The Construction and Comprehensive Analysis of Inflammation-Related ceRNA Networks and Tissue-Infiltrating Immune Cells in Ulcerative Progression.
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ABSTRACT:
SUBMITTER: Lu JW
PROVIDER: S-EPMC8277522 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundAs the second most common malignancy in adults, papillary renal cell carcinoma (PRCC) has shown an increasing trend in both incidence and mortality. Effective treatment for advanced metastatic PRCC is still lacking. In this study, we aimed to establish competitive endogenous RNA (ceRNA) networks related to PRCC tumorigenesis, and analyze the specific role of differentially expressed ceRNA components and infiltrating immune cells in tumorigenesis.MethodsCeRNA networks were established to identify the key ceRNAs related to PRCC tumorigenesis based on the 318 samples from The Cancer Genome Atlas database (TCGA), including 285 PRCC and 33 normal control samples. The R package, "CIBERSORT," was used to evaluate the infiltration of 22 types of immune cells. Then we identified the significant ceRNAs and immune cells, based on which two nomograms were obtained for predicting the prognosis in PRCC patients. Finally, we investigated the co-expression of PRCC-specific immune cells and core ceRNAs via Pearson correlation test.ResultsCOL1A1, H19, ITPKB, LDLR, TCF4, and WNK3 were identified as hub genes in ceRNA networks. Four prognostic-related tumor-infiltrating immune cells, including T cells CD4 memory resting, Macrophages M1, and Macrophages M2 were revealed. Pearson correlation test indicated that Macrophage M1 was negatively related with COL1A1 (p < 0.01) and LDLR (p < 0.01), while Macrophage M2 was positively related with COL1A1 (p < 0.01), TCF4 (p < 0.01), and H19 (p = 0.032). Two nomograms were conducted with favorable accuracies (area under curve of 1-year survival: 0.935 and 0.877; 3-year survival: 0.849 and 0.841; and 5-year survival: 0.818 and 0.775, respectively).ConclusionThe study constructed two nomograms suited for PRCC prognosis predicting. Moreover, we concluded that H19-miR-29c-3p-COL1A1 axis might promote the polarization of M2 macrophages and inhibit M1 macrophage activation through Wnt signaling pathway, collaborating to promote PRCC tumorigenesis and lead to poor overall survival of PRCC patients.
| S-EPMC8607257 | biostudies-literature
Project description:Background/Aims: As a malignant and melanocytic tumor, cutaneous melanoma is the devastating skin tumor with high rates of recurrence and metastasis. Bone is the common metastatic location, and bone metastasis may result in pathologic fracture, neurologic damage, and severe bone pain. Although metastatic melanoma was reported to get benefits from immunotherapy, molecular mechanisms and immune microenviroment underlying the melanoma bone metastasis and prognostic factors are still unknown. Methods: Gene expression profiling of 112 samples, including 104 primary melanomas and 8 bone metastatic melanomas from The Cancer Genome Atlas database, was assayed to construct a ceRNA network associated with bone metastases. Besides, we detected the fraction of 22 immune cell types in melanoma via the algorithm of "cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT)." Based on the significant ceRNAs or immune cells, we constructed nomograms to predict the prognosis of patients with melanoma. Ultimately, correlation analysis was implemented to discover the relationship between the significant ceRNA and immune cells to reveal the potential signaling pathways. Results: We constructed a ceRNA network based on the interaction among 8 pairs of long noncoding RNA-microRNA and 15 pairs of microRNA-mRNA. CIBERSORT and ceRNA integration analysis discovered that AL118506.1 has both significant prognostic value (P = 0.002) and high correlation with T follicular helper cells (P = 0.033). Meanwhile, T cells CD8 and macrophages M2 were negatively correlated (P < 0.001). Moreover, we constructed two satisfactory nomograms (area under curve of 3-year survival: 0.899; 5-year survival: 0.885; and concordance index: 0.780) with significant ceRNAs or immune cells, to predict the prognosis of patients. Conclusions: In this study, we suggest that bone metastasis in melanoma might be related to AL118506.1 and its role in regulating thrombospondin 2 and T follicular helper cells. Two nomograms were constructed to predict the prognosis of patients with melanoma and demonstrated their value in improving the personalized management.
| S-EPMC6774271 | biostudies-literature
Project description:Soft tissue sarcoma (STS) is one of the most challenging tumors for medical oncologists, with a high rate of recurrence after initial resection. In this study, a recurrent STS-specific competitive endogenous RNA (ceRNA) network including seven recurrence and overall survival (OS)-associated genes (LPP-AS2, MUC1, GAB2, hsa-let-7i-5p, hsa-let-7f-5p, hsa-miR-101-3p and hsa-miR-1226-3p) was established based on the gene expression profiling of 259 primary sarcomas and 3 local recurrence samples from the TCGA database. The algorithm "cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT)" was applied to estimate the fraction of immune cells in sarcomas. Based on 5 recurrence and OS-associated immune cells (NK cells activated, dendritic cells resting, mast cells resting, mast cells activated and macrophages M1), we constructed a recurrent STS-specific immune cells network. Both nomograms were identified to have good reliabilities (Area Under Curve (AUC) of 5-year survival is 0.724 and 0.773, respectively). Then the co-expression analysis was performed to identify the potential regulation network among recurrent STS-specific immune cells and ceRNAs. Hsa-miR-1226-3p and MUC1 were significantly correlated and dendritic cells resting was related to hsa-miR-1226-3p. Additionally, the expression of MUC1 and dendritic cell marker CD11c were also verified by immunohistochemistry (IHC) assay and multidimensional databases. In conclusion, this study illustrated the potential mechanism of hsa-miR-1226-3p regulating MUC1 and dendritic cells resting might play an important role in STS recurrence. These findings might provide potential prognostic biomarkers and therapeutic targets for recurrent STS.
| S-EPMC6914407 | biostudies-literature
Project description:BackgroundAt present, the mechanisms behind atrial fibrillation (AF) pathogenesis are still unclear. We construct a ceRNA immunoregulatory network to further understand the mechanism of AF.MethodsFour AF mRNA datasets from the Gene Expression Omnibus (GEO) database were integrated by SVA method. AF-related immune genes (AF-IRGs) were selected via combining ImmPort database with the genes in the module most associated with AF obtained by a weighted gene coexpression network analysis (WGCNA). Then, circRNA and miRNA expressions from the GEO database were extracted and mapped with related databases. Next, an immune-related circRNA-miRNA-mRNA ceRNA network was constructed and hub genes were filtered from a protein-protein interaction (PPI) network, and the differentially expressed (DE) hub genes in AF were further screened. Additionally, immune infiltration was investigated in AF by using CIBERSORT. Subsequently, the relationships between DE hub genes and AF-related infiltrating immune cells were performed by using Pearson correlation coefficients. Ulteriorly, the immune-cells-related ceRNA subnetwork in AF was built.ResultsA total of 95 AF-IRGs were detected, and an immune-related ceRNA network in AF was constructed with 12 circRNAs, 7 miRNAs and 50 mRNAs. The immune infiltration analysis indicated that a higher level of neutrophils, as well as a lower level of T cells regulatory (Tregs) and NK cells activated in AF. Four DE hub genes (CXCL12, IL7R, TNFSF13B, CD8A) were associated with Tregs or NK cells activated immune cells (P < 0.05). Tregs or NK cells activated immune cells-related ceRNA subnetwork including 5 circRNAs (has_circ_0001190, has_circ_0006725, has_circ_0079284, has_circ_0005299, and has_circ_0002103), 4 miRNAs (has-miR-198, has-miR-623, has-miR-1246, and has-miR-339-3p) and 4 DE hub genes was eventually constructed in AF.ConclusionOur results provide new insights into the molecular mechanisms governing AF progression from the perspective of immune-related ceRNA network.
| S-EPMC8643171 | biostudies-literature
Project description:BackgroundBladder cancer (BLCA) is the 11th most common malignancy worldwide. Although significant improvements have been made in screening, diagnosis, and precise management in recent years, the prognosis of BLCA remains bleak.ObjectivesThis study aimed to investigate the prognostic significance of tumor-infiltrating immune cells and construct ceRNA networks in BLCA patients.MethodsThe expression data of BLCA patients were obtained from The Cancer Genome Atlas (TCGA) database. A competing endogenous RNA (ceRNA) network was constructed to identify the hub genes involved in the prognosis of BLCA. The CIBERSORT algorithm was utilized to investigate the infiltration levels of 22 subsets of immune cells. Ultimately, the nomogram was generated to visualize the survival probability of each patient, with the calibration curve being performed to assess its performance. Furthermore, the Pearson correlation test was used to explore the correlation between the identified hub genes in the ceRNA network and the prognostic-related immune cells.ResultsA total of eight elements in the ceRNA network were considered as key members and correlated with the prognosis of BLCA, including ELN, SREBF1, DSC2, TTLL7, DIP2C, SATB1, hsa-miR-20a-5p, and hsa-miR-29c-3p. T cells CD8, T cells follicular helper (Tfh), and neutrophils were identified as independent prognostic factors in BLCA. The co-expression analysis showed that there was a significant correlation between the identified hub genes and immune cells.ConclusionOur results suggest that the mechanism of hsa-miR-29c-3p regulates the expression of ELN and DSC2, and the infiltration of Tfh and neutrophils might play pivotal roles in the progression of BLCA.
| S-EPMC7775311 | biostudies-literature
Project description:BackgroundDiabetic foot ulcer (DFU) is a severe complication characterized by low-grade infectious inflammation and probably associated with specific competitive endogenous RNAs (ceRNAs) and infiltrating immune cells. Nonetheless, no reliable biomarkers are used for detecting infectious inflammation in DFU. Therefore, it is essential to explore potential biomarkers for the accurate diagnosis and treatment of DFU.MethodsThe gene expression profile was retrieved from Gene Expression Omnibus (GEO) database and divided into two groups, namely, standard samples and DFU samples. To establish the ceRNA networks, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were utilized to analyze differential expression genes (DEGs). The cell type identification was achieved by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm to screen-specific immune-infiltrating cells associated with DFU.ResultsA ceRNA network was constructed with 20 differential expression circRNA (DEcircRNAs), 11 differential expression microRNAs (DEmiRNAs), and 9 differential expression mRNAs (DEmRNAs). Functional enrichment analysis demonstrated that DFU was mainly enriched in vascular endothelial growth factor (VEGF) and T-cell receptor signaling. In addition, CIBERSORT estimation indicated that CD8+ T cells and Monocytes were significantly related to the expression of IL-6, a DFU-specific infectious inflammation factor.ConclusionThis study identified that some significant ceRNAs (JUNB, GATA3, hsa-circ-0049271 and hsa-circ-0074559) and infiltrating immune cells (CD8+ T cells and monocytes) might be related to DFU infectious inflammation.
| S-EPMC9329527 | biostudies-literature
Project description:PURPOSE:To construct and analyze tumor-infiltrating immune cell and ceRNA (competitive endogenous RNA) networks in metastatic adrenal cortical carcinoma (ACC). METHODS:A ceRNA network was established to identify the ceRNAs involved in metastasis of ACC based on 92 samples from TCGA, including 18 cases of metastasis and 74 cases of non-metastatic primary tumors. And the algorithm "cell type identification by estimating relative subsets of RNA transcripts (CIBERSORT)" was used to quantify the proportion of immune cells in ACC. In addition, predictive nomograms based on the types of important immune cells or ceRNAs were constructed to predict ACC prognosis. Moreover, we evaluated the relationships between metastatic ACC-specific immune cells and ceRNA networks to identify the potential immune gene characteristics. RESULTS:Ten prognostic biomarkers were identified as key members of the ceRNA network and three tumor-infiltrating immune cells were identified by CIBERSORT algorithm. Some important co-expression patterns between immune cells and ceRNAs network indicate significant correlation between Macrophages M0 and hsa-miR-130b-3p (P < 0.001), Macrophages M0 and H2AFX (P = 0.003). CONCLUSIONS:The present study inferred that the metastasis-related ceRNAs of H2AFX, hsa-miR-130b-3p and Macrophages M0 might play important roles in ACC metastasis.
| S-EPMC7103591 | biostudies-literature
Project description:Adiponectin (APN) is an endogenous adipokine secreted from adipocytes that exerts an anti-inflammation property. AdipoAI is an orally active adiponectin receptor agonist identified by our group, which can emulate APN's anti-inflammatory properties through mechanisms not fully understood. To explore AdipoAI function, we used lncRNA microarray and got differential lncRNA/mRNA expression medicated by AdipoAI. Identified as one kind of non-coding RNA with more than 200bp length, lncRNA has been demonstrated to have abundance biological functions, including anti-inflammatory response. In the current study, we performed an lncRNA microarray in LPS-induced Raw264.7 cells which pre-stimulated with AdipoAI, and screened 110 DElncRNAs and 190 DEmRNAs. Enrichment analyses were conducted to total mRNAs and DEmRNAs, including GSVA, ssGSEA, GO/KEGG, GSEA and PPI analysis. Among all these processes, endocytosis was significantly enriched. A co-expression analysis was built based on DElncRNAs and DEmRNAs. Then, using Targetscan and miRwalk to predict related microRNAs of DElncRNAs and DEmRNAs respectively, we established competing endogenous RNA (ceRNA) networks including 54 mRNAs from 8 GO items. Furthermore, 33 m6A methylation related marker genes were obtained from previous study and used for the construction of m6A related-lncRNA network using the co-expression analysis. We identified FTO as the hub gene of the network, and 14 lncRNAs that interacted with it. The expression levels of 10 lncRNAs selected from ceRNA and FTO- related lncRNAs networks were validated with qRT-PCR. Finally, Macrophage phenotype scores showed that AdipoAI could attenuate the M2b and M2c polarization of macrophage and correlate with the above lncRNAs. Our work reveals that lncRNA might involve in the anti-inflammation process of AdipoAI in LPS-induced macrophages through ceRNA network and epigenetic regulation of m6A. Mechanistically, these lncRNAs associated with AdipoAI might be related to endocytosis and polarization in macrophage, and provide new candidates for the anti-inflammatory application of APN and its receptor agonist.
2023-01-01 | GSE212065 | GEO
Project description:Septic cardiomyopathy (SCM) is a cardiac dysfunction caused by severe sepsis, which greatly increases the risk of heart failure and death, and its molecular mechanism is unclear. The immune response has been reported to be an important process in septic cardiomyopathy and is present in the cardiac tissue of patients with sepsis, suggesting that the immune response may be an underlying mechanism of myocardial injury in SCM. Therefore, we explored the role of immune-related genes (IRGs) in SCM and aimed to identify pivotal immune-related targets with the aim of identifying key immune-related targets in SCM and potential therapeutic mechanisms involved in the pathological process of SCM. To explore the regulatory mechanisms of immune responses in SCM, we identified differentially expressed genes (DEGs) shared in the SCM datasets GSE179554 and GSE40180 by bioinformatics analysis and then obtained hub genes from the DEGs. Then, we obtained the immune-related hub genes (IRHGs) by intersecting the hub genes with IRGs and performed quantitative reverse transcription polymerase chain reaction to confirm the abnormal expression of IRHGs. Finally, we further constructed an immune-related lncRNA-miRNA-IRHG ceRNA regulatory network. In this study, we identified an IRHG that may be involved in the pathogenesis of SCM, which helps us to further elucidate the role of immune response in SCM and gain insights into the molecular mechanisms and potential therapeutic targets of SCM.
| S-EPMC9243365 | biostudies-literature
Project description:BackgroundCompeting endogenous RNA (ceRNA) represents a class of RNAs (e.g., long noncoding RNAs [lncRNAs]) with microRNA (miRNA) binding sites, which can competitively bind miRNA and inhibit its regulation of target genes. Increasing evidence has underscored the involvement of dysregulated ceRNA networks in the occurrence and progression of colorectal cancer (CRC). The purpose of this study was to construct a ceRNA network related to the prognosis of CRC and further explore the potential mechanisms that affect this prognosis.MethodsRNA-Seq and miRNA-Seq data from The Cancer Genome Atlas (TCGA) were used to identify differentially expressed lncRNAs (DElncRNAs), microRNAs (DEmiRNAs), and mRNAs (DEmRNAs), and a prognosis-related ceRNA network was constructed based on DElncRNA survival analysis. Subsequently, pathway enrichment, Pearson correlation, and Gene Set Enrichment Analysis (GSEA) were performed to determine the function of the genes in the ceRNA network. Gene Expression Profiling Interactive Analysis (GEPIA) and immunohistochemistry (IHC) were also used to validate differential gene expression. Finally, the correlation between lncRNA and immune cell infiltration in the tumor microenvironment was evaluated based on the CIBERSORT algorithm.ResultsA prognostic ceRNA network was constructed with eleven key survival-related DElncRNAs (MIR4435-2HG, NKILA, AFAP1-AS1, ELFN1-AS1, AC005520.2, AC245884.8, AL354836.1, AL355987.4, AL591845.1, LINC02038, and AC104823.1), 54 DEmiRNAs, and 308 DEmRNAs. The MIR4435-2HG- and ELFN1-AS1-associated ceRNA subnetworks affected and regulated the expression of the COL5A2, LOX, OSBPL3, PLAU, VCAN, SRM, and E2F1 target genes and were found to be related to prognosis and tumor-infiltrating immune cell types.ConclusionsMIR4435-2HG and ELFN1-AS1 are associated with prognosis and tumor-infiltrating immune cell types and could represent potential prognostic biomarkers or therapeutic targets in colorectal carcinoma.
| S-EPMC7941714 | biostudies-literature