Upregulation of B3GNT3 Correlates With Poor Prognosis and Decreased Immune Cell Infiltration In Pancreatic Adenocarcinoma

Abstract While previous studies have suggested that B3GNT3 is associated with tumorigenesis and progression of several tumors, its expression level and clinical significance in pancreatic adenocarcinoma (PAAD) remains unclear. Our study aimed to investigate the role of B3GNT3 in PAAD. B3GNT3 RNA sequencing and clinicopathological data were collected from the TCGA, GEO and GTEx databases. We assessed the expression and prognostic value of B3GNT3 in PAAD using R program and attached packages. Additionally, we investigate the correlation between B3GNT3 expression and tumor-infiltrating immune cells using CIBERSORT and the “correlation” module of GEPIA. Finally, gene set enrichment analysis (GSEA) was used to elucidate B3GNT3 related signaling pathways in PAAD. Results showed that B3GNT3 expression was significantly higher in tumor tissues compared to normal tissues (P <0.05). Increased B3GNT3 expression was correlated with advanced histologic grade and stage (Ⅰ Vs Ⅱ). Patients with high B3GNT3 expression had a worse OS (HR = 1.713, P = 0.0005). Moreover, a negative correlation between increased B3GNT3 expression and immune infiltrating level of naive B cells, CD8 T cells, and CD4 memory activated T cells was revealed by CIBERSORT analysis. Then, further analysis verified the correlation using the “correlation” module of GEPIA. Finally, GSEA suggested that functional enrichment of B3GNT3 was mainly involved in pathways in cancer, p53 signaling pathway, TGF beta signaling pathway, catabolic and transport processes of proteins, etc. Collectively, these results suggested that overexpression of B3GNT3 might affect the infiltration of immune cells and could act as a potential prognostic biomarker of PAAD.

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

10.21203/rs.3.rs-15489/v4 ◽

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

Cancer Cell International ◽

10.1186/s12935-020-01672-3 ◽

2020 ◽

Vol 20 (1) ◽

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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CENPF/CDK1 Signaling Pathway Enhances the Progression of Adrenocortical Carcinoma by Regulating the G2/M-phase Cell Cycle

10.21203/rs.3.rs-1012618/v1 ◽

2021 ◽

Author(s):

Yugang Huang ◽

Dan Li ◽

Li Wang ◽

Xiaomin Su ◽

Xian-bin Tang

Keyword(s):

Cell Cycle ◽

Signaling Pathway ◽

Adrenocortical Carcinoma ◽

Immune Cell ◽

Interaction Network ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Phase Cell ◽

Aberrant Expression ◽

M Phase

Abstract Adrenocortical carcinoma (ACC) is an aggressive and rare malignant tumor and prone to local invasion and metastasis. While, overexpressed Centromere Protein F (CENPF) is closely related to oncogenesis of various neoplasms, including ACC. However, the prognosis and exact biological function of CENPF in ACC remains largely unclear. In present essay, the expression of CENPF in human ACC samples, GEO and TCGA databases depicted that CENPF were overtly hyper-expressed in ACC patients and positively correlated with tumor stage. The aberrant expression of CENPF was significantly correlated with unfavorable overall survival (OS) in ACC patients. Then, the application of gene-set enrichment analysis (GSEA) declared that CENPF was mainly involved in the G2/M-phase mediated cell cycle and p53 signaling pathway. Further, a small RNA interference experiment was conducted to demonstrate that the interaction between CENPF and CDK1 enhanced the G2/M-phase transition of mitosis, cell proliferation and might induce p53 mediated anti-tumor effect in human ACC cell line, SW13 cells. Lastly, two available therapeutic strategies, including immunotherapy and chemotherapy, have been further probed. Immune infiltration analysis highlighted that ACC patients with high CENPF expression harbored significantly different immune cell populations, and high TMB/MSI score. Then, the gene-drug interaction network stated that CENPF inhibitors, such as Cisplatin, Sunitinib, and Etoposide, might serve as potential drugs for the therapy of ACC. Briefly, CENPF and related genes might be served as a novel prognostic biomarker or latent therapeutic target for ACC patients.

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Prognostic and immunological value of LTB4R in pan-cancer

Mathematical Biosciences and Engineering ◽

10.3934/mbe.2021459 ◽

2021 ◽

Vol 18 (6) ◽

pp. 9336-9356

Author(s):

Sidan Long ◽

◽

Shuangshuang Ji ◽

Kunmin Xiao ◽

Peng Xue ◽

...

Keyword(s):

Immune Cells ◽

Prognostic Significance ◽

Enrichment Analysis ◽

Negative Influence ◽

Leukotriene B4 ◽

Gene Set Enrichment Analysis ◽

Functional Enrichment ◽

Immune Infiltration ◽

Significant Difference ◽

Pan Cancer

<abstract> <sec><title>Background</title>LTB4 receptor 1 (LTB4R), as the high affinity leukotriene B4 receptor, is rapidly revealing its function in malignancies. However, it is still uncertain. </sec> <sec><title>Methods</title>We investigated the expression pattern and prognostic significance of LTB4R in pan-cancer across different databases, including ONCOMINE, PrognoScan, GEPIA, and Kaplan-Meier Plotter, in this study. Meanwhile, we explored the significance of LTB4R in tumor metastasis by HCMDB. Then functional enrichment analysis of related genes was performed using GeneMANIA and DAVID. Lastly, utilizing the TIMER datasets, we looked into the links between LTB4R expression and immune infiltration in malignancies. </sec> <sec><title>Results</title>In general, tumor tissue displayed higher levels of LTB4R expression than normal tissue. Although LTB4R had a negative influence on pan-cancer, a high expression level of LTB4R was protective of LIHC (liver hepatocellular carcinoma) patients' survival. There was no significant difference in the distribution of LTB4R between non-metastatic and metastatic tumors. Based on Gene Set Enrichment Analysis, LTB4R was implicated in pathways involved in inflammation, immunity, metabolism, and cancer diseases. The correlation between immune cells and LTB4R was found to be distinct across cancer types. Furthermore, markers of infiltrating immune cells, such as Treg, T cell exhaustion and T helper cells, exhibited different LTB4R-related immune infiltration patterns. </sec> <sec><title>Conclusion</title>The LTB4R is associated with immune infiltrates and can be used as a prognostic biomarker in pan-cancer. </sec> </abstract>

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The Role of Circular RNA CDR1as/ciRS-7 in Regulating Tumor Microenvironment: A Pan-Cancer Analysis

Biomolecules ◽

10.3390/biom9090429 ◽

2019 ◽

Vol 9 (9) ◽

pp. 429 ◽

Cited By ~ 24

Author(s):

Zou ◽

Zheng ◽

Deng ◽

Yang ◽

Xie ◽

...

Keyword(s):

Tumor Microenvironment ◽

Signaling Pathway ◽

Malignant Tumors ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Circular Rna ◽

Gene Set Enrichment Analysis ◽

Functional Enrichment ◽

Receptor Interaction

Circular RNA CDR1as/ciRS-7 functions as an oncogenic regulator in various cancers. However, there has been a lack of systematic and comprehensive analysis to further elucidate its underlying role in cancer. In the current study, we firstly performed a bioinformatics analysis of CDR1as among 868 cancer samples by using RNA-seq datasets of the MiOncoCirc database. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set enrichment analysis (GSEA), CIBERSORT, Estimating the Proportion of Immune and Cancer cells (EPIC), and the MAlignant Tumors using Expression data (ESTIMATE) algorithm were applied to investigate the underlying functions and pathways. Functional enrichment analysis suggested that CDR1as has roles associated with angiogenesis, extracellular matrix (ECM) organization, integrin binding, and collagen binding. Moreover, pathway analysis indicated that it may regulate the TGF-β signaling pathway and ECM-receptor interaction. Therefore, we used CIBERSORT, EPIC, and the ESTIMATE algorithm to investigate the association between CDR1as expression and the tumor microenvironment. Our data strongly suggest that CDR1as may play a specific role in immune and stromal cell infiltration in tumor tissue, especially those of CD8+ T cells, activated NK cells, M2 macrophages, cancer-associated fibroblasts (CAFs) and endothelial cells. Generally, systematic and comprehensive analyses of CDR1as were conducted to shed light on its underlying pro-cancerous mechanism. CDR1as regulates the TGF-β signaling pathway and ECM-receptor interaction to serve as a mediator in alteration of the tumor microenvironment.

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Association between cetuximab response and differential immunologic gene expression signatures in colorectal cancer metastases.

Journal of Clinical Oncology ◽

10.1200/jco.2016.34.4_suppl.558 ◽

2016 ◽

Vol 34 (4_suppl) ◽

pp. 558-558 ◽

Cited By ~ 1

Author(s):

Michael Sangmin Lee ◽

Benjamin Garrett Vincent ◽

Autumn Jackson McRee ◽

Hanna Kelly Sanoff

Keyword(s):

Gene Expression ◽

Colorectal Cancer ◽

T Cells ◽

T Cell ◽

Immune Cell ◽

Expression Profiles ◽

Gene Set Enrichment Analysis ◽

Activated T Cells ◽

Gene Sets

558 Background: Different immune cell infiltrates into colorectal cancer (CRC) tumors are associated with different prognoses. Tumor-associated macrophages contribute to immune evasion and accelerated tumor progression. Conversely, tumor infiltrating lymphocytes at the invasive margin of CRC liver metastases are associated with improved outcomes with chemotherapy. Cetuximab is an IgG1 monoclonal antibody against epidermal growth factor receptor (EGFR) and stimulates antibody-dependent cellular cytotoxicity (ADCC) in vitro. However, it is unclear in humans if response to cetuximab is modulated by the immune response. We hypothesized that different immune patterns detected in gene expression profiles of CRC metastases are associated with different responses to cetuximab. Methods: We retrieved gene expression data from biopsies of metastases from 80 refractory CRC patients treated with cetuximab monotherapy (GEO GSE5851). Samples were dichotomized by cetuximab response as having either disease control (DC) or progressive disease (PD). We performed gene set enrichment analysis (GSEA) with GenePattern 3.9.4 using gene sets of immunologic signatures obtained from the Molecular Signatures Database v5.0. Results: Among the 68 patients with response annotated, 25 had DC and 43 had PD. In the PD cohort, 59/1910 immunologic gene sets had false discovery rate (FDR) < 0.1. Notably, multiple gene sets upregulated in monocyte signatures were associated with PD. Also, gene sets consistent with PD1-ligated T cells compared to control activated T cells (FDR = 0.052) or IL4-treated CD4 T cells compared to controls (FDR = 0.087) were associated with PD. Conclusions: Cetuximab-resistant patients tended to have baseline increased expression of gene signatures reflective of monocytic infiltrates, consistent with also having increased expression of the IL4-treated T-cell signature. Cetuximab resistance was also associated with increased expression of the PD1-ligated T cell signature. These preliminary findings support further evaluation of the effect of differential immune infiltrates in prognosis of metastatic CRC treated with cetuximab.

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DNAJC10 Correlates with Tumor Immune Characteristics and Predicts the Prognosis of Glioma Patients

10.21203/rs.3.rs-761056/v1 ◽

2021 ◽

Author(s):

Feng Liu ◽

Zewei Tu ◽

Junzhe Liu ◽

Xiaoyan Long ◽

Bing Xiao ◽

...

Keyword(s):

T Cell ◽

Immune Cell ◽

Cox Regression ◽

Predictive Accuracy ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Functional Enrichment ◽

Time Dependent ◽

Prognostic Role

Abstract Background: A role of DNAJC10 has been reported in several cancers, but its function in glioma is not clear. The purpose of this study was to investigate the prognostic role and the underlying functions of DNAJC10 in glioma.Methods: Reverse transcription and quantitative polymerase chain reaction and western blotting were performed to quantify the relative DNAJC10 mRNA and protein expressions of clinical samples. Wilcoxon rank sum tests were used to compare DNAJC10 expression between or among glioma subgroups with different clinicopathological features. The overall survival (OS) rates of glioma patients with different DNAJC10 expression were compared with the Kaplan-Meier method (two-sided log-rank test). The prognosis-predictive accuracy of the DNAJC10 was evaluated by time-dependent receiver operating characteristic (ROC) curves. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes annotations were conducted using the “clusterProfiler” package. Single-sample gene set enrichment analysis was used to estimate immune cell infiltrations and immune-related function levels. The independent prognostic role of DNAJC10 was determined by univariate and multivariate Cox regression analyses. A DNAJC10-based nomogram model was established using multivariate Cox regression in the R package “rms.” Results: Higher DNAJC10 expression was observed in gliomas. It was upregulated in tumors with higher World Health Organization grade, isocitrate dehydrogenase wild-type status, 1p/19q non-co-deletion, and methylguanine-DNA methyltransferase unmethylated gliomas. Patients with gliomas with higher DNAJC10 expression had poorer prognoses than those with low-DNAJC10 gliomas. The predictive accuracy of 1/3/5-year OS of DNAJC10 was stable and robust using a time-dependent ROC model. Functional enrichment analysis recognized that T cell activation and T cell receptor signaling were enriched in higher DNAJC10 gliomas. Immune cell and stromal cell infiltrations, tumor mutation burden, copy number alteration burden, and immune checkpoint genes were also positively correlated with glioma DNAJC10 expression. A DNAJ10-based nomogram model was established and showed strong prognosis-predictive ability.Conclusion: Higher DNAJC10 expression correlates with poor prognosis of patients with glioma and is a potential and useful prognostic biomarker.

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