Identification and Validation of Key miRNAs for Colon Cancer Based on miRNA-Gene Integration Analysis

Abstract

Background

MicroRNAs (miRNAs) plays an essential role in the pathogenesis of colon cancer. This study aims to identify and verify key miRNAs that may serve as potential biomarkers for early diagnosis and treatment of colon cancer.

Methods

Two miRNA microarray datasets (GSE53339 and GSE126093) were downloaded from the Gene Expression Omnibus (GEO) database, and the common differentially expressed miRNAs (DEMis) of both were identified by the “limma” package and the intersect function in R. Then, the miRwalk online tool was used to predict the target genes of the common DEMis and perform Gene Ontology (GO) functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis on those DEMis. The miRNA-gene network was constructed using Cytoscape software to identify key miRNAs and validated using quantitative real-time PCR (qRT-PCR) and The Cancer Genome Atlas (TCGA) dataset information for experimental and external database validation, respectively. In addition, we explored the correlation between key miRNAs and infiltrating immune cells and immunotherapy biomarkers.

Results

Fourteen common DEMis were identified from the GEO database, and five targeted genes were predicted. A microRNA-gene network was subsequently constructed to identify three key miRNAs (miR-363-3p, miR-520e, and miR-330-5p). Both qRT-PCR and external database validation confirmed our findings. In addition, we found that miR-520e was significantly associated with infiltrating immune cells and established immune checkpoints.

Conclusion

Our study identified three key miRNAs that influence the development of colon cancer. In addition, further studies suggest that infiltrating immune cells may play an essential role in the pathogenesis of colon cancer. These findings assist in early diagnosis and precision-targeted therapies.

Keywords:

• colon cancer
• GEO
• miRNA
• qRT-PCR
• immune cell infiltration

Abbreviations

DEMis, Differentially expressed miRNAs; ECM, Extracellular matrix; GEO, Gene Expression Omnibus; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; miRNA, MicroRNA; qRT-PCR, Quantitative Real-Time Polymerase Chain Reaction; TCGA, The Cancer Genome Atlas.

Data Sharing Statement

The datasets generated and/or analyzed during the current study are available in the GEO database repository: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE53339 and https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE126093.

Ethics Approval and Consent to Participate

The research was approved by the Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine (2019LWKZ009). All the procedures were followed in accordance with the Declaration of Helsinki under the Ethics approval and consent to participate heading.

Author Contributions

Yi Ji: Investigation, Writing - Original Draft and Funding acquisition; Jialin Gu: Visualization and Writing - Review & Editing; Hongqun Zhang: Supervision; Houxi Xu: Conceptualization, Methodology and Funding acquisition. All authors contributed to data analysis, drafting, or revising the article, have agreed on the journal to which the article will be submitted, gave final approval of the version to be published, and agree to be accountable for all aspects of the work.

Disclosure

The authors declare that they have no competing interests.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China (No. 82004288) and Traditional Chinese and Western Medicine Clinical Medicine Brand Construction Project of Jiangsu Higher Education Institutions (Phase II).