Background The positive prediction of prognosis and immunotherapy within tertiary lymphoid structure (TLS) in cancerous tissue has been well demonstrated, including liver cancer. However, the relationship between TLS and prognosis in the peritumoral region of hepatocellular carcinoma (HCC) has received less attention. Few studies on whether TLS, as a typical representative of acquired immune cell groups, is associated with innate immune cells. The aim of this paper was to identify the prognostic role of peritumor TLS in HCC and to simply explore the relationship with neutrophils infiltration. Methods This study included cancerous and paracancerous tissue from 170 patients after surgical resection of HCC. TLS was examined and identified by pathological H&E examination, and the impact on prognosis was further classified by determination of total TLS area. Immunohistochemical staining of CD15+ neutrophils was also performed on half of the cases. The obtained results were validated by external public database, as TLS has been widely shown to be tagged with 12 chemokines. Results In peritumoral tissue, the TLS− group had better overall survival (OS) and disease‐free survival (DFS) outcomes compared with the TLS+ group. On the contrary, the intratumor TLS+ group showed better DFS outcomes. When further investigating the relationship between TLS area distribution and DFS, progressively worse prognosis was only found in the peritumor region with increasing TLS density (TLS− vs. TLS L vs. TLS H ). In addition, neutrophil infiltration increased in parallel with TLS density in the peritumoral region, which was not observed in the intratumoral region. Conclusions TLS might have a dual prognostic role in different regions of HCC. The abundance of peritumoral TLS is an independent influence of DFS. The inconsistent correlation between neutrophils and corresponding TLS in different regions may indicate different pathways of immune aggregation and may serve as an explanation for the different prognosis of TLS, which needs to be specifically explored.
Background: Tertiary lymphoid structures (TLSs) are formed by the aggregation of tumour-infiltrating lymphocytes (TILs), which is driven by chemokines or cytokines in the tumour microenvironment. Studies have shown that TLSs are associated with good prognosis in patients with various solid tumours and can improve patient responses to immunotherapy. However, the role of TLSs in hepatocellular carcinoma (HCC) remains controversial, and the underlying molecular mechanism is unclear. Methods: According to haematoxylin-eosin (HE) staining results, HCC patients in Xijing Hospital data and TCGA data were divided into TLS+ and TLS- groups, and Kaplan–Meier (KM) analysis was performed to assess overall survival (OS) and recurrence-free survival (RFS). Immunofluorescence (IF) and immunohistochemistry (IHC) were used to identify TILs in the TLS+ group. Lymphocyte-specific protein tyrosine kinase (LCK), a molecule involved in TLS formation, was explored in LinkedOmics. TILs were divided into two groups by drawing receiver operating characteristic (ROC) curves to calculate cut-off values. Spearman correlation analysis was used to calculate the correlation between LCK and TILs, and the molecular pathways by which LCK regulates immunotherapy were clarified through enrichment analysis. The half-maximal inhibitory concentration (IC50) distribution of sorafenib was observed in groups that varied in LCK expression. Results: According to the HE results, 61 cases in the Xijing Hospital cohort and 195 cases in the TCGA cohort had TLSs, while 89 cases and 136 cases did not. The KM results showed that TLSs had no effect on the OS of HCC patients but significantly affected RFS. The IF/IHC results showed that higher TIL numbers in TLSs were correlated with better prognosis in HCC patients. Spearman correlation analysis showed that LCK expression was positively correlated with TIL numbers. Enrichment analysis showed that upregulation of LCK expression mainly regulated the cytokine signalling pathway, the chemokine signalling pathway and T-cell activation. The IC50 scores of sorafenib in HCC patients with high LCK expression were lower, and the sensitivity was higher. Conclusion: TLSs mainly affected the early RFS of HCC patients but had no effect on OS. The high expression of the TLS formation-related gene LCK can increase the sensitivity of HCC patients to ICIs.
Tertiary lymphoid structures (TLSs) are organized aggregates of immune cells found in the tumor microenvironment. TLS can influence primary hepatic carcinoma (PHC) occurrence and have an active role in cancer. TLS can promote or inhibit the growth of PHC depending on their location, and although available findings are controversial, they suggest that TLS have a protective role in PHC tissues and a non-protective role in paracancerous tissues. In addition, the cellular composition of TLS can also influence the outcome of PHC. As an immunity marker, TLS can act as a marker of immunotherapy to predict its effect and help to identify patients who will respond well to immunotherapy. Modulation of TLS formation through the use of chemokines/cytokines, immunotherapy, or induction of high endothelial vein to interfere with tumor growth has been studied extensively in PHC and other cancers. In addition, new tools such as genetic interventions, cellular crosstalk, preoperative radiotherapy, and advances in materials science have been shown to influence the prognosis of malignant tumors by modulating TLS production. These can also be used to develop PHC treatment.
BackgroundTertiary lymphoid structures (TLS) have an effect on hepatocellular carcinoma (HCC), but the underlying mechanism remains to be elucidated.MethodsIntratumoral 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.ResultsThere 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.ConclusionsThe 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.
Immunotherapy has shown strong anti-tumor activity in a subset of patients. However, many patients do not benefit from the treatment, and there is no effective method to identify sensitive immunotherapy patients. Cuproptosis as a non-apoptotic programmed cell death caused by excess copper, whether it is related to tumor immunity has attracted our attention. In the study, we constructed the prognostic model of 9 cuproptosis-related LncRNAs (crLncRNAs) and assessed its predictive capability, preliminarily explored the potential mechanism causing treatment sensitivity difference between the high-/low-risk group. Our results revealed that the risk score was more effective than traditional clinical features in predicting the survival of HCC patients (AUC = 0.828). The low-risk group had more infiltration of immune cells (B cells, CD8+ T cells, CD4+ T cells), mainly with anti-tumor immune function (p < 0.05). It showed higher sensitivity to immune checkpoint inhibitors (ICIs) treatment (p < 0.001) which may exert the effect through the AL365361.1/hsa-miR-17-5p/NLRP3 axis. In addition, NLRP3 mutation-sensitive drugs (VNLG/124, sunitinib, linifanib) may have better clinical benefits in the high-risk group. All in all, the crLncRNAs model has excellent specificity and sensitivity, which can be used for classifying the therapy-sensitive population and predicting the prognosis of HCC patients.
This study aims to construct immunogenic cell death(ICD) related LncRNA signature to explore the prognosis and immune infiltration of hepatocellular carcinoma(HCC) patients. The Cancer Genome Atlas (TCGA) database was randomly divided into training and test sets, while co-expression analysis was used to find relevant LncRNA. Next, the least absolute choice operator (LASSO) and Cox regression analysis were performed, and a total of 6 relevant LncRNAs (GAL, HOXD13, CTSV, SLC6A3, NR0B1, DCAF8L1) were found to establish the signature. Kaplan-Meier analysis showed that expression of high-risk LncRNAs scores correlated with poor overall survival of HCCs. Then, a prognostic nomogram containing LncRNA features and clinicopathological features was constructed, which verified the good predictive performance of the model on the prognosis of HCC patients. Immune-related functions differed significantly between high-risk and low-risk groups. Tumor mutation burden (TMB) and immune checkpoint expression also differed significantly between the two groups. Finally, HCC patients with high-risk scores were more sensitive to several chemotherapy drugs. In conclusion, we have developed a new HCC classification system based on the characteristics of ICD, which has important clinical implications for assessing the prognosis and treatment of HCC patients.
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