Dataset Information

[Expression of MIER3 in colorectal cancer and bioinformatic analysis of MIER3- interacting proteins].

ABSTRACT: OBJECTIVE:To explore role of MIER3 gene in the development and progression of human colorectal carcinoma (CRC) and analyze the proteins that interact with MIER3 using bioinformatic techniques. METHODS:MIER3 mRNA and protein expressions were detected in 8 CRC biopsy samples and paired adjacent tissues using real-time PCR and Western blotting. A recombinant eukaryotic expression vector pcDNA3-MIER3 was constructed and its effect on the proliferation and invasion of CRC cells were tested using CCK8 assay and Transwell migration assay. Bioinformatic methods were used to predict and analyze MIER3-interacting proteins. RESULTS:MIER3 was obviously down-regulated in the 8 CRC tissues as compared with the paired adjacent tissues. In human CRC cell line DLD1, MIER3 overexpression induced by transfection of the cells with pcDNA3-MIER3 significantly inhibited the cell proliferation and suppressed cell invasiveness in vitro. Bioinformatics analyses indicated that NAT9 was a potential MIER3-interacting protein and MIER3 was probably associated with tumor susceptibility. CONCLUSION:MIER3, which is obviously down-regulated in CRC tissues, is closely associated with the proliferation and invasion of CRC, and NAT9 protein is a probable MIER3-interacting protein.

SUBMITTER: Song W

PROVIDER: S-EPMC6765740 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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[Expression of MIER3 in colorectal cancer and bioinformatic analysis of MIER3- interacting proteins].

Song Wen W Peng Man M Duan Shi-Yu SY Lin Chuang C Xu Qiong Q Zhou Jun J

Nan fang yi ke da xue xue bao = Journal of Southern Medical University 20170801 8

<h4>Objective</h4>To explore role of MIER3 gene in the development and progression of human colorectal carcinoma (CRC) and analyze the proteins that interact with MIER3 using bioinformatic techniques.<h4>Methods</h4>MIER3 mRNA and protein expressions were detected in 8 CRC biopsy samples and paired adjacent tissues using real-time PCR and Western blotting. A recombinant eukaryotic expression vector pcDNA3-MIER3 was constructed and its effect on the proliferation and invasion of CRC cells were te ...[more]

PMID: 28801283

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Project description:BackgroundExosomes play important roles in angiogenesis, drug resistance, and metastasis of colorectal cancer (CRC), but the underlying mechanism has seldom been reported. Herein, our study aimed to reveal an exosomal miRNA-mRNA network involved in CRC by performing bioinformatical analysis.MethodsThe mRNA and miRNA data of colon adenocarcinoma and rectal adenocarcinoma were downloaded from The Cancer Genome Atlas (TCGA) database, and exosomal miRNAs data were downloaded from the GEO dataset GSE39833. The differential expression analysis was performed using "limma" and "edgeR". Target mRNAs of miRNAs were predicted using FunRich 3.1.3, miRNAtap and multiMiR. The candidate mRNAs and exosomal miRNAs were obtained by intersecting two groups of differentially expressed miRNAs and intersection of the differential expressed mRNAs and the target mRNAs, respectively. Key mRNAs and exosomal miRNAs were identified by the least absolute shrinkage and selection operator regression analysis, and used to construct the exosomal miRNA-mRNA network. The network verified was by receiver operating characteristic curve, GEPIA and LinkedOmics. Functional enrichment analysis was also performed for studied miRNAs and mRNAs.ResultsA total of 6568 differentially expressed mRNAs and 531 differentially expressed miRNAs from TCGA data, and 166 differentially expressed exosomal miRNAs in GSE39833 dataset were identified. Next, 16 key mRNAs and five key exosomal miRNAs were identified from the 5284 candidate mRNAs and 61 candidate exosomal miRNAs, respectively. The exosomal miRNA-mRNA network with high connectivity contained 13 hub mRNAs (CBFB, CDH3, ETV4, FOXQ1, FUT1, GCNT2, GRIN2D, KIAA1549, KRT80, LZTS1, SLC39A10, SPTBN2, and ZSWIM4) and five hub exosomal miRNAs (hsa-miR-126, hsa-miR-139, hsa-miR-141, hsa-miR-29c, and hsa-miR-423). The functional annotation revealed that these hub mRNAs were mainly involved in the regulation of B cell receptor signaling pathway and glycosphingolipid biosynthesis related pathways. All hub mRNAs and hub exosomal miRNAs exhibited high diagnosis value for CRC. Furthermore, the association of the hub mRNAs with overall survival, stages, and MSI phenotype of CRC revealed their important roles in CRC progression.ConclusionThis study constructed an exosomal miRNA-mRNA network which may play crucial roles in the carcinogenesis and progression of CRC, thus providing potential diagnostic biomarkers and therapeutic targets for CRC.

Project description:Background: Colorectal cancer (CRC) is one gastrointestinal malignancy, accounting for 10% of cancer diagnoses and cancer-related deaths worldwide each year. Therefore, it is urgent to identify genes involved in CRC predicting the prognosis. Methods: CRC's data were acquired from the Gene Expression Omnibus (GEO) database (GSE39582 and GSE41258 datasets) and The Cancer Genome Atlas (TCGA) database. The differentially expressed necroptosis-related genes (DENRGs) were sorted out between tumor and normal tissues. Univariate Cox regression analysis and least absolute shrinkage and selectionator operator (LASSO) analysis were applied to selected DENRGs concerning patients' overall survival and to construct a prognostic biomarker. The effectiveness of this biomarker was assessed by the Kaplan-Meier curve and the receiver operating characteristic (ROC) analysis. The GSE39582 dataset was utilized as external validation for the prognostic signature. Moreover, using univariate and multivariate Cox regression analyses, independent prognostic factors were identified to construct a prognostic nomogram. Next, signaling pathways regulated by the signature were explored through the gene set enrichment analysis (GSEA). The single sample gene set enrichment analysis (ssGSEA) algorithm and tumor immune dysfunction and exclusion (TIDE) were used to explore immune correlation in the two groups, high-risk and low-risk ones. Finally, prognostic genes' expression was examined in the GSE41258 dataset. Results: In total, 27 DENRGs were filtered, and a necroptosis-related prognostic signature based on 6 DENRGs was constructed, which may better understand the overall survival (OS) of CRC. The Kaplan-Meier curve manifested the effectiveness of the prognostic signature, and the ROC curve showed the same result. In addition, univariate and multivariate Cox regression analyses revealed that age, pathology T, and risk score were independent prognostic factors, and a nomogram was established. Furthermore, the prognostic signature was most significantly associated with the apoptosis pathway. Meanwhile, 24 immune cells represented significant differences between two groups, like the activated B cell. Furthermore, 32 immune checkpoints, TIDE scores, PD-L1 scores, and T-cell exclusion scores were significantly different between the two groups. Finally, a 6-gene prognostic signature represented different expression levels between tumor and normal samples significantly in the GSE41258 dataset. Conclusion: Our study established a signature including 6 genes and a prognostic nomogram that could significantly assess the prognosis of patients with CRC.

Dataset Information

[Expression of MIER3 in colorectal cancer and bioinformatic analysis of MIER3- interacting proteins].

Publications

[Expression of MIER3 in colorectal cancer and bioinformatic analysis of MIER3- interacting proteins].

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