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OX40 expression in hepatocellular carcinoma is associated with a distinct immune microenvironment, specific mutation signature, and poor prognosis.

ABSTRACT: Immunotherapy's effect against hepatocellular carcinoma (HCC) is hampered by immunosuppressive mechanisms in the tumor microenvironment. We assessed the clinicopathologic and biologic relevance of OX40, a costimulatory molecular expressed by regulatory T cells (Tregs), in HCC. We analyzed the immunohistochemistry data of 316 patients treated at West China Hospital (WCH) and the RNA sequencing data of 370 patients in The Cancer Genome Atlas (TCGA) to determine the clinicopathologic significance of OX40 in HCC. We also assessed associations between OX40 and multiple immune-related markers. Using the TCGA data, we further characterized the transcriptome, immune cell functions, and mutation signature related to OX40. We found that OX40 expression was higher in HCC than in adjacent liver tissue. In the WCH set, 136 (43%) patients had high-OX40 expression, whereas in the TCGA set, 247 (67%) patients had high-OX40 expression as determined by the X-tile program. High-OX40 expression was associated with high serum alpha-fetoprotein level, vascular invasion, and shorter survival. The prognostic significance of OX40 was validated in additional cohorts. OX40 expression was also associated with CD8A, CD68, LAG3, TIM-3, and PD-1 expression. High-OX40 expression tumors were characterized by upregulated cytokines and exhaustion-specific markers. Analysis of the enrichment data of immune cell types indicated that OX40 expression was associated with the functions of macrophages, plasmacytoid dendritic cells, and co-inhibitory T cells. Finally, high-and low-OX40 expressions were associated with mutations in AKT/mTOR and Wnt/?-catenin signaling, respectively. These results indicate that high-OX40 expression represents the activation of multiple immunosuppressive pathways and provide a rationale for the therapeutic targeting OX40 in HCC patients.

SUBMITTER: Xie K

PROVIDER: S-EPMC5889283 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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OX40 expression in hepatocellular carcinoma is associated with a distinct immune microenvironment, specific mutation signature, and poor prognosis.

Xie Kunlin K Xu Lin L Wu Hao H Liao Haotian H Luo Lin L Liao Mingheng M Gong Jianping J Deng Yang Y Yuan Kefei K Wu Hong H Zeng Yong Y

Oncoimmunology 20180306 4

Immunotherapy's effect against hepatocellular carcinoma (HCC) is hampered by immunosuppressive mechanisms in the tumor microenvironment. We assessed the clinicopathologic and biologic relevance of OX40, a costimulatory molecular expressed by regulatory T cells (Tregs), in HCC. We analyzed the immunohistochemistry data of 316 patients treated at West China Hospital (WCH) and the RNA sequencing data of 370 patients in The Cancer Genome Atlas (TCGA) to determine the clinicopathologic significance o ...[more]

PMID: 29632718

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Project description:Hepatocellular carcinoma (HCC) is one of the malignant tumors with high mortality and a worse prognosis globally. Necroptosis is a programmed death mediated by receptor-interacting Protein 1 (RIP1), receptor-interacting Protein 1 (RIP3), and Mixed Lineage Kinase Domain-Like (MLKL). Our study aimed to create a new Necroptosis-related lncRNAs (NRlncRNAs) risk model that can predict survival and tumor immunity in HCC patients. The RNA expression and clinical data originated from the TCGA database. Pearson correlation analysis was applied to identify the NRlncRNAs. The LASSO-Cox regression analysis was employed to build the risk model. Next, the ROC curve and the area under the Kaplan-Meier curve were utilized to evaluate the accuracy of the risk model. In addition, based on the two groups of risk model, we performed the following analysis: clinical correlation, differential expression, PCA, TMB, GSEA analysis, immune cells infiltration, and clinical drug prediction analysis. Plus, qRT-PCR was applied to test the expression of genes in the risk model. Finally, a prognosis model covering six necroptosis-related lncRNAs was constructed to predict the survival of HCC patients. The ROC curve results showed that the risk model possesses better accuracy. The 1, 3, and 5-years AUC values were 0.746, 0.712, and 0.670, respectively. Of course, we also observed that significant differences exist in the following analysis, such as functional signaling pathways, immunological state, mutation profiles, and medication sensitivity between high-risk and low-risk groups of HCC patients. The result of qRT-PCR confirmed that three NRlncRNAs were more highly expressed in HCC cell lines than in the normal cell line. In conclusion, based on the bioinformatics analysis, we constructed an NRlncRNAs associated risk model, which predicts the prognosis of HCC patients. Although our study has some limitations, it may greatly contribute to the treatment of HCC and medical progression.

Project description:Little is known on the relationship between the expression of pyroptosis related genes (PRGs) and prognosis of hepatocellular carcinoma (HCC). In this study, a specific PRGs prognostic model was developed with an aim to improve therapeutic efficiency among HCC patients. In total, 42 PRGs that were differentially expressed between HCC tissues and adjacent tissues and we exhibited the mutation frequency, classification, the location of copy number variation (CNV) alteration and the CNV variation frequency of PRGs. Two clusters were distinguished by the consensus clustering analysis based on the 42 differentially expressed genes (DEGs). There were significant differences in clinical features including T stage, grade, gender, and stage among different clusters. Kaplan-Meier curve analysis showed that cluster 1 had a better prognosis than cluster 2. The prognostic value of PRGs for survival was evaluated to construct a multigene signature using The Cancer Genome Atlas (TCGA) cohort. Based on the univariate analysis and multivariate analysis, a 10-gene signature was built and all HCC patients in the TCGA cohort were divided into low-risk group and high-risk group. HCC patients in the high-risk group showed significantly lower survival possibilities than those in the low-risk group (P < 0.001). Utilizing the median risk score from the TCGA cohort, HCC patients from International Cancer Genome Consortium (ICGC)-LIRI-JP cohort and Gene Expression Omnibus (GEO) cohort (GSE14520) were divided into two risk subgroups. The result showed that overall survival (OS) time was decreased in the high-risk group. Combined with the clinical characteristics, the risk score was an independent factor for predicting the OS of HCC patients. Then, ROC curve and survival analysis were performed to evaluate the prognostic prediction value of the model. Finally, we constructed a PRGs clinical characteristics nomogram to further predict HCC patient survival probability. There were significant differences in immune cell infiltration, GSEA enrichment pathway, IC50 of chemotherapeutics, PRGs mutation frequency between high-risk group and low-risk group. This work suggests PRGs signature played a crucial role in predicting the prognosis, infiltration of cancer microenvironment, and sensitivity of chemotherapeutic agents.

Project description:BackgroundHepatocellular carcinoma (HCC) is a life-threatening and refractory malignancy with poor outcome. Genetic mutations are the hallmark of cancer. Thus far, there is no comprehensive prognostic model constructed by mutation-gene transcriptome in HCC. The prognostic value of mutation-gene signature in HCC remains elusive.MethodsRNA expression profiles and the corresponding clinical information were recruited from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. The least absolute shrinkage and selection operator (LASSO) Cox regression analysis was employed to establish gene signature. Kaplan-Meier curve and time-dependent receiver operating characteristic curve were implemented to evaluate the prognostic value. The Wilcoxon test was performed to analyze the expression of immune checkpoint genes, cell cycle genes, and tumor drug resistance genes in different risk groups. Finally, quantitative real-time PCR (qRT-RCR) and immunohistochemistry (IHC) were performed to validate the mRNA and protein expression between HCC and adjacent nontumorous tissues in an independent cohort.ResultsA prognostic model consisting of five mutated genes was established by LASSO Cox regression analysis. The prognostic model classified patients into high- and low-risk groups. Compared with the low-risk group, patients in the high-risk group had significantly worse survival results. The prognostic model can accurately predict the overall survival of HCC patients and predict overall survival more accurately when combined with stage. Furthermore, the immune checkpoint genes, cell cycle genes, and tumor drug resistance genes were higher expressed in the high-risk group compared in the low-risk group. In addition, the expression level of prognostic signature genes was validated in an independent sample cohort, which was consistent with RNA sequencing expression in the TCGA database.ConclusionThe prediction model of HCC constructed using mutation-related genes is of great significance for clinical decision making and the personalized treatment of patients with HCC.

Dataset Information

OX40 expression in hepatocellular carcinoma is associated with a distinct immune microenvironment, specific mutation signature, and poor prognosis.

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OX40 expression in hepatocellular carcinoma is associated with a distinct immune microenvironment, specific mutation signature, and poor prognosis.

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