Mining TCGA Database for Tumor Microenvironment-Related Genes of Prognostic Value in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most common and lethal malignancies. Recent studies reveal that tumor microenvironment (TME) components significantly affect HCC growth and progression, particularly the infiltrating stromal and immune cells. Thus, mining of TME-related biomarkers is crucial to improve the survival of patients with HCC. Public access of The Cancer Genome Atlas (TCGA) database allows convenient performance of gene expression-based analysis of big data, which contributes to the exploration of potential association between genes and prognosis of a variety of malignancies, including HCC. The “Estimation of STromal and Immune cells in MAlignant Tumors using Expression data” algorithm renders the quantification of the stromal and immune components in TME possible by calculating the stromal and immune scores. Differentially expressed genes (DEGs) were screened by dividing the HCC cohort of TCGA database into high- and low-score groups according to stromal and immune scores. Further analyses of functional enrichment and protein-protein interaction networks show that the DEGs are mainly involved in immune response, cell adhesion, and extracellular matrix. Finally, seven DEGs have significant association with HCC poor outcomes. These genes contain FABP3, GALNT5, GPR84, ITGB6, MYEOV, PLEKHS1, and STRA6 and may be candidate biomarkers for HCC prognosis.

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Identification of Prognostic Stromal-Immune Score–Based Genes in Hepatocellular Carcinoma Microenvironment

Frontiers in Genetics ◽

10.3389/fgene.2021.625236 ◽

2021 ◽

Vol 12 ◽

Author(s):

Shanshan Liu ◽

Guangchuang Yu ◽

Li Liu ◽

Xuejing Zou ◽

Lang Zhou ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Liver Cancer ◽

Immune Cells ◽

Malignant Tumors ◽

Clinical Importance ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Immune Score

A growing amount of evidence has suggested the clinical importance of stromal and immune cells in the liver cancer microenvironment. However, reliable prognostic signatures based on assessments of stromal and immune components have not been well-established. This study aimed to identify stromal-immune score–based potential prognostic biomarkers for hepatocellular carcinoma. Stromal and immune scores were estimated from transcriptomic profiles of a liver cancer cohort from The Cancer Genome Atlas using the ESTIMATE (Estimation of STromal and Immune cells in MAlignant Tumors using Expression data) algorithm. Least absolute shrinkage and selection operator (LASSO) algorithm was applied to select prognostic genes. Favorable overall survivals and progression-free interval were found in patients with high stromal score and immune score, and 828 differentially expressed genes were identified. Functional enrichment analysis and protein–protein interaction networks further showed that these genes mainly participated in immune response, extracellular matrix, and cell adhesion. MMP9 (matrix metallopeptidase 9) was identified as a prognostic tumor microenvironment–associated gene by using LASSO and TIMER (Tumor IMmune Estimation Resource) algorithms and was found to be positively correlated with immunosuppressive molecules and drug response.

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DUSP12 regulates the tumorigenesis and prognosis of hepatocellular carcinoma

PeerJ ◽

10.7717/peerj.11929 ◽

2021 ◽

Vol 9 ◽

pp. e11929

Author(s):

Gaoda Ju ◽

Tianhao Zhou ◽

Rui Zhang ◽

Xiaozao Pan ◽

Bing Xue ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

T Cells ◽

Immune Cells ◽

Malignant Tumors ◽

Critical Role ◽

Normal Liver ◽

Functional Enrichment ◽

Loss Of Function ◽

Liver Tissues

Background Dual specificity protein phosphatase (DUSP)12 is an atypical member of the protein tyrosine phosphatase family, which are overexpressed in multiple types of malignant tumors. This protein family protect cells from apoptosis and promotes the proliferation and motility of cells. However, the pathological role of DUSP12 in hepatocellular carcinoma (HCC) is incompletely understood. Methods We analyzed mRNA expression of DUSP12 between HCC and normal liver tissues using multiple online databases, and explored the status of DUSP12 mutants using the cBioPortal database. The correlation between DUSP12 expression and tumor-infiltrating immune cells was demonstrated using the Tumor Immune Estimation Resource database and the Tumor and Immune System Interaction Database. Loss of function assay was utilized to evaluate the role of DUSP12 in HCC progression. Results DUSP12 had higher expression along with mRNA amplification in HCC tissues compared with those in normal liver tissues, which suggested that higher DUSP12 expression predicted shorter overall survival. Analyses of functional enrichment of differentially expressed genes suggested that DUSP12 regulated HCC tumorigenesis, and that knockdown of DUSP12 expression by short hairpin (sh)RNA decreased the proliferation and migration of HCC cells. Besides, DUSP12 expression was positively associated with the infiltration of cluster of differentiation (CD)4+ T cells (especially CD4+ regulatory T cells), macrophages, neutrophils and dendritic cells. DUSP12 expression was positively associated with immune-checkpoint moieties, and was downregulated in a C3 immune-subgroup of HCC (which had the longest survival). Conclusion These data suggest that DUSP12 may have a critical role in the tumorigenesis, infiltration of immune cells, and prognosis of HCC.

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Systematic Profiling of Diagnostic and Prognostic Value of Autophagy-Related Genes for Sarcoma Patients

10.21203/rs.3.rs-76971/v1 ◽

2020 ◽

Author(s):

Yuanhe Wang ◽

Jianyi Li ◽

Cheng Shao ◽

Xiaojie Tang ◽

Yukun Du ◽

...

Keyword(s):

Tumor Microenvironment ◽

Immune Cells ◽

Disease Free Survival ◽

Independent Set ◽

Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Differentially Expressed ◽

Immune Checkpoints ◽

Systematic Analysis

Abstract Background: Autophagy-related genes (ARGs) have been confirmed to have an important role in tumorigenesis and tumor microenvironment formation. Nevertheless, a systematic analysis of ARGs and their clinical significance in sarcoma patients is lacking.Methods: Gene expression files from The Cancer Genome Atlas (TCGA) database and Genotype-Tissue Expression (GTEx) were used to select differentially expressed genes (DEGs). Differentially expressed ARGs (DEARGs) were determined by matching the DEG and HADb gene sets, which were evaluated by functional enrichment analysis. Unsupervised clustering of the identified DEARGs was conducted, and associations with tumor microenvironment (TME), immune checkpoints, and immune cells were analyzed simultaneously. Two prognostic signatures, one for overall survival (OS) and one for disease-free survival (DFS), were established and validated in an independent set. Results: In total, 84 DEIRGs and two clusters were identified. TME scores, five immune checkpoints, and several types of immune cells were found to be significantly different between twp clusters. Two prognostic signatures incorporating DEARGs showed favorable discrimination and were successfully validated. Two nomograms combining signature and clinical variables were generated. The C-indexes were 0.818 and 0.636 for the OS and DFS nomograms, respectively.Conclusion: This comprehensive analyses of the ARG landscape in sarcoma showed novel ARGs related to carcinogenesis and the immune microenvironment. These findings have implications for prognosis and therapeutic responses, which reveal novel potential prognostic biomarkers, promote precision medicine, and provide potential novel targets for immunotherapy.

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Development of a prognostic model based on immunogenomic landscape analysis of hepatocellular carcinoma

10.21203/rs.3.rs-238684/v1 ◽

2021 ◽

Author(s):

ligong lu ◽

Shaoqing Liu ◽

Shengni Hua ◽

Zhenlin Zhang ◽

Meixiao Zhan ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Prediction Model ◽

Risk Score ◽

Immune Cells ◽

Bioinformatics Analysis ◽

Cox Regression ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Differentially Expressed ◽

Prognostic Indicators

Abstract Background Hepatocellular carcinoma (HCC) is the most common subtype of liver cancer, and the systematic exploration of its prognostic indicators is urgently needed. In this study, we obtained 12 IRGs for the construction of a risk score prediction model in HCC by bioinformatics analysis. Methods Differentially expressed genes were screened using the R software edgeR package. Functional enrichment analysis was performed through gene ontology analyses as well as the Kyoto Encyclopedia of Genes and Genomes pathway analysis. Single factor and multi-factor Cox analysis were employed for survival analysis. We used the Timer software to examine the correlation between risk score and tumor-infiltrating immune cells. Results We identified 3,215 up-regulated and 1,044 down-regulated genes in HCC tissues based on a cohort from The Cancer Genome Atlas (TCGA). Differentially expressed immune-related genes (IRGs) and survival-associated IRGs were further identified. We also integrated multivariate Cox regression analyses to obtain 12 IRGs for the construction of a risk score prediction model, whose performance was verified using the Kaplan-Meier survival and receiver operating characteristic curve analyses. Our findings suggest that the risk score was associated with clinical characteristics and the infiltration of immune cells in HCC patients. Conclusions We obtained a risk score prediction model of 12 IRGs in HCC by bioinformatics analysis and confirmed its performance.

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Identification of prognostic alternative splicing events related to the immune microenvironment of hepatocellular carcinoma

Molecular Medicine ◽

10.1186/s10020-021-00294-3 ◽

2021 ◽

Vol 27 (1) ◽

Author(s):

Shanshan Yu ◽

Luya Cai ◽

Chuan Liu ◽

Ruihong Gu ◽

Lingyi Cai ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Alternative Splicing ◽

Cox Regression ◽

Malignant Tumors ◽

Prognostic Significance ◽

Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Immune Microenvironment ◽

The Impact

Abstract Background Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world, and its 5-year survival rate is less than 20%, despite various treatments being available. Increasing evidence indicates that alternative splicing (AS) plays a nonnegligible role in the formation and development of the tumor microenvironment (TME). However, the comprehensive analysis of the impact on prognostic AS events on immune-related perspectives in HCC is lacking but urgently needed. Methods The transcriptional data and clinical information of HCC patients were downloaded from TCGA (The Cancer Genome Atlas) database for calculating immune and stromal scores by ESTIMATE algorithm. We then divided patients into high/low score groups and explored their prognostic significance using Kaplan–Meier curves. Based on stromal and immune scores, differentially expressed AS events (DEASs) were screened and evaluated with functional enrichment analysis. Additionally, a risk score model was established by applying univariate and multivariate Cox regression analyses. Finally, gene set variation analysis (GSVA) was adopted to explore differences in biological behaviors between the high- and low-risk subgroups. Results A total of 370 HCC patients with complete and qualified corresponding data were included in the subsequent analysis. According to the results of ESTIMATE analysis, we observed that the high immune/stromal score group had a longer survival probability, which was significantly correlated with prognosis in HCC patients. In addition, 467 stromal/immune score-related DEASs were identified, and enrichment analysis revealed that DEASs were significantly enriched in pathways related to HCC tumorigenesis and the immune microenvironment. More importantly, the final prognostic signature containing 16 DEASs showed powerful predictive ability. Finally, GSVA demonstrated that activation of carcinogenic pathways and immune-related pathways in the high-risk group may lead to poor prognosis. Conclusions Collectively, these outcomes revealed prognostic AS events related to carcinogenesis and the immune microenvironment, which may yield new directions for HCC immunotherapy.

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Systematic profiling of diagnostic and prognostic value of autophagy-related genes for sarcoma patients

BMC Cancer ◽

10.1186/s12885-020-07596-5 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Yuanhe Wang ◽

Jianyi Li ◽

Cheng Shao ◽

Xiaojie Tang ◽

Yukun Du ◽

...

Keyword(s):

Tumor Microenvironment ◽

Immune Cells ◽

Disease Free Survival ◽

Independent Set ◽

Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Differentially Expressed ◽

Immune Checkpoints ◽

Systematic Analysis

Abstract Background Autophagy-related genes (ARGs) have been confirmed to have an important role in tumorigenesis and tumor microenvironment formation. Nevertheless, a systematic analysis of ARGs and their clinical significance in sarcoma patients is lacking. Methods Gene expression files from The Cancer Genome Atlas (TCGA) database and Genotype-Tissue Expression (GTEx) were used to select differentially expressed genes (DEGs). Differentially expressed ARGs (DEARGs) were determined by matching the DEG and HADb gene sets, which were evaluated by functional enrichment analysis. Unsupervised clustering of the identified DEARGs was conducted, and associations with tumor microenvironment (TME), immune checkpoints, and immune cells were analyzed simultaneously. Two prognostic signatures, one for overall survival (OS) and one for disease-free survival (DFS), were established and validated in an independent set. Results In total, 84 DEARGs and two clusters were identified. TME scores, five immune checkpoints, and several types of immune cells were found to be significantly different between two clusters. Two prognostic signatures incorporating DEARGs showed favorable discrimination and were successfully validated. Two nomograms combining signature and clinical variables were generated. The C-indexes were 0.818 and 0.747 for the OS and DFS nomograms, respectively. Conclusion This comprehensive analyses of the ARG landscape in sarcoma showed novel ARGs related to carcinogenesis and the immune microenvironment. These findings have implications for prognosis and therapeutic responses, which reveal novel potential prognostic biomarkers, promote precision medicine, and provide potential novel targets for immunotherapy.

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MCEMP1 as a Tumor Microenvironment and Immune Infiltration Related Gene for Prognostic Prediction in Advanced Gastric Cancer

10.21203/rs.3.rs-678280/v1 ◽

2021 ◽

Author(s):

Daijun Wang ◽

Yanmei Gu ◽

Yang Zhao ◽

Yumin Li

Keyword(s):

Gastric Cancer ◽

Tumor Microenvironment ◽

Advanced Gastric Cancer ◽

Cancer Progression ◽

Immune Cells ◽

Cox Regression ◽

The Cancer Genome Atlas ◽

Tissue Samples ◽

Protein Protein Interaction ◽

Immunotherapy Target

Abstract Background Tumor microenvironment (TME) has displayed profound clinical significance in cancer progression, prognosis and the efficacy of immunotherapy. However, the overall characteristics of TME in patients with advanced gastric cancer (AGC) have not been intensively studied. In order to get a more comprehensive understanding, this study aimed to investigate TME-related prognostic genes in patients with AGC based on bioinformatics, combined with histological verification.Methods Transcriptome and clinical data on stage III/IV GC were obtained from The Cancer Genome Atlas (TCGA) database. The data of stromal, immune scores and 22 infiltrating immune cells from AGC samples were evaluated by ESTIMATE and CIBERSORT algorithms. Then, mast cell-expressed membrane protein 1 (MCEMP1) was focused by integrated protein-protein interaction (PPI) network and Cox regression. The survival and expression analysis of MCEMP1 was evaluated and verified in tissues by immunohistochemistry (IHC) and quantitative real-time PCR (qRT-PCR).Results There was a positive correlation between TME scores and pathological grades. A total of 666 TME-related differential genes were screened. MCEMP1 was identified as a predictive factor related to the prognosis of AGC both in TCGA database and tissue samples. Further analysis indicated that MCEMP1 was involved in regulating pathways of immune activities. The results of CIBERSORT demonstrated that MCEMP1 expression was significantly correlated with the proportion of 8 kinds of infiltrating immune cells. Conclusion As a TME-related prognostic gene, MCEMP1 might play a crucial role in remodeling immune infiltrates in AGC patients, which might be a potential immunotherapy target for patients with AGC.

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As a Newly-Discovered Component in Tumor Microenvironment RUFY4 Participates in Regulation of T cell via Cytokine-Interaction and Predicts Prognosis and Immunotherapy Responsiveness of Clear Cell Renal Carcinoma Patients

10.21203/rs.3.rs-125317/v1 ◽

2020 ◽

Author(s):

Daojia Miao ◽

Jian Shi ◽

Zhiyong Xiong ◽

Changfei Yuan ◽

Wen Xiao ◽

...

Keyword(s):

Overall Survival ◽

T Cells ◽

Tumor Microenvironment ◽

Immune Cells ◽

Clear Cell ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Sequencing Data ◽

Cell Renal Cell Carcinoma ◽

Immune Infiltration

Abstract Background: clear cell renal cell carcinoma (ccRCC) is one of the most lethal kinds of malignancies in urinary system and the existing immunotherapy have not achieved satisfactory outcomes. Therefore, this study aims to establish a brand-new gene signature for immune-infiltration and clinical outcome (overall survival and immunotherapy responsiveness) of patients with ccRCC. Methods: Based on RNA sequencing data and clinical information in the Cancer Genome Atlas Project (TCGA) database, we investigated proportions of immune cells in 611 samples by an online tool CIBERSORTx. Multivariate survival analysis was used to determine crucial survival-associated immune cells and immune-infiltration-related genes (IIRGs). Next ROC analysis was carried on to evaluate the ability of IIRGs to distinguish patients and functional enrichment analysis were implemented to explore potential interaction network between immune cells and IIRGs. Results: T cells follicular helper (TFHs) and T cells regulatory (Tregs) were highly infiltrated in the tumor microenvironment and their abundance ratios were independent prognostic factors for overall survival. Among IIRGs of TFHs and TREGs, RUFY4 was found to be highly activated in tumor microenvironment and its co-expression network was enriched in regulation of T cells via cytokine-cytokine receptor interactions.Conclusion: These two cells and RUFY4, considered prognostic biomarkers and immunotherapeutic predictors of ccRCC patients, might also simultaneously affect the regulatory network in tumor microenvironment (TME) through cytokine interactions.

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An independent poor-prognosis subtype of hepatocellular carcinoma based on the tumor microenvironment

Journal of International Medical Research ◽

10.1177/0300060520980646 ◽

2021 ◽

Vol 49 (2) ◽

pp. 030006052098064

Author(s):

Junfeng Wang ◽

Jianying Lou ◽

Lei Fu ◽

Qu Jin

Keyword(s):

Gene Expression ◽

Hepatocellular Carcinoma ◽

Tumor Microenvironment ◽

Poor Prognosis ◽

Molecular Mechanisms ◽

Immune Cell ◽

Gene Expression Omnibus ◽

The Cancer Genome Atlas ◽

Functional Enrichment ◽

Using Data

Background Hepatocellular carcinoma (HCC) is a highly malignant tumor with a particularly poor prognosis. The tumor microenvironment (TME) is closely associated with tumorigenesis, progression, and treatment. However, the relationship between TME genes and HCC patient prognosis is poorly understood. Methods In this study, we identified two prognostic subtypes based on the TME using data from The Cancer Genome Atlas and Gene Expression Omnibus. The Microenvironment Cell Populations-counter method was used to evaluate immune cell infiltration in HCC. Differentially expressed genes between molecular subtypes were calculated with the Limma package, and clusterProfiler was used for Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functional enrichment analyses to identify genes related to the independent subtypes. We also integrated mRNA expression data into our bioinformatics analysis. Results We identified 4227 TME-associated genes and 640 genes related to the prognosis of HCC. We defined two major subtypes (Clusters 1 and 2) based on the analysis of TME-associated gene expression. Cluster 1 was characterized by increased expression of immune-associated genes and a worse prognosis than Cluster 2. Conclusions The identification of these HCC subtypes based on the TME provides further insight into the molecular mechanisms and prediction of HCC prognosis.

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ADAMTS12 acts as a tumor microenvironment related cancer promoter in gastric cancer

Scientific Reports ◽

10.1038/s41598-021-90330-3 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Yangming Hou ◽

Yingjuan Xu ◽

Dequan Wu

Keyword(s):

Gastric Cancer ◽

Tumor Microenvironment ◽

Immune Cell ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Tumor Promoter ◽

Protein Protein Interaction ◽

Oxidative Phosphorylation Pathway ◽

Cox Proportional Hazard Regression

AbstractThe infiltration degree of immune and stromal cells has been shown clinically significant in tumor microenvironment (TME). However, the utility of stromal and immune components in Gastric cancer (GC) has not been investigated in detail. In the present study, ESTIMATE and CIBERSORT algorithms were applied to calculate the immune/stromal scores and the proportion of tumor-infiltrating immune cell (TIC) in GC cohort, including 415 cases from The Cancer Genome Atlas (TCGA) database. The differentially expressed genes (DEGs) were screened by Cox proportional hazard regression analysis and protein–protein interaction (PPI) network construction. Then ADAMTS12 was regarded as one of the most predictive factors. Further analysis showed that ADAMTS12 expression was significantly higher in tumor samples and correlated with poor prognosis. Gene Set Enrichment Analysis (GSEA) indicated that in high ADAMTS12 expression group gene sets were mainly enriched in cancer and immune-related activities. In the low ADAMTS12 expression group, the genes were enriched in the oxidative phosphorylation pathway. CIBERSORT analysis for the proportion of TICs revealed that ADAMTS12 expression was positively correlated with Macrophages M0/M1/M2 and negatively correlated with T cells follicular helper. Therefore, ADAMTS12 might be a tumor promoter and responsible for TME status and tumor energy metabolic conversion.

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