Integrative analysis of miRNA expression data reveals a minimal signature for tumour cells classification.

ABSTRACT: MicroRNAs (miRNAs) are pivotal biomarkers for cancer screening. Identifying distinctive expression patterns of miRNAs in specific cancer types can serve as an effective strategy for classification and characterization. However, the development of a minimal signature of miRNAs for accurate cancer classification remains challenging, hindered by the lack of integrated approaches that systematically analyse miRNA expression levels of miRNAs alongside their associated biological pathways. In this study, we present a comprehensive integrative approach that utilizes transcriptomic data from lung, breast, and melanoma cancer cell lines to identify specific expression patterns. By combining bioinformatics, dimensionality reduction techniques, machine learning, and experimental validation, we pinpoi

SUBMITTER: Napoletano S 

PROVIDER: S-EPMC11760817 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature