CAMIRADA: Cancer microRNA association discovery algorithm, a case study on breast cancer

TL;DR

This paper introduces CAMIRADA, a computational framework that integrates microRNA, gene, and transcription factor relationships within networks to accurately identify cancer-related microRNAs, demonstrated on breast cancer data with high predictive accuracy.

Contribution

CAMIRADA is a novel computational method that combines multiple biological network relationships to improve microRNA-cancer association prediction accuracy.

Findings

Achieved an AUC of 0.95 for top microRNAs in breast cancer.

Outperformed existing methods in microRNA-cancer association detection.

Validated effectiveness on breast cancer datasets from HMDD and miR2Disease.

Abstract

In recent studies, non-coding protein RNAs have been identified as microRNA that can be used as biomarkers for early diagnosis and treatment of cancer, that decrease mortality in cancer. A microRNA may target hundreds or thousands of genes and a gene may regulate several microRNAs, so determining which microRNA is associated with which cancer is a big challenge. Many computational methods have been performed to detect micoRNAs association with cancer, but more effort is needed with higher accuracy. Increasing research has shown that relationship between microRNAs and TFs play a significant role in the diagnosis of cancer. Therefore, we developed a new computational framework (CAMIRADA) to identify cancer-related microRNA based on the relationship between microRNAs and disease genes (DG) in the protein network, the functional relationships between microRNAs and Transcription Factors (TF) on the co-expression network, and the relationship between microRNAs and the Differential Expression Gene (DEG) on co-expression network. The CAMIRADA was applied to assess breast cancer data from two HMDD and miR2Disease databases. In this study, the AUC for the 65 microRNA of the top of the list was 0.95, which was more accurate than the similar methods used to detect microRNA associated with the cancer artery.