scholarly journals Landscape of associations between long non‐coding RNAs and infiltrating immune cells in liver hepatocellular carcinoma

2020 ◽  
Vol 24 (19) ◽  
pp. 11243-11253 ◽  
Author(s):  
Li Li ◽  
Xiaowei Song ◽  
Yanju Lv ◽  
Qiuying Jiang ◽  
Chengjuan Fan ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Immune Cells ◽  
Non Coding Rnas ◽  
Liver Hepatocellular Carcinoma

scholarly journals Expression and prognosis analysis of JMJD5 in human cancers

2020 ◽  
Author(s):  
Hui Li ◽  
Qun Li ◽  
Hong Jing ◽  
Jianghai Zhao ◽  
Hui Zhang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
T Cells ◽  
B Cells ◽  
Lung Adenocarcinoma ◽  
Immune Cells ◽  
Prognostic Value ◽  
Normal Tissues ◽  
Human Cancers ◽  
Stomach Adenocarcinoma ◽  
Liver Hepatocellular Carcinoma

Abstract BackgroundJumonjiC (JmjC) domain-containing protein 5 (JMJD5) plays an important role in cancer metabolism. However, the prognostic value of JMJD5 in most human cancers is still unknown. In this study, we aim to investigate the expression and prognostic value of JMJD5, immune cells infiltration, and the correlations among them. MethodsWe performed a detailed cancer vs. normal analysis of JMJD5 mRNA expression via online Tumor Immune Estimation Resource (TIMER). The protein expressions of JMJD5 in various cancers vs. adjacent normal tissues were examined by immunohistochemistry (IHC) of tissue microarray sections (TMAs). Moreover, the Kaplan-Meier Plotter databases were used to evaluate the prognostic values in above cancers. The correlations between JMJD5 expression level and abundances of six immune infiltrating cells (B cells, CD4+ T cells, CD8+ T cells, macrophages, neutrophils and dendritic cells) were explored by TIMER database in breast cancer (BRCA), liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC) and stomach adenocarcinoma (STAD). The prognostic values of tumor- infiltrating immune cells were also investigated by TIMER in above four cancers. Finally, the COX proportional hazards model was used to investigate the correlations among clinical outcome, the abundance of immune cell infiltrates and the expression of JMJD5 in above four cancer types.ResultsThe expression of JMJD5 was significantly lower in human breast carcinoma (BRCA), cholangiocarcinoma (CHOL), liver hepatocellular carcinoma (LIHC) and lung cancer (LUC) but higher in prostate adenocarcinoma (PRAD) and stomach adenocarcinoma (STAD) comparing to their respective normal tissues. And high expression of JMJD5 has better prognosis only in BRCA, LIHC, LUC but the opposite effect in STAD. JMJD5 expression is significant correlation with the abundance of six immune cells infiltration in above four cancers. Both the BRCA or lung adenocarcinoma (LUAD) patients with abundance of B cell and the STAD patients with low level of macrophage have a better cumulative survival. ConclusionsWe provided novel evidence of JMJD5 as an essential prognostic biomarker in cancers through analyses the correlation of the JMJD5 expression, tumor-infiltrating B cells and macrophages and prognostic value. This study offers new perspectives therapeutic target in BRCA, LUAD and STAD.

scholarly journals Immune Cell Composition of Liver Hepatocellular Carcinoma and its clinical relevance: A research based on TCGA database

2019 ◽  
Author(s):  
Yucheng Ji ◽  
Guang-xiang Gu
Keyword(s):  
Hepatocellular Carcinoma ◽  
Nk Cells ◽  
Survival Time ◽  
Clinical Data ◽  
Immune Cells ◽  
Immune Cell ◽  
Transcriptome Profiling ◽  
Statistical Analyses ◽  
Lower Amount ◽  
Liver Hepatocellular Carcinoma

Abstract Background Liver hepatocellular carcinoma (LIHC), as the main type of liver cancer, has become a main health issue as the third-most common cause of mortality in cancer patients. However, conventional chemo- or radio- therapies shows little improvement in survival, which calls for novel therapies. Because of the immunotolerance mechanism existing naturally in liver, immunotherapy provides significant effect in treatment of LIHC patients. Up to now, various immunotherapies have been proposed, but due to the complex pathways from which LIHC cancerous cell escape immunosurveillance, combined therapies are often needed, which are still under development. Methods In the current study, with data downloaded from TCGA database, CIBERSORT was performed for identifying the composition of infiltrating immune cells and further statistical analyses using R 3.5.3 were carried out, aiming at connecting specific immune cells with clinical survival. Results With data of immune and stromal scores downloaded from the website of MD Anderson Cancer Centre, both showed significance in survival time. Further analyses based on the result of CIBERSORT demonstrated that the number of macrophages M0 and T cells CD8 infiltration between para-carcinoma and tumour tissues are markedly different. With combination of clinical data, we were able to identify that a higher amount of activated NK cells (p=0.008) and a lower amount of resting NK cells (p=0.047) presented a longer survival time. Conclusion With the help of the TCGA database and multiple techniques, statistical analyses of transcriptome profiling data and clinical data were successfully carried out. The results in this study may pave the way for a new therapeutic strategy which could be combined with current treatments to further improve the clinical outcome of LIHC patients. Further and deeper investigation of other available data, however, were needed in order to verify the results of current study.

scholarly journals Systematic Analyses of the Role of the Reader Protein of N6-Methyladenosine RNA Methylation, YTH Domain Family 2, in Liver Hepatocellular Carcinoma

2020 ◽  
Vol 7 ◽  
Author(s):  
Xiang-yang Shao ◽  
Jin Dong ◽  
Han Zhang ◽  
Ying-song Wu ◽  
Lei Zheng
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Immune Cells ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
Domain Family ◽  
Rna Methylation ◽  
Yth Domain ◽  
Liver Hepatocellular Carcinoma

BackgroundYTH domain family (YTHDF) 2 acts as a “reader” protein for RNA methylation, which is important in tumor regulation. However, the effect of YTHDF2 in liver hepatocellular carcinoma (LIHC) has yet to be elucidated.MethodsWe explored the role of YTHDF2 in LIHC based on publicly available datasets [The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and Gene Expression Omnibus (GEO)]. A bioinformatics approach was employed to analyze YTHDF2. Logistic regression analyses were applied to analyze the correlation between YTHDF2 expression and clinical characteristics. To evaluate the effect of YTHDF2 on the prognosis of LIHC patients, we used Kaplan–Meier (K–M) curves. Gene set enrichment analysis (GSEA) was undertaken using TCGA dataset. Univariate and multivariate Cox analyses were used to ascertain the correlations between YTHDF2 expression and clinicopathologic characteristics with survival. Genes co-expressed with YTHDF2 were identified and detected using publicly available datasets [LinkedOmics, University of California, Santa Cruz (UCSC), Gene Expression Profiling Interactive Analysis (GEPIA), and GEO]. Correlations between YTHDF2 and infiltration of immune cells were investigated by Tumor Immune Estimation Resource (TIMER) and GEPIA.ResultsmRNA and protein expression of YTHDF2 was significantly higher in LIHC tissues than in non-cancerous tissues. High YTHDF2 expression in LIHC was associated with poor prognostic clinical factors (high stage, grade, and T classification). K–M analyses indicated that high YTHDF2 expression was correlated with an unfavorable prognosis. Univariate and multivariate Cox analyses revealed that YTHDF2 was an independent factor for a poor prognosis in LIHC patients. GSEA revealed that the high-expression phenotype of YTHDF2 was consistent with the molecular pathways implicated in LIHC carcinogenesis. Analyses of receiver operating characteristic curves showed that YTHDF2 might have a diagnostic value in LIHC patients. YTHDF2 expression was associated positively with SF3A3 expression, which implied that they may cooperate in LIHC progression. YTHDF2 expression was associated with infiltration of immune cells and their marker genes. YTHDF2 had the potential to regulate polarization of tumor-associated macrophages, induce T-cell exhaustion, and activate T-regulatory cells.ConclusionYTHDF2 may be a promising biomarker for the diagnosis and prognosis of LIHC and may provide new directions and strategies for LIHC treatment.

scholarly journals Identification of Therapeutic Targets and Prognostic Biomarkers Among Chemokine (C-C Motif) Ligands in the Liver Hepatocellular Carcinoma Microenvironment

2021 ◽  
Vol 9 ◽  
Author(s):  
Zhongyi Jiang ◽  
Changchang Xing ◽  
Pusen Wang ◽  
Xueni Liu ◽  
Lin Zhong
Keyword(s):  
Hepatocellular Carcinoma ◽  
T Cells ◽  
Western Blot ◽  
Signaling Pathway ◽  
Immune Cells ◽  
Stromal Cells ◽  
Prognostic Biomarkers ◽  
Immune Checkpoints ◽  
Immunological Therapy ◽  
Liver Hepatocellular Carcinoma

Background: Liver hepatocellular carcinoma (LIHC) is the third leading cause of cancer-related death and the sixth most common solid tumor worldwide. In the tumor microenvironment, the cross-talk between cancer cells, immune cells, and stromal cells exerts significant effects on neoplasia and tumor development and is modulated in part by chemokines. Chemokine (C-C motif) ligands (CCL) can directly target tumor cells and stromal cells, and they have been shown to regulate tumor cell proliferation, cancer stem-like cell properties, cancer invasiveness and metastasis, which directly and indirectly affect tumor immunity and influence cancer progression, therapy and patient outcomes. However, the prognostic values of chemokines CCL in LIHC have not been clarified.Methods: In this study, we comprehensively analyzed the relationship between transcriptional chemokines CCL and disease progression of LIHC using the ONCOMINE dataset, GEPIA, UALCAN, STRING, WebGestalt, GeneMANIA, TRRUST, DAVID 6.8, LinkedOmics, TIMER, GSCALite, and Open Targets. We validated the protein levels of chemokines CCL through western blot and immunohistochemistry.Results: The transcriptional levels of CCL5/8/11/13/15/18/20/21/25/26/27/28 in LIHC tissues were significantly elevated while CCL2/3/4/14/23/24 were significantly reduced. A significant correlation was found between the expression of CCL14/25 and the pathological stage of LIHC patients. LIHC patients with low transcriptional levels of CCL14/21 were associated with a significantly poor prognosis. The functions of differentially expressed chemokines CCL were primarily related to the chemokine signaling pathway, cytokine–cytokine receptor interactions, and TNF-α signaling pathway. Our data suggested that RELA/REL, NFKB1, STAT1/3/6, IRF3, SPI1, and JUN were key transcription factors for chemokines CCL. We found significant correlations among the expression of chemokines CCL and the infiltration of six types of immune cells (B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells) and immune checkpoints (PD-1. PD-L1, and CTLA-4). The western blot and immunohistochemistry results showed that protein expression levels of CCL5 and CCL20 were upregulated in LIHC. CCL5 and CCL20 were significantly correlated with the clinical outcome of patients with LIHC, and could be negatively regulated by some drugs or small molecules.Conclusions: Our results may provide novel insights for the potential suitable targets of immunological therapy and prognostic biomarkers for LIHC.

scholarly journals Novel Prognostic Markers for Liver Hepatocellular Carcinoma and Their Roles in Immune Infiltration of the Tumor Microenvironment

2021 ◽  
Author(s):  
Meihai Deng ◽  
Hao Liang ◽  
Kunpeng Hu ◽  
Zhaozhong Zhong ◽  
Zhiyong Xiong ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
T Cells ◽  
Tumor Microenvironment ◽  
Immune Cells ◽  
Rna Seq ◽  
Hub Genes ◽  
Novel Biomarkers ◽  
Liver Hepatocellular Carcinoma ◽  
Memory Cd4 T Cells

Abstract Background: Liver hepatocellular carcinoma (LIHC) is one of the most common malignant cancers worldwide, the overall prognosis of LIHC remains unsatisfactory. Valuable prognostic biomarkers are still urgently needed for LIHC. This study aimed to explore hub genes associated with the prognosis of LIHC and tumor microenvironmental immune infiltration, providing potential prognostic biomarker and therapeutic target for LIHC. Methods: RNA-seq counts data for LIHC samples were obtained from TCGA database. RNA-seq counts data for normal liver samples were obtained from GTEx database. Weighted gene co-expression network analysis (WGCNA) was used to cluster differentially expressed genes with similar expression profiles to form modules and significant modules and key genes were screened. Next, these genes was verified by cox analyses and overall survival analysis. Further, CIBERSORT was used to explore the relationship between these genes and tumor infiltrating immune cells. Results: A total number of 2661 significant DEGs were included for consensus WGCNA analysis, which identified 6 modules. Blue module (r=0.85, p<0.0001) showed high relationship with LIHC, which included 400 genes. After the overall survival analyses of hub genes, CDC20, CDCA5, CDCA8, KIF2C and KIFC1 were identified as five potential marker genes, which would result in an unfavorable prognosis in LIHC. Further CIBERSORT analysis showed these novel biomarkers expression levels in LIHC were positively correlated with activated memory CD4+ T cells, follicular helper T cells, regulatory T cells and macrophages M0. While, resting memory CD4+ T cells, monocytes, macrophages M2, resting mast cells showed a negative correlation with the 5 novel biomarkers expression levels. Conclusions: The study screened 5 genes with marked prognostic capability for LIHC and found these genes were correlated with the infiltration of immune cells in LIHC tumor microenvironment. The findings might provide a more detailed molecular mechanism underlying LIHC occurrence and progression, holding promise for acting as potential biomarkers and therapeutic targets.

Biomarker Identification for Liver Hepatocellular Carcinoma and Cholangiocarcinoma Based on Gene Regulatory Network Analysis

2020 ◽  
Vol 15 ◽  
Author(s):  
Qiuyan Huo ◽  
Yuying Ma ◽  
Yu Yin ◽  
Guimin Qin
Keyword(s):  
Hepatocellular Carcinoma ◽  
Regulatory Networks ◽  
Primary Liver Cancer ◽  
Endocrine Resistance ◽  
Molecular Characteristics ◽  
Network Clustering ◽  
Resistance Pathway ◽  
Gene Regulatory ◽  
Tf Gene ◽  
Liver Hepatocellular Carcinoma

Aims: We aimed to find common and distinct molecular characteristics between LIHC and CHOL based on miRNA-TF-gene FFL. Background: Liver hepatocellular carcinoma (LIHC) and cholangiocarcinoma (CHOL) are two main histological subtypes of primary liver cancer with a unified molecular landscape, and feed-forward loops (FFLs) have been shown to be relevant in these complex diseases. Objective: To date, there has been no comparative analysis of the pathogenesis of LIHC and CHOL based on regulatory relationships. Therefore, we investigated the common and distinct regulatory properties of LIHC and CHOL in terms of gene regulatory networks. Method: Based on identified FFLs and an analysis of pathway enrichment, we constructed pathway-specific co-expression networks and further predicted biomarkers for these cancers by network clustering. Resul: We identified 20 and 36 candidate genes for LIHC and CHOL, respectively. The literature from PubMed supports the reliability of our results. Conclusion: Our results indicated that the hsa01522-Endocrine resistance pathway was associated with both LIHC and CHOL. Additionally, six genes (SPARC, CTHRC1, COL4A1, EDIL3, LAMA4 and OLFML2B) were predicted to be highly associated with both cancers, of which SPARC was significantly highly ranked. Other: In addition, we inferred that the Collagen gene family, which appeared more frequently in our overall prediction results, might be closely related to cancer development.

scholarly journals Identification of glycolysis related pathways in pancreatic adenocarcinoma and liver hepatocellular carcinoma based on TCGA and GEO datasets

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ji Li ◽  
Chen Zhu ◽  
Peipei Yue ◽  
Tianyu Zheng ◽  
Yan Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Energy Metabolism ◽  
Pancreatic Adenocarcinoma ◽  
Digestive System ◽  
Prognostic Significance ◽  
R Package ◽  
The Cancer Genome Atlas ◽  
System Structure ◽  
Liver Hepatocellular Carcinoma

Abstract Background Abnormal energy metabolism is one of the characteristics of tumor cells, and it is also a research hotspot in recent years. Due to the complexity of digestive system structure, the frequency of tumor is relatively high. We aim to clarify the prognostic significance of energy metabolism in digestive system tumors and the underlying mechanisms. Methods Gene set variance analysis (GSVA) R package was used to establish the metabolic score, and the score was used to represent the metabolic level. The relationship between the metabolism and prognosis of digestive system tumors was explored using the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Volcano plots and gene ontology (GO) analyze were used to show different genes and different functions enriched between different glycolysis levels, and GSEA was used to analyze the pathway enrichment. Nomogram was constructed by R package based on gene characteristics and clinical parameters. qPCR and Western Blot were applied to analyze gene expression. All statistical analyses were conducted using SPSS, GraphPad Prism 7, and R software. All validated experiments were performed three times independently. Results High glycolysis metabolism score was significantly associated with poor prognosis in pancreatic adenocarcinoma (PAAD) and liver hepatocellular carcinoma (LIHC). The STAT3 (signal transducer and activator of transcription 3) and YAP1 (Yes1-associated transcriptional regulator) pathways were the most critical signaling pathways in glycolysis modulation in PAAD and LIHC, respectively. Interestingly, elevated glycolysis levels could also enhance STAT3 and YAP1 activity in PAAD and LIHC cells, respectively, forming a positive feedback loop. Conclusions Our results may provide new insights into the indispensable role of glycolysis metabolism in digestive system tumors and guide the direction of future metabolism–signaling target combined therapy.

Sign in / Sign up

Export Citation Format

Share Document