Dataset Information

The Construction and Analysis of ceRNA Network and Patterns of Immune Infiltration in Colon Adenocarcinoma Metastasis.

ABSTRACT: Background:Colon adenocarcinoma (COAD) is a malignant and lethal tumor in digestive system and distance metastasis lead to poor prognosis. The metastasis-specific ceRNAs (competitive endogenous RNAs) and tumor-infiltrating immune cells might associate with tumor prognosis and distance metastasis. Nonetheless, few studies have concentrated on ceRNAs and Immune cells in COAD. Methods:The gene expression profile and clinical information of COAD were downloaded from TCGA and divided into two groups: primary tumors with or without distance metastasis. We applied comprehensive bioinformatics methods to analyze differential expression genes (DEGs) related to metastasis and establish the ceRNA networks. The Cox analysis and Lasso regression were utilized to screen the pivotal genes and prevent overfitting. Based on them, the prognosis prediction nomograms were established. The cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm was then applied to screen significant tumor immune-infiltrating cells associated with COAD metastasis and established another prognosis prediction model. Ultimately, co-expression analysis was applied to explore the relationship between key genes in ceRNA networks and significant immune cells. Multiple databases and preliminary clinical specimen validation were used to test the expressions of key biomarkers at the cellular and tissue levels. Results:We explored 1 significantly differentially expressed lncRNA, 1 significantly differentially expressed miRNA, 8 survival-related immune-infiltrating cells, 5 immune cells associated with distance metastasis. Besides, 3 pairs of important biomarkers associated with COAD metastasis were also identified: T cells follicular helper and hsa-miR-125b-5p (R = -0.200, P < 0.001), Macrophages M0 and hsa-miR-125b-5p (R = 0.170, P < 0.001) and Macrophages M0 and FAS (R = -0.370, P < 0.001). Multidimensional validation and preliminary clinical specimen validation also supported the results. Conclusion:In this research, we found some significant ceRNAs (FAS and hsa-miR-125b-5p) and tumor-infiltrating immune cells (T cells follicular helper and Macrophages M0) might related to distance metastasis and prognosis of COAD. The nomograms could assist scientific and medical researchers in clinical management.

SUBMITTER: Chang Z

PROVIDER: S-EPMC7417319 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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The Construction and Analysis of ceRNA Network and Patterns of Immune Infiltration in Colon Adenocarcinoma Metastasis.

Chang Zhengyan Z Huang Runzhi R Fu Wanting W Li Jiehan J Ji Guo G Huang Jinglei J Shi Weijun W Yin Huabin H Wang Weifeng W Meng Tong T Huang Zongqiang Z Wei Qing Q Qin Huanlong H

Frontiers in cell and developmental biology 20200804

<h4>Background</h4>Colon adenocarcinoma (COAD) is a malignant and lethal tumor in digestive system and distance metastasis lead to poor prognosis. The metastasis-specific ceRNAs (competitive endogenous RNAs) and tumor-infiltrating immune cells might associate with tumor prognosis and distance metastasis. Nonetheless, few studies have concentrated on ceRNAs and Immune cells in COAD.<h4>Methods</h4>The gene expression profile and clinical information of COAD were downloaded from TCGA and divided i ...[more]

PMID: 32850813

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Project description:BackgroundCompetitive Endogenous RNA (ceRNA) may be closely associated with tumor progression. However, studies on ceRNAs and immune cells in LUAD are scarce.MethodThe profiles of gene expression and clinical data of LUAD patients were extracted from the TCGA database. Bioinformatics methods were used to evaluate differentially-expressed genes (DEGs) and to form a ceRNA network. Preliminary verification of clinical specimens was utilized to detect the expressions of key biomarkers at the tissues. Cox and Lasso regressions were used to identify key genes, and prognosis prediction nomograms were formed. The mRNA levels of 9 genes in the risk score model in independent clinical LUAD samples were detected by qRT-PCR. The interconnection between the risk of cancer and immune cells was evaluated using the CIBERSORT algorithm, while the conformation of notable tumor-infiltrating immune cells (TIICs) in the LUAD tissues of the high and low risk groups was assessed using the RNA transcript subgroup in order to identify tissue types. Finally, co-expression study was used to examine the interconnection between the key genes in the ceRNA networks and the immune cells.ResultA ceRNA network of 115 RNAs was established, and nine key genes were identified to construct a Cox proportional-hazard model and create a prognostic nomogram. This risk-assessment model might serve as an independent factor to forecast the prognosis of LUAD, and it was consistent with the preliminary verification of clinical specimens. Survival analysis of clinical samples further validated the potential value of high risk groups in predicting LUAD prognosis. Five immune cells were identified with significant differences in the LUAD tissues of the high and low risk groups. Besides, two pairs of biomarkers associated with the growth of LUAD were found, i.e., E2F7 and macrophage M1 (R = 0.419, p = 1.4e- 08) and DBF4 and macrophage M1 (R = 0.282, p < 2.2 e- 16).ConclusionThis study identified several important ceRNAs, i.e. (E2F7 and BNF4) and TIICs (macrophage M1), which might be related to the development and prognosis of LUAD. The established risk-assessment model might be a potential tool in predicting LUAD of prognosis.

Project description:Background: Mesothelioma is a rare and aggressive tumor. Bone metastasis often occurs in the later stages of this disease along with poor quality of life. Thus, it is important to explore the tumorigenesis and bone metastasis mechanism of invasive mesothelioma. For this purpose, we established two nomograms based on tumor-infiltrating immune cells and ceRNA networks to describe the molecular immunity and the clinical prediction of mesothelioma patients with bone metastasis. Method: The expression profiles of mRNAs, lncRNAs, and miRNAs of 87 primary mesotheliomas were obtained from the TCGA database; there were four patients with bone metastasis and 83 patients without. We constructed a ceRNAs network based on the differentially expressed RNAs between mesothelioma and bone metastasis. CIBERSORT was used to distinguish 22 immune cell types from the tumor transcriptomes. Kaplan-Meier survival analysis and the Cox proportional hazards model were used to evaluate the prognostic value of each factor. Prognosis-associated immune cells and ceRNAs were applied to establish prediction nomograms. The receiver operating characteristic curves (ROC) and calibration curves were utilized to assess the discrimination and accuracy of the nomogram. Results: Differential analysis revealed that 20 lncRNAs, 15 miRNAs, and 230 mRNAs were significantly different in mesothelioma samples vs. bone metastasis samples. We constructed the ceRNA network to include 10 protein-coding mRNAs, 8 lncRNAs, and 10 miRNAs. Nine of 28 ceRNAs were found to be significant in the Kaplan-Meier analysis. Out of the 22 cell types, the fraction of dendritic cells resting (P = 0.018) was significantly different between the bone metastasis group and the non-bone metastasis group. The ROC and the calibration curves, based on ceRNA networks and tumor-infiltrating immune cells, respectively, suggested acceptable accuracy (AUC of 3-year survival: 0.827, AUC of 5-year survival: 0.840; AUC of 3-year survival: 0.730; AUC of 5-year survival: 0.753). Notably, based on the co-expression patterns between ceRNAs and Immune cells, we found that the hsa-miR-582-5p, CASP9, dendritic cells resting, ANIX2, T cells CD8, and T cells CD4 memory resting might be associated with the mesothelioma bone metastasis. Conclusion: Based on ceRNA networks and patterns of immune infiltration, our study provided a valid bioinformatics basis in order to explore the molecular mechanism and predict the possibility of mesothelioma bone metastasis.

Project description:BackgroundBladder cancer (BC) is the ninth most common malignant tumor, accounting for an estimate of 549,000 new BC cases and 200,000 BC-related deaths worldwide in 2018. The prognosis of BC has not substantially improved despite significant advances in the diagnosis and treatment of the disease.MethodsThe RNA sequencing (RNA-seq) data and clinical information of BC patients were downloaded from The Cancer Genome Atlas (TCGA) database. The Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) algorithm was used to assess immune infiltration. The survival analyses were performed using the selected components of a ceRNA network and selected immune cell types by least absolute shrinkage and selection operator (LASSO) Cox regression to calculate the risk score. The accuracy of prognosis prediction was determined by receiver operating characteristic (ROC) curves, survival curves, and nomograms. Finally, the correlation analysis was performed to investigate the relationships between the signature components of the ceRNA network and the immune cell signature.ResultsTwo completed survival analyses included selected components of the ceRNA network (ELN, SREBF1, DSC2, TTLL7, DIP2C, SATB1, hsa-miR-20a-5p, and hsa-miR-29c-3p) and selected immune cell types (M0 macrophages, M2 macrophages, resting mast cells, and neutrophils). ROC curves, survival curves (all P values <0.05), nomograms, and calibration curves indicated that the accuracy of the two survival analyses was acceptable. Moreover, the correlations between TTLL7 and resting mast cells (R=0.24, P<0.001), DSC2 and resting mast cells (R=-0.23, P<0.001), ELN and resting mast cells (R=0.44, P<0.001), and hsa-miR-29c-3p and M0 macrophages (R=-0.29, P<0.001) were significant, indicating that interactions of these factors may play significant roles in the prognosis of BC.ConclusionsTTLL7, DSC2, ELN, hsa-miR-29c-3p, resting mast cells, and M0 macrophages may play an important role in the development of BC. However, additional studies are needed to confirm this hypothesis.

Project description:Purpose: Kidney stones is a common medical issue that mediates kidney injury and even kidney function loss. However, the exact pathogenesis still remains unclear. This study aimed to explore the potential competing endogenous RNA (ceRNA)-related pathogenesis of kidney stones and identify the corresponding immune infiltration signature. Methods: One mRNA and one long non-coding RNA (lncRNA) microarray dataset was obtained from the GEO database. Subsequently, we compared differentially expressed mRNAs (DE-mRNAs) and lncRNAs between Randall's plaques in patients with calcium oxalate (CaOx) stones and controls with normal papillary tissues. lncRNA-targeted miRNAs and miRNA-mRNA pairs were predicted using the online databases. lncRNA-related DE-mRNAs were identified using the Venn method, and GO and KEGG enrichment analyses were subsequently performed. The immune-related lncRNA-miRNA-mRNA ceRNA network was developed. The CIBERSORT algorithm was used to estimate the rate of immune cell infiltration in Randall's plaques. The ceRNA network and immune infiltration were validated in the glyoxylate-induced hyperoxaluric mouse model and oxalate-treated HK-2 cells. Results: We identified 2,340 DE-mRNAs and 929 DE-lncRNAs between Randall's plaques in patients with CaOx stones and controls with normal papillary tissues. lncRNA-related DE-mRNAs were significantly enriched in extracellular matrix organization and collagen-containing extracellular matrix, which were associated with kidney interstitial fibrosis. The immune-related ceRNA network included 10 lncRNAs, 23 miRNAs, and 20 mRNAs. Moreover, we found that M2 macrophages and resting mast cells were differentially expressed between Randall's plaques and normal tissues. Throughout kidney stone development, kidney tubular injury, crystal deposition, collagen fiber deposition, TGF-β expression, infiltration of M1 macrophages, and activation of mast cells were more frequent in glyoxylate-induced hyperoxaluric mice compared with control mice. Nevertheless, M2 macrophage infiltration increased in early stages (day 6) and decreased as kidney stones progressed (day 12). Furthermore, treatment with 0.25 and 0.5 mM of oxalate for 48 h significantly upregulated NEAT1, PVT1, CCL7, and ROBO2 expression levels and downregulated hsa-miR-23b-3p, hsa-miR-429, and hsa-miR-139-5p expression levels in the HK-2 cell line in a dose-dependent manner. Conclusion: We found that significant expressions of ceRNAs (NEAT1, PVT1, hsa-miR-23b-3p, hsa-miR-429, hsa-miR-139-5p, CCL7, and ROBO2) and infiltrating immune cells (macrophages and mast cells) may be involved in kidney stone pathogenesis. These findings provide novel potential therapeutic targets for kidney stones.

Project description:Background: Kidney renal clear cell carcinoma (KIRC) has the highest invasion, mortality and metastasis of the renal cell carcinomas and seriously affects patient's quality of life. However, the composition of the immune microenvironment and regulatory mechanisms at transcriptomic level such as ceRNA of KIRC are still unclear. Methods: We constructed a ceRNA network associated with KIRC by analyzing the long non-coding RNA (lncRNA), miRNA and mRNA expression data of 506 tumor tissue samples and 71 normal adjacent tissue samples downloaded from The Cancer Genome Atlas (TCGA) database. In addition, we estimated the proportion of 22 immune cell types in these samples through "The Cell Type Identification by Estimating Relative Subsets of RNA Transcripts." Based on the ceRNA network and immune cells screened by univariate Cox analysis and Lasso regression, two nomograms were constructed to predict the prognosis of patients with KIRC. Receiver operating characteristic curves (ROC) and calibration curves were employed to assess the discrimination and accuracy of the nomograms. Consequently, co-expression analysis was carried out to explore the relationship between each prognostic gene in a Cox proportional hazards regression model of ceRNA and each survival-related immune cell in a Cox proportional hazards regression model of immune cell types to reveal the potential regulatory mechanism. Results: We established a ceRNA network consisting of 12 lncRNAs, 25 miRNAs and 136 mRNAs. Two nomograms containing seven prognostic genes and two immune cells, respectively, were successfully constructed. Both ROC [area under curves (AUCs) of 1, 3, and 5-year survival in the nomogram based on ceRNA network: 0.779, 0.747, and 0.772; AUCs of 1, 3, and 5-year survivals in nomogram based on immune cells: 0.603, 0.642, and 0.607] and calibration curves indicated good accuracy and clinical application value of both models. Through co-correlation analysis between ceRNA and immune cells, we found both LINC00894 and KIAA1324 were positively correlated with follicular helper T (Tfh) cells and negatively correlated with resting mast cells. Conclusion: Based on the ceRNA network and tumor-infiltrating immune cells, we constructed two nomograms to predict the survival of KIRC patients and demonstrated their value in improving the personalized management of KIRC.

Project description:Recent studies have revealed the significant role of the competing endogenous RNA (ceRNA) network in human diseases. However, systematic analysis of the ceRNA mechanism in chronic rhinosinusitis with nasal polyps (CRSwNP) is limited. In this study, we constructed a competitive endogenous RNA (ceRNA) network and identified a potential regulatory axis in CRSwNP based on bioinformatics analysis and experimental verification. We obtained lncRNA, miRNA, and mRNA expression profiles from the Gene Expression Omnibus. After analysis of CRSwNP patients and the control groups, we identified 565 DE-lncRNAs, 23 DE-miRNAs, and 1799 DE-mRNAs by the DESeq2 R package or limma R package. Enrichment analysis of 1799 DE-mRNAs showed that CRSwNP was associated with inflammation and immunity. Moreover, we identified 21 lncRNAs, 8 miRNAs and 8 mRNAs to construct the lncRNA-miRNA-mRNA ceRNA network. A potential MIAT/miR-125a/IRF4 axis was determined according to the degree and positive correlation between a lncRNA and its competitive endogenous mRNAs. The GSEA results suggested that IRF4 may be involved in immune cell infiltration. The validation of another dataset confirmed that MIAT and IRF4 were differentially expressed between the CRSwNP and control groups. The area under the ROC curve (AUC) of MIAT and IRF4 was 0.944. The CIBERSORT analysis revealed that eosinophils and M2 macrophages may be involved in the CRSwNP process. MIAT was correlated with dendritic cells and M2 macrophages, and IRF4 was correlated with dendritic cells. Finally, to validate the key genes, we performed in-silico validation using another dataset and experimental validation using immunohistochemistry, immunofluorescence, and Western blot. In summary, the constructed novel MIAT/miR-125a/IRF4 axis may play a critical role in the development and progression of CRSwNP. We believe that the ceRNA network and immune cell infiltration could offer further insight into novel molecular therapeutic targets for CRSwNP.

Dataset Information

The Construction and Analysis of ceRNA Network and Patterns of Immune Infiltration in Colon Adenocarcinoma Metastasis.

Publications

The Construction and Analysis of ceRNA Network and Patterns of Immune Infiltration in Colon Adenocarcinoma Metastasis.

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