Tertiary lymphoid structure was a predictor of favorable prognosis in muscle-invasive bladder cancer

Tertiary lymphoid structure was a predictor of favorable prognosis in muscle-invasive bladder cancer | 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 Tertiary lymphoid structure was a predictor of favorable prognosis in muscle-invasive bladder cancer Xiaodong Teng, Zhen Chen, Yanfeng Bai, Hui Cao, Jing Zhang, Liming Xu, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4011123/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Tertiary lymphoid structure (TLS) has been reported to be associated with prognosis and immunotherapy in certain cancers. In this study, we aimed to explore the prognostic role of TLS in Muscle-invasive bladder cancer (MIBC), and to analyze the clinicopathological and molecular factors affecting the formation of TLS. Methods: Immunohistochemistry was used to detect the expression of TLS, CD8+ T cells, B cells, and plasma cells in 119 MIBC cases, of which 80 cases were tested by next generation sequencing (NGS) for analysising the differences in gene alterations between TLS-negative and TLS-positive. Results: TLSs were present in 52.1% of MIBC cases. Patients with TLS had lower T and TNM stages, and had longer overall survival (OS) than patients without TLS. Multivariate analysis showed that TLS was an independent prognostic factor. The densities of B cells, CD8+ T cells, and plasma cells in tumors were significantly correlated with TLS, but in the cases with low density B cells, high density CD8+ T cells or high density plasma cells, differences in OS between the tumors with TLS and without TLS were not significant. Compared with TLS-negative tumors, TLS-positive tumors had lower frequency of TP53 mutations and higher frequencies of FAT1 , CDKN1A mutations. Tumor mutational burden (TMB)was not significantly different between the two groups, but was significantly associated with TLS in TP53 wild-type tumors. Conclusions: TLS was an independent predictor of favorableprognosis in MIBC, and mainly played antitumor role effect through B cells. TP53 mutations could inhibit the formation of TLS. Urinary Bladder Neoplasms Tertiary Lymphoid Structures Tumor Microenvironment TP53 Genes Figures Figure 1 Figure 2 Figure 3 Figure 4 Background Bladder cancer was a major cause of morbidity and mortality worldwide, with 82000 new cases and 34000 deaths reported each year in China [ 1 ]. Muscle-invasive bladder cancer (MIBC), accounted for about 25% of all bladder cancers, usually had a high degree of malignancy and was prone to recurrence and metastasis, the 5-year survival rate of patients was still low after radical bladder cancer resection [ 2 ]. Finding new prognostic predictors and therapeutic targets plays an important role in the treatment of MIBC. Recently Tertiary lymphoid structure (TLS), characterized by ectopic aggregated lymphocytes with high endothelial venules [ 3 ], had gained attention due to their associations with prognosis and immunotherapy in certain cancers [ 4 – 7 ]. TLS was also present in bladder cancer, and was associated with better patient outcomes, more frequent in MIBC relative to non-muscle-invasive bladder cancer [ 8 , 9 ]. However, the clinicopathological and molecular factors of TLS, which may affect the formation of TLS, were not clearly understood in MIBC. To address this question, we reviewed and analyzed tissue samples from 119 cases of MIBC surgical resection. Methods Patients A total of 119 cases of MIBC received radical cystectomy from the First Affiliated Hospital, Zhejiang University School of Medicine were enrolled from 2016 to 2018, all cases were re-evaluated by two experienced pathologists (Y.B and X.T) and were treatment naïve. Twenty representative unstained formalin fifixed paraffifin embedded (FFPE) sections with 4µm thickness from a representative block of each tumour were selected for further immunohistochemistry and next-generation sequencing (NGS) analysis. Tumor clinical and pathological staging system was based on the Eighth Edition of the Union for International Cancer Control/American Joint Committee on Cancer. Patient survival data were available until the end of December 2019. The present study was approved by the Ethics Committee of the First Affiliated Hospital, Zhejiang University School of Medicine, and complied with the Declaration of Helsinki. TLS evaluation All cases were reviewed blindly by two pathologists (Y.B and X.T) to determine the presence and state of maturity of TLS according to immunohistochemical stainings (CD3-CD20). For the rare discordant cases, the final TLS status of the samples was agreed on consensus with a board gathering of team members. TLS was defined as lymphoid aggregates of more than 50 B lymphocytes and T lymphocytes, as previously described [ 10 ]. Mature TLS (mTLS) was defined as TLS with a obvious germinal center according on hematoxylin eosin saffron (HE) slices. TLS density was defined as the number of TLS divided by the tumor area, which achieved on a slice scanning system (Konfoong biotech, Ningbo, China ). TLS-high was defined as TLS-positive and had a density higher than or equal to the median of the TLS-positive group. TLS-low was defined as TLS-positive and had a density lower than the median of the TLS-positive group. Immunohistochemistry stainings The double CD3-CD20 immunohistochemistry staining was performed with the primary antibodies CD3 and CD20 (all antibody information can be found in Table S1 ). The staining procedure was performed with a Bond-III Automated IHC Staining System (Leica, Germany) following the manufacturer’s recommendations. CD8 and CD138 stainings were performed with a Bond-III Automated IHC Staining System using the Bond Polymer Refine detection kits (Leica, Germany) according to the manufacturer’s recommendations. The slides were scanned using the PANNORAMIC 250 Flash III DX system (3DHISTECH, Hungary). CD8 + T cell densities were evaluated by pathologists (Y.B) using a QuanCenter automated analysis system (3DHISTECH, Hungary). Plasma cell counts were enumerated in 5 immune cell-positive hot 20× fields on CD138-stained sections. B cell counts were enumerated in 10 immune cell-positive hot 20× fields on CD3-CD20-stained sections (only the lymphocytes stained with CD20 were scored). The grouping of B cell densities, CD8 + T cell densities and plasma cell densities were divided by the respective median of cell numbers as the cut-off values. PD-L1 staining was performed using the Ventana Medical Systems(Tucson, AZ, USA) according to the manufacturer’s recommendations. The evaluation rules for each score in PD-L1 expression (tumor proportion score, TPS; immune cell proportion score, IPS; combined positive score, CPS) according to the report by Shitara [ 11 ]. Each countable array core section contained at least 100 viable tumor cells. PD-L1 scores ≥ 25% were considered positive. Next-generation sequencing A total of 80 samples achieved NGS detection. Genomic DNA was extracted from FFPE samples with the QIAamp DNA FFPE Tissue Kit (Qiagen, Germany). FFPE DNA quality was evaluated by 1% agarose gel electrophoresis, and any FFPE DNA that was severely degraded was removed. DNA quantification was conducted with a Qubit 3.0 fluorometer and a Qubit dsDNA HS assay kit (Life Technologies, USA). An hybrid-based targeted NGS assay was used for library preparation with an GeneseeqPrime™ Kit (covering 425 common cancer-associated genes, Table S2 )(Geneseeq, Nanjing, China). Experiments were performed according to the kit instructions. Twenty nanograms of DNA was used for library preparation as recommended by the kit instructions. The library product was sequenced using 75-bp paired-end runs on the Illumina Nextseq550 after quantification using a KAPA Library Quantification Kit (Kapa, KK4824). Sequencing data were processed by the manufacturer’s supplied bioinformatics software, tumor mutational burden (TMB) and microsatellite instability (MSI) were also included in the result analysis. Statistical analysis Overall survival (OS) was defined as the time from the date of diagnosis to the date of death or last visit. The Kaplan-Meier method with a log-rank test and Cox regression analysis were used for survival analyses. The correlation of different groups with clinicopathological characteristics was studied via chi-square test or Fisher’s test. Mann-Whitney test was used for nonparametric tests. All tests were two-sided and P < 0.05 was considered to indicate a statistically significant. Chi square test, non-parametric test and survival analysis were performed using IBM SPSS 28.0 software (Chicago, USA). The differences in gene mutations between TLS-positive and TLS-negative cases were analyzed using R packages “maftools” and “complexheatmap” (R version 4.2.2). Results TLS was a predictor of good prognosis in MIBC TLS was detected in 52.1% (62/119) of MIBC cases, mostly at the edge of the tumor (Figure 1A-C), only 6 cases were present mTLS. TLS did not differ with gender, age, N-stage, vascular invasion, nerve invasion or PD-L1 expression, but was higher in cases with lower T-stage and TNM stage (Table 1). Table 1. Associations between TLS and investigative factors. Factor TLS-negative TLS-positive P value Gender Female 5 11 Male 52 51 0.152 Age < 70y 23 34 ≥ 70y 34 28 0.114 Tummor size < 3.8cm 27 35 ≥ 3.8cm 30 27 0.322 PD-L1(TPS) Negative 44 45 Positive 13 17 0.563 PD-L1(IPS) Negative 51 48 Positive 6 14 0.079 PD-L1(CPS) Negative 40 39 Positive 17 23 0.402 TNM-stage II 7 21 III 48 39 IV 2 2 0.018 T-stage 2 9 24 3 34 30 4 14 8 0.014 N-stage 0 43 48 1 5 5 2 9 9 0.968 Vascular invasion Without 33 41 With 24 21 0.355 Nerve invasion Without 42 52 With 15 10 0.173 Log-rank tests showed that TLS status, age of patients at diagnosis, CD8+ T cell density, and nerve invasion significantly affect the OS of patients with MIBC (Table 2, Table S3). Patients in the TLS-positive group had a longer OS than those in the TLS-negative group (Figure 1D). Patients with TLS-high had a longer OS than those with TLS-low, but the difference did not reach statistical significance (Figure 1E). We aslo evaluated the relationship between various clinicopathological characteristics combined with TLS status and OS. Cox regression analysis showed that TLS status (HR 1.701, P < 0.05) and age of patients at diagnosis (HR 0.556, P < 0.05) were independent factors affecting OS (Table 2). Table 2. Univariate and multivariate analysis of over all survival in MIBC. Univariate Multivariate Variables P value HR(95% CI) P value TLS (negative vs positive) 0.001 1.701 (1.018-2.842) 0.043 Age (<70y vs ≥70y) 0.001 0.556 (0.341-0.9070 0.019 CD8+ cell desity (low vs high) 0.029 1.214 (0.744-1.982) 0.438 Nerve invasion (without vs with) 0.009 0.641 (0.379-1.087) 0.099 TLS was associated with more tumor-infiltrating lymphocytes In order to understand the mechanism by which TLS exerted its anti-tumor effect, we compared the relationship between TLS and various tumor-infiltrating lymphocytes, and found that densities of CD8+ T cells, B cells, and plasma cells in TLS-positive group were significantly higher than those in TLS-negative group (Figure 2A-C). We also analyzed the association of TLS status with OS in patients with MIBC under different B cell, CD8+ T cell and plasma cell density statuses. The presence of TLS was significantly associated with improved overall survival in the groups with high B cell density (Figure 2D), low CD8+ T cell density (Figure 2G) and low plasma cell density (Figure 2I). However, there no significant differences were observed in the groups with low B cell density (Figure 2E), high CD8+ T cell density (Figure 2F) or high plasma cell density (Figure 2H). These suggested that the anti-tumor effect of TLS was mainly achieved through antigen presentation by B cells, rather than maturation into plasma cells to secrete specific antibodies. Correlation between TLS and molecular characteristics A total of 1006 variants in 282 genes were identified in our cohort (Figure 3A). Among the cases, 56% (45/80) showed high TMB (TMB ≥ 10), and only one case showed MSI, which was TLS-positive. The most frequently mutated genes in MIBC were TP53 (68%) and TERT (66%), followed by ARID1A , PIK3CA , EP300 . We compared the mutation rates of the top 50 genes with different TLS statuses (Figure 3B) and found that the TP53 mutation rate was lower in the TLS-positive group than in the TLS-negative group (53.8% vs. 80.5%, P = 0.011 ), CDKN1A (15.4% vs. 0%, P = 0.011) and FAT1 (20.5% vs. 4.9%, P = 0.045) mutation rates were higher in the TLS-positive group than in the TLS-negative group. We also examined typical cancer-related pathways, no significant differences were found between different TLS statuses but cell cycle pathway (Table S4). TP53 mutations inhibited TLS production by inhibiting the immunogenicity of neoantigens As TP53 mutations were present in significant numbers, we decided to investigate this association further to better understand why TP53 mutations associates with fewer TLSs. In our cohort, TP53 mutations were mainly located in exons 4-8, which are the DNA-binding regions, consistent with previous literature [14] (Figure 4A). We confirmed that patients with TP53 mutations in exons 4-8 had a trend toward fewer TLSs except exon 6, which may be due to the small sample size. The same trends were present but less pronounced when analysis was restricted to disruptive TP53 mutations (Figure 4A), defined as truncating mutations or nonsynonymous alterations affecting the L2 to L3 region, described by Natalie et al [12]. Neoantigens generated by mutations could be presented to effector cells by presenting cells to activate immune responses, and the neoantigen burden is highly related to TMB [13]. As part of tumor immunity, we speculated that TLS could be initiated by high TMB. However, no significantly correlation between TMB and TLS, CD8+T cells, B cells were observed in our cohort (Figure 4B, Figure S1). When we combined TP53 mutation status, TLS and TMB remained uncorrelated in TP53 mutant patients but showed a significant correlation in TP53 wild type patients (Figure 4C-D, Figure S1). These finding suggested that TP53 mutations may inhibit the immunogenicity of the neoantigens. Discussion TLS had shown antitumor effects in a variety of tumors, including colorectal cancer [ 14 ], breast cancer [ 15 ], NSCLC [ 16 ], and other cancers [ 17 ], but it had also been reported that TLS had a tumor-promoting effect in kidney clear cell carcinoma, and the higher the TLS density, the worse the prognosis of patients [ 9 ]. Our results showed that TLS exhibited an antitumor effect in MIBC, which was associated with lower T-stage and was an independent factor of good prognosis. The mechanism by which TLS in anti-tumor process is still unclear, it may involve cellular immunity, as many studies had confirmed that the existence of TLS was related to the number of Th1 and CD8 + T cells [ 10 , 18 ]. In our cohort, although the density of CD8 + T cells was significantly associated with TLS, the good prognostic effect of TLS did not depend on the high density of CD8 + T cells but rather on B cells, suggesting that TLS mainly exerts its antitumor effect through B cells, which consistent with previous literature [ 6 , 19 , 20 ]. B cells could affect tumors in two ways: by differentiating and mature into plasma cells to produce tumor-specific antibodies, or by presenting tumor-associated antigens to T cells to enhance cellular immune effects [ 21 ]. Plasma cells could be generated in mature TLS but are absent or rare in immature TLS [ 19 , 20 ]. In our cohort, there were few mature TLSs, mostly immature TLSs. However, TLS was still significantly associated with plasma cells, suggesting that immature TLS has some mechanism by which plasma cells could be recruited. Similar to CD8 + T cells, the good prognostic effect of TLS did not depend on a high density of plasma cells, suggesting that B cells in TLS may primarily play an antigen-presenting role. The formation of TLS is a complex process and is orchestrated by several lympho-organogenic chemokines in response to inflammatory stimuli [ 22 , 23 ]. However, the relationship between TLS and gene mutations in tumor cells is still unclear. Masuda, T et al [ 9 ] analyzed 43 cases of renal clear cell carcinoma and found that the gene mutation rate of PI3K-mTOR pathway was significantly increased in TLS-positive tumors. Florian Posch et al [ 6 ] found in 109 patients with stage II/III non-metastatic colorectal carcinoma that TLS was more common in BRAF -mutated tissues. Morcrette, G., et al [ 24 ] reported that TLSs were present in all 11 APC germline mutated hepatoblastoma (APC-HB) tumors treated with cisplatin neoadjuvant chemotherapy, whereas TLSs were present in only 6 of 15 tumors without APC mutations. Notably, TLS was absent in pre-chemotherapy specimens, suggesting that APC mutations played a certain role in the formation of TLS. In our corhoet, we performed NGS analysis in 80 cases and found that compared with TLS-negative cases, TLS-positive tumors had lower TP53 mutation rates, higher CDKN1A and FAT1 mutation rates, and lower mutation rates in cell cycle pathway-related genes. This suggested that mutations in TP53 gene and cell cycle pathway-related genes could inhibit the formation of TLS, while CDKN1A and FAT1 mutations may promote the formation of TLS. TP53 mutations are one of the most frequent genetic alterations in human cancer [ 12 , 25 ], and the p53 pathway could regulate many targets transcriptionally and non-transcriptionally [ 26 , 27 ]. TP53 mutations in stromal cells could cause changes in various immune microenvironments, but the impact of TP53 mutations in tumor cells on the immune microenvironment has not been deeply explored. In bladder cancer, the immune assessment models based on TP53 mutations could predict prognosis well [ 28 , 29 ]. TP53 mutations could increase tumor mutation burden (TMB) in various tumors [ 30 , 31 ], and TMB was closely related to neoantigens which could induce immune response [ 13 ]. Therefore, it is inferred that TP53 mutations should promote tumor immunity, included the formation of TLS. However, the fact is that TP53 -mutated tumors often had fewer tumor-infiltrating lymphocytes, lower cytokine activity, and down-regulated inflammatory activity 32–34 . Our results showed that TP53 mutations had a negative role in the formation of TLS and the relationship between TMB and numbers of tumor-infiltrating lymphocytes was not close. However, after we excluded the TP53 mutations, the connection between TMB and TLS, CD8 + T cells were established. This suggested that that TP53 mutations could inhibit the immunogenicity of neoantigens caused by TMB through some mechanism to suppress the immune response. Conclusions We described the clinicopathological and molecular features of TLS in MIBC and found that TLS was a favorable prognostic factor, and its formation could be inhibited by TP53 mutations. However, some limitations remain to be addressed at this stage. We were able to further explore the specific mechanism that affects TLS formation, which would be helpful for understanding of the immune microenvironment in MIBC more comprehensively. Abbreviations FFPE: Formalin Fifixed Paraffifin Embedded MIBC: Muscle-Invasive Bladder Cancer MSI: Microsatellite Instability mTLS: Mature Tertiary Lymphoid Structure NGS: Next Generation Sequencing OS: Overall Survival TLS: Tertiary Lymphoid Structure TMB: Tumor Mutational Burden Declarations Ethics approval and consent to participate The present study was approved by the Ethics Committee of the First Affiliated Hospital, Zhejiang University School of Medicine. Consent for publication Not applicable. Availability of data and material The datasets used and during the current study are available from the corresponding author on reasonable request. Competing interests Kaihua Liu, , Yuqian Shi, Yang Shao are employees of Nanjing Geneseeq Technology Inc., other authors have no competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Funding This study was funded by Zhejiang Provincial Research Center for Cancer Intelligent Diagnosis and Molecular Technology (JBZX-202003) and Zhejiang Provincial Natural Science Foundation of China (No.LQ19H160038). Authors’ contributions XT conceived and designed the study and wrote the manuscript. ZC and YB conducted most experiments, analyzed data. HC and JZ collected the clinical samples and data. LX, KL, YS and YS performed parts of the experiments. All authors have read and agreed to the published version of the manuscript. Acknowledgements We would like to thank Qi Zhang for the help in statistical analysis. References Zheng R, Zhang S, Zeng H, Wang S, Sun K, Chen R, Li L, Wei W, He J: Cancer incidence and mortality in China, 2016 . Journal of the National Cancer Center 2022, 2 (1):1-9. https://doi.org/10.1016/j.jncc.2022.02.002 Lenis AT, Lec PM, Chamie K, Mshs MD: Bladder Cancer: A Review . 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DNA repair 2020, 88 :102785. https://doi.org/10.1016/j.dnarep.2020.102785 Blagih J, Zani F, Chakravarty P, Hennequart M, Pilley S, Hobor S, Hock AK, Walton JB, Morton JP, Gronroos E et al : Cancer-Specific Loss of p53 Leads to a Modulation of Myeloid and T Cell Responses . Cell reports 2020, 30 (2):481-496 e486. https://doi.org/10.1016/j.celrep.2019.12.028 Jiang Z, Liu Z, Li M, Chen C, Wang X: Immunogenomics Analysis Reveals that TP53 Mutations Inhibit Tumor Immunity in Gastric Cancer . Translational oncology 2018, 11 (5):1171-1187. https://doi.org/10.1016/j.tranon.2018.07.012 Cooks T, Pateras IS, Jenkins LM, Patel KM, Robles AI, Morris J, Forshew T, Appella E, Gorgoulis VG, Harris CC: Mutant p53 cancers reprogram macrophages to tumor supporting macrophages via exosomal miR-1246 . Nature communications 2018, 9 (1):771. https://doi.org/10.1038/s41467-018-03224-w Additional Declarations Competing interest reported. Kaihua Liu, , Yuqian Shi, Yang Shao are employees of Nanjing Geneseeq Technology Inc., other authors have no competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Supplementary Files Additionalfile1.docx Additionalfile2.docx 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-4011123","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":277437115,"identity":"c8fb8a57-f23a-4cb0-bcc4-12fc84dfa6de","order_by":0,"name":"Xiaodong Teng","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAElEQVRIiWNgGAWjYLCCBAMJOTb25oMPGHjAXPyqwWoeFNgY8/McSzYgWgvjgw9piTNn+JhJQC3Fr8WevffwiwSDw4wbbvCYVf6QOczAz55jwPBzBx5beM6lWQC1MBvcbiu7IcFzmEGy540BY+8ZPFokcswMgFrYDO4c3nbDAKjF4EaOATNjGx4t8m/AWngMbiSYFSQAtdgT1CLBY/wgwSBNQnJGihnDAZAtEoS0nMkxA8aLjQEokCUbeNJ5JM48KzjYi0cLe/sZ448//kjUtwGj8uPPHms5/vbkjQ9+4tECBGwScCZjDyQyD+DVwMDA/AHB/kFA7SgYBaNgFIxIAAAPklGkdNTcAgAAAABJRU5ErkJggg==","orcid":"","institution":"the First Affiliated Hospital, Zhejiang University School of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Xiaodong","middleName":"","lastName":"Teng","suffix":""},{"id":277437116,"identity":"d59e3442-9695-4d23-8eaf-e51f77fc3dfc","order_by":1,"name":"Zhen Chen","email":"","orcid":"","institution":"the First Affiliated Hospital, Zhejiang University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Zhen","middleName":"","lastName":"Chen","suffix":""},{"id":277437117,"identity":"76214c87-1ae9-4adb-9a86-9a52068cd3d1","order_by":2,"name":"Yanfeng Bai","email":"","orcid":"","institution":"the First Affiliated Hospital, Zhejiang University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Yanfeng","middleName":"","lastName":"Bai","suffix":""},{"id":277437118,"identity":"7c87dcdf-b709-4068-9563-79765d36c2fc","order_by":3,"name":"Hui Cao","email":"","orcid":"","institution":"the First Affiliated Hospital, Zhejiang University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Hui","middleName":"","lastName":"Cao","suffix":""},{"id":277437119,"identity":"c5725e7e-fd1d-49ee-837d-9a29a976a100","order_by":4,"name":"Jing Zhang","email":"","orcid":"","institution":"the First Affiliated Hospital, Zhejiang University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Zhang","suffix":""},{"id":277437120,"identity":"41426ef2-bbaf-4224-8fb4-2b0b6859652e","order_by":5,"name":"Liming Xu","email":"","orcid":"","institution":"the First Affiliated Hospital, Zhejiang University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Liming","middleName":"","lastName":"Xu","suffix":""},{"id":277437121,"identity":"df96c1b7-dfc4-46a0-b8c1-4da4099835ae","order_by":6,"name":"Kaihua Liu","email":"","orcid":"","institution":"Nanjing Geneseeq Technology Inc","correspondingAuthor":false,"prefix":"","firstName":"Kaihua","middleName":"","lastName":"Liu","suffix":""},{"id":277437122,"identity":"b3499f83-3c59-4de2-a282-95db9c47c5d4","order_by":7,"name":"Yuqian Shi","email":"","orcid":"","institution":"Nanjing Geneseeq Technology Inc","correspondingAuthor":false,"prefix":"","firstName":"Yuqian","middleName":"","lastName":"Shi","suffix":""},{"id":277437123,"identity":"bf089272-dba6-4d43-b435-147525ccca19","order_by":8,"name":"Yang Shao","email":"","orcid":"","institution":"Nanjing Geneseeq Technology Inc","correspondingAuthor":false,"prefix":"","firstName":"Yang","middleName":"","lastName":"Shao","suffix":""}],"badges":[],"createdAt":"2024-03-04 08:31:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4011123/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4011123/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":52455393,"identity":"a0cd3e7c-ebea-4837-a12c-c14e391b5fc3","added_by":"auto","created_at":"2024-03-11 19:56:22","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1947391,"visible":true,"origin":"","legend":"\u003cp\u003eTLS in MIBC. TLS was mainly formed by the aggregation of B cells and T cells (B, C), and most of them are located at the edge of the tumor (A). The OS of patients in the TLS-positive group was significantly longer than that in the TLS-negative group (D), and the OS of patients in TLS-high group was longer than that in TLS-low group, but not significantly (E)..\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4011123/v1/3e778e329a99039a9b3096a0.jpg"},{"id":52456022,"identity":"49d1e7c9-74fb-4da4-8ef9-d58f7200eacb","added_by":"auto","created_at":"2024-03-11 20:04:22","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1076154,"visible":true,"origin":"","legend":"\u003cp\u003eThe relationship between TLS and tumor-infiltrating lymphocytes in MIBC. The densities of CD8+ T cells (A), B cells (B) and plasma cells (C) in the TLS-positive group were significantly higher than that in the TLS-negative group. In the cases with high densities of B cells (D), low densities of CD8+ T cells (G) or low densities of plasma cells (I), TLS-positive patients had longer OS than TLS-negative patients. However, there was no significant differences in OS between TLS-positive and TLS-negative groups in the cases with low-density B cells (E), high-density CD8+ T cells (F) or high-density plasma cells (H). *, P \u0026lt; 0.05; **, P \u0026lt; 0.01; ***, P \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4011123/v1/21741ebee2e6962deb2cebee.jpg"},{"id":52455397,"identity":"069c19f9-5e2e-411b-b45b-628207e6784d","added_by":"auto","created_at":"2024-03-11 19:56:22","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":3124290,"visible":true,"origin":"","legend":"\u003cp\u003eThe molecular characteristics of TLS in MIBC. (A) Mutational spectrum of the patients grouped according to TLS status. (B) Heatmap for comparison of genomic alteration frequencies between TLS-positive and TLS-negative groups. *, P \u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4011123/v1/31d8d1bea37de115676024d6.jpg"},{"id":52455396,"identity":"805464a2-6b63-412c-901e-27deea9803e5","added_by":"auto","created_at":"2024-03-11 19:56:22","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":852330,"visible":true,"origin":"","legend":"\u003cp\u003eAssociation between TLS and\u003cem\u003e TP53 \u003c/em\u003emutations and TMB. (A) The rates of TLS-positive in cases with \u003cem\u003eTP53 \u003c/em\u003ewild type (WT) status,\u003cem\u003e TP53\u003c/em\u003eexons4-8 mutations, \u003cem\u003eTP53 \u003c/em\u003enon-exons4-8 mutations, \u003cem\u003eTP53\u003c/em\u003e disruptive mutations and\u003cem\u003e TP53\u003c/em\u003e non-disruptive mutations. Association between TLS status and TMB in all 80 cases (B), \u003cem\u003eTP53 \u003c/em\u003eWT cases (C) and \u003cem\u003eTP53\u003c/em\u003emutation type (MT) cases (D). **, P \u0026lt; 0.01; ns, P \u0026gt; 0.05.\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4011123/v1/8e1cac6f0cf655035aad3c86.jpg"},{"id":55265167,"identity":"65dd65c0-ad19-4253-8b89-b0c7645e5ff6","added_by":"auto","created_at":"2024-04-25 01:56:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1939349,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4011123/v1/b61ebd86-1126-4b4b-b72d-98a92fee8306.pdf"},{"id":52455395,"identity":"abf0315f-d26d-4474-a60f-32e62e37fa70","added_by":"auto","created_at":"2024-03-11 19:56:22","extension":"docx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":33909,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-4011123/v1/f141f8e2c29eda58197982fd.docx"},{"id":52455398,"identity":"e2d17127-44c5-4391-8dfb-f6ce05dcfdfd","added_by":"auto","created_at":"2024-03-11 19:56:23","extension":"docx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":314606,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile2.docx","url":"https://assets-eu.researchsquare.com/files/rs-4011123/v1/71a65664db9e151d8d894399.docx"}],"financialInterests":"Competing interest reported. Kaihua Liu, , Yuqian Shi, Yang Shao are employees of Nanjing Geneseeq Technology Inc., other authors have no competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.","formattedTitle":"Tertiary lymphoid structure was a predictor of favorable prognosis in muscle-invasive bladder cancer","fulltext":[{"header":"Background","content":"\u003cp\u003eBladder cancer was a major cause of morbidity and mortality worldwide, with 82000 new cases and 34000 deaths reported each year in China [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Muscle-invasive bladder cancer (MIBC), accounted for about 25% of all bladder cancers, usually had a high degree of malignancy and was prone to recurrence and metastasis, the 5-year survival rate of patients was still low after radical bladder cancer resection [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Finding new prognostic predictors and therapeutic targets plays an important role in the treatment of MIBC.\u003c/p\u003e \u003cp\u003eRecently Tertiary lymphoid structure (TLS), characterized by ectopic aggregated lymphocytes with high endothelial venules [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], had gained attention due to their associations with prognosis and immunotherapy in certain cancers [\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. TLS was also present in bladder cancer, and was associated with better patient outcomes, more frequent in MIBC relative to non-muscle-invasive bladder cancer [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. However, the clinicopathological and molecular factors of TLS, which may affect the formation of TLS, were not clearly understood in MIBC. To address this question, we reviewed and analyzed tissue samples from 119 cases of MIBC surgical resection.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e \u003cb\u003ePatients\u003c/b\u003e \u003c/p\u003e \u003cp\u003eA total of 119 cases of MIBC received radical cystectomy from the First Affiliated Hospital, Zhejiang University School of Medicine were enrolled from 2016 to 2018, all cases were re-evaluated by two experienced pathologists (Y.B and X.T) and were treatment na\u0026iuml;ve. Twenty representative unstained formalin fifixed paraffifin embedded (FFPE) sections with 4\u0026micro;m thickness from a representative block of each tumour were selected for further immunohistochemistry and next-generation sequencing (NGS) analysis. Tumor clinical and pathological staging system was based on the Eighth Edition of the Union for International Cancer Control/American Joint Committee on Cancer. Patient survival data were available until the end of December 2019. The present study was approved by the Ethics Committee of the First Affiliated Hospital, Zhejiang University School of Medicine, and complied with the Declaration of Helsinki.\u003c/p\u003e\n\u003ch3\u003eTLS evaluation\u003c/h3\u003e\n\u003cp\u003eAll cases were reviewed blindly by two pathologists (Y.B and X.T) to determine the presence and state of maturity of TLS according to immunohistochemical stainings (CD3-CD20). For the rare discordant cases, the final TLS status of the samples was agreed on consensus with a board gathering of team members. TLS was defined as lymphoid aggregates of more than 50 B lymphocytes and T lymphocytes, as previously described [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Mature TLS (mTLS) was defined as TLS with a obvious germinal center according on hematoxylin eosin saffron (HE) slices. TLS density was defined as the number of TLS divided by the tumor area, which achieved on a slice scanning system (Konfoong biotech, Ningbo, China ). TLS-high was defined as TLS-positive and had a density higher than or equal to the median of the TLS-positive group. TLS-low was defined as TLS-positive and had a density lower than the median of the TLS-positive group.\u003c/p\u003e\n\u003ch3\u003eImmunohistochemistry stainings\u003c/h3\u003e\n\u003cp\u003eThe double CD3-CD20 immunohistochemistry staining was performed with the primary antibodies CD3 and CD20 (all antibody information can be found in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). The staining procedure was performed with a Bond-III Automated IHC Staining System (Leica, Germany) following the manufacturer\u0026rsquo;s recommendations.\u003c/p\u003e \u003cp\u003eCD8 and CD138 stainings were performed with a Bond-III Automated IHC Staining System using the Bond Polymer Refine detection kits (Leica, Germany) according to the manufacturer\u0026rsquo;s recommendations. The slides were scanned using the PANNORAMIC 250 Flash III DX system (3DHISTECH, Hungary). CD8\u0026thinsp;+\u0026thinsp;T cell densities were evaluated by pathologists (Y.B) using a QuanCenter automated analysis system (3DHISTECH, Hungary). Plasma cell counts were enumerated in 5 immune cell-positive hot 20\u0026times; fields on CD138-stained sections. B cell counts were enumerated in 10 immune cell-positive hot 20\u0026times; fields on CD3-CD20-stained sections (only the lymphocytes stained with CD20 were scored). The grouping of B cell densities, CD8\u0026thinsp;+\u0026thinsp;T cell densities and plasma cell densities were divided by the respective median of cell numbers as the cut-off values.\u003c/p\u003e \u003cp\u003ePD-L1 staining was performed using the Ventana Medical Systems(Tucson, AZ, USA) according to the manufacturer\u0026rsquo;s recommendations. The evaluation rules for each score in PD-L1 expression (tumor proportion score, TPS; immune cell proportion score, IPS; combined positive score, CPS) according to the report by Shitara [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Each countable array core section contained at least 100 viable tumor cells. PD-L1 scores\u0026thinsp;\u0026ge;\u0026thinsp;25% were considered positive.\u003c/p\u003e\n\u003ch3\u003eNext-generation sequencing\u003c/h3\u003e\n\u003cp\u003eA total of 80 samples achieved NGS detection. Genomic DNA was extracted from FFPE samples with the QIAamp DNA FFPE Tissue Kit (Qiagen, Germany). FFPE DNA quality was evaluated by 1% agarose gel electrophoresis, and any FFPE DNA that was severely degraded was removed. DNA quantification was conducted with a Qubit 3.0 fluorometer and a Qubit dsDNA HS assay kit (Life Technologies, USA). An hybrid-based targeted NGS assay was used for library preparation with an GeneseeqPrime\u0026trade; Kit (covering 425 common cancer-associated genes, Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e)(Geneseeq, Nanjing, China). Experiments were performed according to the kit instructions. Twenty nanograms of DNA was used for library preparation as recommended by the kit instructions. The library product was sequenced using 75-bp paired-end runs on the Illumina Nextseq550 after quantification using a KAPA Library Quantification Kit (Kapa, KK4824). Sequencing data were processed by the manufacturer\u0026rsquo;s supplied bioinformatics software, tumor mutational burden (TMB) and microsatellite instability (MSI) were also included in the result analysis.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eOverall survival (OS) was defined as the time from the date of diagnosis to the date of death or last visit. The Kaplan-Meier method with a log-rank test and Cox regression analysis were used for survival analyses. The correlation of different groups with clinicopathological characteristics was studied via chi-square test or Fisher\u0026rsquo;s test. Mann-Whitney test was used for nonparametric tests. All tests were two-sided and \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered to indicate a statistically significant. Chi square test, non-parametric test and survival analysis were performed using IBM SPSS 28.0 software (Chicago, USA). The differences in gene mutations between TLS-positive and TLS-negative cases were analyzed using R packages \u0026ldquo;maftools\u0026rdquo; and \u0026ldquo;complexheatmap\u0026rdquo; (R version 4.2.2).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eTLS was a predictor of good prognosis in MIBC\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTLS was detected in 52.1% (62/119) of MIBC cases, mostly at the edge of the tumor (Figure 1A-C), only 6 cases were present mTLS. TLS did not differ with gender, age, N-stage, vascular invasion, nerve invasion or PD-L1 expression, but was higher in cases with lower T-stage and TNM stage (Table\u0026nbsp;1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 1. Associations between TLS and investigative factors.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.734693877551024%\"\u003e\n \u003cp\u003eFactor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003eTLS-negative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003eTLS-positive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\"\u003e\n \u003cp\u003eP\u003cem\u003e\u0026nbsp;\u003c/em\u003evalue\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"76.60377358490567%\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.81132075471698%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"76.60377358490567%\"\u003e\n \u003cp\u003e\u0026nbsp; Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.81132075471698%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"76.60377358490567%\"\u003e\n \u003cp\u003e\u0026nbsp; Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.81132075471698%\"\u003e\n \u003cp\u003e0.152\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"76.60377358490567%\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.81132075471698%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"76.60377358490567%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026lt; 70y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.81132075471698%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"76.60377358490567%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026ge; 70y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.81132075471698%\"\u003e\n \u003cp\u003e0.114\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.734693877551024%\"\u003e\n \u003cp\u003eTummor size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.734693877551024%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026lt; 3.8cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.734693877551024%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026ge; 3.8cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\"\u003e\n \u003cp\u003e0.322\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.734693877551024%\"\u003e\n \u003cp\u003ePD-L1(TPS)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.734693877551024%\"\u003e\n \u003cp\u003e\u0026nbsp; Negative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.734693877551024%\"\u003e\n \u003cp\u003e\u0026nbsp; Positive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\"\u003e\n \u003cp\u003e0.563\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"76.60377358490567%\"\u003e\n \u003cp\u003ePD-L1(IPS)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.81132075471698%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"76.60377358490567%\"\u003e\n \u003cp\u003e\u0026nbsp; Negative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.81132075471698%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"76.60377358490567%\"\u003e\n \u003cp\u003e\u0026nbsp; Positive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.81132075471698%\"\u003e\n \u003cp\u003e0.079\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"76.60377358490567%\"\u003e\n \u003cp\u003ePD-L1(CPS)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.81132075471698%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"76.60377358490567%\"\u003e\n \u003cp\u003e\u0026nbsp; Negative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.81132075471698%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"76.60377358490567%\"\u003e\n \u003cp\u003e\u0026nbsp; Positive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.81132075471698%\"\u003e\n \u003cp\u003e0.402\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.734693877551024%\"\u003e\n \u003cp\u003eTNM-stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.734693877551024%\"\u003e\n \u003cp\u003e\u0026nbsp; II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.734693877551024%\"\u003e\n \u003cp\u003e\u0026nbsp; III\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.734693877551024%\"\u003e\n \u003cp\u003e\u0026nbsp; IV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"76.60377358490567%\"\u003e\n \u003cp\u003eT-stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.81132075471698%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"76.60377358490567%\"\u003e\n \u003cp\u003e\u0026nbsp; 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.81132075471698%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"76.60377358490567%\"\u003e\n \u003cp\u003e\u0026nbsp; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.81132075471698%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"76.60377358490567%\"\u003e\n \u003cp\u003e\u0026nbsp; 4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.81132075471698%\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"76.60377358490567%\"\u003e\n \u003cp\u003eN-stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.81132075471698%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"76.60377358490567%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.81132075471698%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"76.60377358490567%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.81132075471698%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.734693877551024%\"\u003e\n \u003cp\u003e\u0026nbsp; 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.367346938775512%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.53061224489796%\"\u003e\n \u003cp\u003e0.968\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"76.60377358490567%\"\u003e\n \u003cp\u003eVascular invasion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.81132075471698%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"76.60377358490567%\"\u003e\n \u003cp\u003e\u0026nbsp; Without\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.81132075471698%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"76.60377358490567%\"\u003e\n \u003cp\u003e\u0026nbsp; With\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.81132075471698%\"\u003e\n \u003cp\u003e0.355\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"76.60377358490567%\"\u003e\n \u003cp\u003eNerve invasion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.81132075471698%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"76.60377358490567%\"\u003e\n \u003cp\u003e\u0026nbsp; Without\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.81132075471698%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"76.60377358490567%\"\u003e\n \u003cp\u003e\u0026nbsp; With\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7924528301886795%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.81132075471698%\"\u003e\n \u003cp\u003e0.173\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eLog-rank tests showed that TLS status, age of patients at diagnosis, CD8+ T cell density, and nerve invasion significantly affect the OS of patients with MIBC (Table 2, Table S3). Patients in the TLS-positive group had a longer OS than those in the TLS-negative group (Figure 1D). Patients with TLS-high had a longer OS than those with TLS-low, but the difference did not reach statistical significance (Figure 1E).\u0026nbsp;We aslo evaluated the relationship between various clinicopathological characteristics combined with TLS status and OS.\u0026nbsp;Cox regression analysis showed that TLS status (HR 1.701, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05) and age of patients at diagnosis (HR 0.556, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05) were independent factors affecting OS (Table 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2. Univariate and multivariate analysis of over all survival in MIBC.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"99%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.36082474226804%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003eUnivariate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.0618556701030926%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"37.11340206185567%\" colspan=\"2\"\u003e\n \u003cp\u003eMultivariate\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.36082474226804%\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.0618556701030926%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003eHR(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.36082474226804%\"\u003e\n \u003cp\u003eTLS (negative vs positive)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.0618556701030926%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e1.701 (1.018-2.842)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.36082474226804%\"\u003e\n \u003cp\u003eAge (\u0026lt;70y vs\u0026nbsp;\u0026ge;70y)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.0618556701030926%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e0.556 (0.341-0.9070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.36082474226804%\"\u003e\n \u003cp\u003eCD8+ cell desity (low vs high)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.0618556701030926%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e1.214 (0.744-1.982)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e0.438\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.36082474226804%\"\u003e\n \u003cp\u003eNerve invasion (without vs with)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.463917525773196%\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"2.0618556701030926%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.804123711340207%\"\u003e\n \u003cp\u003e0.641 (0.379-1.087)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.309278350515465%\"\u003e\n \u003cp\u003e0.099\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTLS was associated with more tumor-infiltrating lymphocytes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn order to understand the mechanism by which TLS exerted its anti-tumor effect, we compared the relationship between TLS and various tumor-infiltrating lymphocytes, and found that densities of CD8+ T cells, B cells, and plasma cells in TLS-positive group were significantly higher than those in TLS-negative group (Figure 2A-C).\u003c/p\u003e\n\u003cp\u003eWe also analyzed the association of TLS status with OS in patients with MIBC under different B cell, CD8+ T cell and plasma cell density statuses. The presence of TLS was significantly associated with improved overall survival in the groups with high B cell density (Figure 2D), low CD8+ T cell density (Figure 2G) and low plasma cell density (Figure 2I). However, there no significant differences were observed in the groups with low B cell density (Figure 2E), high CD8+ T cell density (Figure 2F) or high plasma cell density (Figure 2H). These suggested that the anti-tumor effect of TLS was mainly achieved through antigen presentation by B cells, rather than maturation into plasma cells to secrete specific antibodies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrelation between TLS and molecular characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 1006 variants in 282 genes were identified in our cohort (Figure 3A). Among the cases, 56% (45/80) showed high TMB (TMB \u0026ge; 10), and only one case showed MSI, which was TLS-positive. The most frequently mutated genes in MIBC were \u003cem\u003eTP53\u0026nbsp;\u003c/em\u003e(68%) and \u003cem\u003eTERT\u003c/em\u003e (66%), followed by \u003cem\u003eARID1A\u003c/em\u003e, \u003cem\u003ePIK3CA\u003c/em\u003e, \u003cem\u003eEP300\u003c/em\u003e. We compared the mutation rates of the top 50 genes with different TLS statuses (Figure 3B) and found that the \u003cem\u003eTP53\u003c/em\u003e mutation rate was lower in the TLS-positive group than in the TLS-negative group (53.8% vs. 80.5%, \u003cem\u003eP\u003c/em\u003e = 0.011 ), \u003cem\u003eCDKN1A\u003c/em\u003e (15.4% vs. 0%, \u003cem\u003eP\u003c/em\u003e = 0.011) and \u003cem\u003eFAT1\u003c/em\u003e (20.5% vs. 4.9%, \u003cem\u003eP\u003c/em\u003e = 0.045) mutation rates were higher in the TLS-positive group than in the TLS-negative group. We also examined typical cancer-related pathways, no significant differences were found between different TLS statuses but cell cycle pathway (Table S4).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eTP53\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;mutations inhibited TLS production by inhibiting the immunogenicity of neoantigens\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs \u003cem\u003eTP53\u003c/em\u003e mutations were present in significant numbers, we decided to investigate this association further to better understand why \u003cem\u003eTP53\u003c/em\u003e mutations associates with fewer TLSs. In our cohort, \u003cem\u003eTP53\u003c/em\u003e mutations were mainly located in exons 4-8, which are the DNA-binding regions, consistent with previous literature [14] (Figure 4A). We confirmed that patients with \u003cem\u003eTP53\u003c/em\u003e mutations in exons 4-8 had a trend toward fewer TLSs except exon 6, which may be due to the small sample size. The same trends were present but less pronounced when analysis was restricted to disruptive \u003cem\u003eTP53\u003c/em\u003e mutations (Figure 4A), defined as truncating mutations or nonsynonymous alterations affecting the L2 to L3 region, described by Natalie et al [12].\u003c/p\u003e\n\u003cp\u003eNeoantigens generated by mutations could be presented to effector cells by presenting cells to activate immune responses, and the neoantigen burden is highly related to TMB [13]. As part of tumor immunity, we speculated that TLS could be initiated by high TMB. However, no significantly correlation between TMB and TLS, CD8+T cells, B cells were observed in our cohort (Figure 4B, Figure S1). When we combined \u003cem\u003eTP53\u003c/em\u003e mutation status, TLS and TMB remained uncorrelated in \u003cem\u003eTP53\u003c/em\u003e mutant patients but showed a significant correlation in \u003cem\u003eTP53\u003c/em\u003e wild type patients (Figure 4C-D, Figure S1). These finding suggested that \u003cem\u003eTP53\u003c/em\u003e mutations may inhibit the immunogenicity of the neoantigens.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eTLS had shown antitumor effects in a variety of tumors, including colorectal cancer [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], breast cancer [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], NSCLC [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], and other cancers [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], but it had also been reported that TLS had a tumor-promoting effect in kidney clear cell carcinoma, and the higher the TLS density, the worse the prognosis of patients [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Our results showed that TLS exhibited an antitumor effect in MIBC, which was associated with lower T-stage and was an independent factor of good prognosis.\u003c/p\u003e \u003cp\u003eThe mechanism by which TLS in anti-tumor process is still unclear, it may involve cellular immunity, as many studies had confirmed that the existence of TLS was related to the number of Th1 and CD8\u0026thinsp;+\u0026thinsp;T cells [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In our cohort, although the density of CD8\u0026thinsp;+\u0026thinsp;T cells was significantly associated with TLS, the good prognostic effect of TLS did not depend on the high density of CD8\u0026thinsp;+\u0026thinsp;T cells but rather on B cells, suggesting that TLS mainly exerts its antitumor effect through B cells, which consistent with previous literature [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. B cells could affect tumors in two ways: by differentiating and mature into plasma cells to produce tumor-specific antibodies, or by presenting tumor-associated antigens to T cells to enhance cellular immune effects [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Plasma cells could be generated in mature TLS but are absent or rare in immature TLS [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In our cohort, there were few mature TLSs, mostly immature TLSs. However, TLS was still significantly associated with plasma cells, suggesting that immature TLS has some mechanism by which plasma cells could be recruited. Similar to CD8\u0026thinsp;+\u0026thinsp;T cells, the good prognostic effect of TLS did not depend on a high density of plasma cells, suggesting that B cells in TLS may primarily play an antigen-presenting role.\u003c/p\u003e \u003cp\u003eThe formation of TLS is a complex process and is orchestrated by several lympho-organogenic chemokines in response to inflammatory stimuli [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. However, the relationship between TLS and gene mutations in tumor cells is still unclear. Masuda, T et al [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] analyzed 43 cases of renal clear cell carcinoma and found that the gene mutation rate of PI3K-mTOR pathway was significantly increased in TLS-positive tumors. Florian Posch et al [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] found in 109 patients with stage II/III non-metastatic colorectal carcinoma that TLS was more common in \u003cem\u003eBRAF\u003c/em\u003e-mutated tissues. Morcrette, G., et al [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] reported that TLSs were present in all 11 \u003cem\u003eAPC\u003c/em\u003e germline mutated hepatoblastoma (APC-HB) tumors treated with cisplatin neoadjuvant chemotherapy, whereas TLSs were present in only 6 of 15 tumors without \u003cem\u003eAPC\u003c/em\u003e mutations. Notably, TLS was absent in pre-chemotherapy specimens, suggesting that \u003cem\u003eAPC\u003c/em\u003e mutations played a certain role in the formation of TLS. In our corhoet, we performed NGS analysis in 80 cases and found that compared with TLS-negative cases, TLS-positive tumors had lower \u003cem\u003eTP53\u003c/em\u003e mutation rates, higher \u003cem\u003eCDKN1A\u003c/em\u003e and \u003cem\u003eFAT1\u003c/em\u003e mutation rates, and lower mutation rates in cell cycle pathway-related genes. This suggested that mutations in \u003cem\u003eTP53\u003c/em\u003e gene and cell cycle pathway-related genes could inhibit the formation of TLS, while \u003cem\u003eCDKN1A\u003c/em\u003e and \u003cem\u003eFAT1\u003c/em\u003e mutations may promote the formation of TLS.\u003c/p\u003e \u003cp\u003e \u003cem\u003eTP53\u003c/em\u003e mutations are one of the most frequent genetic alterations in human cancer [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], and the p53 pathway could regulate many targets transcriptionally and non-transcriptionally [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. \u003cem\u003eTP53\u003c/em\u003e mutations in stromal cells could cause changes in various immune microenvironments, but the impact of \u003cem\u003eTP53\u003c/em\u003e mutations in tumor cells on the immune microenvironment has not been deeply explored. In bladder cancer, the immune assessment models based on \u003cem\u003eTP53\u003c/em\u003e mutations could predict prognosis well [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. \u003cem\u003eTP53\u003c/em\u003e mutations could increase tumor mutation burden (TMB) in various tumors [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], and TMB was closely related to neoantigens which could induce immune response [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Therefore, it is inferred that \u003cem\u003eTP53\u003c/em\u003e mutations should promote tumor immunity, included the formation of TLS. However, the fact is that \u003cem\u003eTP53\u003c/em\u003e-mutated tumors often had fewer tumor-infiltrating lymphocytes, lower cytokine activity, and down-regulated inflammatory activity\u003csup\u003e32\u0026ndash;34\u003c/sup\u003e. Our results showed that \u003cem\u003eTP53\u003c/em\u003e mutations had a negative role in the formation of TLS and the relationship between TMB and numbers of tumor-infiltrating lymphocytes was not close. However, after we excluded the \u003cem\u003eTP53\u003c/em\u003e mutations, the connection between TMB and TLS, CD8\u0026thinsp;+\u0026thinsp;T cells were established. This suggested that that \u003cem\u003eTP53\u003c/em\u003e mutations could inhibit the immunogenicity of neoantigens caused by TMB through some mechanism to suppress the immune response.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eWe described the clinicopathological and molecular features of TLS in MIBC and found that TLS was a favorable prognostic factor, and its formation could be inhibited by \u003cem\u003eTP53\u003c/em\u003e mutations. However, some limitations remain to be addressed at this stage. We were able to further explore the specific mechanism that affects TLS formation, which would be helpful for understanding of the immune microenvironment in MIBC more comprehensively.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eFFPE: Formalin Fifixed Paraffifin Embedded\u003c/p\u003e\n\u003cp\u003eMIBC: Muscle-Invasive Bladder Cancer\u003c/p\u003e\n\u003cp\u003eMSI: Microsatellite Instability\u003c/p\u003e\n\u003cp\u003emTLS: Mature Tertiary Lymphoid Structure\u003c/p\u003e\n\u003cp\u003eNGS: Next Generation Sequencing\u003c/p\u003e\n\u003cp\u003eOS: Overall Survival\u003c/p\u003e\n\u003cp\u003eTLS: Tertiary Lymphoid Structure\u003c/p\u003e\n\u003cp\u003eTMB: Tumor Mutational Burden\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e The present study was approved by the Ethics Committee of the First Affiliated Hospital, Zhejiang University School of Medicine.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e The datasets used and during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e Kaihua Liu, , Yuqian Shi, Yang Shao are employees of Nanjing Geneseeq Technology Inc., other authors have no competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e This study was funded by Zhejiang Provincial Research Center for Cancer Intelligent Diagnosis and Molecular Technology (JBZX-202003) and Zhejiang Provincial Natural Science Foundation of China (No.LQ19H160038).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e XT conceived and designed the study and wrote the manuscript. ZC and YB conducted most experiments, analyzed data. HC and JZ collected the clinical samples and data. LX, KL, YS and YS performed parts of the experiments. 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\u003cstrong\u003e9\u003c/strong\u003e(1):771. https://doi.org/10.1038/s41467-018-03224-w\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Urinary Bladder Neoplasms, Tertiary Lymphoid Structures, Tumor Microenvironment, TP53 Genes","lastPublishedDoi":"10.21203/rs.3.rs-4011123/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4011123/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Tertiary lymphoid structure (TLS) has been reported to be associated with prognosis and immunotherapy in certain cancers. In this study, we aimed to explore the prognostic role of TLS in Muscle-invasive bladder cancer (MIBC), and to analyze the clinicopathological and molecular factors affecting the formation of TLS.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eImmunohistochemistry was used to detect the expression of TLS, CD8+ T cells, B cells, and plasma cells in 119 MIBC cases, of which 80 cases were tested by next generation sequencing (NGS) for analysising the differences in gene alterations between TLS-negative and TLS-positive.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003eTLSs were present in 52.1% of MIBC cases. Patients with TLS had lower T and TNM stages, and had longer overall survival (OS) than patients without TLS. Multivariate analysis showed that TLS was an independent prognostic factor. The densities of B cells, CD8+ T cells, and plasma cells in tumors were significantly correlated with TLS, but in the cases with low density B cells, high density CD8+ T cells or high density plasma cells, differences in OS between the tumors with TLS and without TLS were not significant. Compared with TLS-negative tumors, TLS-positive tumors had lower frequency of \u003cem\u003eTP53\u003c/em\u003emutations and higher frequencies of \u003cem\u003eFAT1\u003c/em\u003e, \u003cem\u003eCDKN1A\u003c/em\u003e mutations. Tumor mutational burden (TMB)was not significantly different between the two groups, but was significantly associated with TLS in \u003cem\u003eTP53 \u003c/em\u003ewild-type tumors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003eTLS was an independent predictor of favorableprognosis in MIBC, and mainly played antitumor role effect through B cells. \u003cem\u003eTP53\u003c/em\u003emutations could inhibit the formation of TLS.\u003c/p\u003e","manuscriptTitle":"Tertiary lymphoid structure was a predictor of favorable prognosis in muscle-invasive bladder cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-11 19:56:18","doi":"10.21203/rs.3.rs-4011123/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":"bfc6be22-5a03-4cf4-80aa-d7c2bbdd7de8","owner":[],"postedDate":"March 11th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-04-24T11:28:23+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-11 19:56:18","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4011123","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4011123","identity":"rs-4011123","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}