The prognostic value and molecular properties of tertiary lymphoid structures in oesophageal squamous cell carcinoma

Computational methods for metastasis detection in lymph nodes and characterization of the metastasis-free lymph node microarchitecture: A systematic-narrative hybrid review

Background

Histological examination of tumor draining lymph nodes (LNs) plays a vital role in cancer staging and prognostication. However, as soon as a LN is classed as metastasis-free, no further investigation will be performed and thus, potentially clinically relevant information detectable in tumor-free LNs is currently not captured.

Objective

To systematically study and critically assess methods for the analysis of digitized histological LN images described in published research.

Methods

A systematic search was conducted in several public databases up to December 2023 using relevant search terms. Studies using brightfield light microscopy images of hematoxylin and eosin or immunohistochemically stained LN tissue sections aiming to detect and/or segment LNs, their compartments or metastatic tumor using artificial intelligence (AI) were included. Dataset, AI methodology, cancer type, and study objective were compared between articles.

Results

A total of 7201 articles were collected and 73 articles remained for detailed analyses after article screening. Of the remaining articles, 86% aimed at LN metastasis identification, 8% aimed at LN compartment segmentation, and remaining focused on LN contouring. Furthermore, 78% of articles used patch classification and 22% used pixel segmentation models for analyses. Five out of six studies (83%) of metastasis-free LNs were performed on publicly unavailable datasets, making quantitative article comparison impossible.

Conclusions

Multi-scale models mimicking multiple microscopy zooms show promise for computational LN analysis. Large-scale datasets are needed to establish the clinical relevance of analyzing metastasis-free LN in detail. Further research is needed to identify clinically interpretable metrics for LN compartment characterization.

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.

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.

Impact of tertiary lymphoid structures on prognosis and therapeutic response in pancreatic ductal adenocarcinoma

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is known to have a heterogeneous desmoplastic tumour microenvironment (TME) with a large number of immunosuppressive cells. Recently, high B-cell infiltration in PDAC has received growing interest as a potential therapeutic target.

METHODS

Our literature review summarises the characteristics of tumour-associated tertiary lymphoid structures (TLSs) and highlight the key studies exploring the clinical outcomes of TLSs in PDAC patients and the direct effect on the TME.

RESULTS

The location, density and maturity stages of TLSs within tumours play a key role in determining the prognosis and is a new emerging target in cancer immunotherapy.

DISCUSSION

TLS development is imperative to improve the prognosis of PDAC patients. In the future, studying the genetics and immune characteristics of tumour infiltrating B cells and TLSs may lead towards enhancing adaptive immunity in PDAC and designing personalised therapies.

Tertiary lymphoid structures associated with enhanced anti-tumor immunity and favorable prognosis in cervical squamous carcinoma

BACKGROUND

Cervical squamous carcinoma (CESC) is the main subtype of cervical cancer. Unfortunately, there are presently no effective treatment options for advanced and recurrent CESC. Tertiary lymphoid structures (TLSs) are clusters of lymphoid cells that resemble secondary lymphoid organs; nevertheless, there is no summary of the clinical importance of TLS in CESC.

METHODS

A large set of transcriptomic and single-cell RNA-sequencing (scRNA-seq) datasets were used to analyze the pattern of TLS and its immuno-correlations in CESC. Additionally, an independent in-house cohort was collected to validate the correlation between TLS and TME features.

RESULTS

In the current study, we found that the presence of TLS could predict better prognosis in CESC and was correlated with the activation of immunological signaling pathways and enrichment of immune cell subpopulations. In addition, TLS was associated with reduced proliferation activity in tumor cells, indicating the negative correlation between TLS and the degree of malignancy. Last but not least, in two independent immunotherapy cohorts, tumors with the presence of TLS were more sensitive to immunotherapy.

CONCLUSION

Overall, TLS is related to an inflamed TME and identified immune-hot tumors, which could be an indicator for the identification of immunological features in CESC.

Tertiary lymphoid structures in cancer: maturation and induction

Tertiary lymphoid structure (TLS) is an ectopic lymphocyte aggregate formed in peripheral non-lymphoid tissues, including inflamed or cancerous tissue. Tumor-associated TLS serves as a prominent center of antigen presentation and adaptive immune activation within the periphery, which has exhibited positive prognostic value in various cancers. In recent years, the concept of maturity regarding TLS has been proposed and mature TLS, characterized by well-developed germinal centers, exhibits a more potent tumor-suppressive capacity with stronger significance. Meanwhile, more and more evidence showed that TLS can be induced by therapeutic interventions during cancer treatments. Thus, the evaluation of TLS maturity and the therapeutic interventions that induce its formation are critical issues in current TLS research. In this review, we aim to provide a comprehensive summary of the existing classifications for TLS maturity and therapeutic strategies capable of inducing its formation in tumors.

Artificial intelligence-driven prognostic system for conception prediction and management in intrauterine adhesions following hysteroscopic adhesiolysis: a diagnostic study using hysteroscopic images

Introduction

Intrauterine adhesions (IUAs) caused by endometrial injury, commonly occurring in developing countries, can lead to subfertility. This study aimed to develop and evaluate a DeepSurv architecture-based artificial intelligence (AI) system for predicting fertility outcomes after hysteroscopic adhesiolysis.

Methods

This diagnostic study included 555 intrauterine adhesions (IUAs) treated with hysteroscopic adhesiolysis with 4,922 second-look hysteroscopic images from a prospective clinical database (IUADB, NCT05381376) with a minimum of 2 years of follow-up. These patients were randomly divided into training, validation, and test groups for model development, tuning, and external validation. Four transfer learning models were built using the DeepSurv architecture and a code-free AI application for pregnancy prediction was also developed. The primary outcome was the model's ability to predict pregnancy within a year after adhesiolysis. Secondary outcomes were model performance which evaluated using time-dependent area under the curves (AUCs) and C-index, and ART benefits evaluated by hazard ratio (HR) among different risk groups.

Results

External validation revealed that using the DeepSurv architecture, InceptionV3+ DeepSurv, InceptionResNetV2+ DeepSurv, and ResNet50+ DeepSurv achieved AUCs of 0.94, 0.95, and 0.93, respectively, for one-year pregnancy prediction, outperforming other models and clinical score systems. A code-free AI application was developed to identify candidates for ART. Patients with lower natural conception probability indicated by the application had a higher ART benefit hazard ratio (HR) of 3.13 (95% CI: 1.22-8.02, p = 0.017).

Conclusion

InceptionV3+ DeepSurv, InceptionResNetV2+ DeepSurv, and ResNet50+ DeepSurv show potential in predicting the fertility outcomes of IUAs after hysteroscopic adhesiolysis. The code-free AI application based on the DeepSurv architecture facilitates personalized therapy following hysteroscopic adhesiolysis.

Heterogeneity of Cervical Cancer-Associated Tertiary Lymphoid Structures (TLSs) and Their Specific Interrelation With Clinicopathological Parameters

OBJECTIVE

The study investigates morphological variants of tertiary lymphoid structures (TLSs) in relation to cervical cancer development, from intraepithelial neoplastic lesions to invasive carcinomas with locoregional lymph node metastases.

MATERIALS AND METHODS

This retrospective analysis comprised 100 cervical cancer cases who had had total hysterectomy with lymphadenectomy in the Obstetrics and Gynecology Clinic of the Municipal Emergency Clinical Hospital of Timisoara, Romania, from 2020 to 2023. Bilateral ilio obturator lymphadenectomy and total hysterectomy were used to acquire biopsy samples. The presence of germinal centers, other stromal structures, TLS density, topography relative to the tumor lesion, and malignant cell islets are used to evaluate and classify TLS.

RESULTS

We first globally evaluated the total number of TLSs (TLS.T). We observed topographically two places in the cervical stroma: TLS immediately peritumorally positioned and TLS away from tumor lesions. Invasive carcinomas have bigger superficial TLSs with a well-defined germinal center. As they approached the tumor, TLSs increased in size and density. We also detected a special type of TLS associated with nerve fibers, which we named tertiary lymphoid structures associated with nerves (TLS.N). The total number of TLSs did not correlate with age, but 85.71% of patients presenting TLS.N were aged between 59 and 72 years old. Our findings showed a strong correlation between age (postmenopausal, p = 0.005) and TLS-N presence. Similarly, TLS parameters evolved with tumor differentiation. Only in the TLS.N group did the tumoral grading (G) 3 correlate with TLS (p = 0.041), while TLS.T did not correlate with G. All TLS.N. patients, except one, had lymphovascular invasion and massive histiocytosis. On the first point, TLS.N correlated with lymphovascular invasion (p = 0.032).

CONCLUSION

Tertiary lymphoid structures associated with nerves have not been previously reported in cervical cancer, and their effects on prognosis and aggression are unknown. There was a substantial association between TLSs.N presence and age over 60, suggesting it is exclusive to menopausal women. They were also substantially connected with lymphovascular invasion and G3, suggesting they may be a poor cervical cancer prognostic factor.

Deep learning on tertiary lymphoid structures in hematoxylin-eosin predicts cancer prognosis and immunotherapy response

Tertiary lymphoid structures (TLSs) have been associated with favorable immunotherapy responses and prognosis in various cancers. Despite their significance, their quantification using multiplex immunohistochemistry (mIHC) staining of T and B lymphocytes remains labor-intensive, limiting its clinical utility. To address this challenge, we curated a dataset from matched mIHC and H&E whole-slide images (WSIs) and developed a deep learning model for automated segmentation of TLSs. The model achieved Dice coefficients of 0.91 on the internal test set and 0.866 on the external validation set, along with intersection over union (IoU) scores of 0.819 and 0.787, respectively. The TLS ratio, defined as the segmented TLS area over the total tissue area, correlated with B lymphocyte levels and the expression of CXCL13, a chemokine associated with TLS formation, in 6140 patients spanning 16 tumor types from The Cancer Genome Atlas (TCGA). The prognostic models for overall survival indicated that the inclusion of the TLS ratio with TNM staging significantly enhanced the models' discriminative ability, outperforming the traditional models that solely incorporated TNM staging, in 10 out of 15 TCGA tumor types. Furthermore, when applied to biopsied treatment-naïve tumor samples, higher TLS ratios predicted a positive immunotherapy response across multiple cohorts, including specific therapies for esophageal squamous cell carcinoma, non-small cell lung cancer, and stomach adenocarcinoma. In conclusion, our deep learning-based approach offers an automated and reproducible method for TLS segmentation and quantification, highlighting its potential in predicting immunotherapy response and informing cancer prognosis.

Analyzing the associations between tertiary lymphoid structures and postoperative prognosis, along with immunotherapy response in gastric cancer: findings from pooled cohort studies

BACKGROUND

The clinical significance of tertiary lymphoid structure (TLS) in gastric cancer (GC) was uncertain.

METHODS

A systematic search was performed in public databases for eligible studies as of April 2, 2023. Meta-analyses were performed to interrogate the associations between TLS levels and prognosis and immunotherapy response of GC. Bioinformatic analyses based on the nine-gene signature of TLS were further conducted to capture the biological underpinnings.

RESULTS

Eleven studies containing 4224 GC cases were enrolled in the meta-analysis. TLS levels positively correlated with smaller tumor size, earlier T stage and N stage. Moreover, higher TLS levels were detected in diffuse and mix subtypes of GC (P < 0.001). Higher TLS levels strongly predicted favorable postoperative overall survival of GC, with HR of 0.36 (95%CI 0.26-0.50, P < 0.001) and 0.55 (95%CI 0.45-0.68, P < 0.001) of univariate and multivariate Cox analysis, respectively. Higher TLS levels were also in favor of the treatment response of anti-PD-1 inhibitors as later-line therapy of GC. TLS levels positively correlated with immune effector cells infiltration, diversity and richness of T cell receptor and B cell receptor repertoire, immune checkpoint genes expression, and immune-related genes mutation of GC in the TCGA-STAD cohort, representing higher immunogenicity and immunoactivity. Moreover, moderate accuracy of TLS levels in predicting benefit from anti-PD-1 inhibitors in the PRJEB25780 cohort was also validated (AUC 0.758, 95%CI 0.583-0.933), higher than the microsatellite instability-score and Epstein-Barr virus status.

CONCLUSIONS

TLS levels demonstrated potential in predicting the postoperative prognosis and immunotherapy response of GC.

Tertiary lymphoid structures in cancer: immune mechanisms and clinical implications

Cancer is a major cause of death globally, and traditional treatments often have limited efficacy and adverse effects. Immunotherapy has shown promise in various malignancies but is less effective in tumors with low immunogenicity or immunosuppressive microenvironment, especially sarcomas. Tertiary lymphoid structures (TLSs) have been associated with a favorable response to immunotherapy and improved survival in cancer patients. However, the immunological mechanisms and clinical significance of TLS in malignant tumors are not fully understood. In this review, we elucidate the composition, neogenesis, and immune characteristics of TLS in tumors, as well as the inflammatory response in cancer development. An in-depth discussion of the unique immune characteristics of TLSs in lung cancer, breast cancer, melanoma, and soft tissue sarcomas will be presented. Additionally, the therapeutic implications of TLS, including its role as a marker of therapeutic response and prognosis, and strategies to promote TLS formation and maturation will be explored. Overall, we aim to provide a comprehensive understanding of the role of TLS in the tumor immune microenvironment and suggest potential interventions for cancer treatment.

Infiltrating characteristics and prognostic value of tertiary lymphoid structures in resected gastric neuroendocrine neoplasm patients

Objectives

Tertiary lymphoid structures (TLSs) are lymphocyte aggregates that play an anti-tumor role in most solid tumors. However, the functions of TLS in gastric neuroendocrine neoplasms (GNENs) remain unknown. This study aimed to determine the characteristics and prognostic values of TLS in resected GNEN patients.

Methods

Haematoxylin-eosin, immunohistochemistry (IHC) and multiple fluorescent IHC staining were used to assess TLS to investigate the correlation between TLSs and clinicopathological characteristics and its prognostic value.

Results

Tertiary lymphoid structures were identified in 84.3% of patients with GNEN. They were located in the stromal area or outside the tumor tissue and mainly composed of B and T cells. A high density of TLSs promoted an anti-tumor immune response in GNEN. CD15+ TANs and FOXP3+ Tregs in TLSs inhibited the formation of TLSs. High TLS density was significantly associated with prolonged recurrence-free survival (RFS) and overall survival (OS) of GNENs. Univariate and multivariate Cox regression analyses revealed that TLS density, tumor size, tumor-node-metastasis (TNM) stage and World Health Organisation (WHO) classification were independent prognostic factors for OS, whereas TLS density, tumor size and TNM stage were independent prognostic factors for RFS. Finally, OS and RFS nomograms were developed and validated, which were superior to the WHO classification and the TNM stage.

Conclusion

Tertiary lymphoid structures were mainly located in the stromal area or outside the tumor area, and high TLS density was significantly associated with the good prognosis of patients with GNEN. Incorporating TLS density into a nomogram may improve survival prediction in patients with resected GNEN.

Unravelling the role of long non-coding RNAs in modulating the Hedgehog pathway in cancer

Cancer is a multifactorial pathological condition characterized by uncontrolled cellular proliferation, genomic instability, and evasion of regulatory mechanisms. It arises from the accumulation of genetic mutations confer selective growth advantages, leading to malignant transformation and tumor formation. The intricate interplay between LncRNAs and the Hedgehog pathway has emerged as a captivating frontier in cancer research. The Hedgehog pathway, known for its fundamental roles in embryonic development and tissue homeostasis, is frequently dysregulated in various cancers, contributing to aberrant cellular proliferation, survival, and differentiation. The Hh pathway is crucial in organizing growth and maturation processes in multicellular organisms. It plays a pivotal role in the initiation of tumors as well as in conferring resistance to conventional therapeutic approaches. The crosstalk among the Hh pathway and lncRNAs affects the expression of Hh signaling components through various transcriptional and post-transcriptional processes. Numerous pathogenic processes, including both non-malignant and malignant illnesses, have been identified to be induced by this interaction. The dysregulation of lncRNAs has been associated with the activation or inhibition of the Hh pathway, making it a potential therapeutic target against tumorigenesis. Insights into the functional significance of LncRNAs in Hedgehog pathway modulation provide promising avenues for diagnostic and therapeutic interventions. The dysregulation of LncRNAs in various cancer types underscores their potential as biomarkers for early detection and prognostication. Additionally, targeting LncRNAs associated with the Hedgehog pathway presents an innovative strategy for developing precision therapeutics to restore pathway homeostasis and impede cancer progression. This review aims to elucidate the complex regulatory network orchestrated by LncRNAs, unravelling their pivotal roles in modulating the Hedgehog pathway and influencing cancer progression.

IGH repertoire analysis at scale: deciphering the complexity of B cell infiltration and migration in esophageal squamous cell carcinoma

Tumor-infiltrating B-lineage cells have become predictors of prognosis and immunotherapy responses in various cancers. However, limited knowledge about their infiltration and migration patterns has hindered the understanding of their anti-tumor functions. Here, we examined the immunoglobulin heavy chain (IGH) repertoires in 496 multi-regional tumor, 107 normal tissue, and 48 metastatic lymph node samples obtained from 107 patients with esophageal squamous cell carcinoma (ESCC). Our study revealed higher IgG-type B-lineage cells infiltration in tumors than in healthy tissue, which was associated with improved patient outcomes. Genes such as ACTN1, COL6A5, and pathways like focal adhesion, which shapes the physical structure of tumors, could affect B-lineage cell infiltration. Notably, the IGH sequence was used as an identity-tag to monitor B cell migration, and their infiltration schema within the tumor were depicted based on our multi-regional tumor specimens. This analysis revealed an escalation in B cell clones overlapped between metastatic lymph nodes and tumors. Therefore, the Lymph Node Activation Index was defined, which could predict the outcomes of patients with lymph node metastasis. This research introduces a novel framework for probing B cell infiltration and migration within the tumor microenvironment using large-scale transcriptome data, while simultaneously providing fresh perspectives on B cell immunology within ESCC.

Prognostic value of tertiary lymphoid structures (TLS) in digestive system cancers: a systematic review and meta-analysis

BACKGROUND

Existing literature suggests that tertiary lymphatic structure (TLS) is associated with the progression of cancer. However, the prognostic role of TLS in digestive system cancers remains controversial. This meta-analysis aims to synthesize currently available evidence in the association between TLS and the survival of digestive system cancers.

METHODS

We systematically searched three digital databases (PubMed, Embase, Web of Science) for articles published from database inception to December 23, 2022. Study selection criteria are based on PECO framework: P (population: patients with digestive system cancers), E (exposure: presence of TLS), C (comparator: absence of TLS), O (outcome: overall survival, OS; recurrence-free survival, RFS; disease-free survival, DFS). The Quality in Prognostic Studies (QUIPS) tool was used to assess risk of bias for included studies. The study protocol was registered with PROSPERO (CRD42023416307).

RESULTS

A total of 25 studies with 6910 patients were included into the final meta-analysis. Random-effects models revealed that the absence of TLS was associated with compromised OS, RFS, and DFS of digestive system cancers, with pooled hazard ratios (HRs) of 1.74 (95% CI: 1.50-2.03), 1.96 (95% CI: 1.58-2.44), and 1.81 (95% CI: 1.49-2.19), respectively. Subgroup analyses disclosed a stronger TLS-survival association for pancreatic cancer, compared with other digestive system cancers.

CONCLUSION

TLS may be of prognostic significance for digestive system cancers. More original studies are needed to further corroborate this finding.

Combined inflammatory parameters and tertiary lymphoid structure predict prognosis in patients with resectable non-small cell lung cancer treated with neoadjuvant chemoimmunotherapy

Introduction

Neoadjuvant chemoimmunotherapy shows great potential for patients with non-small cell lung cancer (NSCLC), but no clear prognostic markers have been identified. This study investigates the correlation between inflammatory parameters and the expression of tertiary lymphoid structures (TLS) and the predictive ability of inflammatory parameters combined with TLS for disease-free survival (DFS) in patients with resectable NSCLC receiving neoadjuvant chemotherapy.

Materials and methods

We retrospectively analyzed the clinical data and hematological parameters of 117 patients with NSCLC who underwent neoadjuvant chemoimmunotherapy and radical surgery. TLS were evaluated by observing H&E stained and immunohistochemically stained tissue sections. Univariate chi-square and multifactor logistic analyses were used to determine the correlation between hematological parameters and TLS. The Kaplan-Meier method, univariate and multivariate Cox regression analysis and constructed nomogram models were used to assess the prognostic value of the investigated parameters on DFS. Receiver operating characteristic (ROC) curves analyses were used to compare the performances of the three models.

Results

After logistic analysis, it was found that platelet-to-lymphocyte ratio (PLR) ≤288.78 (odds ratio OR=0.122, P=0.009) was an independent predictor of high TLS expression. The Cox regression analyses showed that Histology (HR=0.205, P=0.002), systemic immune inflammation index (SII) (HR=2.758, P=0.042) and TLS (HR=0.057, P<0.05) were independent prognostic factors in patients with NSCLC. The combined SII-TLS model was better than the single-indicator model in assessing the 1-year and 18-months DFS rates in patients with NSCLC.

Conclusion

Our study showed that PLR was an independent predictor of TLS and that both TLS and SII predicted prognosis in patients with neoadjuvant chemoimmunotherapy-resectable NSCLC; however, combining SII and TLS to assess DFS was more accurate than using either parameter alone.

Integrative analysis of tertiary lymphoid structures and immune microenvironment in patients with esophageal carcinoma

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) is one of the most common upper gastrointestinal malignancies worldwide. Tertiary lymphoid structures (TLS) are tumor-infiltrating immune cells aggregates coupled with stromal cells which are similar to secondary lymphoid organs. The objective of this study is to explore the predictive effects of two common genes associated with TLS models on prognosis and immunotherapy effects in ESCC patients.

METHODS

Clinical information for ESCC patients in the TCGA(The Cancer Genome Altas) cohort and GSE 53625 were collected. All of the samples were classified as either high score group or low score group based on two TLS signatures, and the association between TLS signatures and survival, clinical indicators, genomic burden, stemness indices analysis, tumor microenvironment and immunotherapy response were performed. Furthermore, the mature TLS was also assessed in ESCC tissue microarray.

RESULTS

In our study, we quantified the score of TLS_9 and TLS_12, respectively, reflecting the different statuses of TLS (TLS_9 = B and T cells in TLSs; TLS_12 = neogenesis of TLSs). Subsequently, we explored the effect of TLS score on ESCC tumor microenvironment quantified by multiple algorithms. We found that a correlation analysis indicated that TLS_9 and TLS_12 were all positively correlated with CD8+ T cell, NK cells, CD4+ T cells, M1 macrophages and so on. Meanwhile, some cells present a different correlation pattern of TLS_9 and TLS_12, including activated CD4+ memory T cells and Tgd cells. Immune-related analysis revealed that the TLS_12 and TLS_9 scores were all positively correlated with immune dysfunction, yet negatively correlated with immune exclusion. Following this, the biological roles of TLS_9 and TLS_12 scores were investigated. Also, we noticed that the TLS score could significantly affect the CAFs infiltration and be associated with the genomic burden and tumor stemness. In addition, we explored the prognostic value of mature TLS through tissue microarray (TMA). Our result displayed ESCC patients with the presence of mature TLS had a better prognosis than ESCC patients without it.

CONCLUSIONS

Our study indicated that ESCC patients with the presence of TLS had better outcomes and an inflamed immune microenvironment. In addition, both TLS-9 and TLS-12 gene signatures could be used as potential biomarkers for the immunotherapy of ESCC patients.

Tertiary lymphoid structures and cytokines interconnections: The implication in cancer immunotherapy

Tertiary lymphoid structures (TLSs) are organized aggregates of lymphocytes and antigen-presenting cells that develop in non-lymphoid tissues during chronic inflammation, resembling the structure and features of secondary lymphoid organs. Numerous studies have shown that TLSs may be an important source of antitumor immunity within solid tumors, facilitating T cell and B cell differentiation and the subsequent production of antitumor antibodies, which are beneficial for cancer prognosis and responses to immunotherapy. The formation of TLS relies on the cytokine signaling network between heterogeneous cell populations, such as stromal cells, lymphocytes and cancer cells. The coordinated action of various cytokines drives the complex process of TLS development. In this review, we will comprehensively describe the mechanisms by which various cytokines regulate TLS formation and function, and the recent advancements and therapeutic potential of exploiting these mechanisms to induce TLS as an emerging immunotherapeutic approach or to enhance existing immunotherapy.

Recent advancements in tumour microenvironment landscaping for target selection and response prediction in immune checkpoint therapies achieved through spatial protein multiplexing analysis

Immune checkpoint therapies have significantly advanced cancer treatment. Nevertheless, the high costs and potential adverse effects associated with these therapies highlight the need for better predictive biomarkers to identify patients who are most likely to benefit from treatment. Unfortunately, the existing biomarkers are insufficient to identify such patients. New high-dimensional spatial technologies have emerged as a valuable tool for discovering novel biomarkers by analysing multiple protein markers at a single-cell resolution in tissue samples. These technologies provide a more comprehensive map of tissue composition, cell functionality, and interactions between different cell types in the tumour microenvironment. In this review, we provide an overview of how spatial protein-based multiplexing technologies have fuelled biomarker discovery and advanced the field of immunotherapy. In particular, we will focus on how these technologies contributed to (i) characterise the tumour microenvironment, (ii) understand the role of tumour heterogeneity, (iii) study the interplay of the immune microenvironment and tumour progression, (iv) discover biomarkers for immune checkpoint therapies (v) suggest novel therapeutic strategies.

The prognostic value and molecular properties of tertiary lymphoid structures in oesophageal squamous cell carcinoma

BACKGROUND

Tertiary lymphoid structures (TLSs) play key roles in tumour adaptive immunity. However, the prognostic value and molecular properties of TLSs in oesophageal squamous cell carcinoma (ESCC) patients have not been studied.

METHODS

The prognostic values of the presence and maturation status of tumour-associated TLSs were determined in 394 and 256 ESCC patients from Sun Yat-sen University Cancer Center (Centre A) and the Cancer Hospital of Shantou University Medical College (Centre B), respectively. A deep-learning (DL) TLS classifier was established with haematoxylin and eosin (H&E)-stained slides using an inception-resnet-v2 neural network. Digital spatial profiling was performed to determine the cellular and molecular properties of TLSs in ESCC tissues.

RESULTS

TLSs were observed in 73.1% of ESCCs from Centre A via pathological examination of H&E-stained primary tumour slides, among which 42.9% were TLS-mature and 30.2% were TLS-immature tumours. The established DL TLS classifier yielded favourable sensitivities and specificities for patient TLS identification and maturation evaluation, with which 55.1%, 39.5% and 5.5% of ESCCs from Centre B were identified as TLS-mature, TLS-immature and TLS-negative tumours. Multivariate analyses proved that the presence of mature TLSs was an independent prognostic factor in both the Centre A and Centre B cohorts (p < .05). Increased proportions of proliferative B, plasma and CD4+ T helper (Th) cells and increased B memory and Th17 signatures were observed in mature TLSs compared to immature ones. Intratumoural CD8+ T infiltration was increased in TLS-mature ESCC tissues compared to mature TLS-absent tissues. The combination of mature TLS presence and high CD8+ T infiltration was associated with the best survival in ESCC patients.

CONCLUSIONS

Mature TLSs improve the prognosis of ESCC patients who underwent complete resection. The use of the DL TLS classifier would facilitate precise and efficient evaluation of TLS maturation status and offer a novel probability of ESCC treatment individualization.