A pan-cancer analysis revealing the role of TIGIT in tumor microenvironment

AbstractT cell immunoreceptor with immunoglobulin and ITIM domain (TIGIT), an immune checkpoint, plays a pivotal role in immune suppression. However its role in tumor immunity and correlation with the genetic and epigenetic alterations remains unknown. Here, we comprehensively analyzed the expression patterns of the TIGIT and its value of prognostic prediction among 33 types of cancers based on the data collected from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression projects (GTEx). Furthermore, the correlations of TIGIT with pathological stages, tumor-infiltrating immune cells (TIICs), signatures of T cells subtypes, immune checkpoint genes, the degree of Estimation of STromal and Immune cells in MAlignant Tumor tissues using the Expression data (ESTIMATE), tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repair (MMR) genes, and DNA methyltransferases (DNMTs) were also explored. Gene functional enrichment was conducted by Gene Set Enrichment Analysis (GSEA). Our results showed that the expression of TIGIT was upregulated in most of the cancer types. Cox regression model showed that high expression of TIGIT in tumor samples correlates with poor prognosis in KIRC, KIRP, LGG, UVM, and with favorable prognosis in BRCA, CECS, HNSC, SKCM. TIGIT expression positively correlated with advanced stages, TIICs, the signatures of effector T cells, exhausted T cells, effector Tregs and the degree of ESTIMATE in KIRC, KIRP and UVM. TIGIT expression also positively correlated with CTLA4, PDCD1 (PD-1), CD274 (PD-L1), ICOS in most of the cancer types. Furthermore, the expression of TIGIT was correlated with TMB, MSI, MMR genes and DNMTs in different types of cancers. GSEA analysis showed that the expression of TIGIT was related to cytokine-cytokine receptor interaction, allograft rejection, oxidative phosphorylation. These findings suggested that TIGIT could serve as a potential biomarker for prognosis and a novel target for immunotherapies in cancers.

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A Pan-Cancer Analysis Revealing the Role 2 of TIGIT in Tumor Microenvironment

10.21203/rs.3.rs-638517/v1 ◽

2021 ◽

Author(s):

Jie Wen ◽

Xueyi Mao ◽

Quan Cheng ◽

Zhixiong Liu ◽

Fangkun Liu

Keyword(s):

Immune Cells ◽

Immune Checkpoint ◽

Cox Regression ◽

Expression Patterns ◽

Gene Set Enrichment Analysis ◽

Functional Enrichment ◽

Receptor Interaction ◽

Mmr Genes ◽

Potential Biomarker ◽

Cancer Types

Abstract T cell immunoreceptor with immunoglobulin and ITIM domain (TIGIT), an immune checkpoint, plays a pivotal role in immune suppression. However its role in tumor immunity and correlation with the genetic and epigenetic alterations remains unknown.Here, we comprehensively analyzed the expression patterns of the TIGIT and its value of prognostic prediction among 33 types of cancers based on the data collected from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression projects (GTEx). Furthermore, the correlations of TIGIT with tumor-infiltrating immune cells (TIICs), immune checkpoint genes, the degree of Estimation of STromal and Immune cells in MAlignant Tumor tissues using the Expression data (ESTIMATE), tumor mutation burden (TMB), microsatellite instability (MSI), mismatch repair (MMR) genes, and DNA methyltransferases (DNMTs) were also explored. Gene functional enrichment was conducted by Gene Set Enrichment Analysis (GSEA). Our results showed that the expression of TIGIT was upregulated in most of the cancer types. Cox regression model showed that high expression of TIGIT in tumor samples correlates with poor prognosis in KIRC, KIRP, LGG, UVM, and with favorable prognosis in BRCA, CECS , HNSC, SKCM. TIGIT expression significantly correlated with TIICs and the degree of ESTIMATE in KIRC, KIRP and UVM. TIGIT expression also correlated with CTLA4, PDCD1 (PD-1), CD274 (PD-L1), ICOS in most of the cancer types. Furthermore, the expression of TIGIT was correlated with TMB, MSI, MMR genes and DNMTs in different types of cancers. GSEA analysis showed that the expression of TIGIT was related to cytokine-cytokine receptor interaction, allograft rejection, oxidative phosphorylation.These findings suggested that TIGIT could serve as a potential biomarker for prognosis and a novel target for immunotherapies in cancers.

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Identification of a ZC3H12D-Regulated Competing Endogenous RNA Network for Prognosis of Lung Adenocarcinoma at Single-Cell Level

10.21203/rs.3.rs-603118/v1 ◽

2021 ◽

Author(s):

Wenhan Chen ◽

Zhifeng Guo ◽

Jingyang Wu ◽

Guofu Lin ◽

Shaohua Chen ◽

...

Keyword(s):

T Cells ◽

Lung Adenocarcinoma ◽

Single Cell ◽

Rna Sequencing ◽

Immune Cells ◽

Functional Enrichment ◽

Receptor Interaction ◽

Competing Endogenous Rna ◽

Hub Genes ◽

Cerna Network

Abstract Objective To identify hub genes from the competing endogenous RNA (ceRNA) network of lung adenocarcinoma (LUAD) and to explore their potential function on prognosis of patients from a single-cell perspective.Methods We performed RNA-sequencing of LUAD to construct ceRNA regulatory network, integrating with public databases to identify the vital pathways related to patients’ prognosis and to reveal the expression level of hub genes under different conditions, the functional enrichment of co-expressed genes and their potential immune-related mechanisms.Results ZC3H12D-hsa-miR-4443-ENST00000630242 axis was found to be related with LUAD. Lower ZC3H12D expression was significantly associated with shorter overall survival (OS) of patients (HR=2.007, P<0.05), and its expression was higher in early-stage patients, including T1 (P<0.05) and N0 (P<0.05). Additionally, ZC3H12D expression was higher in immune cells displayed by single-cell RNA-sequencing data, especially in Treg cells of lung cancer and CD8 T cells, B cells and CD4 T cells of LUAD. In the brain metastasized, the expression of ZC3H12D in macrophages was relatively abundant. The functional enrichment analysis showed that the co-expressed genes mainly played a role in lymphocyte activation and cytokine-cytokine receptor interaction. In addition, ZC3H12D was associated with multiple immune cells and immune molecules, including immune checkpoints CTLA4, CD96 and TIGIT.Conclusion ZC3H12D-hsa-miR-4443-ENST00000630242 ceRNA network was identified in LUAD. ZC3H12D could affect the survival and prognosis of patients by regulating mRNA, miRNA, lncRNA, immune cells and immune molecules. Therefore, it may serve as a vital predictive marker and could be regarded as a potential therapeutic target for LUAD in the future.

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Upregulation of B3GNT3 Correlates With Poor Prognosis and Decreased Immune Cell Infiltration In Pancreatic Adenocarcinoma

10.21203/rs.3.rs-218028/v1 ◽

2021 ◽

Author(s):

Long-Jiang Chen ◽

Lu-Lu Zhai ◽

Wei Wang ◽

Lun Wu ◽

Li-Chao Yao ◽

...

Keyword(s):

T Cells ◽

Signaling Pathway ◽

Pancreatic Adenocarcinoma ◽

Immune Cells ◽

Immune Cell ◽

Enrichment Analysis ◽

Transport Processes ◽

Gene Set Enrichment Analysis ◽

Functional Enrichment ◽

Activated T Cells

Abstract While previous studies have suggested that B3GNT3 is associated with tumorigenesis and progression of several tumors, its expression level and clinical significance in pancreatic adenocarcinoma (PAAD) remains unclear. Our study aimed to investigate the role of B3GNT3 in PAAD. B3GNT3 RNA sequencing and clinicopathological data were collected from the TCGA, GEO and GTEx databases. We assessed the expression and prognostic value of B3GNT3 in PAAD using R program and attached packages. Additionally, we investigate the correlation between B3GNT3 expression and tumor-infiltrating immune cells using CIBERSORT and the “correlation” module of GEPIA. Finally, gene set enrichment analysis (GSEA) was used to elucidate B3GNT3 related signaling pathways in PAAD. Results showed that B3GNT3 expression was significantly higher in tumor tissues compared to normal tissues (P <0.05). Increased B3GNT3 expression was correlated with advanced histologic grade and stage (Ⅰ Vs Ⅱ). Patients with high B3GNT3 expression had a worse OS (HR = 1.713, P = 0.0005). Moreover, a negative correlation between increased B3GNT3 expression and immune infiltrating level of naive B cells, CD8 T cells, and CD4 memory activated T cells was revealed by CIBERSORT analysis. Then, further analysis verified the correlation using the “correlation” module of GEPIA. Finally, GSEA suggested that functional enrichment of B3GNT3 was mainly involved in pathways in cancer, p53 signaling pathway, TGF beta signaling pathway, catabolic and transport processes of proteins, etc. Collectively, these results suggested that overexpression of B3GNT3 might affect the infiltration of immune cells and could act as a potential prognostic biomarker of PAAD.

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Tumor-Infiltrating PD-1hiCD8+-T-Cell Signature as an Effective Biomarker for Immune Checkpoint Inhibitor Therapy Response Across Multiple Cancers

Frontiers in Oncology ◽

10.3389/fonc.2021.695006 ◽

2021 ◽

Vol 11 ◽

Author(s):

Zhenyu Yang ◽

Yulan Deng ◽

Jiahan Cheng ◽

Shiyou Wei ◽

Hao Luo ◽

...

Keyword(s):

Lung Cancer ◽

T Cells ◽

T Cell ◽

Immune Cells ◽

Immune Checkpoint ◽

Immune Checkpoint Inhibitor ◽

Checkpoint Inhibitor ◽

Therapy Response ◽

Rna Seq ◽

Cancer Types

BackgroundStratification of patients who could benefit from immune checkpoint inhibitor (ICI) therapy is of much importance. PD-1hiCD8+ T cells represent a newly identified and effective biomarker for ICI therapy response biomarker in lung cancer. Accurately quantifying these T cells using commonly available RNA sequencing (RNA-seq) data may extend their applications to more cancer types.MethodWe built a transcriptome signature of PD-1hiCD8+ T cells from bulk RNA-seq and single-cell RNA-seq (scRNA-seq) data of tumor-infiltrating immune cells. The signature was validated by flow cytometry and in independent datasets. The clinical applications of the signature were explored in non-small-cell lung cancer, melanoma, gastric cancer, urothelial cancer, and a mouse model of breast cancer samples treated with ICI, and systematically evaluated across 21 cancer types in The Cancer Genome Atlas (TCGA). Its associations with other biomarkers were also determined.ResultsSignature scores could be used to identify the PD-1hiCD8+ T subset and were correlated with the fraction of PD-1hiCD8+ T cells in tumor tissue (Pearson correlation, R=0.76, p=0.0004). Furthermore, in the scRNA-seq dataset, we confirmed the capability of PD-1hiCD8+ T cells to secrete CXCL13, as well as their interactions with other immune cells. In 581 clinical samples and 204 mouse models treated with ICIs, high signature scores were associated with increased survival, and the signature achieved area under the receiver operating characteristic curve scores of 0.755 (ranging from 0.61 to 0.91) in predicting therapy response. In TCGA pan-cancer datasets, our signature scores were consistently correlated with therapy response (R=0.78, p<0.0001) and partially explained the diverse response rates among different cancer types. Finally, our signature generally outperformed other mRNA-based predictors and showed improved predictive performance when used in combination with tumor mutational burden (TMB). The signature score is available in the R package “PD1highCD8Tscore” (https://github.com/Liulab/PD1highCD8Tscore).ConclusionThrough estimating the fraction of the PD-1hiCD8+ T cell, our signature could predict response to ICI therapy across multiple cancers and could serve as a complementary biomarker to TMB.

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Pan-Cancer Analysis Revealed SRSF9 as a New Biomarker for Prognosis and Immunotherapy

Journal of Oncology ◽

10.1155/2022/3477148 ◽

2022 ◽

Vol 2022 ◽

pp. 1-21

Author(s):

Jinhui Liu ◽

Yuanyuan Wang ◽

Jian Yin ◽

Yan Yang ◽

Rui Geng ◽

...

Keyword(s):

Cancer Patients ◽

Immune Checkpoint ◽

Negative Relationship ◽

Dna Methyltransferases ◽

Gene Set Enrichment Analysis ◽

Mmr Genes ◽

Free Interval ◽

Cancer Types ◽

Immune Score ◽

Pan Cancer

Background. Serine/arginine-rich splicing factor 9 (SRSF9) is one of the members of SRSF gene family and related to the tumorigenesis and the progression of tumor. However, whether SRSF9 has a crucial role across pan-cancer is still unknown. Methods. In this study, we used public databases, such as The Cancer Genome Atlas (TCGA), Cancer Cell Line Encyclopedia (CCLE), and Genotype-Tissue Expression (GTEx), to analyze SRSF9 expression level among tumor and normal cells. Survival analysis, K-M plotter, and PrognoScan were used to analyze the prognosis value of SRSF9, regarding to overall survival (OS), disease-specific survival (DSS), disease-free interval (DFI), and progression-free interval (PFI). Moreover, we performed the correlation between SRSF9 and clinical characteristics (including the outcome of prognosis), as well as molecular events of tumor mutation burden (TMB), microsatellite instability (MSI), immune checkpoint gene, tumor microenvironment (TME), immune infiltrating cells, mismatch repair (MMR) genes, m6A genes, DNA methyltransferases, and neoantigen with bioinformatics methods and TISIDB, TIMER, and Sangerbox websites. Results. In general, SRSF9 expression was upregulated in most cancers, such as BLCA, CHOL, and UCEC, which SRSF9 was associated with short survival and severe progression. In COAD, STAD, and UCEC, SRSF9 expression was positively related to both TMB and MSI. In BRCA, BLCA, ESCA, GBM, HNSC, LUSC, LUAD, OV, PRAD, TGCT, THCA, and UCEC, both immune score and stomal score showed a negative relationship with SRSF9 expression. Immune score showed a positive relationship with SRSF9 expression in LGG. SRSF9 expression had a significant and positive correlation with six types of immune infiltration cells in LGG, KIRC, LIHC, PCPG, PRAD, SKCM, THCA, and THYM, except in LUSC. In LIHC, SRSF9 was highly significant correlated with most immune checkpoint genes. For neoantigens, correlation between SRSF9 and the quantity of neoantigens was significantly positive in some cancer types. SRSF9 was also correlated with MMR genes, m6A genes, and DNA methyltransferases. In the 33 cancer types, gene set enrichment analysis (GSEA) demonstrated that SRSF9 was correlated with multiple functions and signaling pathways. Conclusion. These findings demonstrated that SRSF9 may be a new biomarker for the prognosis and immunotherapy in various cancers. As a result, it will be beneficial to provide new therapies for cancer patients, thereby improving the treatment and prognosis of cancer patients.

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The Immune Subtypes and Landscape of Gastric Cancer and to Predict Based on the Whole-Slide Images Using Deep Learning

Frontiers in Immunology ◽

10.3389/fimmu.2021.685992 ◽

2021 ◽

Vol 12 ◽

Author(s):

Yan Chen ◽

Zepang Sun ◽

Wanlan Chen ◽

Changyan Liu ◽

Ruoyang Chai ◽

...

Keyword(s):

Gastric Cancer ◽

T Cells ◽

Deep Learning ◽

Immune Cells ◽

Gene Set Enrichment Analysis ◽

Functional Enrichment ◽

Resting Cells ◽

M1 Macrophages ◽

Immune Score ◽

Subtype 3

BackgroundGastric cancer (GC) is a highly heterogeneous tumor with different responses to immunotherapy. Identifying immune subtypes and landscape of GC could improve immunotherapeutic strategies.MethodsBased on the abundance of tumor-infiltrating immune cells in GC patients from The Cancer Genome Atlas, we used unsupervised consensus clustering algorithm to identify robust clusters of patients, and assessed their reproducibility in an independent cohort from Gene Expression Omnibus. We further confirmed the feasibility of our immune subtypes in five independent pan-cancer cohorts. Finally, functional enrichment analyses were provided, and a deep learning model studying the pathological images was constructed to identify the immune subtypes.ResultsWe identified and validated three reproducible immune subtypes presented with diverse components of tumor-infiltrating immune cells, molecular features, and clinical characteristics. An immune-inflamed subtype 3, with better prognosis and the highest immune score, had the highest abundance of CD8+ T cells, CD4+ T–activated cells, follicular helper T cells, M1 macrophages, and NK cells among three subtypes. By contrast, an immune-excluded subtype 1, with the worst prognosis and the highest stromal score, demonstrated the highest infiltration of CD4+ T resting cells, regulatory T cells, B cells, and dendritic cells, while an immune-desert subtype 2, with an intermediate prognosis and the lowest immune score, demonstrated the highest infiltration of M2 macrophages and mast cells, and the lowest infiltration of M1 macrophages. Besides, higher proportion of EVB and MSI of TCGA molecular subtyping, over expression of CTLA4, PD1, PDL1, and TP53, and low expression of JAK1 were observed in immune subtype 3, which consisted with the results from Gene Set Enrichment Analysis. These subtypes may suggest different immunotherapy strategies. Finally, deep learning can predict the immune subtypes well.ConclusionThis study offers a conceptual frame to better understand the tumor immune microenvironment of GC. Future work is required to estimate its reference value for the design of immune-related studies and immunotherapy selection.

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Single Cell Profiling Reveals Unique CXCL13 Positive T Cell Subsets in the Tumor Microenvironment of Lymphocyte Rich Classic Hodgkin Lymphoma

Blood ◽

10.1182/blood-2020-134929 ◽

2020 ◽

Vol 136 (Supplement 1) ◽

pp. 32-33

Author(s):

Tomohiro Aoki ◽

Lauren C. Chong ◽

Katsuyoshi Takata ◽

Katy Milne ◽

Elizabeth Chavez ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

B Cells ◽

Single Cell ◽

Immune Cells ◽

Research Funding ◽

Immune Cell ◽

Expression Patterns ◽

The Other ◽

Tfh Cells

Introduction: Classic Hodgkin lymphoma (CHL) features a unique crosstalk between malignant cells and different types of normal immune cells in the tumor-microenvironment (TME). On the basis of histomorphologic and immunophenotypic features of the malignant Hodgkin and Reed-Sternberg (HRS) cells and infiltrating immune cells, four histological subtypes of CHL are recognized: Nodular sclerosing (NS), Mixed cellularity, Lymphocyte-rich (LR) and Lymphocyte-depleted CHL. Recently, our group described the high abundance of various types of immunosuppressive CD4+ T cells including LAG3+ and/or CTLA4+ cells in the TME of CHL using single cell RNA sequencing (scRNAseq). However, the TME of LR-CHL has not been well characterized due to the rarity of the disease. In this study, we aimed at characterizing the immune cell profile of LR-CHL at single cell resolution. METHODS: We performed scRNAseq on cell suspensions collected from lymph nodes of 28 primary CHL patients, including 11 NS, 9 MC and 8 LR samples, with 5 reactive lymph nodes (RLN) serving as normal controls. We merged the expression data from all cells (CHL and RLN) and performed batch correction and normalization. We also performed single- and multi-color immunohistochemistry (IHC) on tissue microarray (TMA) slides from the same patients. In addition, an independent validation cohort of 31 pre-treatment LR-CHL samples assembled on a TMA, were also evaluated by IHC. Results: A total of 23 phenotypic cell clusters were identified using unsupervised clustering (PhenoGraph). We assigned each cluster to a cell type based on the expression of genes described in published transcriptome data of sorted immune cells and known canonical markers. While most immune cell phenotypes were present in all pathological subtypes, we observed a lower abundance of regulatory T cells (Tregs) in LR-CHL in comparison to the other CHL subtypes. Conversely, we found that B cells were enriched in LR-CHL when compared to the other subtypes and specifically, all four naïve B-cell clusters were quantitatively dominated by cells derived from the LR-CHL samples. T follicular helper (TFH) cells support antibody response and differentiation of B cells. Our data show the preferential enrichment of TFH in LR-CHL as compared to other CHL subtypes, but TFH cells were still less frequent compared to RLN. Of note, Chemokine C-X-C motif ligand 13 (CXCL13) was identified as the most up-regulated gene in LR compared to RLN. CXCL13, which is a ligand of C-X-C motif receptor 5 (CXCR5) is well known as a B-cell attractant via the CXCR5-CXCL13 axis. Analyzing co-expression patterns on the single cell level revealed that the majority of CXCL13+ T cells co-expressed PD-1 and ICOS, which is known as a universal TFH marker, but co-expression of CXCR5, another common TFH marker, was variable. Notably, classical TFH cells co-expressing CXCR5 and PD-1 were significantly enriched in RLN, whereas PD-1+ CXCL13+ CXCR5- CD4+ T cells were significantly enriched in LR-CHL. These co-expression patterns were validated using flow cytometry. Moreover, the expression of CXCR5 on naïve B cells in the TME was increased in LR-CHL compared to the other CHL subtypes We next sought to understand the spatial relationship between CXCL13+ T cells and malignant HRS cells. IHC of all cases revealed that CXCL13+ T cells were significantly enriched in the LR-CHL TME compared to other subtypes of CHL, and 46% of the LR-CHL cases showed CXCL13+ T cell rosettes closely surrounding HRS cells. Since PD-1+ T cell rosettes are known as a specific feature of LR-CHL, we confirmed co-expression of PD-1 in the rosetting cells by IHC in these cases. Conclusions: Our results reveal a unique TME composition in LR-CHL. LR-CHL seems to be distinctly characterized among the CHL subtypes by enrichment of CXCR5+ naïve B cells and CD4+ CXCL13+ PD-1+ T cells, indicating the importance of the CXCR5-CXCL13 axis in the pathogenesis of LR-CHL. Figure Disclosures Savage: BeiGene: Other: Steering Committee; Merck, BMS, Seattle Genetics, Gilead, AstraZeneca, AbbVie: Honoraria; Roche (institutional): Research Funding; Merck, BMS, Seattle Genetics, Gilead, AstraZeneca, AbbVie, Servier: Consultancy. Scott:Janssen: Consultancy, Research Funding; Celgene: Consultancy; NanoString: Patents & Royalties: Named inventor on a patent licensed to NanoString, Research Funding; NIH: Consultancy, Other: Co-inventor on a patent related to the MCL35 assay filed at the National Institutes of Health, United States of America.; Roche/Genentech: Research Funding; Abbvie: Consultancy; AstraZeneca: Consultancy. Steidl:AbbVie: Consultancy; Roche: Consultancy; Curis Inc: Consultancy; Juno Therapeutics: Consultancy; Bayer: Consultancy; Seattle Genetics: Consultancy; Bristol-Myers Squibb: Research Funding.

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Prognostic and immunological value of LTB4R in pan-cancer

Mathematical Biosciences and Engineering ◽

10.3934/mbe.2021459 ◽

2021 ◽

Vol 18 (6) ◽

pp. 9336-9356

Author(s):

Sidan Long ◽

◽

Shuangshuang Ji ◽

Kunmin Xiao ◽

Peng Xue ◽

...

Keyword(s):

Immune Cells ◽

Prognostic Significance ◽

Enrichment Analysis ◽

Negative Influence ◽

Leukotriene B4 ◽

Gene Set Enrichment Analysis ◽

Functional Enrichment ◽

Immune Infiltration ◽

Significant Difference ◽

Pan Cancer

<abstract> <sec><title>Background</title>LTB4 receptor 1 (LTB4R), as the high affinity leukotriene B4 receptor, is rapidly revealing its function in malignancies. However, it is still uncertain. </sec> <sec><title>Methods</title>We investigated the expression pattern and prognostic significance of LTB4R in pan-cancer across different databases, including ONCOMINE, PrognoScan, GEPIA, and Kaplan-Meier Plotter, in this study. Meanwhile, we explored the significance of LTB4R in tumor metastasis by HCMDB. Then functional enrichment analysis of related genes was performed using GeneMANIA and DAVID. Lastly, utilizing the TIMER datasets, we looked into the links between LTB4R expression and immune infiltration in malignancies. </sec> <sec><title>Results</title>In general, tumor tissue displayed higher levels of LTB4R expression than normal tissue. Although LTB4R had a negative influence on pan-cancer, a high expression level of LTB4R was protective of LIHC (liver hepatocellular carcinoma) patients' survival. There was no significant difference in the distribution of LTB4R between non-metastatic and metastatic tumors. Based on Gene Set Enrichment Analysis, LTB4R was implicated in pathways involved in inflammation, immunity, metabolism, and cancer diseases. The correlation between immune cells and LTB4R was found to be distinct across cancer types. Furthermore, markers of infiltrating immune cells, such as Treg, T cell exhaustion and T helper cells, exhibited different LTB4R-related immune infiltration patterns. </sec> <sec><title>Conclusion</title>The LTB4R is associated with immune infiltrates and can be used as a prognostic biomarker in pan-cancer. </sec> </abstract>

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Prognostic value of CLIC3 mRNA overexpression in bladder cancer

PeerJ ◽

10.7717/peerj.8348 ◽

2020 ◽

Vol 8 ◽

pp. e8348

Author(s):

Mei Chen ◽

Shufang Zhang ◽

Xiaohong Wen ◽

Hui Cao ◽

Yuanhui Gao

Keyword(s):

Gene Expression ◽

Bladder Cancer ◽

Mrna Expression ◽

Prognostic Value ◽

Multivariate Analyses ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Receptor Interaction ◽

Normal Tissues

Background Human intracellular chloride channel 3 (CLIC3) is involved in the development of various cancers, but the expression and prognostic value of CLIC3 mRNA in bladder cancer (BC) remain unclear. Methods The gene expression data and clinical information of CLIC3 were obtained from the Gene Expression Omnibus (GEO) database and verified in the Oncomine and The Cancer Genome Atlas (TCGA) database. The expression of CLIC3 mRNA in BC tissues and adjacent normal tissues was detected by quantitative real-time polymerase chain reaction (qRT-PCR). The Kaplan-Meier method was used to analyze the relationship between the expression of CLIC3 mRNA and the prognosis of BC. Cox univariate and multivariate analyses were performed on the overall survival and tumor-specific survival of BC patients. The genes coexpressed with CLIC3 were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). CLIC3-related signal transduction pathways in BC were explored with gene set enrichment analysis (GSEA). Results The expression of CLIC3 mRNA in BC tissues was higher than that in normal tissues (P < 0.01). High CLIC3 mRNA expression was associated with age (P = 0.021) and grade (P = 0.045) in BC patients. High CLIC3 mRNA expression predicted a poor prognosis in BC patients (P < 0.05). Cox univariate and multivariate analyses showed that high CLIC3 mRNA expression was associated with tumor-specific survival in BC patients (P < 0.05). Functional enrichment analyses indicated that CLIC3 may be significantly associated with the cell cycle, focal adhesion, the extracellular matrix (ECM) receptor interaction and the P53 signaling pathway. Conclusions CLIC3 mRNA is highly expressed in BC, and its high expression is related to the adverse clinicopathological factors and prognosis of BC patients. CLIC3 can be used as a biomarker for the prognosis of BC patients.

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Transcriptional heterogeneity in cancer-associated regulatory T cells is predictive of survival

10.1101/478628 ◽

2018 ◽

Cited By ~ 2

Author(s):

Nicholas Borcherding ◽

Kawther K. Ahmed ◽

Andrew P. Voigt ◽

Ajaykumar Vishwakarma ◽

Ryan Kolb ◽

...

Keyword(s):

T Cells ◽

Regulatory T Cells ◽

Immune Cells ◽

Ex Vivo ◽

Expression Patterns ◽

Suppressive Effect ◽

Renal Clear Cell Carcinoma ◽

Cell Fates ◽

Treg Subset

Regulatory T cells (Tregs) are a population of T cells that exert a suppressive effect on a variety of immune cells and non-immune cells. The suppressive effects of Tregs are detrimental to anti-tumor immunity. Recent investigations into cancer-associated Tregs have identified common expression patterns for tumor-infiltration, however the functional heterogeneity in tumor-infiltrating (TI) Treg is largely unknown. We performed single-cell sequencing on immune cells derived from renal clear cell carcinoma (ccRCC) patients, isolating 160 peripheral-blood (PB) Tregs and 574 TI Tregs. We identified distinct transcriptional TI Treg cell fates, with a suppressive subset expressing CD177. We demonstrate CD177+ TI-Tregs have preferential suppressive effects in vivo and ex vivo. Gene signatures derived the CD177+ Treg subset had superior ability to predict survival in ccRCC and seven other cancer types. Further investigation into the development and regulation of TI-Treg heterogeneity will be vital to the application of tumor immunotherapies that possess minimal side effects.

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