A Critical Role of Peptidylprolyl Isomerase A Pseudogene 22/microRNA-197-3p/Peptidylprolyl Isomerase A Axis in Hepatocellular Carcinoma

The burden of hepatocellular carcinoma (HCC) worldwide is increasing over time, while the underlying molecular mechanism of HCC development is still under exploration. Pseudogenes are classified as a special type of long non-coding RNAs (lncRNAs), and they played a vital role in regulating tumor-associated gene expression. Here, we report that a pseudogene peptidylprolyl isomerase A pseudogene 22 (PPIAP22) and its parental gene peptidylprolyl isomerase A (PPIA) were upregulated in HCC and were associated with the clinical outcomes of HCC. Further investigation revealed that PPIAP22 might upregulate the expression of PPIA through sponging microRNA (miR)-197-3p, behaving as competing endogenous RNA (ceRNA). PPIA could participate in the development of HCC by regulating mRNA metabolic process and tumor immunity based on the functional enrichment analysis. We also found a strong correlation between the expression levels of PPIA and the immune cell infiltration or the expression of chemokines, especially macrophage, C-C motif chemokine ligand 15 (CCL15), and C-X-C motif chemokine ligand 12 (CXCL12). Our findings demonstrate that the PPIAP22/miR-197-3p/PPIA axis plays a vital role in the progression of HCC by increasing the malignancy of tumor cells and regulating the immune cell infiltration, especially macrophage, through CCL15-CCR1 or CXCL12-CXCR4/CXCR7 pathways.

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Identification of Prognostic Genes in the Tumor Microenvironment of Hepatocellular Carcinoma

Frontiers in Immunology ◽

10.3389/fimmu.2021.653836 ◽

2021 ◽

Vol 12 ◽

Author(s):

Shixin Xiang ◽

Jing Li ◽

Jing Shen ◽

Yueshui Zhao ◽

Xu Wu ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Regression Analysis ◽

Tumor Microenvironment ◽

Immune Cell ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Functional Enrichment ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Tumor Purity

Background: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world. The efficacy of immunotherapy usually depends on the interaction of immunomodulation in the tumor microenvironment (TME). This study aimed to explore the potential stromal-immune score-based prognostic genes related to immunotherapy in HCC through bioinformatics analysis.Methods: ESTIMATE algorithm was applied to calculate the immune/stromal/Estimate scores and tumor purity of HCC using the Cancer Genome Atlas (TCGA) transcriptome data. Functional enrichment analysis of differentially expressed genes (DEGs) was analyzed by the Database for Annotation, Visualization, and Integrated Discovery database (DAVID). Univariate and multivariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis were performed for prognostic gene screening. The expression and prognostic value of these genes were further verified by KM-plotter database and the Human Protein Atlas (HPA) database. The correlation of the selected genes and the immune cell infiltration were analyzed by single sample gene set enrichment analysis (ssGSEA) algorithm and Tumor Immune Estimation Resource (TIMER).Results: Data analysis revealed that higher immune/stromal/Estimate scores were significantly associated with better survival benefits in HCC within 7 years, while the tumor purity showed a reverse trend. DEGs based on both immune and stromal scores primarily affected the cytokine–cytokine receptor interaction signaling pathway. Among the DEGs, three genes (CASKIN1, EMR3, and GBP5) were found most significantly associated with survival. Moreover, the expression levels of CASKIN1, EMR3, and GBP5 genes were significantly correlated with immune/stromal/Estimate scores or tumor purity and multiple immune cell infiltration. Among them, GBP5 genes were highly related to immune infiltration.Conclusion: This study identified three key genes which were related to the TME and had prognostic significance in HCC, which may be promising markers for predicting immunotherapy outcomes.

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Glucose-6-Phosphate Dehydrogenase is a Prognostic Biomarker and Correlated with Immune Infiltrates in Hepatocellular Carcinoma

10.21203/rs.3.rs-1232206/v1 ◽

2022 ◽

Author(s):

Yang Bu ◽

Kejun Liu ◽

Yiming Niu ◽

Ji Hao ◽

Lei Cui ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Tumor Microenvironment ◽

Liver Cancer ◽

Immune Cell ◽

Cox Regression ◽

Functional Enrichment ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Potential Biomarker ◽

Glucose 6 Phosphate Dehydrogenase

Abstract Background: Glucose-6-phosphate dehydrogenase (G6PD) plays an important role in the metabolic and immunological aspects of tumors. In hepatocellular carcinoma (HCC), the alteration of tumor microenvironment influences recurrence and metastasis. We extracted G6PD-related data from public databases of HCC tissues and used a bioinformatics approach to explore the correlation between G6PD expression and clinicopathological features and prognosis of immune cell infiltration in HCC.Methods: We extract G6PD expression information from TCGA and GEO databases in liver cancer tissues and normal tissues, validated by immunohistochemistry, and the correlation between G6PD expression and clinical features is analyzed, and the clinical significance of G6PD in liver cancer is assessed by Kaplan-Meier, Cox regression and prognostic line graph models. Functional enrichment analysis is performed by protein-protein interaction (PPI) network, GO/KEGG, GSEA and G6PD-associated differentially expressed genes (DEGs). TIMER and ssGSEA packages are used to assess the correlation between expression and the level of immune cell infiltration.Results: Our results show that G6PD expression is significantly upregulated in hepatocellular carcinoma tissues (P < 0.001). G6PD expression is associated with histological grade, pathological stage, T-stage, vascular infiltration and AFP level (P < 0.05); HCC patients in the low G6PD expression group had longer overall survival and better prognosis compared with the high G6PD expression group (P < 0.05). The level of G6PD expression also affects the levels of macrophages, unactivated dendritic cells, B cells, and follicular helper T cells in the tumor microenvironment.Conclusion: High expression of G6PD is a potential biomarker for poor prognosis of hepatocellular carcinoma, and G6PD may be a target for immunotherapy of HCC.

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ARID1A Is a Prognostic Biomarker and Associated with Immune Infiltrates in Hepatocellular Carcinoma

Canadian Journal of Gastroenterology and Hepatology ◽

10.1155/2022/3163955 ◽

2022 ◽

Vol 2022 ◽

pp. 1-14

Author(s):

Yuanyuan Feng ◽

Xinfang Tang ◽

Changcheng Li ◽

Ying Su ◽

Xiaoyu Wang ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Overall Survival ◽

Immune Cell ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Cell Infiltration ◽

Migration And Invasion ◽

Risk Indicator ◽

Immune Cell Infiltration

Objective. ARID1A has been discovered as a potential cancer biomarker. But its role in hepatocellular carcinoma (HCC) is subject to considerable dispute. Methods. The relationship between ARID1A and clinical factors was investigated. Clinicopathological variables related to overall survival in HCC subjects were identified using Cox and Kaplan–Meier studies. The connection between immune infiltrating cells and ARID1A expression was investigated using the tumor Genome Atlas (TCGA) dataset for gene set enrichment analysis (GSEA). Finally, a cell experiment was used to confirm it. Results. The gender and cancer topography (T) categorization of HCC were linked to increased ARID1A expression. Participants with advanced levels of ARID1A expression had a worse prognosis than someone with lower levels. ARID1A was shown to be a risk indicator of overall survival on its own. ARID1A expression is inversely proportional to immune cell infiltration. In vitro, decreasing ARID1A expression substantially slowed the cell cycle and decreased HCC cell proliferation, migration, and invasion. Conclusion. The expression of ARID1A could be used to predict the outcome of HCC. It is closely related to tumor immune cell infiltration.

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Bioinformatics analysis of the differentially co-expressed genes and immune cell infiltration features associated with pulmonary arterial hypertension

Archives of Medical Science ◽

10.5114/aoms/142102 ◽

2021 ◽

Author(s):

Wenshi Liu ◽

Dongdong Zheng ◽

Wenjing Lv ◽

Ying Hua ◽

Rong Huang ◽

...

Keyword(s):

Immune Cell ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Cell Infiltration ◽

Integrin Subunit ◽

Immune Cell Infiltration ◽

Control Groups ◽

Immune Infiltration ◽

And Control

IntroductionThis study aimed to identify novel differentially co-expressed genes and to investigate the features of immune cell infiltration in PAH.Material and methodsThe GSE113439 and GSE117261 datasets were acquired from the Gene Expression Omnibus database. And the differentially expressed genes between PAH and control groups were identified based on the GSE117261 dataset. Weighted Gene Co-Expression Network Analysis (WGCNA) was adopted to analyze the pre-processed data. Functional enrichment analysis was then carried out to explore the biological functions of these genes modules. The differentially co-expressed key genes modules were in-depth verified by GEO2R analysis. The immune infiltration in PAH was investigated by Cell type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT).ResultsWGCNA analysis found 15 differentially co-expressed genes modules, amongst which module blue indicated that it exhibited the strongest positive link to PAH, whereas module green presented the strongest negative association with PAH. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that the genes in module blue were largely enriched in Lysosome, Complement, and coagulation cascades, and others, while the genes in module green were primarily enriched in the Chemokine signaling pathway, Platelet activation, etc. Integrin subunit alpha M (ITGAM) was identified as the differentially co-expressed key gene. Immune infiltration analysis by CIBERSORT showed that the differences between PAH and control groups or between PAH subgroups.ConclusionsITGAM was considered a promising biomarker to discriminate PAH from the control. Obvious differences were observed in immune infiltration between patients with PAH and normal groups.

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Assessing immune infiltration and the tumor microenvironment for the diagnosis and prognosis of sarcoma

10.21203/rs.3.rs-15489/v3 ◽

2020 ◽

Author(s):

Naiqiang Zhu ◽

Jingyi Hou

Keyword(s):

T Cells ◽

Cd8 T Cells ◽

Immune Cells ◽

Molecular Mechanisms ◽

Immune Cell ◽

Enrichment Analysis ◽

Functional Enrichment ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Blue Module

Abstract Background: Sarcomas, cancers originating from mesenchymal cells, are comprehensive tumors with poor prognoses, yet their tumorigenic mechanisms are largely unknown. In this study, we characterize infiltrating immune cells and analyze immune scores to identify the molecular mechanism of immunologic response to sarcomas.Method: The “CIBERSORT” algorithm was used to calculate the amount of L22 immune cell infiltration in sarcomas. Then, the “ESTIMATE” algorithm was used to assess the “Estimate,” “Immune,” and “Stromal” scores. Weighted gene co-expression network analysis (WGCNA) was utilized to identify the significant module related to the immune therapeutic target. Gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using the “clusterProfiler” package in R for annotation and visualization. Results: Macrophages were the most common immune cells infiltrating sarcomas. The number of CD8 T cells was negatively associated with that of M0 and M2 macrophages, and positively associated with M macrophages in sarcomas samples. The clinical parameters (disease type, gender) significantly increased with higher Estimate, Immune, and Stromal scores, and with a better prognosis. The blue module was significantly associated with CD8 T cells. Functional enrichment analysis showed that the blue module was mainly involved in chemokine signaling and the PI3K-Akt signaling pathway. CD48, P2RY10 and RASAL3 were identified and validated at the protein level.Conclusion: Based on the immune cell infiltration and immune microenvironment, three key genes were identified, thus presenting novel molecular mechanisms of sarcoma metastasis.

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Assessing immune infiltration and the tumor microenvironment for the diagnosis and prognosis of sarcoma

10.21203/rs.3.rs-15489/v2 ◽

2020 ◽

Author(s):

Naiqiang Zhu ◽

Jingyi Hou

Keyword(s):

T Cells ◽

Cd8 T Cells ◽

Immune Cells ◽

Molecular Mechanisms ◽

Immune Cell ◽

Enrichment Analysis ◽

Functional Enrichment ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Blue Module

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Assessing immune infiltration and the tumor microenvironment for the diagnosis and prognosis of sarcoma

10.21203/rs.3.rs-15489/v1 ◽

2020 ◽

Author(s):

Naiqiang Zhu ◽

Jingyi Hou

Keyword(s):

T Cells ◽

Cd8 T Cells ◽

Immune Cells ◽

Molecular Mechanisms ◽

Immune Cell ◽

Enrichment Analysis ◽

Functional Enrichment ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Blue Module

Abstract Background Sarcomas, cancers originating from mesenchymal cells, are comprehensive tumors with poor prognoses, yet their tumorigenic mechanisms are largely unknown. In this study, we aimed to characterize infiltrating immune cells and genes associated with the immunologic response to sarcomas. Method The “CIBERSORT” algorithm was used to calculate the amount of L22 immune cell infiltration in sarcomas. Then, the “ESTIMATE” algorithm was used to assess the “Estimate,” “Immune,” and “Stromal” scores. Weighted gene co-expression network analysis (WGCNA) was utilized to identify the significant module related to the immune therapeutic target. Gene ontology (GO) enrichment and Kyoto Encyclopedia of Gens and Genomes (KEGG) analysis were applied using the “clusterProfiler” package in R for annotation and visualization. Results Macrophages were the most common immune cells infiltrating sarcomas. The number of CD8 T cells was negatively associated with that of M0 and M2 macrophages, and positively associated with M macrophages in sarcomas samples. The clinical parameters (disease type, gender) significantly increased with higher Estimate, Immune, and Stromal scores, and with a better prognosis. The blue module was significantly associated with CD8 T cells. Functional enrichment analysis showed that the blue module was mainly involved in chemokine signaling and the PI3K-Akt signaling pathway. CD48, P2RY10 and RASAL3 were identified and validated at the protein level. Conclusion Based on the immune cell infiltration and immune microenvironment, three key genes were identified, which suggest novel molecular mechanisms of sarcoma metastasis.

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Identification of lncRNA FAM99A gene as a prognostic biomarker of hepatocellular carcinoma

10.21203/rs.3.rs-16068/v1 ◽

2020 ◽

Author(s):

Manyi Sun ◽

Shuhua Lv ◽

Jin Zhong

Keyword(s):

Hepatocellular Carcinoma ◽

Dna Methylation ◽

Molecular Mechanism ◽

Immune Cell ◽

Sequence Similarity ◽

Enrichment Analysis ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Hepatic Cancer ◽

Clinical Prognosis

Abstract Background The complicated pathogenesis of hepatic cancer involves multiple clinical prognosis-associated oncogenes. Methods We utilized the bioinformatics approach to analyze the data from hepatic cancer cases collected by TCGA repository. Results We first found that the FAM99A (Family With Sequence Similarity 99 Member A) gene, a long non-coding RNA (lncRNA), is lowly expressed in hepatocellular carcinoma and closely related to clinical prognosis. We further analyzed the underling molecular mechanism from the perspectives of copy number variation (CNV), DNA methylation, immune cell infiltration, and related cellular pathway. Even though we did not observe a strong correlation between the FAM99A expression and the CNV or immune cell infiltration, the high methylation levels of the five methylated probe sites (cg24218935, cg01745044, cg04353359, cg04938738, cg25356611) were found to be negatively correlated with low expression level of FAM99A. Besides, we performed the enrichment analysis to screen out a group of FAM99A-correlated genes and molecular pathways, such as complement cascade, RNA metabolism, drug metabolic process, PPAR signaling pathway, or cell cycle. Conclusions The liver-specific FAM99A gene was first identified as a prognosis marker of hepatocellular carcinoma, and the underlying molecular mechanism involves DNA methylation and a series of cellular pathways.

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EPDR1 correlates with immune cell infiltration in hepatocellular carcinoma and can be used as a prognostic biomarker

10.21203/rs.3.rs-28073/v1 ◽

2020 ◽

Author(s):

Ruochan Chen ◽

Yiya Zhang

Keyword(s):

Hepatocellular Carcinoma ◽

Functional Analysis ◽

Immune Cell ◽

Prognostic Biomarker ◽

Prognostic Significance ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Normal Tissues

Abstract Background: Hepatocellular carcinoma (HCC) has high mortality rate and is a serious disease burden globally. Hence, identification and characterization of novel biomarkers for the diagnosis and prognosis of HCC are critically important. The protein EPDR1 (ependymin related 1) is a member of piscine brain glycoproteins and is involved in cell adhesion. This is the first study to report the expression of EPDR1 and its prognostic significance, pathological role, and association with cancer immunity in HCC.Methods: The gene expression, prognostic, and clinicopathological analyses were performed based on the data obtained from multiple transcriptome databases. Protein expression of EPDR1 in HCC was verified using human protein atlas and CPTAC databases. Co-expression network analysis using the LinkedOmics database was performed to identify genes co-expressed with EPDR1 expression. Functional analysis of the co-expressed genes, including gene set enrichment analysis was performed to identify the functional role of EPDR1. The statistical analysis was conducted in R, and the relationship between EPDR1 expression and immune cell infiltration was analyzed using TIMER and CIBERSORT resources. Results: The expression of EPDR1 was found to be significantly higher in HCC tissues than in the normal tissues and is an independent prognostic factor for the overall survival of HCC patients. Further, a high level of EPDR1 was shown to be correlated with advanced stage of HCC. Functional analysis revealed that EPDR1 is associated with multiple signaling pathways as well as pathways related to cancer and apoptosis. Notably, EPDR1 expression significantly correlated with purity and the infiltration levels of B cells, CD8+ and CD4+ T cells, macrophages, neutrophils, and dendritic cells in HCC. Further, the EPDR1 expression significantly correlated with the expression of immune signatures, such as KIR2DL4, ITGAM, GATA3, STAT6, STAT5A, BCL6, STAT3, and HAVCR2.Conclusions: Our study identified EPDR1 as a novel prognostic biomarker in HCC. The expression of EPDR1 was shown to be associated with immune cell infiltration as well as the signature molecules that potentially regulate these processes during the carcinogenesis of HCC. With better understanding of its biological function, EPDR1 could become an effective target for HCC diagnosis and treatment in the future.

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Omics- and Pharmacogenomic Evidence for the Prognostic, Regulatory, and Immune-Related Roles of PBK in a Pan-Cancer Cohort

Frontiers in Molecular Biosciences ◽

10.3389/fmolb.2021.785370 ◽

2021 ◽

Vol 8 ◽

Author(s):

Yi Liu ◽

Juan Xiang ◽

Gang Peng ◽

Chenfu Shen

Keyword(s):

Cell Cycle ◽

T Cells ◽

Cell Carcinoma ◽

Immune Cell ◽

Tumor Development ◽

Enrichment Analysis ◽

Functional Enrichment ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Poor Overall Survival

PDZ-binding kinase (PBK) is known to regulate tumor progression in some cancer types. However, its relationship to immune cell infiltration and prognosis in different cancers is unclear. This was investigated in the present study by analyzing data from TCGA, GEO, GETx, TIMER, CPTAC, GEPIA2, cBioPortal, GSCALite, PROGNOSCAN, PharmacoDB, STRING, and ENCORI databases. PBK was overexpressed in most tumors including adenocortical carcinoma (hazard ratio [HR] = 2.178, p < 0.001), kidney renal clear cell carcinoma (KIRC; HR = 1.907, p < 0.001), kidney renal papillary cell carcinoma (HR = 3.024, p < 0.001), and lung adenocarcinoma (HR = 1.255, p < 0.001), in which it was associated with poor overall survival and advanced pathologic stage. PBK methylation level was a prognostic marker in thyroid carcinoma (THCA). PBK expression was positively correlated with the levels of BIRC5, CCNB1, CDC20, CDK1, DLGAP5, MAD2L1, MELK, PLK1, TOP2A, and TTK in 32 tumor types; and with the levels of the transcription factors E2F1 and MYC, which regulate apoptosis, the cell cycle, cell proliferation and invasion, tumorigenesis, and metastasis. It was also negatively regulated by the microRNAs hsa-miR-101-5p, hsa-miR-145-5p, and hsa-miR-5694. PBK expression in KIRC, liver hepatocellular carcinoma, THCA, and thymoma was positively correlated with the infiltration of immune cells including B cells, CD4+T cells, CD8+ T cells, macrophages, monocytes, and neutrophils. The results of the functional enrichment analysis suggested that PBK and related genes contribute to tumor development via cell cycle regulation. We also identified 20 drugs that potentially inhibit PBK expression. Thus, PBK is associated with survival outcome in a variety of cancers and may promote tumor development and progression by increasing immune cell infiltration into the tumor microenvironment. These findings indicate that PBK is a potential therapeutic target and has prognostic value in cancer treatment.

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