Dataset Information

Expression profile analysis of long non-coding RNAs in condyloma acuminatum in a Chinese female population by RNA-sequencing and bioinformatics [RNA-seq]

ABSTRACT: This study aimed to explore the differential lncRNAs in CA and their probable function on CA development.We used RNA-sequencing to assess the genome-wide expression levels of lncRNAs in CA and paired adjacent normal tissues. We further validated the candidate lncRNAs in larger-size of CA specimen using RT-qPCR. Furthermore, the functional enrichment analysis for these candidate lncRNAs and differential mRNAs were analyzed using GO terms, KEGG and STRING database. The coexpressed mRNAs for the candidate lncRNAs, calculated by Pearson?s correlation coefficient, were also analyzed using GO analysis.A total of 657 lncRNAs and 1486 mRNAs were found to dysregulated in CA compared to adjacent mucosal tissues. The microarray data of candidate lncRNAs, including HOXC13-AS, HOTAIR, PICSAR, FGF14-AS1, ADGRD1-AS1, TMEM108-AS1, TUSC7 and FGF10-AS1, were validated with a larger-size of specimen using RT-qPCR. The functional GO term and pathways analysis of DEGs are associated with the pathogenesis and development of CA, including cell proliferation and development, cellular adhesion, immune defense, cell migration and chemotaxis, angiogenesis, and maintaining skin hemostasis.LncRNAs that were differentially expressed between CA and normal tissues may be helpful to explore effective recurrence risk markers and potential intervention targets for CA.

ORGANISM(S): Homo sapiens

PROVIDER: GSE172137 | GEO | 2024/04/25

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Objective: The diagnostic roles of long non-coding RNAs (lncRNAs) in clear cell renal cell carcinoma (ccRCC) are still not well defined. We aimed to identify differentially expressed lncRNAs and mRNAs in plasma of ccRCC patients and health controls systematically. Methods: Expression profile of lncRNAs and mRNAs in plasma from ccRCC patients and healthy controls was analyzed by microarray assay. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway based approaches were used to investigate biological functions and signaling pathways affected by the differentially expressed mRNAs. SOCS2-AS1 was selected for validation using Real-Time PCR. The differentially expressed genes were further compared with E-MTAB-1830 datasets by Venn and NetworkAnalyst website. The expression level and overall survival (OS) of differentially expressed mRNAs were analyzed in GEPIA and ULCAN website. Results: Compared with healthy controls, a total of 3,664 differentially expressed lncRNAs were revealed by heatmap and volcano-plot, including up-regulation in 1,511 and down-regulation in 2,153 (fold change ≥ 2 and P < 0.05), respectively. And differential expression was noticed in 2,268 mRNAs, including up-regulation in 932 mRNAs and down-regulation in 1,336 mRNAs, respectively (fold change ≥ 2 and P < 0.05). Pathways analysis based on deregulated mRNAs were mainly involved in melanogenesis and Hippo signaling pathway (P < 0.05). The expression of SOCS2-AS1 was down in ccRCC plasma and tissues, as well as in cell lines, which was the same as the results of lncRNA microarray. Compared with the E-MTAB-1830 gene expression profiles, we identified 18 lncRNAs, and 87 mRNAs were differently expressed in both plasma and neoplastic tissues of ccRCC. Ten mRNAs (EPB41L4B, CCND1, GGT1, CGNL1, CYSLTR1, PLAUR, UGT3A1, PROM2, MUC12, and PCK1) were correlated with the overall survival (OS) rate in ccRCC patients based on the GEPIA and ULCAN website.Conclusions: We first reported differentially expressed lncRNAs in ccRCC patient and healthy control systemically. Combined with the published dataset, we identified several differentially expressed lncRNAs and mRNAs which might to be diagnostic or prognostic markers. The biological functions of those lncRNAs and mRNAs should be further validated. Taken together, this study provided the basis for future treatment of ccRCC and novel insights into cancer biology.

Dataset Information

Expression profile analysis of long non-coding RNAs in condyloma acuminatum in a Chinese female population by RNA-sequencing and bioinformatics [RNA-seq]

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets