Unveiling promising breast cancer biomarkers: an integrative approach combining bioinformatics analysis and experimental verification.

ABSTRACT:

Background

Breast cancer remains a significant health challenge worldwide, necessitating the identification of reliable biomarkers for early detection, accurate prognosis, and targeted therapy.

Materials and methods

Breast cancer RNA expression data from the TCGA database were analyzed to identify differentially expressed genes (DEGs). The top 500 up-regulated DEGs were selected for further investigation using random forest analysis to identify important genes. These genes were evaluated based on their potential as diagnostic biomarkers, their overexpression in breast cancer tissues, and their low median expression in normal female tissues. Various validation methods, including online tools and quantitative Real-Time PCR (qRT-PCR), were used to confirm the potential of the i

SUBMITTER: Golestan A 

PROVIDER: S-EPMC10829368 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature