SNHG3/miR-148a-3p Axis–mediated High Expression of DNMT1 Correlates with Poor Prognosis and Tumor Immune Infiltration of Hepatocellular Carcinoma

Abstract Background Epigenetic reprogramming plays an important role in the occurrence, development, and prognosis of hepatocellular carcinoma (HCC). DNA methylation is a key epigenetic regulatory mechanism, and DNA methyltransferase 1 (DNMT1) is the major enzyme responsible for maintenance methylation. Nevertheless, the role and mechanism of DNMT1 in HCC remains poorly defined. Methods In the current study, we conducted pan-cancer analysis for DNMT1’s expression and prognosis using The Cancer Genome Atlas (TCGA) data set. We conducted gene Set Enrichment Analysis (GSEA) between high-and-low DNMT1 expression groups to identify DNMT1-related functional significance. We also investigated the relationship between DNMT1 expression and tumor immune microenvironment, including immune cell infiltration and the expression of immune checkpoints. Through a combination series of computer analyses (including expression analyses, correlation analyses, and survival analyses), the noncoding RNAs (ncRNAs) that contribute to the overexpression of DNMT1 were ultimately identified. Results We found that DNMT1 was upregulated in 16 types of human carcinoma including HCC, and DNMT1 might be a biomarker predicting unfavorable prognosis in HCC patients. DNMT1 mRNA expression was statistically associated with age, histological grade, and the level of serum AFP. Moreover, DNMT1 level was significantly and positively linked to tumor immune cell infiltration, immune cell biomarkers, and immune checkpoint expression. Meanwhile, Gene Set Enrichment Analysis (GSEA) revealed that high-DNMT1 expression was associated with epithelial mesenchymal transition (EMT), E2F target, G2M checkpoint, and inflammatory response. Finally, through a combination series of computer analyses the SNHG3/hsa-miR-148a-3p/DNMT1 axis was confirmed as the potential regulatory pathway in HCC. Conclusion SNHG3/miR-148a-3p axis upregulation of DNMT1 may be related to poor outcome, tumor immune infiltration, and regulated malignant properties in HCC.

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PVT1 is a prognostic marker associated with immune invasion of bladder urothelial carcinoma

Mathematical Biosciences and Engineering ◽

10.3934/mbe.2022009 ◽

2021 ◽

Vol 19 (1) ◽

pp. 169-190

Author(s):

Peiyuan Li ◽

◽

Gangjie Qiao ◽

Jian Lu ◽

Wenbin Ji ◽

...

Keyword(s):

Urothelial Carcinoma ◽

Immune Cell ◽

Cox Regression ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Gene Set Enrichment ◽

Cox Regression Analysis ◽

Gene Set ◽

Bladder Urothelial Carcinoma

<abstract> <p>Plasmacytoma variant translocation 1 (PVT1) is involved in multiple signaling pathways and plays an important regulatory role in a variety of malignant tumors. However, its role in the prognosis and immune invasion of bladder urothelial carcinoma (BLCA) remains unclear. This study investigated the expression of PVT1 in tumor tissue and its relationship with immune invasion, and determined its prognostic role in patients with BLCA. Patients were identified from the cancer genome atlas (TCGA). The enrichment pathway and function of PVT1 were explained by gene ontology (GO) term analysis, gene set enrichment analysis (GSEA) and single-sample gene set enrichment analysis (ssGSEA), and the degree of immune cell infiltration was quantified. Kaplan–Meier analysis and Cox regression were used to analyze the correlation between PVT1 and survival rate. PVT1-high BLCA patients had a lower 10-year disease-specific survival (DSS P < 0.05) and overall survival (OS P < 0.05). Multivariate Cox regression analysis showed that PVT1 (high vs. low) (P = 0.004) was an independent prognostic factor. A nomogram was used to predict the effect of PVT1 on the prognosis. PVT1 plays an important role in the progression and prognosis of BLCA and can be used as a medium biomarker to predict survival after cystectomy.</p> </abstract>

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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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RNA N6-Methyladenosine Regulator-Mediated Methylation Modifications Pattern and Immune Infiltration Features in Glioblastoma

Frontiers in Oncology ◽

10.3389/fonc.2021.632934 ◽

2021 ◽

Vol 11 ◽

Author(s):

Yimin Pan ◽

Kai Xiao ◽

Yue Li ◽

Yuzhe Li ◽

Qing Liu

Keyword(s):

Immune Cell ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Lasso Regression ◽

Gene Set Enrichment ◽

Clinical Prognosis ◽

Prognostic Assessment ◽

The Relationship

Glioblastoma (GBM) is a group of intracranial neoplasms with intra-tumoral heterogeneity. RNA N6-methyladenosine (m6A) methylation modification reportedly plays roles in immune response. The relationship between the m6A modification pattern and immune cell infiltration in GBM remains unknown. Utilizing expression data of GBM patients, we thoroughly explored the potential m6A modification pattern and m6A-related signatures based on 21 regulators. Thereafter, the m6A methylation modification-based prognostic assessment pipeline (MPAP) was constructed to quantitatively assess GBM patients’ clinical prognosis combining the Robustness and LASSO regression. Single-sample gene-set enrichment analysis (ssGSEA) was used to estimate the specific immune cell infiltration level. We identified two diverse clusters with diverse m6A modification characteristics. Based on differentially expressed genes (DEGs) within two clusters, m6A-related signatures were identified to establish the MPAP, which can be used to quantitatively forecast the prognosis of GBM patients. In addition, the relationship between 21 m6A regulators and specific immune cell infiltration was demonstrated in our study and the m6A regulator ELAVL1 was determined to play an important role in the anticancer response to PD-L1 therapy. Our findings indicated the relationship between m6A methylation modification patterns and tumor microenvironment immune cell infiltration, through which we could comprehensively understand resistance to multiple therapies in GBM, as well as accomplish precise risk stratification according to m6A-related signatures.

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m6A-Mediated Tumor Invasion and Methylation Modification in Breast Cancer Microenvironment

Journal of Oncology ◽

10.1155/2021/9987376 ◽

2021 ◽

Vol 2021 ◽

pp. 1-17

Author(s):

Fei Liu ◽

Xiaopeng Yu ◽

Guijin He

Keyword(s):

Breast Cancer ◽

Tumor Microenvironment ◽

Immune Cell ◽

Principal Component ◽

Enrichment Analysis ◽

Genomic Variation ◽

Gene Set Enrichment Analysis ◽

Single Sample ◽

Gene Set Enrichment ◽

Gene Set

Background. We analyzed the n6-methyladenosine (m6A) modification patterns of immune cells infiltrating the tumor microenvironment of breast cancer (BC) to provide a new perspective for the early diagnosis and treatment of BC. Methods. Based on 23 m6A regulatory factors, we identified m6A-related gene characteristics and m6A modification patterns in BC through unsupervised cluster analysis. To examine the differences in biological processes among various m6A modification modes, we performed genomic variation analysis. We then quantified the relative infiltration levels of different immune cell subpopulations in the tumor microenvironment of BC using the CIBERSORT algorithm and single-sample gene set enrichment analysis. Univariate Cox analysis was used to screen for m6A characteristic genes related to prognosis. Finally, we evaluated the m6A modification pattern of patients with a single BC by constructing the m6Ascore based on principal component analysis. Results. We identified three different m6A modification patterns in 2128 BC samples. A higher abundance of the immune infiltration of the m6Acluster C was indicated by the results of CIBERSORT and the single-sample gene set enrichment analysis. Based on the m6A characteristic genes obtained through screening, the m6Ascore was determined. The BC patients were segregated into m6Ascore groups of low and high categories, which revealed significant survival benefits among patients with low m6Ascores. Additionally, the high-m6Ascore group had a higher mutation frequency and was associated with low PD-L1 expression, and the m6Ascore and tumor mutation burden showed a positive correlation. In addition, treatment effects were better in patients in the high-m6Ascore group. Conclusions. In case of a single patient with BC, the immune cell infiltration characteristics of the tumor microenvironment and the m6A methylation modification pattern could be evaluated using the m6Ascore. Our results provide a foundation for improving personalized immunotherapy of BC.

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Immune cell confrontation in the papillary thyroid carcinoma microenvironment

10.21203/rs.3.rs-33230/v1 ◽

2020 ◽

Author(s):

Zhenyu Xie ◽

Xin Li ◽

Yuzhen He ◽

Song Wu ◽

Shiyue Wang ◽

...

Keyword(s):

T Cells ◽

Papillary Thyroid Carcinoma ◽

Thyroid Carcinoma ◽

Immune Cell ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Immune Cell Infiltration ◽

M2 Macrophages ◽

Papillary Thyroid ◽

Gene Set Enrichment

Abstract Background Papillary thyroid carcinoma (PTC) is classified as an inflammation-driven cancer. A systematic understanding of immune cell infiltration in PTC is essential for subsequent immune research and new diagnostic and therapeutic strategies. Methods Three different algorithms, single-sample gene set enrichment analysis (ssGSEA), immune cell marker and CIBERSORT, were used to evaluate the immune cell infiltration levels (abundance and proportion) in 10 data sets (The Cancer Genome Atlas [TCGA], GSE3467, GSE3678, GSE5364, GSE27155, GSE33630, GSE50901, GSE53157, GSE58545, and GSE60542; a total of 799 PTC and 194 normal thyroid samples). Consensus unsupervised clustering divided PTC patients into low-immunity and high-immunity groups. Weighted gene coexpression network analysis (WGCNA) and gene set enrichment analysis (GSEA) were used to analyze the potential mechanisms that cause differences in the immune response. Results Compared with normal tissues, PTC tissues had a higher overall immune level, and the M2 macrophages, Tregs, monocytes, neutrophils, dendritic cells (DCs), mast cells (MCs), and M0 macrophages had higher abundances and proportions in PTC tissues. Compared with early PTC, advanced PTC had higher immune infiltration, and M2 macrophages, Tregs, monocytes, neutrophils, DCs, MCs, and M0 macrophages had higher abundances and proportions in advanced PTC. Compared to the low-immunity group patients, the high-immunity group patients presented with a more advanced stage, a larger tumor size, greater lymph node metastasis, higher tall-cell PTC, lower follicular PTC proportions, more BRAF mutations and fewer RAS mutations. Epstein-Barr virus (EBV) infection was the most significantly enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway for key module genes. Conclusions In human PTC, M2 macrophages, Tregs, monocytes, neutrophils, DCs, MCs, and M0 macrophages played a tumor-promoting role, while M1 macrophages, CD8 + T cells, B cells, NK cells, and T follicular helper (TFH) cells (including eosinophils, γδ T cells, and Th17 cells, with weak supporting evidence) played an antitumor role. During the occurrence and development of PTC, the overall immune level was increased, and the abundance and proportion of tumor-promoting immune cells were significantly increased, indicating that immune escape had aggravated. Finally, we speculate that EBV may play an important role in changing the immune microenvironment of PTC tumors.

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Hepcidin Upregulation in Lung Cancer: A Potential Therapeutic Target Associated With Immune Infiltration

Frontiers in Immunology ◽

10.3389/fimmu.2021.612144 ◽

2021 ◽

Vol 12 ◽

Author(s):

Yumei Fan ◽

Bing Liu ◽

Fei Chen ◽

Zhiyuan Song ◽

Bihui Han ◽

...

Keyword(s):

Lung Cancer ◽

Cancer Patients ◽

Prognostic Value ◽

Immune Cell ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Gene Set Enrichment ◽

Hepcidin Expression ◽

Lung Cancer Patients ◽

Immune Infiltration

Lung cancer has the highest death rate among cancers globally. Hepcidin is a fascinating regulator of iron metabolism; however, the prognostic value of hepcidin and its correlation with immune cell infiltration in lung cancer remain unclear. Here, we comprehensively clarified the prognostic value and potential function of hepcidin in lung cancer. Hepcidin expression was significantly increased in lung cancer. High hepcidin expression was associated with sex, age, metastasis, and pathological stage and significantly predicted an unfavorable prognosis in lung cancer patients. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA) results suggested that hepcidin is involved in the immune response. Furthermore, hepcidin expression was positively correlated with the infiltration levels of immune cells and the expression of diverse immune cell marker sets. Importantly, hepcidin may affect prognosis partially by regulating immune infiltration in lung cancer patients. Hepcidin may serve as a candidate prognostic biomarker for determining prognosis associated with immune infiltration in lung cancer.

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Construction and Validation of a Reliable Six-Gene Prognostic Signature Based on the TP53 Alteration for Hepatocellular Carcinoma

Frontiers in Oncology ◽

10.3389/fonc.2021.618976 ◽

2021 ◽

Vol 11 ◽

Author(s):

Junyu Huo ◽

Liqun Wu ◽

Yunjin Zang

Keyword(s):

Gene Expression ◽

Hepatocellular Carcinoma ◽

Regression Analysis ◽

Cox Regression ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Prognostic Signature ◽

Gene Set Enrichment ◽

Cox Regression Analysis ◽

Gene Set

BackgroundThe high mutation rate of TP53 in hepatocellular carcinoma (HCC) makes it an attractive potential therapeutic target. However, the mechanism by which TP53 mutation affects the prognosis of HCC is not fully understood.Material and ApproachThis study downloaded a gene expression profile and clinical-related information from The Cancer Genome Atlas (TCGA) database and the international genome consortium (ICGC) database. We used Gene Set Enrichment Analysis (GSEA) to determine the difference in gene expression patterns between HCC samples with wild-type TP53 (n=258) and mutant TP53 (n=116) in the TCGA cohort. We screened prognosis-related genes by univariate Cox regression analysis and Kaplan–Meier (KM) survival analysis. We constructed a six-gene prognostic signature in the TCGA training group (n=184) by Lasso and multivariate Cox regression analysis. To assess the predictive capability and applicability of the signature in HCC, we conducted internal validation, external validation, integrated analysis and subgroup analysis.ResultsA prognostic signature consisting of six genes (EIF2S1, SEC61A1, CDC42EP2, SRM, GRM8, and TBCD) showed good performance in predicting the prognosis of HCC. The area under the curve (AUC) values of the ROC curve of 1-, 2-, and 3-year survival of the model were all greater than 0.7 in each independent cohort (internal testing cohort, n = 181; TCGA cohort, n = 365; ICGC cohort, n = 229; whole cohort, n = 594; subgroup, n = 9). Importantly, by gene set variation analysis (GSVA) and the single sample gene set enrichment analysis (ssGSEA) method, we found three possible causes that may lead to poor prognosis of HCC: high proliferative activity, low metabolic activity and immunosuppression.ConclusionOur study provides a reliable method for the prognostic risk assessment of HCC and has great potential for clinical transformation.

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Uncovering of the Association Between m5C Regulator-Mediated Methylation Modification Patterns and Tumor Microenvironment Infiltration Characteristics in Hepatocellular Carcinoma

10.21203/rs.3.rs-580707/v1 ◽

2021 ◽

Author(s):

Xinyu Gu ◽

Haibo Zhou ◽

Qingfei Chu ◽

Qiuxian Zheng ◽

Jing Wang ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Immune Cells ◽

Immune Cell ◽

Enrichment Analysis ◽

Tumour Microenvironment ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Cell Infiltration ◽

Gene Set ◽

Normal Tissues

Abstract Background: 5-Methylcytosine (m5C) plays essential roles in hepatocellular carcinoma (HCC), but the association between m5C regulation and immune cell infiltration in HCC has not yet been clarified.Methods: In this study, we analysed 371 patients with HCC from The Cancer Genome Atlas (TCGA) database, and the expression of 13 m5C regulators was investigated. Additionally, gene set variation analysis (GSVA), unsupervised clustering analysis, single-sample gene set enrichment analysis (ssGSEA), correlation analysis, and immunohistochemical (IHC) staining were performed.Results: Among the 371 patients, 41 had mutations in m5C regulators, the frequency of which was 11.26%. Then, we identified three m5C modification patterns that had obvious tumour microenvironment (TME) cell infiltration characteristics. Cluster-1 had an immune rejection phenotype; Cluster-2 had an immunoinflammatory phenotype; and Cluster-3 had an immune desert phenotype. In addition, we found that DNMT1 was highly expressed in tumour tissues compared with normal tissues in a tissue microarray (TMA) and that it was positively correlated with many TME-infiltrating immune cells. High expression of the m5C regulator DNMT1 was related to a poor prognosis in patients with HCC. Furthermore, we developed three Immu-clusters that were consistent with the immune characteristics of the m5C methylation modification patterns. We also discovered differences in the levels of immune cells and expression of chemokines and cytokines among the three Immu-clusters.Conclusions: Our work revealed the association between m5C modification and immune regulators in the TME. These findings also suggest that DNMT1 has great potential as a prognostic biomarker and therapeutic target for HCC.

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Identification METTL18 as a Potential Prognosis Biomarker and Associated With Immune Infiltrates in Hepatocellular Carcinoma

Frontiers in Oncology ◽

10.3389/fonc.2021.665192 ◽

2021 ◽

Vol 11 ◽

Author(s):

Tian-Hao Li ◽

Cheng Qin ◽

Bang-Bo Zhao ◽

Hong-Tao Cao ◽

Xiao-Ying Yang ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Multivariate Analysis ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Wilcoxon Test ◽

Hepatic Tissue ◽

Gene Set Enrichment ◽

Poor Overall Survival ◽

Gene Set

Methyltransferase-like 18 (METTL18), a METTL family member, is abundant in hepatocellular carcinoma (HCC). Studies have indicated the METTL family could regulate the progress of diverse malignancies while the role of METTL18 in HCC remains unclear. Data of HCC patients were acquired from the cancer genome atlas (TCGA) and gene expression omnibus (GEO). The expression level of METTL18 in HCC patients was compared with normal liver tissues by Wilcoxon test. Then, the logistic analysis was used to estimate the correlation between METTL18 and clinicopathological factors. Besides, Gene Ontology (GO), Gene Set Enrichment Analysis (GSEA), and single-sample Gene Set Enrichment Analysis (ssGSEA) were used to explore relevant functions and quantify the degree of immune infiltration for METTL18. Univariate and Multivariate Cox analyses and Kaplan–Meier analysis were used to estimate the association between METTL18 and prognosis. Besides, by cox multivariate analysis, a nomogram was conducted to forecast the influence of METTL18 on survival rates. METTL18-high was associated with Histologic grade, T stage, Pathologic stage, BMI, Adjacent hepatic tissue inflammation, AFP, Vascular invasion, and TP53 status (P < 0.05). HCC patients with METTL18-high had a poor Overall-Survival [OS; hazard ratio (HR): 1.87, P < 0.001), Disease-Specific Survival (DSS, HR: 1.76, P = 0.015), and Progression-Free Interval (PFI, HR: 1.51, P = 0.006). Multivariate analysis demonstrated that METTL18 was an independent factor for OS (HR: 2.093, P < 0.001), DSS (HR: 2.404, P = 0.015), and PFI (HR: 1.133, P = 0.006). Based on multivariate analysis, the calibration plots and C-indexes of nomograms showed an efficacious predictive effect for HCC patients. GSEA demonstrated that METTL18-high could activate G2M checkpoint, E2F targets, KRAS signaling pathway, and Mitotic Spindle. There was a positive association between the METTL18 and abundance of innate immunocytes (T helper 2 cells) and a negative relation to the abundance of adaptive immunocytes (Dendritic cells, Cytotoxic cells etc.). Finally, we uncovered knockdown of METTL18 significantly suppressed the proliferation, invasion, and migration of HCC cells in vitro. This research indicates that METTL18 could be a novel biomarker to evaluate HCC patients’ prognosis and an important regulator of immune responses in HCC.

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