Bioinformatics analysis of the prognostic value of NEK8 and its effects on immune cell infiltration in glioma

AIM: To investigate the role of tumor microenvironment (TME)-related long non-coding RNA (lncRNA) in uveal melanoma (UM), probable prognostic signature and potential small molecule drugs using bioinformatics analysis. METHODS: UM expression profile data were downloaded from the Cancer Genome Atlas (TCGA) and bioinformatics methods were used to find prognostic lncRNAs related to UM immune cell infiltration. The gene expression profile data of 80 TCGA specimens were analyzed using the single sample Gene Set Enrichment Analysis (ssGSEA) method, and the immune cell infiltration of a single specimen was evaluated. Finally, the specimens were divided into high and low infiltration groups. The differential expression between the two groups was analyzed using the R package ‘edgeR’. Univariate, multivariate and Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analyses were performed to explore the prognostic value of TME-related lncRNAs. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional analyses were also performed. The Connectivity Map (CMap) data set was used to screen molecular drugs that may treat UM. RESULTS: A total of 2393 differentially expressed genes were identified and met the criteria for the low and high immune cell infiltration groups. Univariate Cox analysis of lncRNA genes with differential expression identified 186 genes associated with prognosis. Eight prognostic markers of TME-included lncRNA genes were established as potentially independent prognostic elements. Among 269 differentially expressed lncRNAs, 69 were up-regulated and 200 were down-regulated. Univariate Cox regression analysis of the risk indicators and clinical characteristics of the 8 lncRNA gene constructs showed that age, TNM stage, tumor base diameter, and low and high risk indices had significant prognostic value. We screened the potential small-molecule drugs for UM, including W-13, AH-6809 and Imatinib. CONCLUSION: The prognostic markers identified in this study are reliable biomarkers of UM. This study expands our current understanding of the role of TME-related lncRNAs in UM genesis, which may lay the foundations for future treatment of this disease.

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Characteristics of immune cell infiltration and associated diagnostic biomarkers in ulcerative colitis: results from bioinformatics analysis

Bioengineered ◽

10.1080/21655979.2020.1863016 ◽

2020 ◽

Author(s):

Guohui Xue ◽

Lin Hua ◽

Nanjin Zhou ◽

Junming Li

Keyword(s):

Ulcerative Colitis ◽

Bioinformatics Analysis ◽

Immune Cell ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Diagnostic Biomarkers

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The prognostic value of a tumor microenvironment-based immune cell infiltration score model in colon cancer

10.21203/rs.3.rs-496500/v1 ◽

2021 ◽

Author(s):

Xiaofen Pan ◽

Xingkui Tang ◽

Minling Liu ◽

Xijun Luo ◽

Mengyuan Zhu ◽

...

Keyword(s):

Colon Cancer ◽

Signaling Pathway ◽

Immune Cells ◽

Evaluation System ◽

Prognostic Value ◽

Immune Cell ◽

Wnt Signaling Pathway ◽

Mapk Signaling ◽

Cell Infiltration ◽

Immune Cell Infiltration

Abstract BackgroundTumor microenvironment consists of tumor cells, immune cells and other matric components. Tumor infiltration immune cells are associated with prognosis. But all the current prognosis evaluation system dose not take tumor immune cells other matrix component into consideration. In the current study, we aimed to construct a prognosis predictive model based on tumor microenvironment.MethodCIBERSORT and ESTIMATE algorithms were used to reveal the immune cell infiltration landscape of colon cancer. Patients were classified into three clusters by ConsensusClusterPlus algorithm. Immune cell infiltration (ICI) scores of each patient were determine by principal-component analysis. Patients were divided to high and low ICI score groups. Survival, gene expression and somatic mutation of the two groups were compared.ResultsPatients with no lymph node invasion, no metastasis, T1-2 disease and stage I-II had higher ICI scores. Calcium signaling pathway, leukocyte transendothelial migration pathway, MAPK signaling pathway, TGF β pathway, and WNT signaling pathway were enriched in high ICI score group. Immune-checkpoint genes and immune-activity associated genes were significantly decreased in high ICI score. Patients in high ICI score group had better survival than low ICI score group. Prognostic value of ICI score was independent of TMB.ConclusionICI score might serve as an independent prognostic biomarker in colon cancer.

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YAP1 is a Prognostic Biomarker and Correlated with Immune Cell Infiltration in Pancreatic Cancer

Frontiers in Molecular Biosciences ◽

10.3389/fmolb.2021.625731 ◽

2021 ◽

Vol 8 ◽

Author(s):

Kai Sun ◽

Xue-de Zhang ◽

Xiao-yang Liu ◽

Pei Lu

Keyword(s):

Gene Expression ◽

Pancreatic Cancer ◽

Gene Expression Profiling ◽

Expression Profiling ◽

Prognostic Value ◽

Immune Cell ◽

Prognostic Biomarker ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Long Term Outcome

Yes-associated protein-1 (YAP1) is an important effector of the Hippo pathway and has crosstalk with other cancer signaling pathways. It induces an immunosuppressive tumor microenvironment by activating pathways in several cellular components. However, the mechanisms by which it drives immune infiltration in pancreatic cancer remain poorly understood. We analyzed the expression of YAP1 as well as its prognostic value and correlations with immune infiltrates in various cancers, with a focus on pancreatic cancer. In particular, using the Oncomine database and Gene Expression Profiling Interactive Analysis (GEPIA) database, we found that YAP1 is differentially expressed between tumor tissues and control tissues in a number of cancers and in particular, is elevated in pancreatic cancer. Using the Kaplan–Meier plotter, GEPIA, and Long-term Outcome and Gene Expression Profiling database of pan-cancers (LOGpc), we further established the prognostic value of YAP1. We found that YAP1 expression was significantly related to outcomes in multiple types of cancer based on data from The Cancer Genome Atlas, particularly in pancreatic cancer. Correlations between YAP1 and immune cell infiltration and immune cell marker expression were examined using Tumor Immune Estimation Resource and GEPIA. High expression levels of YAP1 were significantly associated with a variety of immune markers and immune cell subsets in pancreatic cancer. These results suggest that YAP1 is correlated with patient outcomes and tumor immune cell infiltration in multiple cancer types and is a valuable prognostic biomarker in pancreatic cancer.

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The Prognostic Value of a Tumor Microenvironment-Based Immune Cell Infiltration Score Model in Colon Cancer

Frontiers in Oncology ◽

10.3389/fonc.2021.728842 ◽

2021 ◽

Vol 11 ◽

Author(s):

Xingkui Tang ◽

Minling Liu ◽

Xijun Luo ◽

Mengyuan Zhu ◽

Shan Huang ◽

...

Keyword(s):

Colon Cancer ◽

Tumor Microenvironment ◽

Signaling Pathway ◽

Prognostic Value ◽

Immune Cell ◽

Wnt Signaling Pathway ◽

Mapk Signaling ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Score Model

The current study aimed to construct a prognostic predictive model based on tumor microenvironment. CIBERSORT and ESTIMATE algorithms were used to reveal the immune cell infiltration (ICI) landscape of colon cancer. Patients were classified into three clusters by ConsensusClusterPlus algorithm. ICI scores of each patient were determined by principal component analysis. Patients were divided into high and low ICI score groups. Survival, gene expression, and somatic mutation of the two groups were compared. We found that patients with no lymph node invasion, no metastasis, T1–2 disease, and stage I–II had higher ICI scores. Calcium signaling pathway, leukocyte transendothelial migration pathway, MAPK signaling pathway, TGF β pathway, and Wnt signaling pathway were enriched in the high ICI score group. Immune-checkpoint and immune-activity associated genes were decreased in high ICI score patients. Patients in the high ICI score group had better survival. Prognostic value of ICI score was independent of tumor mutational burden (TMB). The ICI score model constructed in the current study may serve as an independent prognostic biomarker in colon cancer.

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Comprehensive Analysis of YTH Domain Family in Lung Adenocarcinoma: Expression Profile, Association with Prognostic Value, and Immune Infiltration

Disease Markers ◽

10.1155/2021/2789481 ◽

2021 ◽

Vol 2021 ◽

pp. 1-12

Author(s):

Kuan Hu ◽

Lei Yao ◽

Yuanliang Yan ◽

Lei Zhou ◽

Juanni Li

Keyword(s):

T Cells ◽

Lung Adenocarcinoma ◽

Prognostic Value ◽

Immune Cell ◽

Expression Profiles ◽

Family Members ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Domain Family ◽

Yth Domain

Background. All YTH domain family members are m6A reader proteins accounting for the methylation modulation involved in the process of tumorgenesis and tumor progression. However, the expression profiles and roles of the YTH domain family in lung adenocarcinoma (LUAD) remain to be further illustrated. Methods. GEPIA2 and TNMplot databases were used to generate the expression profiles of the YTH family. Kaplan-Meier plotter database was employed to analysis the prognostic value of the YTH family. Coexpression profiles and genetic alterations analysis of the YTH family were undertaken using the cBioPortal database. YTH family protein-associated protein-protein interaction (PPI) network was identified by using STRING. Functional enrichment analysis was performed with the help of the WebGestalt database. The correlation analysis between the YTH family and immune cell infiltration in LUAD was administrated by using the TIMER2.0 database. Results. mRNA expression of YTHDC1 and YTHDC2 was significantly lower in LUAD, whereas YTHDF1, YTHDF2, and YTHDF3 with apparently higher expression. YTHDF2 expression was observed to be the highest in the nonsmoker subgroup, and its expression gradually decreased with the increased severity of smoking habit. LUAD patients with low expression of YTHDC2, YTHDF1, and YTHDF2 were correlated with a better overall survival (OS) time. The YTHDF1 genetic alteration rate was 26%, which was the highest in the YTH family. The major cancer-associated functions of YTH family pointed in the direction of immunomodulation, especially antigen processing and presentation. Most of the YTH family members were significantly correlated with the infiltration of CD4+ T cells, CD8+ T cells, macrophages, and neutrophils, indicating the deep involvement of the YTH domain family in the immune cell infiltration in LUAD. Conclusion. The molecular and expression profiles of the YTH family were dysregulated in LUAD. YTH family members (especially YTHDC2) were promising biomarkers and potential therapeutic targets that may bring benefit for the patients with LUAD.

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Identification of new biomarkers and pathways associated with treatment and prognosis in melanoma patients

10.21203/rs.2.23305/v1 ◽

2020 ◽

Author(s):

Biao Huang ◽

Wei Han ◽

Zu-Feng Sheng ◽

Guo-Liang Shen

Keyword(s):

Gene Expression ◽

T Cells ◽

Tumor Microenvironment ◽

Prognostic Value ◽

Immune Cell ◽

Gene Interaction ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Strong Positive Correlation ◽

Hub Genes

Abstract Background Skin cutaneous melanoma (SKCM) is known as the most malignancy and treatment-resistant in human tumor, causing about 72% of deaths in skin carcinoma. However, the potential mechanism and new effective targets remain to be further elucidated. Available datasets such as Gene Expression Omnibus (GEO) can be utilized to search for novel therapeutic targets and prognostic biomarkers. Methods Three data sets were downloaded from GEO database . The differentially expressed genes (DEGs) were identified via Venn software. Protein‐protein interaction network of DEGs was developed and the module hub genes analysis was constructed by Cytoscape. Subsequently, multiple online tools and Kaplan-Meier survival curves were analyzed to detect underlying signaling pathways, gene expression, drug-gene interaction and prognostic value of hub genes. In addition, we explored the correlation between hub genes and immune cell infiltration. At last, the related miRNA, lncRNA networks were constructed by R software. Results A total of 308 DEGs and 12 hub genes were identified. Function and pathway enrichment results demonstrated a correlation between DEGs and the tumor microenvironment, immune response and melanoma tumorigenesis. Subsequently, we focused on assessing potential value of 12 hub genes. Seven hub genes ( CCL4, CCL5, NMU, GAL, CXCL9, CXCL10, CXCL13 ) were identified with significant overall survival for prognosis. What’s more, five of these seven hub genes were found to be related to clinical stages (P values<0.05). In addition, the most important pathways of hub genes include interleukin-10 signaling, peptide ligand-binding receptors, which play important roles in tumor microenvironment for immune activation or immunosuppressive by regulating the infiltration of immune cells. Our results revealed a strong positive correlation between gene expression (CCL4, CCL5, CXCL9, CXCL10 and CXCL13) and immune cell infiltration (B-cell, CD8+ T cells, CD4+ T cells, macrophages, Neutrophils, Dendritic cells). Interestingly, 8 of 12 hub genes (CXCL10, CCL4, CCL5, IL6, CXCL2, PTGER3, GAL, NPY1R) were also found in the predicted drug-gene interaction. The related miRNA, lncRNA for diagnosis and prognosis were found in networks. Conclusion In conclusion, CCL4, CCL5, NMU, GAL, CXCL9, CXCL10, CXCL13 were of high prognostic value and may be potential targets for the diagnosis and therapy of patients with melanoma.

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Integrated Bioinformatics Analysis of Differentially-Expressed Genes and Immune Cell Infiltration Characteristics in Esophageal Squamous Cell Carcinoma

10.21203/rs.3.rs-153887/v1 ◽

2021 ◽

Author(s):

Zitong Feng ◽

Jingge Qu ◽

Xiao Liu ◽

Jinghui Liang ◽

Yongmeng Li ◽

...

Keyword(s):

Gene Expression ◽

Squamous Cell Carcinoma ◽

Esophageal Squamous Cell Carcinoma ◽

Cell Carcinoma ◽

Differentially Expressed Genes ◽

Squamous Cell ◽

Bioinformatics Analysis ◽

Immune Cell ◽

Cell Infiltration ◽

Immune Cell Infiltration

Abstract Esophageal squamous cell carcinoma (ESCC) is a life-threatening thoracic tumor with a poor prognosis. Identifying the best-targeted therapy, appropriate biomarkers and individual treatment for patients with ESCC remains a significant challenge. The present study aimed to elucidate key candidate genes and immune cell infiltration characteristics in ESCC by integrated bioinformatics analysis. We downloaded nine gene expression datasets from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between ESCC tissues and normal tissues in each dataset were identified by the “limma” R package, and a total of 152 robust DEGs were identified by robust rank aggregation (RRA) algorithm. Functional enrichment analyses of the robust DEGs showed that these genes were significantly associated with extracellular matrix related process. Immune cell infiltration analysis was also conducted by CIBERSORT algorithm. We found that M0 and M1 macrophages were increased dramatically in ESCC while M2 macrophages decreased. Nine hub genes were picked out from a protein-protein interaction (PPI) network used by the CytoHubba plugin in Cytoscape. According to the receiver operating characteristic (ROC) curves and Kaplan-Meier survival analysis, the genes PLAU, SPP1 and VCAN had high diagnostic and prognostic values for ESCC patients. Based on univariate and multivariate regression analyses, seven genes (IL18, PLAU, ANO1, SLCO1B3, CST1, NELL2 and MAGEA11) from the robust DEGs were used to construct a good prognostic model. A nomogram that incorporates seven genes signature was established to develop a quantitative method for ESCC prognosis. Our results might provide aid for exploring potential therapeutic targets and prognosis evaluation in ESCC.

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