Dataset Information

Comprehensive analysis of ceRNA network of ERCC4 in colorectal cancer.

ABSTRACT:

Objective

ERCC4 is one of the most significant molecules of Nucleotide Excision Repair (NER), which has been researched due to its high expression in colorectal cancer (CRC). This study aimed to find out the ceRNA (competitive endogenous RNA) network of ERCC4 in CRC.

Methods and materials

Pan cancer mRNA expression of ERCC4 was evaluated using TCGA database. The protein expression of ERCC4 was evaluated based on the Human Protein Atlas (HPA). We screened DElncRNAs and DEmiRNAs in two groups of ERCC4 ^high and ERCC4 ^low expression in CRC. Then a lncRNA-miRNA-ERCC4 regulatory network was constructed based on DElncRNAs and DEmiRNAs using Starbase database and visualized by Cytoscape software. Kaplan-Meier analysis was performed to evaluate the prognostic value of the ceRNA network. Further, RT-PCR was performed to validate the expression of the representative molecules in the ceRNA network in CRC and normal tissues. The relationship between drug sensitivity and these molecules were also evaluated using RNAactDrug database.

Results

ERCC4 was overexpressed in a variety of tumors at mRNA levels, including CRC. High expression of ERCC4 was also observed on protein level in CRC. A total of 1,885 DElncRNAs and 68 DEmiRNAs were identified from CRC samples in ERCC4 ^high and ERCC4 ^low expression groups. Predicted by the Starbase database, we got interacting miRNAs and lncRNAs of ERCC4 from the DEmiRNAs and DElncRNAs, and a lncRNA-miRNA-ERCC4 regulatory network was constructed. Kaplan-Meier survival curves results showed that miR-200c-3p (hazard ratio [HR] = 0.62, P = 0.032), MALAT1 (HR = 1.54, P = 0.016), and AC005520.2 (hazard ratio [HR] = 1.75, P = 0.002) were significantly associated with the prognosis of CRC. After validation by RT-PCR, we found that ERCC4 and MALAT1 were up-regulated in CRC compared with normal tissues, while miR-200c-3p was down-regulated. A strong negative correlation was observed between MALAT1 and miR-200c-3p. Drug sensitivity analysis showed that ERCC4, miR-200c and MALAT1 were all associated with Cisplatin.

Conclusion

We constructed a ceRNA network of ERCC4 in CRC, of which the MALAT1-miR-200c-3p-ERCC4 axis may be involved in the development, prognosis and chemotherapy sensitivity of CRC. These findings might provide novel clues and insights on the molecular mechanisms of ERCC4 and NER pathway in CRC.

SUBMITTER: Hu H

PROVIDER: S-EPMC8679902 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Previous studies have suggested that long non‑coding RNAs (lncRNAs) are closely associated with human diseases, particularly cancer, including cancer of the lung, breast and stomach. A variety of lncRNAs are abnormally expressed in cancer and participate in several pathways including cell proliferation and apoptosis; these elements are closely associated with the development of cancer. The Cancer Genome Atlas (TCGA) is an important cancer database. It consists of clinical data, genomic variation, mRNA, microRNA (miRNA) and lncRNAs expression, methylation and other data for various types of human cancer. In the present study, differential expression of RNA was identified using the edgeR package. A total 1,222 RNA sequencing profiles from patients with breast cancer were downloaded from TCGA. A competing endogenous RNA (ceRNA) network was constructed for breast cancer based on miRcode and miRTarBase. The top 10 lncRNAs were selected using Cox regression analysis. Survival analysis was performed using Kaplan‑Meier analysis. A total of 1,028 breast cancer‑associated lncRNAs and 89 miRNAs (fold change >2; P<0.05) were identified; among these, 93 lncRNAs and 19 miRNAs were included in the ceRNA network. Subsequently, 10 basic lncRNAs were selected and their associations with overall survival were identified. In addition, 5 lncRNAs (ADAM metallopeptidase with thrombospondin type 1 motif 9‑antisense RNA 1, AL513123.1, chromosome 10 open reading frame 126, long intergenic non‑protein coding RNA 536 and Wilms tumor 1 antisense RNA) were identified to be significantly associated with overall survival (P<0.05, log rank test). These results suggested that mRNAs, lncRNAs and miRNAs were involved in pathological mechanisms of breast cancer. The newly‑identified ceRNA network included 93 breast cancer‑specific lncRNAs, 19 miRNAs and 27 mRNAs. The results of the present study highlight the potential of lncRNAs in understanding the development and pathogenesis of breast cancer, and suggest novel concepts and an experimental basis for the identification of prognostic biomarkers and therapeutic targets for breast cancer.

Project description:Objective: This study mainly focused on revealing ceRNA network in gastric cancer (GC) with Hp infection after comparing with GC without Hp infection and exploring the biological function and prognostic relevance of related molecules. Methods: The RNA expression profile data of GC patients with or without Hp infection were extracted from TCGA GDC data portal, including 20 GC cases with Hp infection and 168 GC cases without Hp infection. Differentially expressed lncRNAs, miRNAs and mRNAs were unveiled by package edgeR of R, and lncRNA-miRNA-mRNA ceRNA network was constructed by integrating the miRNA target information and the expression data of lncRNAs, miRNAs and mRNAs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of aberrantly expressed mRNAs were performed to identify the related biological functions and pathologic pathways, and protein-protein interaction (PPI) network was constructed by STRING database. The overall survival (OS) of aberrantly expression lncRNAs and miRNAs were analyzed by package survival of R. A total of 30 gastric cancer tissues were used to validate the bioinformatics analysis results by real-time PCR. Results: Among the 32 differentially expressed miRNAs, 27 differentially expressed lncRNAs and 257 differentially expressed mRNAs were identified by comparing GC patients with and without Hp infection. Totally 10 miRNA, 11 lncRNA, 219 mRNA were included to build ceRNA network. GO and KEGG analysis revealed that differentially expressed mRNAs involved in the ceRNA network were mainly involved in extracellular exosomes, structural molecular activities, proteolysis and P13K-Akt signaling pathways. And PPI analysis obtained six hub genes of NTS, APOC3, OTX2, KRT13, CALCA, GNG4. Survival analysis showed that four lncRNAs (LINC01254, LINC01287, LINC01524, U95743.1) and four miRNAs (miR-302a, miR-302b, miR-1286, miR-378g) were associated with overall survival of GC with Hp infection. The real-time PCR results showed that, the levels of LINCO1254, LINCO1287, LINCO1524, U95743.1 were significantly higher in Hp positive GC patients than Hp negative patients (P=0.02, 0.048, 0.04, 0.036, respectively). Conclusion: Using TCGA database for data mining, we have successfully constructed a ceRNA regulatory network of GC with Hp infection, consisting of 10 lncRNAs, 11 miRNAs and 219 mRNAs. These findings might provide critical clues for the regulatory role of ceRNA network in the development of GC with Hp infection.

Project description:Background and aim: Competing endogenous RNA (ceRNA) is believed to play vital roles in tumorigenesis. The goal of this study was to screen prognostic biomarkers in lung adenocarcinoma (LUAD). Methods: Common differentially expressed genes (DEGs) were collected from Gene Expression Omnibus (GEO) databases and The Cancer Genome Atlas databases (TCGA) using GEO2R and "limma" package in R, respectively. Overlapping DEGs were conducted using enrichment of functions and protein-protein interaction (PPI) network to discover significant candidate genes. By using a comprehensive analysis, we constructed an mRNA mediated ceRNA network. Survival rates were used Kaplan-Meier analysis. Statistical analysis was used to further identify the prognosis of studied genes. Results: Integrated analysis of GSE32863 and TCGA databases, a total of 886 overlapping DEGs, including 279 up-regulated and 607 down-regulated genes were identified. Considering the highest term of candidate genes in PPI, we identified TPX2, which was enriched in cell division signaling pathway. Besides, 35 differentially expressed miRNAs (DEmiRNAs) were predicted to target TPX2 and only 7 DEmiRNAs were identified to be prognostic biomarkers in LUAD. Then, 30 differentially expressed lncRNAs (DElncRNAs) were predicted to bind these 7 DEmiRNAs. Finally, we found that 7 DElncRNAs were correlated with the overall survival (all p <0.05). Furthermore, we identified elevated TPX2 was strongly correlated with the worse survival rate among 458 samples. Univariate and multivariate cox analysis showed TPX2 may act as an independent factor for prognosis in LUAD (p <0.05). Then pathway enrichment results suggested that TPX2 may facilitate tumorigenesis by participating in several cancer-related signaling pathways in LUAD, especially in Notch signal pathway. Conclusions: TPX2-related lncRNAs and miRNAs are related to the survival of LUAD. 7 lncRNAs, 7 miRNAs and TPX2 may serve as prognostic biomarkers in LUAD.