Dataset Information

The Predictive Competing Endogenous RNA Regulatory Networks and Potential Prognostic and Immunological Roles of Cyclin A2 in Pan-Cancer Analysis.

ABSTRACT: Although accumulating evidence has verified the relationship between CCNA2 and cancers, no pan-cancer analysis about the function and the upstream molecular mechanism of CCNA2 is available. For the first time, we analyzed potential oncogenic roles of CCNA2 in 33 cancer types via The Cancer Genome Atlas (TCGA) database. Overexpression of CCNA2 is widespread in almost all cancer types, and it is related to poor prognosis and advanced pathological stages in most cases. Moreover, we conducted upstream miRNAs and lncRNAs of CCNA2 to establish upstream regulatory networks in kidney renal clear cell carcinoma (LINC00997/miR-27b-3p/CCNA2), liver hepatocellular carcinoma (SNHG16, GUSBP11, FGD5-AS1, LINC00630, CD27-AS1, LINC00997/miR-22-3p/CCNA2, miR-29b-3p/CCNA2, miR-29c-3p/CCNA2, and miR-204-5p/CCNA2), and lung adenocarcinoma (miRNA-218-5p/CCNA2 and miR-204-5p/CCNA2) by expression analysis, survival analysis, and correlation analysis. The CCNA2 expression is positively correlated with Th2 cell infiltration and negatively correlated with CD4⁺ central memory and effector memory T-cell infiltration in different cancer types. Furthermore, CCNA2 is positively associated with expressions of immune checkpoints (CD274, CTLA4, HAVCR2, LAG3, PDCD1, and TIGIT) in most cancer types. Our first CCNA2 pan-cancer study contributes to understanding the prognostic and immunological roles and potential upstream molecular mechanisms of CCNA2 in different cancers.

SUBMITTER: Chen S

PROVIDER: S-EPMC9035520 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The Predictive Competing Endogenous RNA Regulatory Networks and Potential Prognostic and Immunological Roles of Cyclin A2 in Pan-Cancer Analysis.

Chen Shenyong S Zhao Zhijia Z Wang Xiaobo X Zhang Qi Q Lyu Li L Tang Bo B

Frontiers in molecular biosciences 20220411

Although accumulating evidence has verified the relationship between CCNA2 and cancers, no pan-cancer analysis about the function and the upstream molecular mechanism of CCNA2 is available. For the first time, we analyzed potential oncogenic roles of CCNA2 in 33 cancer types <i>via</i> The Cancer Genome Atlas (TCGA) database. Overexpression of CCNA2 is widespread in almost all cancer types, and it is related to poor prognosis and advanced pathological stages in most cases. Moreover, we conducted ...[more]

PMID: 35480884

Similar Datasets

Project description:The present study aimed to screen all types of RNAs involved in the development of papillary thyroid carcinoma (PTC). RNA‑sequencing data of PTC and normal samples were used for screening differentially expressed (DE) microRNAs (DE‑miRNAs), long non‑coding RNAs (DE‑lncRNAs) and genes (DEGs). Subsequently, lncRNA‑miRNA, miRNA‑gene (that is, miRNA‑mRNA) and gene‑gene interaction pairs were extracted and used to construct regulatory networks. Feature genes in the miRNA‑mRNA network were identified by topological analysis and recursive feature elimination analysis. A support vector machine (SVM) classifier was built using 15 feature genes, and its classification effect was validated using two microarray data sets that were downloaded from the Gene Expression Omnibus (GEO) database. In addition, Gene Ontology function and Kyoto Encyclopedia Genes and Genomes pathway enrichment analyses were conducted for genes identified in the ceRNA network. A total of 506 samples, including 447 tumor samples and 59 normal samples, were obtained from The Cancer Genome Atlas (TCGA); 16 DE‑lncRNAs, 917 DEGs and 30 DE‑miRNAs were screened. The miRNA‑mRNA regulatory network comprised 353 nodes and 577 interactions. From these data, 15 feature genes with high predictive precision (>95%) were extracted from the network and were used to form an SVM classifier with an accuracy of 96.05% (486/506) for PTC samples downloaded from TCGA, and accuracies of 96.81 and 98.46% for GEO downloaded data sets. The ceRNA regulatory network comprised 596 lines (or interactions) and 365 nodes. Genes in the ceRNA network were significantly enriched in 'neuron development', 'differentiation', 'neuroactive ligand‑receptor interaction', 'metabolism of xenobiotics by cytochrome P450', 'drug metabolism' and 'cytokine‑cytokine receptor interaction' pathways. Hox transcript antisense RNA, miRNA‑206 and kallikrein‑related peptidase 10 were nodes in the ceRNA regulatory network of the selected feature gene, and they may serve import roles in the development of PTC.

Dataset Information

The Predictive Competing Endogenous RNA Regulatory Networks and Potential Prognostic and Immunological Roles of Cyclin A2 in Pan-Cancer Analysis.

Publications

The Predictive Competing Endogenous RNA Regulatory Networks and Potential Prognostic and Immunological Roles of Cyclin A2 in Pan-Cancer Analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets