Multi-omics profiling and experimental verification of tertiary lymphoid structure-related genes: molecular subgroups, immune infiltration, and prognostic implications in lung adenocarcinoma.

Lung adenocarcinoma (LUAD), characterized by a low 5-year survival rate, is the most common and aggressive type of lung cancer. Recent studies have shown that tertiary lymphoid structures (TLS), which resemble lymphoid structures, are closely linked to the immune response and tumor prognosis. The functions of the tertiary lymphoid structure-related genes (TLS-RGs) in the tumor microenvironment (TME) are poorly understood. Based on publicly available data, we conducted a comprehensive study of the function of TLS-RGs in LUAD. Initially, we categorized LUAD patients into two TLS and two gene subtypes. Subsequently, risk scores were calculated, and prognostic models were constructed using seven genes (CIITA, FCRL2, GBP1, BIRC3, SCGB1A1, CLDN18, and S100P). To enhance the clinical application of TLS scores, we have developed a precise nomogram. Furthermore, drug sensitivity, tumor mutational burden (TMB), and the cancer stem cell (CSC) index were found to be substantially correlated with the TLS scores. Single-cell sequencing results reflected the distribution of TLS-RGs in cells. Finally, we took the intersection of overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) prognosis-related genes and then further validated the expression of these genes by qRT-PCR. Our in-depth investigation of TLS-RGs in LUAD revealed their possible contributions to the clinicopathological features, prognosis, and characteristics of TME. These findings underscore the potential of TLS-RGs as prognostic biomarkers and therapeutic targets for LUAD, thereby paving the way for personalized treatment strategies.

Single-cell and spatial transcriptome analyses reveal tertiary lymphoid structures linked to tumour progression and immunotherapy response in nasopharyngeal carcinoma.

Tertiary lymphoid structures are immune cell aggregates linked with cancer outcomes, but their interactions with tumour cell aggregates are unclear. Using nasopharyngeal carcinoma as a model, here we analyse single-cell transcriptomes of 343,829 cells from 77 biopsy and blood samples and spatially-resolved transcriptomes of 31,316 spots from 15 tumours to decipher their components and interactions with tumour cell aggregates. We identify essential cell populations in tertiary lymphoid structure, including CXCL13+ cancer-associated fibroblasts, stem-like CXCL13+CD8+ T cells, and B and T follicular helper cells. Our study shows that germinal centre reaction matures plasma cells. These plasma cells intersperse with tumour cell aggregates, promoting apoptosis of EBV-related malignant cells and enhancing immunotherapy response. CXCL13+ cancer-associated fibroblasts promote B cell adhesion and antibody production, activating CXCL13+CD8+ T cells that become exhausted in tumour cell aggregates. Tertiary lymphoid structure-related cell signatures correlate with prognosis and PD-1 blockade response, offering insights for therapeutic strategies in cancers.

Tertiary lymphoid structures in diseases: immune mechanisms and therapeutic advances.

Tertiary lymphoid structures (TLSs) are defined as lymphoid aggregates formed in non-hematopoietic organs under pathological conditions. Similar to secondary lymphoid organs (SLOs), the formation of TLSs relies on the interaction between lymphoid tissue inducer (LTi) cells and lymphoid tissue organizer (LTo) cells, involving multiple cytokines. Heterogeneity is a distinguishing feature of TLSs, which may lead to differences in their functions. Growing evidence suggests that TLSs are associated with various diseases, such as cancers, autoimmune diseases, transplant rejection, chronic inflammation, infection, and even ageing. However, the detailed mechanisms behind these clinical associations are not yet fully understood. The mechanisms by which TLS maturation and localization affect immune function are also unclear. Therefore, it is necessary to enhance the understanding of TLS development and function at the cellular and molecular level, which may allow us to utilize them to improve the immune microenvironment. In this review, we delve into the composition, formation mechanism, associations with diseases, and potential therapeutic applications of TLSs. Furthermore, we discuss the therapeutic implications of TLSs, such as their role as markers of therapeutic response and prognosis. Finally, we summarize various methods for detecting and targeting TLSs. Overall, we provide a comprehensive understanding of TLSs and aim to develop more effective therapeutic strategies.

Exploring prognostic and immunological characteristics of pancreatic ductal adenocarcinoma through comprehensive genomic analysis of tertiary lymphoid structures and CD8 + T-cells.

PURPOSE: Tertiary lymphoid structures (TLSs) and CD8 + T-cells are potential prognostic indicators for pancreatic ductal adenocarcinoma (PDAC). We established a novel scoring system for evaluating the risk for PDAC based on TLS- and CD8 + T-cell-related genes. METHODS: We analyzed single-cell sequence data from PDAC patients in the Genome Sequence Archive. Bioinformatics and machine algorithms established and validated a scoring method (T-C score) based on PDAC survival-related genes highly expressed in TLSs and CD8 + T-cells. Patients were stratified into the low- and high-T-C score groups. Differences in survival, pathway enrichment, mutation status, immune cell infiltration, expression of immune checkpoint-associated genes, tumor stemness, and response to antitumor therapy were compared through computer simulation methods. RESULTS: Overall survival differed significantly between the training and validation cohorts' low- and high-T-C score groups. The low-T-C score group correlated with lower tumor mutation burden and lower levels of tumor stemness compared with the high-T-C score group. Patients with lower T-C scores exhibited advantages in immunotherapeutic responses and might be more sensitive to the chemotherapeutic regimen and multi-kinase inhibitors. CONCLUSION: The T-C score could serve as an effective model for predicting the survival and therapeutic responses of patients with PDAC.

Deciphering tertiary lymphoid structure heterogeneity reveals prognostic signature and therapeutic potentials for colorectal cancer: a multicenter retrospective cohort study.

BACKGROUND: Tertiary lymphoid structures (TLSs) exert a crucial role in the tumor microenvironment (TME), impacting tumor development, immune escape, and drug resistance. Nonetheless, the heterogeneity of TLSs in colorectal cancer (CRC) and their impact on prognosis and treatment response remain unclear. METHODS: The authors collected genome, transcriptome, clinicopathological information, and digital pathology images from multiple sources. An unsupervised clustering algorithm was implemented to determine diverse TLS patterns in CRC based on the expression levels of 39 TLS signature genes (TSGs). Comprehensive explorations of heterogeneity encompassing mutation landscape, TME, biological characteristics, response to immunotherapy, and drug resistance were conducted using multiomics data. TLSscore was then developed to quantitatively assess TLS patterns of individuals for further clinical applicability. RESULTS: Three distinct TLS patterns were identified in CRC. Cluster 1 exhibited upregulation of proliferation-related pathways, high metabolic activity, and intermediate prognosis, while Cluster 2 displayed activation of stromal and carcinogenic pathways and a worse prognosis. Both Cluster 1 and Cluster 2 may potentially benefit from adjuvant chemotherapy. Cluster 3, characterized by the activation of immune regulation and activation pathways, demonstrated a favorable prognosis and enhanced responsiveness to immunotherapy. The authors subsequently employed a regularization algorithm to construct the TLSscore based on nine core genes. Patients with lower TLSscore trended to prolonged prognosis and a more prominent presence of TLSs, which may benefit from immunotherapy. Conversely, those with higher TLSscore exhibited increased benefits from adjuvant chemotherapy. CONCLUSIONS: The authors identified distinct TLS patterns in CRC and characterized their heterogeneity through multiomics analyses. The TLSscore held promise for guiding clinical decision-making and further advancing the field of personalized medicine in CRC.

To explore the prognostic characteristics of colon cancer based on tertiary lymphoid structure-related genes and reveal the characteristics of tumor microenvironment and drug prediction.

In order to construct a prognostic evaluation model of TLS features in COAD and better realize personalized precision medicine in COAD. Colon adenocarcinoma (COAD) is a common malignant tumor of the digestive system. At present, there is no effective prognostic marker to predict the prognosis of patients. Tertiary lymphoid structure (TLS) affects cancer progression by regulating immune microenvironment. Mining COAD biomarkers based on TLS-related genes helps to improve the prognosis of patients. In order to construct a prognostic evaluation model of TLS features in COAD and better realize personalized precision medicine in COAD. The mRNA expression data and clinical information of COAD and adjacent tissues were downloaded from the Cancer Genome Atlas database. The differentially expressed TLS-related genes of COAD relative to adjacent tissues were obtained by differential analysis. TLS gene co-expression analysis was used to mine genes highly related to TLS, and the intersection of the two was used to obtain candidate genes. Univariate, LASSO, and multivariate Cox regression analysis were performed on candidate genes to screen prognostic markers to construct a risk assessment model. The differences of immune characteristics were evaluated by ESTIMATE, ssGSEA and CIBERSORT in high and low risk groups of prognostic model. The difference of genomic mutation between groups was evaluated by tumor mutation burden score. Screening small molecule drugs through the GDSC library. Finally, a nomogram was drawn to evaluate the clinical value of the prognostic model. Seven TLS-related genes ADAM8, SLC6A1, PAXX, RIMKLB, PTH1R, CD1B, and MMP10 were screened to construct a prognostic model. Survival analysis showed that patients in the high-risk group had significantly lower overall survival rates. Immune microenvironment analysis showed that patients in the high-risk group had higher immune indicators, indicating higher immunity. The genomic mutation patterns of the high-risk and low-risk groups were significantly different, especially the KRAS mutation frequency was significantly higher in the high-risk group. Drug sensitivity analysis showed that the low-risk group was more sensitive to Erlotinib, Savolitinib and VE _ 822, which may be used as a potential drug for COAD treatment. Finally, the nomogram constructed by pathological features combined with RiskScore can accurately evaluate the prognosis of COAD patients. This study constructed and verified a TLS model that can predict COAD. More importantly, it provides a reference standard for guiding the prognosis and immunotherapy of COAD patients.

Identification of a risk score model based on tertiary lymphoid structure-related genes for predicting immunotherapy efficacy in non-small cell lung cancer.

BACKGROUND: Tertiary lymphoid structures (TLSs) affect the prognosis and efficacy of immunotherapy in patients with non-small cell lung cancer (NSCLC), but the underlying mechanisms are not well understood. METHODS: TLSs were identified and categorized online from the Cancer Digital Slide Archive (CDSA). Overall survival (OS) and disease-free survival (DFS) were analyzed. GSE111414 and GSE136961 datasets were downloaded from the GEO database. GSVA, GO and KEGG were used to explore the signaling pathways. Immune cell infiltration was analyzed by xCell, ssGSEA and MCP-counter. The analysis of WGCNA, Lasso and multivariate cox regression were conducted to develop a gene risk score model based on the SU2C-MARK cohort. RESULTS: TLS-positive was a protective factor for OS according to multivariate cox regression analysis (p = 0.029). Both the TLS-positive and TLS-mature groups exhibited genes enrichment in immune activation pathways. The TLS-mature group showed more activated dendritic cell infiltration than the TLS-immature group. We screened TLS-related genes using WGCNA. Lasso and multivariate cox regression analysis were used to construct a five-genes (RGS8, RUF4, HLA-DQB2, THEMIS, and TRBV12-5) risk score model, the progression free survival (PFS) and OS of patients in the low-risk group were markedly superior to those in the high-risk group (p < 0.0001; p = 0.0015, respectively). Calibration and ROC curves indicated that the combined model with gene risk score and clinical features could predict the PFS of patients who have received immunotherapy more accurately than a single clinical factor. CONCLUSIONS: Our data suggested a pivotal role of TLSs formation in survival outcome and immunotherapy response of NSCLC patients. Tumors with mature TLS formation showed more activated immune microenvironment. In addition, the model constructed by TLS-related genes could predict the response to immunotherapy and is meaningful for clinical decision-making.

Machine Learning-Based Characterization and Identification of Tertiary Lymphoid Structures Using Spatial Transcriptomics Data.

Tertiary lymphoid structures (TLSs) are organized aggregates of immune cells in non-lymphoid tissues and are associated with a favorable prognosis in tumors. However, TLS markers remain inconsistent, and the utilization of machine learning techniques for this purpose is limited. To tackle this challenge, we began by identifying TLS markers through bioinformatics analysis and machine learning techniques. Subsequently, we leveraged spatial transcriptomic data from Gene Expression Omnibus (GEO) and built two support vector classifier models for TLS prediction: one without feature selection and the other using the marker genes. The comparable performances of these two models confirm the efficacy of the selected markers. The majority of the markers are immunoglobulin genes, demonstrating their importance in the identification of TLSs. Our research has identified the markers of TLSs using machine learning methods and constructed a model to predict TLS location, contributing to the detection of TLS and holding the promising potential to impact cancer treatment strategies.

Tertiary lymphoid structural heterogeneity determines tumour immunity and prospects for clinical application.

Tertiary lymphoid structures (TLS) are clusters of immune cells that resemble and function similarly to secondary lymphoid organs (SLOs). While TLS is generally associated with an anti-tumour immune response in most cancer types, it has also been observed to act as a pro-tumour immune response. The heterogeneity of TLS function is largely determined by the composition of tumour-infiltrating lymphocytes (TILs) and the balance of cell subsets within the tumour-associated TLS (TA-TLS). TA-TLS of varying maturity, density, and location may have opposing effects on tumour immunity. Higher maturity and/or higher density TLS are often associated with favorable clinical outcomes and immunotherapeutic response, mainly due to crosstalk between different proportions of immune cell subpopulations in TA-TLS. Therefore, TLS can be used as a marker to predict the efficacy of immunotherapy in immune checkpoint blockade (ICB). Developing efficient imaging and induction methods to study TA-TLS is crucial for enhancing anti-tumour immunity. The integration of imaging techniques with biological materials, including nanoprobes and hydrogels, alongside artificial intelligence (AI), enables non-invasive in vivo visualization of TLS. In this review, we explore the dynamic interactions among T and B cell subpopulations of varying phenotypes that contribute to the structural and functional diversity of TLS, examining both existing and emerging techniques for TLS imaging and induction, focusing on cancer immunotherapies and biomaterials. We also highlight novel therapeutic approaches of TLS that are being explored with the aim of increasing ICB treatment efficacy and predicting prognosis.

The Absence of Intra-Tumoral Tertiary Lymphoid Structures is Associated with a Worse Prognosis and mTOR Signaling Activation in Hepatocellular Carcinoma with Liver Transplantation: A Multicenter Retrospective Study.

Tertiary lymphoid structure (TLS) can predict the prognosis and sensitivity of tumors to immune checkpoint inhibitors (ICIs) therapy, whether it can be noninvasively predicted by radiomics in hepatocellular carcinoma with liver transplantation (HCC-LT) has not been explored. In this study, it is found that intra-tumoral TLS abundance is significantly correlated with recurrence-free survival (RFS) and overall survival (OS). Tumor tissues with TLS are characterized by inflammatory signatures and high infiltration of antitumor immune cells, while those without TLS exhibit uncontrolled cell cycle progression and activated mTOR signaling by bulk and single-cell RNA-seq analyses. The regulators involved in mTOR signaling (RHEB and LAMTOR4) and S-phase (RFC2, PSMC2, and ORC5) are highly expressed in HCC with low TLS. In addition, the largest cohort of HCC patients is studied with available radiomics data, and a classifier is built to detect the presence of TLS in a non-invasive manner. The classifier demonstrates remarkable performance in predicting intra-tumoral TLS abundance in both training and test sets, achieving areas under receiver operating characteristic curve (AUCs) of 92.9% and 90.2% respectively. In summary, the absence of intra-tumoral TLS abundance is associated with mTOR signaling activation and uncontrolled cell cycle progression in tumor cells, indicating unfavorable prognosis in HCC-LT.

Integrating tertiary lymphoid structure-associated genes into computational models to evaluate prognostication and immune infiltration in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by poor response to all therapeutic modalities and dismal prognosis. The presence of tertiary lymphoid structures (TLSs) in various solid cancers is of crucial prognostic significance, highlighting the intricate interplay between the tumor microenvironment and immune cells aggregation. However, the extent to which TLSs and immune status affect PDAC prognosis remains incompletely understood. Here, we sought to unveil the unique properties of TLSs in PDAC by leveraging both single-cell and bulk transcriptomics, culminating in a risk model that predicts clinical outcomes. We used TLS scores based on a 12-gene (CCL2, CCL3, CCL4, CCL5, CCL8, CCL18, CCL19, CCL21, CXCL9, CXCL10, CXCL11, and CXCL13) and 9-gene (PTGDS, RBP5, EIF1AY, CETP, SKAP1, LAT, CCR6, CD1D, and CD79B) signature, respectively, and examined their distribution in cell clusters of single-cell data from PDAC samples. The markers involved in these clusters were selected to develop a prognostic model using The Cancer Genome Atlas Program database as the training cohort and Gene Expression Omnibus database as the validation cohort. Further, we compared the immune infiltration, drug sensitivity, and enriched and differentially expressed genes between the high- and low-risk groups in our model. Therefore, we established a risk model that has significant implications for the prognostic assessment of PADC patients with remarkable differences in immune infiltration and chemosensitivity between the low- and high-risk groups. This paradigm established by TLS-related cell marker genes provides a prognostic prediction and a panel of novel therapeutic targets for exploring potential immunotherapy.

The molecular subtypes and clinical prognosis characteristic of tertiary lymphoid structures-related gene of cutaneous melanoma.

Despite the remarkable efficacy of PD-1-associated immune checkpoint inhibitors in treating cutaneous melanoma (CM), the inconsistency in the expression of PD-1 and its ligand PD-L1, and resulting variability in the effectiveness of immunotherapy, present significant challenges for clinical application. Therefore, further research is necessary to identify tumor-related biomarkers that can predict the prognosis of immunotherapy. Tertiary lymphoid structures (TLSs) have been recognized as a crucial factor in predicting the response of immune checkpoint inhibitors in solid tumors, including CM. However, the study of TLSs in CM is not yet comprehensive. Gene expression profiles have been shown to correlate with CM risk stratification and patient outcomes. In this study, we identified TLS-related genes that can be used for prognostic purposes and developed a corresponding risk model. The impact of TLS-related genes on clinicopathological characteristics, immune infiltration and drug susceptibility was also explored. Our biological function enrichment analysis provided preliminary evidence of related signaling pathways. Our findings provide a new perspective on risk stratification and individualized precision therapy for CM.

Comprehensive analysis of tertiary lymphoid structures-related genes for prognostic prediction, molecular subtypes and immune infiltration in gastric cancer.

Gastric cancer (GC) is a highly heterogeneous malignancy and survival rates of advanced GC patients are unsatisfactory. Tertiary lymphoid structures (TLS) are recently identified as lymphoid-like structures that are directly related to tumor prognosis and immune response. However, the association of tertiary lymphoid structures-related genes (TLS-RGs) with prognosis and immune response in GC remains unclear. In our study, a comprehensive analysis of the role of TLS-RGs in GC was performed based on public data, and the difference of TLS-RGs expression, TLS-RGs mutation frequency, pathway enrichment, differentially expressed gene, immune landscape, immunotherapy and drug sensitivity was analyzed. We found that TLS-RGs were altered in GC in terms of expression and mutation. The difference of survival, immune landscape and enrichment pathway exists between TLS clusters. Immune checkpoint differences were also evident between gene clusters. The grouping by TLS score indicated that patients in the low TLS score group had a better prognosis and a lower degree of immune escape. For immunotherapy, the low TLS score group showed better outcomes than the high TLS score group. Sensitivity to chemotherapeutic agents differed between TLS score groups. In conclusion, we comprehensively analyzed the role of TLS-RGs in GC, constructed nomogram that can accurately predict the prognosis of GC patients, and the TLS score can reflect the immune landscape of patients, providing the possibility of personalized design of immunotherapy and targeted drug therapy for GC patients.

Single-cell transcriptome sequencing of B-cell heterogeneity and tertiary lymphoid structure predicts breast cancer prognosis and neoadjuvant therapy efficacy.

BACKGROUND: Breast cancer (BC) is a highly heterogeneous disease, and although immunotherapy has recently increased patient survival in a number of solid and hematologic malignancies, most BC subtypes respond poorly to immune checkpoint blockade therapy (ICB). B cells, particularly those that congregate in tertiary lymphoid structures (TLS), play a significant role in antitumour immunity. However, B-cell heterogeneity at single-cell resolution and its clinical significance with TLS in BC need to be explored further. METHODS: Primary tumour lesions and surrounding normal tissues were taken from 14 BC patients, totaling 124,587 cells, for single-cell transcriptome sequencing and bioinformatics analysis. RESULTS: Based on the usual markers, the single-cell transcriptome profiles were classified into various clusters. A thorough single-cell study was conducted with a focus on tumour-infiltrating B cells (TIL-B) and tumour-associated neutrophils (TAN). TIL-B was divided into five clusters, and unusual cell types, such as follicular B cells, which are strongly related to immunotherapy efficacy, were identified. In BC, TAN and TIL-B infiltration are positively correlated, and at the same time, compared with TLS-high, TAN and TIL-B in TLS-low group are significantly positively correlated. CONCLUSIONS: In conclusion, our study highlights the heterogeneity of B cells in BC, explains how B cells and TLS contribute significantly to antitumour immunity at both the single-cell and clinical level, and offers a straightforward marker for TLS called CD23. These results will offer more pertinent information on the applicability and effectiveness of tumour immunotherapy for BC.

Genomic properties and clinical outcomes associated with tertiary lymphoid structures in patients with breast cancer.

Tertiary lymphoid structures (TLSs) play a crucial role in determining prognosis and response to immunotherapy in several solid malignancies. Nevertheless, the effect of TLS-associated gene signature based on The Cancer Genome Atlas (TCGA) cohort in patients with breast cancer (BRCA) remains controversial. Based on TCGA-BRCA dataset (n = 866), 9-gene was identified to construct an TLS signature and further analyzed its prognostic value. Then, we explored the relationship of this TLS signature with molecular subtype, immune microenvironment, tumor mutational burden (TMB). High-TLS signature patients had a better overall survival (OS) than low-TLS signature patients, consistent with the results in the METABRIC cohort. Multivariate analysis revealed that TLS signature remained an independent prognostic indicator for OS. In addition, we established a nomogram with the integration of TLS signature and other independent variables to predict individual risk of death. The comprehensive results showed that patients with high TLS signature benefit from immunotherapy; the signature was also correlated with inhibition of cell proliferation pathways, low TP53 mutation rate, high infiltration of B cells, CD8 + T cells, CD4 + T cells, and M1 macrophages. Therefore, TLS signature is a promising biomarker to distinguish the prognosis and immune microenvironment in BRCA.

Somatic mutation profiling, tumor-infiltrating leukocytes, tertiary lymphoid structures and PD-L1 protein expression in HER2-amplified colorectal cancer.

The status of human epidermal growth factor receptor 2 (HER2) for the prognosis in colorectal cancer (CRC) is controversial, and the characteristics of the somatic mutation spectrum, tumor-infiltrating leukocytes, tertiary lymphoid structures and PD-L1 protein are unknown in HER2-amplified colorectal cancer (HACC). In order to explore these characteristics along with their correlation with clinicopathological factors and prognosis in HACC. Samples of 812 CRC patients was collected. After immunohistochemistry (IHC), 59 of 812 were found to be HER2-positive, then 26 of 59 samples were further determined to be HER2 amplification by fluorescence in situ hybridization (FISH). Somatic mutation profiling of HACC was analysed using whole exome sequencing (WES). Multiplex fluorescence immunohistochemistry (mIHC) was used for tumor-infiltrating leukocytes and tertiary lymphoid structures (TLSs), while PD-L1 protein was detected by IHC. Our results indicate that the detection rates of HER2 positivity by IHC and FISH were 7.3% and 3.2% respectively, and HER2 amplification is correlated with distant tumour metastasis. The somatic mutation profiling revealed no differences between HACC and HER2-negative CRC. However, TP 53 strongly correlated with poor prognosis in HACC. Furthermore, tumor-infiltrating T cells and TLSs in the tumor immune microenvironment, as well as PD-L1 expression, were higher in HACC than in HER2-negative controls. However, none of them were associated with the prognosis of HACC. In all, HER2 amplification is correlated with distant metastasis and TP53 gene mutation may be a potential protective mechanism of HACC.

The roles of tertiary lymphoid structures in chronic diseases.

Tertiary lymphoid structures (TLSs) are ectopic lymphoid tissues that drive antigen-specific immune responses at sites of chronic inflammation. Unlike secondary lymphoid organs such as lymph nodes, TLSs lack capsules and have their own unique characteristics and functions. The presumed influence of TLSs on the disease course has led to widespread interest in obtaining a better understanding of their biology and function. Studies using single-cell analyses have suggested heterogeneity in TLS composition and phenotype, and consequently, functional correlates with disease progression are sometimes conflicting. The presence of TLSs correlates with a favourable disease course in cancer and infection. Conversely, in autoimmune diseases and chronic age-related inflammatory diseases including chronic kidney disease, the presence of TLSs is associated with a more severe disease course. However, the detailed mechanisms that underlie these clinical associations are not fully understood. To what extent the mechanisms of TLS development and maturation are shared across organs and diseases is also still obscure. Improved understanding of TLS development and function at the cellular and molecular levels may enable the exploitation of these structures to improve therapies for chronic diseases, including chronic kidney disease.

The impact of tertiary lymphoid structures on clinicopathological, genetic and gene expression characteristics in lung adenocarcinoma.

INTRODUCTION: Tertiary lymphoid structures (TLS) are observed in several cancers and are associated with favorable prognosis. This study aimed to examine the clinicopathological, genetic, and gene expression profiles of lung adenocarcinoma patients with TLS. METHODS: A total of 112 patients with pathological stage IB lung adenocarcinoma who underwent complete resection between 2011 and 2015 were enrolled in this study. We investigated whether TLS correlated with prognosis and programmed death-ligand 1 (PD-L1) expression. Furthermore, the correlation of TLS with tumor mutation burden (TMB) and genetic mutations was evaluated in patients for whom whole-exon sequencing data were available. In addition, using the Cancer Genome Atlas Lung Adenocarcinoma (TCGA-LUAD) dataset, gene expression analysis according to the TLS status was performed. RESULTS: Among the 112 patients, 49 were TLS-positive (TLS+). TLS+ correlated with longer recurrence-free survival (RFS) than TLS-negative cases (TLS-) (hazard ratio [HR], 0.47; 95 % confidence interval [CI]: 0.23-0.88, p = 0.02). In the multivariate analysis, TLS was a better independent prognostic factor for RFS (HR 0.37, 95 %CI 0.18-0.72, p < 0.01). PD-L1 expression was not significantly different between TLS+ and TLS- patients (p = 0.54). TMB in TLS+ was similar to that in TLS- patients (p = 0.39); however, it tended to be lower than that in TLS- especially among smokers (p = 0.07). In gene expression analysis, RNA expression of chemokines related to lymph node formation, such as CXCL13, CCL19 and CCL21, was significantly higher, and biological processes such as positive regulation of humoral immune response and regulation of antigen receptor-mediated signaling pathway were enhanced in TLS+. CONCLUSIONS: TLS was a favorable prognostic factor and was not associated with PD-L1 expression in patients with lung adenocarcainoma. Moreover, gene expression analysis indicated that TLS is a site for the generation and regulation of antitumor immune responses.

Protective effect of tertiary lymphoid structures against hepatocellular carcinoma: New findings from a genetic perspective.

Background: Tertiary lymphoid structures (TLS) have an effect on hepatocellular carcinoma (HCC), but the underlying mechanism remains to be elucidated. Methods: Intratumoral TLS (iTLS) was classified in the Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) cohort using pathological sections from the Cancer Digital Slide Archive. Univariate and multivariate Cox regression analyses were performed to validate the effect of iTLS on overall survival (OS), relapse-free survival (RFS), and disease-free survival (DFS). The genes differentially expressed between the iTLS-negative and iTLS-positive groups were analyzed in combination with sequencing data. Gene set enrichment analysis (GSEA) was used to explore the signaling pathways affected by these differentially expressed genes. The random forest algorithm was used to identify genes with the highest correlation with the iTLS in the training set. Multivariate logistic regression was used to build a model to predict iTLS in tissue samples. Spearman's correlation was used to analyze the relationship between TLS-associated chemokines and signature genes, and CIBERSORT was used to calculate immune infiltration scores. Copy number variation and its relationship with immune cell infiltration and signature genes were assessed using the gene set cancer analysis (GSCA). The Correlation R package was used for gene ontology (GO), disease ontology (DO), and gene mutation analyses. The GSCA was used for drug sensitivity analysis. LASSO regression was used to build prognostic models, and external data were used to validate the models. Results: There were 218 positive and 146 negative samples for iTLS. iTLS was significantly associated with better RFS and DFS according to Cox regression analysis. Twenty signature genes that were highly associated with iTLS positivity were identified. GO and mutation analyses revealed that the signature genes were associated with immunity. Most signature genes were sensitive to immune checkpoint inhibitors. Risk scores calculated using a characteristic gene-based prognostic model were found to be an independent prognostic factor for OS. Conclusions: The improvement of RFS in HCC by iTLS was not limited to the early period as previously reported. iTLS improved DFS in patients. Characteristic genes are closely related to the formation of iTLS and TLS chemokines in HCC. These genes are closely related to immunity in terms of cellular infiltration, biological functions, and signaling pathways. Most are sensitive to immune checkpoint inhibitors, and their expression levels can affect prognosis.

The association of immune cell infiltration and prognostic value of tertiary lymphoid structures in gastric cancer.

Tertiary lymphoid structures (TLS) are lymphoid aggregates in tumor tissues and their potential significance in clinical applications has not been fully elucidated in gastric cancer. We evaluated TLS and tumor-infiltrating immune cells using H&E and immunohistochemistry staining in the recruited patients with gastric cancer. The prognostic value of TLS was evaluated by Kaplan-Meier analysis and further validated using gene expression profiling. The alterations in gene mutation, copy number variance, and DNA methylation across the TLS signature subtypes were analyzed based on the Cancer Genome Atlas cohort. High TLS density was associated with improved overall survival and disease-free survival. A combination of TLS density and TNM stage obtained higher prognostic accuracy than the TNM stage alone. Tumors with high TLS density showed significantly higher infiltration of CD3+, CD8+, and CD20+ cells but lower infiltration of CD68+ cells. Transcriptomics analysis demonstrated that high TLS signature status was positively associated with the activation of inflammation-related and immune-related pathways. Multi-omics data showed a distinct landscape of somatic mutations, copy number variants, and DNA methylation across TLS signature subtypes. Our results indicated that TLS might link with enhanced immune responses, and represent an independent and beneficial predictor of resected gastric cancer. Multi-omics analysis further revealed key tumor-associated molecular alterations across TLS signature subtypes, which might help explore the potential mechanism of the interaction between TLS formation and cancer cells.