Unknown

Dataset Information

0

Identification of lymph node metastasis-related microRNAs in breast cancer using bioinformatics analysis.


ABSTRACT: BACKGROUND:Lymph node metastasis is a significant problem in breast cancer, and its underlying molecular mechanism is still unclear. The purpose of this study is to research the molecular mechanism and to explore the key RNAs and pathways that mediate lymph node metastasis in breast cancer. METHODS:GSE100453 and GSE38167 were downloaded from the Gene Expression Omnibus (GEO) database and 569 breast cancer statistics were also downloaded from the TCGA database. Differentially expressed miRNAs were calculated by using R software and GEO2R. Gene ontology and Enriched pathway analysis of target mRNAs were analyzed by using the Database for Database of Annotation Visualization and Integrated Discovery (DAVID) and R software. The protein-protein interaction (PPI) network was performed according to Metascape, String, and Cytoscape software. RESULTS:In total, 6 differentially expressed miRNAs were selected, and 499 mRNAs were identified after filtering. The research of the Kyoto Encyclopedia of Genes and Genomes (KEGG) demonstrated that mRNAs enriched in certain tumor pathways. Also, certain hub mRNAs were highlighted after constructed and analyzed the PPI network. A total of 3 out of 6 miRNAs had a significant relationship with the overall survival (P?

SUBMITTER: Gao G 

PROVIDER: S-EPMC7523764 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

altmetric image

Publications

Identification of lymph node metastasis-related microRNAs in breast cancer using bioinformatics analysis.

Gao Guangyu G   Shi Xinya X   Yao Zhen Z   Shen Jiaofeng J   Shen Liqin L  

Medicine 20200901 39


<h4>Background</h4>Lymph node metastasis is a significant problem in breast cancer, and its underlying molecular mechanism is still unclear. The purpose of this study is to research the molecular mechanism and to explore the key RNAs and pathways that mediate lymph node metastasis in breast cancer.<h4>Methods</h4>GSE100453 and GSE38167 were downloaded from the Gene Expression Omnibus (GEO) database and 569 breast cancer statistics were also downloaded from the TCGA database. Differentially expre  ...[more]

Similar Datasets

2022-03-03 | GSE173766 | GEO
| S-EPMC2361648 | biostudies-literature
| S-EPMC5078061 | biostudies-literature
| S-EPMC6194557 | biostudies-literature
| PRJNA726984 | ENA
| S-EPMC7226536 | biostudies-literature
| S-EPMC5983317 | biostudies-literature
2023-02-13 | GSE110317 | GEO