkin lymphoma patients at presentation Item Patient group (n = 100) Number (%) Sex(male/female) (54/46) Age (years) ≤ 60 77 (77%) < 60 23 (23%) B- symptoms Fever, night sweats, weight loss 55 (55%) Lymphadenopathy 91 (91%) Extra-nodal involvement < 2 ≥ 2 81(81%) 19 (19%) Bulky disease 29 (29%) Splenomegaly 58 (58%) Hepatomegaly 43 (43%) Bone marrow infiltration 34 (34%) HCV positivity 25(25%) Clinical stage Early (I&II) Late (III&IV) 24 (24%) 76 (76%) P.S Score < 2 Score ≥ 2 70 (70%) 30 (30%) IPI risk group Low & Low-intermediate High & High-intermediate 62 (62%) 38 (38%) IPI risk groups for DLBC subtype (n = 84) Low/ Intermediate low Intermediate high/ High 57 (67.8%) 27(32.1%) Histological subtypes (High grade Lymphoma) DLBCL THRLBCL 84 (84%) 16 (16%) P.S: Performance status, HCV: Hepatitis C virus , DLBCL: Diffuse large b cell lymphoma, IPI: International prognostic index, THRLBCL: T-cell/histiocyte-rich B-cell lymphoma Table (2): Genotype distribution and allele frequencies of PD-L1 rs4143815 and rs2890658 in B-NHL patients and control groups. Genotype Group P-value Patients (n = 100) Controls (n = 100) No(%) No(%) PD-L1 rs4143815 (C > G) GG 62 (62%) 58 (58%) 0.837 CG 33 (33%) 36 (36%) CC 5 (5%) 6 (6%) G allele C allele 157/200 (78.5%) 43/200 (21.5%) 152 /200 (76%) 48/200 (24%) 0.551 GG vs GC + CC 62 (62%) vs 38 (38%) 58 (58%) vs 42 (42%) 0.564 CC vs GG + GC 5 (5%) vs 95 (95%) 6 (6%) vs 94 (94%) 0.756 PD-L1 rs2890658 (A < C) CC 80 (80%) 77 (77%) * AC 18 (18%) 22 (22%) AA 2 (2%) 1 (1%) C allele A allele 178/200 (89%) 22/200 (11%) 176/200 (88%) 24/200 (12%) 0.787 CC vs AC/AA 80(80%) vs 20(20%) 77 (77%) vs 23(23%) 0.606 AA vs AC/CC 2(2%) vs 98 (98%) 1(1%) vs 99(99%) * P value < 0.05 : Is significant, PD-L1 : Programmed death ligand-1, *: p value cannot be calculated because of small number within strata. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3838300","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":265719387,"identity":"42db2ba3-e149-41da-98f0-8fe72f5b926e","order_by":0,"name":"Laila A Hegazi¹","email":"","orcid":"","institution":"Cairo University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Laila","middleName":"A","lastName":"Hegazi¹","suffix":""},{"id":265719388,"identity":"8af5991c-db43-4bb2-a843-f587b55c8020","order_by":1,"name":"Manal W El-Masry¹","email":"","orcid":"","institution":"Cairo University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Manal","middleName":"W","lastName":"El-Masry¹","suffix":""},{"id":265719389,"identity":"02b4747d-cbc1-47ad-af05-3b10ac85a09c","order_by":2,"name":"Heba M Gouda¹","email":"","orcid":"","institution":"Cairo University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Heba","middleName":"M","lastName":"Gouda¹","suffix":""},{"id":265719390,"identity":"f4c1af3b-c417-46c6-915e-a00a34d568f2","order_by":3,"name":"Mervat M Matter","email":"","orcid":"","institution":"Cairo University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Mervat","middleName":"M","lastName":"Matter","suffix":""},{"id":265719391,"identity":"73fd4292-3867-4728-9dc5-c5bd77602233","order_by":4,"name":"Marwa T Hassan","email":"data:image/png;base64,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","orcid":"","institution":"Cairo University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Marwa","middleName":"T","lastName":"Hassan","suffix":""}],"badges":[],"createdAt":"2024-01-05 22:14:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3838300/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3838300/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":49357422,"identity":"b02aa24b-e9bd-4f54-8f1e-8822e97b34b5","added_by":"auto","created_at":"2024-01-09 08:31:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":463537,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3838300/v1/1eec25ed-63a8-4a58-bca7-44ea416fe50a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association of Gene Polymorphisms in Programmed Death Ligand-1 (PD-L1) with susceptibility and prognosis of B-Cell Non-Hodgkin Lymphoma in a Cohort of Egyptians","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCancer is considered a highly significant global health problem and worldwide leading cause of death. Thus, the etiology and pathogenesis of malignancy have not been completely elucidated and their understanding is still decisive. During the past decades, several investigators focused their research on the functional role of the immune system in the process of carcinogenesis \u003cb\u003e(\u003c/b\u003eDe Visser et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). The results point out that mutations in immune-related genes may alter cancer predisposition and susceptibility \u003cb\u003e(\u003c/b\u003eKim et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHuman cancers, including hematological malignancies, have developed multiple effective strategies to evade the host immune surveillance. Mechanisms used by tumors for immune evasion have been extensively studied in the last decade \u003cb\u003e(\u003c/b\u003eParry et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), and a better understanding of these decisive mechanisms has facilitated the development of novel therapies aimed at stopping tumor immune evasion. Tumor cells are capable of evading immune surveillance by over-expressing the ligands of checkpoint receptors, bringing T lymphocytes to a state of anergy or exhaustion \u003cb\u003e(\u003c/b\u003eWherry and Kurachi \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2015\u003c/span\u003e\u003cb\u003e).\u003c/b\u003e\u003c/p\u003e \u003cp\u003eCancer cells can work on a variety of immune checkpoint signaling pathways such as programmed cell death protein 1 (PD-1) and cytotoxic T lymphocyte antigen 4 (CTLA4) to elicit immunosuppressive functions. The PD-1/PD-L1 signaling pathway has an important role in immune tolerance and prevention of occurrence of autoimmune disorders \u003cb\u003e(\u003c/b\u003eSalmaninejad et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlthough many studies on chemical therapy for cancer have generated promising results, a major breakthrough has been made by using immunotherapeutic agents that unleash our ability to recognize and overcome cancer \u003cb\u003e(\u003c/b\u003eWu et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). During the last decade we have witnessed a remarkable development of immunotherapy targeting numerous checkpoint molecules of the immune system \u003cb\u003e(\u003c/b\u003eKula et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eUnder normal physiological circumstances, the PD-1/PD-L1 checkpoint pathway plays a vital role in maintaining immune homeostasis. PD-L1 is a ligand bound to PD-1 receptor and their interaction down-regulates T cell response for optimal control of the immune system in normal cells. In cancer, tumor cells use PD-L1 to escape from immune surveillance where they overexpress this ligand at a high level to downregulate tumor-specific T lymphocytes and inhibit their proliferation \u003cb\u003e(\u003c/b\u003eZak et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMany single-nucleotide polymorphisms (SNPs) that might alter the genetic predisposition of cancer have been reported in PD-L1 genes recently. These polymorphisms might affect tumor growth, behavior, and response to therapy \u003cb\u003e(\u003c/b\u003eZou et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Since a limited number of studies have investigated the association between PD-L1 polymorphisms and the risk of lymphoma occurrence, it is necessary to examine the effect of these polymorphisms on the tumor behavior, prognosis, and response to treatment. \u003cb\u003eThe Aim of this study was to\u003c/b\u003e investigate the possible relation between polymorphisms of PD-L1 rs4143815 and rs2890658 with the susceptibility and prognosis of B-NHL in a Cohort of Egyptians.\u003c/p\u003e "},{"header":"Materials and Methods","content":" \u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003e1.1. Study Population\u003c/h2\u003e \u003cp\u003eOne hundred adult Egyptians with B-NHL were recruited from the Department of Hematology and Medical Oncology at Kasr Al-Ainy Hospital, Cairo University, and 100 volunteers with similar ages and sexes from The Checkup Clinic served as the control group in this study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e1.2. Sample collection and DNA extraction\u003c/h2\u003e \u003cp\u003eThree ml venous blood were withdrawn from all subjects and collected in EDTA tubes and kept frozen at -20˚C till time of DNA extraction. Genomic DNA was isolated using GeneJET Whole Blood Genomic DNA Purification Mini Kit (Cat No: #K0781, Life Technologies Inc., 5781 Van Allen Way, Carlsbad, California) applied by Thermo Fisher according to the manufacturer\u0026rsquo;s instructions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e1.3. Genotyping of PDL1 rs4143815 (C/G) and rs2890658 (A/C)\u003c/h2\u003e \u003cp\u003e PD-L1 allelic discrimination was assessed using Sequence-specific primers and Custom allele-specific TaqMan\u0026reg; SNP Genotyping Assays provided from Applied biosystems then consequent analysis was performed on DNA-Technology StepOne \u0026trade; Real-Time PCR system. Also, each allele-specific TaqMan probe has a reporter dye at its 5\u0026acute;end (FAM dye is linked to the 5\u0026acute;end of the Allele 1 probe, and VIC dye is linked to the 5\u0026acute; end of the Allele 2 probe), which allows the allele-specific fixation of each probe.\u003c/p\u003e \u003cp\u003eThe context sequence for rs4143815 of PDL1 was:\u003c/p\u003e \u003cp\u003eTTGCCTCCACTCAATGCCTCAATTT\u003cb\u003e[C/G]\u003c/b\u003eTTTTCTGCATGACTGAGAGTCTCAG Variant: G\u0026thinsp;\u0026gt;\u0026thinsp;C, transition substitution, while the context sequence for PDL1 rs2890658 was:\u003c/p\u003e \u003cp\u003eCAAGAGGAAGTGAAATAATCAAGGC\u003cb\u003e[A/C]\u003c/b\u003eGCCATTTAATAGTGAGCAGCCACTC Variant: C\u0026thinsp;\u0026lt;\u0026thinsp;A, transition substitution.\u003c/p\u003e \u003cp\u003eAmplification of DNA was done in a real-time thermocycler. After PCR amplification, an endpoint plate read was performed using an DNA-Technology Real-Time PCR System, The DTMaster Software uses the fluorescence signal measurements which were made during the plate reading to plot fluorescence values based on the signals from each well.\u003c/p\u003e \u003cp\u003e \u003cb\u003eStatistical Analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eWith the help of the statistical program SPSS version 22, data were coded and examined. Analysis of variance (ANOVA) with multiple comparisons post hoc testing was used to compare the groups. An analysis using the Chi square (2) test was done to compare categorical data. It was determined the odds ratio (OR) and its 95% confidence interval. Statistics were considered significant for P-values under 0.05. The Fisher exact test, the Pearson chi-square test, or the Kruskal-Wallis test were all used to analyze univariate association. The Kaplan-Meier method was used to produce the survival curves, and the log-rank test was used to compare them.\u003c/p\u003e "},{"header":"Results","content":"\u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Demographic profile\u003c/h2\u003e \u003cp\u003eThey were 54 males and 46 females with a mean age of 52.7 years for the patients and 52 male and 48 female (with a mean age of 52.5 years for the controls. Clinicopathological data of B-NHL patients at diagnosis are presented in \u003cem\u003eTable\u0026nbsp;1\u003c/em\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Association between PDL-1 polymorphisms and risk of NHL\u003c/h2\u003e \u003cp\u003eGenotype distribution of \u003cb\u003ePD-L1 rs4143815\u003c/b\u003e GG, GC, and CC genotypes were 62%, 33%, and 5% among B-NHL patients, compared to 58%, 36%, and 6% in the control group, respectively (p\u0026thinsp;=\u0026thinsp;0.837). Furthermore, the frequency of G and C alleles was 78.5%, 21.5% among patients compared to 76%, 24% in the controls, respectively with no statistical significance (p\u0026thinsp;=\u0026thinsp;0.551). \u003cb\u003eIn PD-L1 rs2890658\u003c/b\u003e polymorphism, the distribution of CC, AC and AA genotypes were 80%, 18% and 2% among B-NHL patients, compared to 77%, 22% and 1% in the control group, respectively. Furthermore, the frequency of C and A alleles was 89% and 11% among patient group compared to 88% and 12% in the control group respectively with no statistical significance (p\u0026thinsp;=\u0026thinsp;0.787). As a net result, data revealed from analysis of genotype distribution and allele frequencies of PDL-1 rs4143815 (C\u0026thinsp;\u0026lt;\u0026thinsp;G) and rs2890658 (A\u0026thinsp;\u0026gt;\u0026thinsp;C) SNPs, did not show any association with the susceptibility of B-NHL (table 2).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Association between PD-L1 Genotyping and clinicopathological features.\u003c/h2\u003e \u003cp\u003eStatistical comparison between two studied groups of B-NHL regarding allele frequency of PD-L1 rs4143815 revealed that presence of mediastinal lymphadenopathy, hepatomegaly, extra-nodal involvement\u0026thinsp;\u0026ge;\u0026thinsp;2 sites and bone marrow infiltration were more prominent in those harboring the G allele and results showed statistical significance (P\u0026thinsp;=\u0026thinsp;0.001, p\u0026thinsp;=\u0026thinsp;0.009, p\u0026thinsp;=\u0026thinsp;0.013, \u0026lt;\u0026thinsp;0.001), respectively. On multivariate analysis, hepatomegaly retains statistical significance (OR\u0026thinsp;=\u0026thinsp;2.426, P value\u0026thinsp;=\u0026thinsp;0.035).\u003c/p\u003e \u003cp\u003eConcerning PD-L1 rs2890658 analysis, the presence of nodal involvement, advanced clinical stage III \u0026amp; IV, presence of anemia, presence of bone marrow infiltration and increased level of LDH were more prominent in those harboring the C allele and results showed statistical significance (P\u0026thinsp;=\u0026thinsp;0.017, p\u0026thinsp;=\u0026thinsp;0.049, p\u0026thinsp;=\u0026thinsp;0.012, p\u0026thinsp;=\u0026thinsp;0.009, 0.002), respectively. By multivariate analysis of the variables, nodal involvement (OR\u0026thinsp;=\u0026thinsp;4.3, P\u0026thinsp;=\u0026thinsp;0.037), BM involvement (OR\u0026thinsp;=\u0026thinsp;6.2, P\u0026thinsp;=\u0026thinsp;0.017) and high LDH (OR\u0026thinsp;=\u0026thinsp;4.0, P\u0026thinsp;=\u0026thinsp;0.004) show statistical significance. Moreover, co-inheritance of the common alleles of both SNPs of PDL1 show very high statistical significance by both univariate and multivariate analysis (OR\u0026thinsp;=\u0026thinsp;14.086, p\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Regarding the potential role of these SNPs as molecular prognostic markers\u003c/h2\u003e \u003cp\u003eThe 12 months, 36 months, and 60 months DFS rates were estimated and PDL1 rs4143815 \u0026amp; rs2890658 genetic variants were assessed for their impact on patients\u0026rsquo; DFS. The 36 months DFS` rate for the combined genotype (GC \u0026amp; CC) of PD-L1 rs4143815 (C\u0026thinsp;\u0026gt;\u0026thinsp;G) was 63.8% versus 67% for the common genotype (GG), while the 60 months DFS rate for the combined genotype (GC \u0026amp; CC) was 63.8% versus 44.6% for the common genotype (GG) with no statistically significant difference (p\u0026thinsp;=\u0026thinsp;0.249). While the 36 months` DFS rate for the combined genotype (AA \u0026amp; AC) of rs2890658 (A\u0026thinsp;\u0026gt;\u0026thinsp;C) was 83.3% versus 61.5% for the common genotype (CC), and the 60 months DFS rate for the combined genotype (AA \u0026amp; AC) was 83.3% versus 46.1% for the common genotype (CC), which was statistically insignificant \u003cem\u003e(p\u0026thinsp;=\u0026thinsp;0.599)\u003c/em\u003e, therefore PDL1 rs4143815 \u0026amp; rs2890658 polymorphism have no impact on patients\u0026rsquo; DFS.\u003c/p\u003e \u003cp\u003eBy univariate analysis between clinicopathological factors and DFS; patients with B symptoms, PS\u0026thinsp;\u0026ge;\u0026thinsp;2, advanced An Arbor stage, presence of anemia and high TLC count were found to have a statistically significant relation with poorer DFS (p\u0026thinsp;=\u0026thinsp;0.016, p\u0026thinsp;=\u0026thinsp;0.039, p\u0026thinsp;=\u0026thinsp;0.023, p\u0026thinsp;=\u0026thinsp;0.038, p\u0026thinsp;=\u0026thinsp;0.019), respectively. It was found that An Arbor stage (HR\u0026thinsp;=\u0026thinsp;7.53, P\u0026thinsp;=\u0026thinsp;0.053) is independent predictor of DFS by multivariate analysis. Other potential prognostic factors, such as the patients\u0026rsquo; age at diagnosis, sex, International Prognostic Index score, extra-nodal involvement, and LDH level did not affect the DFS of our B-NHL patients.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":" \u003cp\u003eSeveral SNPs in PD-L1 genes are heavily studied for their contribution to the susceptibility of cancer occurrence, tumor growth, behavior, and response to therapy \u003cb\u003e(\u003c/b\u003eLee et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) however, the relationship between the PDL-1 genetic variations and B-NHL remains ambiguous \u003cb\u003e(\u003c/b\u003eHoseini et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSo far, this is considered the first study to address the association between PD-L1 SNPs (rs4143815 and rs2890658) and the susceptibility of NHL in Egypt.\u003c/p\u003e \u003cp\u003eResults of PD-L1 rs4143815 demonstrated similar genotype distribution between both patient and control groups with no statistical significance revealed (p\u0026thinsp;=\u0026thinsp;0.551). These results were in agreement with recent study in 2020, that revealed no significant association between PD-L1 rs4143815 and the risk of NHL incidence \u003cb\u003e(\u003c/b\u003eHoseini et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), also in agreement with \u003cb\u003eDu (2017)\u0026rsquo;\u003c/b\u003e study that revealed no significant association between PD-L1 rs4143815 polymorphism and occurrence of Lung cancer \u003cb\u003e(\u003c/b\u003eDu et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDiscordant results from a meta-analysis by \u003cb\u003eZou (2018)\u003c/b\u003e in Asian population revealed that rs4143815 (C\u0026thinsp;\u0026gt;\u0026thinsp;G) is associated with increased cancer susceptibilities, including gastric, bladder cancer and HCC, indicating that this SNP might be used as a genetic biomarker tool to predict the cancer susceptibility. Moreover, GG genotype in rs4143185 (C\u0026thinsp;\u0026gt;\u0026thinsp;G) SNP was found to be related to increased risk of HCC in another study (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) \u003cb\u003e(\u003c/b\u003eXie et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eHashemi and colleagues\u003c/b\u003e, revealed that PDL-1 rs4143815 polymorphism is associated with decreased overall risk of tumour occurrence giving it a protective value against cancer, while no significant association found between rs2890658 SNP and the overall risk of cancer in parallel to our results \u003cb\u003e(\u003c/b\u003eHashemi et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMoreover, the pooled analysis from \u003cb\u003eZou (2019)\u003c/b\u003e study did not support an association between PD-L1 rs2890658 polymorphism and the cancer susceptibilities.\u003c/p\u003e \u003cp\u003eIn the other side, data reported by \u003cb\u003eHoseini (2020)\u003c/b\u003e demonstrated significant association of PD-L1 rs2890685 (A\u0026thinsp;\u0026gt;\u0026thinsp;C) SNP with increased risk of NHL (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), where rs2890685 AA genotype distribution was significantly prevalent in patients with NHL in comparison to controls, although these results conflict with our observation.\u003c/p\u003e \u003cp\u003eMoreover, \u003cb\u003eZhou (2016)\u003c/b\u003e reported that PD-L1 rs2890658 SNP is associated with increased risk of oesophageal carcinoma in group of smokers.\u003c/p\u003e \u003cp\u003eSince prognostic markers are important clinical tools used in assessing the newly diagnosed patient to help predict the patient\u0026rsquo;s clinical outlook. For B-NHL patients, many prognostic markers such as age\u0026thinsp;\u0026lt;\u0026thinsp;60 years, advanced clinical stage (III\u0026amp;VI), performance status\u0026thinsp;\u0026le;\u0026thinsp;2 on ECOG scale, high LDH level, extra-nodal sites\u0026thinsp;\u0026gt;\u0026thinsp;1, presence of BM involvement, anemia and B symptoms have been used to predict future clinical outcome of patients. Here, we studied the relationship between the allele frequencies of the PD-L1 polymorphisms and adverse clinicopathological factors of the patients which revealed some positive results.\u003c/p\u003e \u003cp\u003eOur findings revealed, the presence of mediastinal nodal involvement, hepatomegaly, extra-nodal involvement and BM infiltration were more prominent in patients with G allele of rs4143815 and results showed a statistical significance (P\u0026thinsp;=\u0026thinsp;0.001, p\u0026thinsp;=\u0026thinsp;0.009, p\u0026thinsp;=\u0026thinsp;0.013, \u0026lt;\u0026thinsp;0.001), respectively. These findings are consistent with \u003cb\u003eWu (2006)\u0026rsquo;\u003c/b\u003e study which found significant relation between rs4143815 SNP and clinicopathological features of gastric cancer including tumour size, differentiation grade, depth of tumour infiltration, lymph node metastasis, and TNM stage, and considered this variant might be a potential risk factor for cancer predisposition.\u003c/p\u003e \u003cp\u003eAnother study done by \u003cb\u003eDu et al.\u003c/b\u003e, was in agreement with our findings, which reported that rs4143815 SNP had significant associations with clinicopathological features, including depth of tumor infiltration, distant metastasis, lymph node metastasis and TNM stage in lung cancer; therefore, it might be possible future prognostic tool \u003cb\u003e(\u003c/b\u003eDu et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eSo, we can conclude\u003c/b\u003e that our results provided the first evidence that PD-L1 rs4143815 and rs2890658 genetic variants are not considered genetic predisposing factors in susceptibility to B-NHL in a cohort of Egyptian population, at least in the studied population. Although the polymorphism at PD-L1 gene has no impact on patients\u0026rsquo; survival; rather, there was a significant association between the major alleles of PD-L1 rs4143815 and rs2890658 SNPs and the adverse clinico-pathological features of B-NHL patients. Therefore, these polymorphic sites could be candidates for predicting the adverse clinicopathological features of B-NHL and might be valuable for prognostic values in Egyptian population. Although, validation by a larger prospective study from diverse ethnic population is warranted to confirm our findings.\u003c/p\u003e \u003cp\u003e \u003cb\u003eStudy Limitations\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe relatively small sample size of this study is a limitation of the present work. Larger sample size is recommended to validate our results regarding the role of the studied SNPs as molecular risk factors for B-NHL and to clarify their impact on therapeutic response and disease course. Furthermore, serum PD-L1 level should have been examined to conclude the association between the examined variations and B-NHL.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by [Marwa T Hassan], [Heba M Gouda] and [Manal W El-Masry]. The first draft of the manuscript was written by [Marwa T Hassan] and all authors commented on previous versions of the manuscript.\u0026nbsp;All\u0026nbsp;authors read and approved the final manuscript.\u0026rdquo;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThis study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Cairo University, faculty of medicine.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eInformed consent was obtained from all individual participants included in the study.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors affirm that human research participants provided informed consent for publication of the images in Figure(s) 1a, 1b and 1c.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eDe Visser KE, Eichten A, and Coussens LM (2006): Paradoxical roles of the immune system during cancer development. Nature Reviews Cancer, 6(1): 24\u0026ndash;37. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/nrc1782\u003c/span\u003e\u003cspan address=\"10.1038/nrc1782\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDu W, Zhu J, Chen Y, et al. (2017): Variant SNPs at the microRNA complementary site in the B7H1 3'untranslated region increase the risk of non-small cell lung cancer. Mol Med Rep, 16(3):2682\u0026ndash;90. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3892/mmr.2017.6902\u003c/span\u003e\u003cspan address=\"10.3892/mmr.2017.6902\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2017 Jun 30. PMID: 28677815; PMCID: PMC5547930.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHashemi M, Karami S, Sarabandi S, et al. (2019): Association between PD-1 and PD-L1 Polymorphisms and the Risk of Cancer: A Meta-Analysis of Case-Control Studies. Cancers (Basel), 11(8):1150. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/cancers11081150\u003c/span\u003e\u003cspan address=\"10.3390/cancers11081150\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHoseini H, Yaghmaei P, Bahari G, and Aminzadeh S. (2020): Correlations of PD-1/PD-L1 Gene Polymorphisms with Susceptibility and Prognosis in Non-Hodgkin Lymphoma in Iranian Population. IRANIAN RED CRESCENT MEDICAL JOURNAL (IRCMJ), 22(11), 0\u0026ndash;0. SID. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://sid.ir/paper/976152/en\u003c/span\u003e\u003cspan address=\"https://sid.ir/paper/976152/en\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim R, Emi M and Tanabe K, (2007): Cancer immunoediting from immune surveillance to immune escape. Immunology, 121 (1): 1\u0026ndash;14. https://doi.org/10.1111/j. 1365-2567.2007.02587.x.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKula A, Dawidowicz M, Kiczmer P, Prawdzic Seńkowska A and Świętochowska E (2020): The role of genetic polymorphism within PD-L1 gene in cancer. Review. Experimental and Molecular Pathology, 104\u0026ndash;494. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.yexmp.2020.104494\u003c/span\u003e\u003cspan address=\"10.1016/j.yexmp.2020.104494\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee SY, Jung DK, Choi JE, et al. (2017): Functional polymorphisms in PD-L1 gene are associated with the prognosis of patients with early-stage non-small cell lung cancer. Gene, 599, 28\u0026ndash;35. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.gene.2016.11.007\u003c/span\u003e\u003cspan address=\"10.1016/j.gene.2016.11.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eParry RV, Chemnitz JM, Frauwirth KA, et al (2005): CTLA-4 and PD-1 receptors inhibit T-cell activation by distinct mechanisms. Mol Cell Biol, 25 (21): 9543\u0026ndash;53. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1128/mcb.25.21.9543-9553.2005\u003c/span\u003e\u003cspan address=\"10.1128/mcb.25.21.9543-9553.2005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSalmaninejad A, Valilou SF, Shabgah AG et al., (2019): PD-1/PD-L1 pathway: Basic biology and role in cancer immunotherapy. J Cell Physiol, 234(10):16824\u0026ndash;37. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/jcp.28358\u003c/span\u003e\u003cspan address=\"10.1002/jcp.28358\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2019 Feb 19. PMID: 30784085.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWherry EJ and Kurachi M. (2015): Molecular and cellular insights into T cell exhaustion. Nat Rev Immunol, 15(8):486\u0026ndash;99.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu C, Zhu Y, Jiang J, et al. (2006): Immunohistochemical localization of programmed death-1 ligand-1 (PD-L1) in gastric carcinoma and its clinical significance. Acta Histochemica, 108(1): 19\u0026ndash;24. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.acthis.2006.01.003\u003c/span\u003e\u003cspan address=\"10.1016/j.acthis.2006.01.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu D, Guo M, Min X, et al. (2018): LY2874455 potently inhibits FGFR gatekeeper mutant and overcomes mutation-based resistance. Chem Commun (Camb), 54(85):12089\u0026ndash;92. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1039/c8cc07546h\u003c/span\u003e\u003cspan address=\"10.1039/c8cc07546h\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXie Q, Chen Z, Xia L, et al. (2018): Correlations of PD-L1 gene polymorphisms with susceptibility and prognosis in hepatocellular carcinoma in a Chinese Han population. Gene, 674, 188\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZak KM, Grudnik P, Magiera K, et al. (2017): Structural Biology of the Immune Checkpoint Receptor PD-1 and Its Ligands PD-L1/PD-L2. Structure, 25(8):1163-74. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.str.2017.06.011\u003c/span\u003e\u003cspan address=\"10.1016/j.str.2017.06.011\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 28768162.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou RM, Li Y, Wang N, et al., (2016): Association of programmed death-1 polymorphisms with the risk and prognosis of esophageal squamous cell carcinoma. Cancer Genet, 209, 365\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou RM, Li Y, Liu JH, et al. (2017): Programmed death-1 ligand-1 gene rs2890658 polymorphism associated with the risk of esophageal squamous cell carcinoma in smokers. Cancer Biomark, 21(1):65\u0026ndash;71. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3233/CBM-170269\u003c/span\u003e\u003cspan address=\"10.3233/CBM-170269\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 29060926.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZou W, Wolchok JD and Chen L, (2016): PD-L1 (B7-H1) and PD-1 pathway blockade for cancer therapy: Mechanisms, response biomarkers, and combinations. Sci Transl Med, 8(328):328rv4. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1126/scitranslmed.aad7118\u003c/span\u003e\u003cspan address=\"10.1126/scitranslmed.aad7118\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 26936508; PMCID: PMC4859220.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZou J, Wu D, Li T, et al. (2019): Association of PD-L1 gene rs4143815 C\u0026thinsp;\u0026gt;\u0026thinsp;G polymorphism and human cancer susceptibility: A systematic review and meta-analysis. Pathol Res Pract, 215(2):229\u0026ndash;34. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.prp.2018.12.002\u003c/span\u003e\u003cspan address=\"10.1016/j.prp.2018.12.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStatements \u0026amp; Declarations\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable (1): Clinicopathological data of B-cell non-Hodgkin lymphoma patients at presentation\u003c/strong\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003ctable id=\"Taba\" border=\"1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eItem Patient group (n\u0026thinsp;=\u0026thinsp;100)\u003c/div\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eNumber (%)\u003c/div\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eSex(male/female)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e(54/46)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eAge (years)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026le;\u0026thinsp;60\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e77 (77%)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;60\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e23 (23%)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eB- symptoms\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003eFever, night sweats, weight loss\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e55 (55%)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eLymphadenopathy\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e91 (91%)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eExtra-nodal involvement\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026lt;\u0026thinsp;2\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e\u0026ge;\u0026thinsp;2\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e81(81%)\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e19 (19%)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eBulky disease\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e29 (29%)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eSplenomegaly\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e58 (58%)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eHepatomegaly\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e43 (43%)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eBone marrow infiltration\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e34 (34%)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eHCV positivity\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e25(25%)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eClinical stage\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003eEarly (I\u0026amp;II)\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003eLate (III\u0026amp;IV)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e24 (24%)\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e76 (76%)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eP.S\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003eScore\u0026thinsp;\u0026lt;\u0026thinsp;2\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003eScore\u0026thinsp;\u0026ge;\u0026thinsp;2\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e70 (70%)\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e30 (30%)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eIPI risk group\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003eLow \u0026amp; Low-intermediate\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003eHigh \u0026amp; High-intermediate\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e62 (62%)\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e38 (38%)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eIPI risk groups for DLBC subtype (n\u0026thinsp;=\u0026thinsp;84)\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003eLow/ Intermediate low\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003eIntermediate high/ High\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e57 (67.8%)\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e27(32.1%)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eHistological subtypes (High grade Lymphoma)\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003eDLBCL\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003eTHRLBCL\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e84 (84%)\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e16 (16%)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eP.S:\u0026nbsp;\u003c/strong\u003ePerformance status, \u003cstrong\u003eHCV:\u0026nbsp;\u003c/strong\u003eHepatitis C virus\u003cstrong\u003e, DLBCL:\u0026nbsp;\u003c/strong\u003eDiffuse large b cell lymphoma, \u003cstrong\u003eIPI:\u0026nbsp;\u003c/strong\u003eInternational prognostic index, \u003cstrong\u003eTHRLBCL:\u003c/strong\u003e T-cell/histiocyte-rich B-cell lymphoma\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u003cstrong\u003eTable (2): Genotype distribution and allele frequencies of PD-L1 rs4143815 and rs2890658 in B-NHL patients and control groups.\u003c/strong\u003e\u003c/div\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tabb\" border=\"1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth colspan=\"2\" rowspan=\"3\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eGenotype\u003c/div\u003e\n \u003c/th\u003e\n \u003cth colspan=\"3\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eGroup\u003c/div\u003e\n \u003c/th\u003e\n \u003cth colspan=\"2\" rowspan=\"3\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eP-value\u003c/div\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003ePatients (n\u0026thinsp;=\u0026thinsp;100)\u003c/div\u003e\n \u003c/th\u003e\n \u003cth colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eControls (n\u0026thinsp;=\u0026thinsp;100)\u003c/div\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eNo(%)\u003c/div\u003e\n \u003c/th\u003e\n \u003cth colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eNo(%)\u003c/div\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003ePD-L1 rs4143815 (C\u0026thinsp;\u0026gt;\u0026thinsp;G)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eGG\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e62 (62%)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e58 (58%)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.837\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eCG\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e33 (33%)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e36 (36%)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eCC\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e5 (5%)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e6 (6%)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eG allele\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003eC allele\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e157/200 (78.5%)\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e43/200 (21.5%)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e152 /200 (76%)\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e48/200 (24%)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.551\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eGG \u003cspan class=\"Italic\"\u003evs\u003c/span\u003e GC\u0026thinsp;+\u0026thinsp;CC\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e62 (62%) \u003cspan class=\"Italic\"\u003evs\u003c/span\u003e 38 (38%)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e58 (58%) vs 42 (42%)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.564\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eCC \u003cspan class=\"Italic\"\u003evs\u003c/span\u003e GG\u0026thinsp;+\u0026thinsp;GC\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e5 (5%) \u003cspan class=\"Italic\"\u003evs\u003c/span\u003e 95 (95%)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e6 (6%) \u003cspan class=\"Italic\"\u003evs\u003c/span\u003e 94 (94%)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.756\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003ePD-L1 rs2890658 (A\u0026thinsp;\u0026lt;\u0026thinsp;C)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eCC\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e80 (80%)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e77 (77%)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e*\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eAC\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e18 (18%)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e22 (22%)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eAA\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e2 (2%)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e1 (1%)\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eC allele\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003eA allele\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e178/200 (89%)\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e22/200 (11%)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e176/200 (88%)\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003e24/200 (12%)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.787\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eCC \u003cspan class=\"Italic\"\u003evs\u003c/span\u003e\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003eAC/AA\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e80(80%) \u003cspan class=\"Italic\"\u003evs\u003c/span\u003e 20(20%)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e77 (77%) \u003cspan class=\"Italic\"\u003evs\u003c/span\u003e 23(23%)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e0.606\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003eAA \u003cspan class=\"Italic\"\u003evs\u003c/span\u003e\u003c/div\u003e\n \u003cdiv class=\"SimplePara\"\u003eAC/CC\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e2(2%) \u003cspan class=\"Italic\"\u003evs\u003c/span\u003e 98 (98%)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e1(1%) \u003cspan class=\"Italic\"\u003evs\u003c/span\u003e 99(99%)\u003c/div\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" align=\"left\"\u003e\n \u003cdiv class=\"SimplePara\"\u003e*\u003c/div\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eP value\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/strong\u003e: Is significant, \u003cstrong\u003ePD-L1\u003c/strong\u003e: Programmed death ligand-1, *: p value cannot be calculated because of small number within strata.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"B-NHL- PDL1- rs4143815- rs2890658- SNP- Real-Time PCR","lastPublishedDoi":"10.21203/rs.3.rs-3838300/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3838300/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose: \u003c/strong\u003eTo investigate the possible relation between polymorphisms of PD-L1 rs4143815 and rs2890658 with the susceptibility and prognosis of B-NHL in a Cohort of Egyptians, we conducted a case-control study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eGenotyping was done using real-time polymerase chain reaction (real-time PCR) for 100 adult B-NHL patients and 100 healthy adults (controls).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003eOur results did not show any significant association between PD-L1 (rs4143815, rs2890658) SNPs and risk of B-NHL occurrence. However, the relationship between allele distribution of rs4143815 (C\u0026gt;G) and rs2890658 (A\u0026gt;C) and adverse clinico-pathological features of B-NHL patients revealed positive results.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eOur results provided the first evidence that PD-L1 rs4143815 (C\u0026gt;G) and rs2890658 (A\u0026gt;C) are not molecular susceptibility markers for B-NHL in Egyptians, at least in the studied population. However, these polymorphic sites could be candidates for predicting some adverse clinico-pathological features and might have a potential prognostic role in B-NHL.\u003c/p\u003e","manuscriptTitle":"Association of Gene Polymorphisms in Programmed Death Ligand-1 (PD-L1) with susceptibility and prognosis of B-Cell Non-Hodgkin Lymphoma in a Cohort of Egyptians","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-09 08:14:59","doi":"10.21203/rs.3.rs-3838300/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a7cef90a-be1d-4fd3-8341-c5e98b209a2a","owner":[],"postedDate":"January 9th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-01-09T08:15:01+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-09 08:14:59","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3838300","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3838300","identity":"rs-3838300","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}