Dataset Information

The Construction and Analysis of ceRNA Network and Patterns of Immune Infiltration in Mesothelioma With Bone Metastasis.

ABSTRACT: 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.

SUBMITTER: Huang R

PROVIDER: S-EPMC6813567 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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The Construction and Analysis of ceRNA Network and Patterns of Immune Infiltration in Mesothelioma With Bone Metastasis.

Huang Runzhi R Wu Jiawen J Zheng Zixuan Z Wang Guanghua G Song Dianwen D Yan Penghui P Yin Huabin H Hu Peng P Zhu Xiaolong X Wang Haiyun H Lv Qi Q Meng Tong T Huang Zongqiang Z Zhang Jie J

Frontiers in bioengineering and biotechnology 20191018

<b>Background:</b> 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. <b>Method:</b> ...[more]

PMID: 31681739

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Project description: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.

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.

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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.

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Dataset Information

The Construction and Analysis of ceRNA Network and Patterns of Immune Infiltration in Mesothelioma With Bone Metastasis.

Publications

The Construction and Analysis of ceRNA Network and Patterns of Immune Infiltration in Mesothelioma With Bone Metastasis.

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