Abstract
Gene expression, signaling pathways and cell function are regulated through dynamic complex molecular interactions networks. Understanding gene expression is thought to be crucial for life science and medical practice but biomedical research in this field is still in its infancy. Previous work using high-throughput (HT) technologies with first generation or arrays-based methods have suggested gene expression profiling-based subtypes and prognostic markers for breast cancer classification and biomarkers identification. Now, in the era of next-generation sequencing (NGS) technologies-based network biology [1] and network medicine [2], much more sophisticated approaches are now used for deeper insights into complex control of gene expression through multiple gene-gene and protein-protein interaction networks. Using latest HT platforms for genomic and transcriptomic analysis of samples from 2000 breast cancer patients in UK and Canada tumor banks, Curtis and colleagues ]3] report in the June 28 issue of Nature, new breast cancer subgroups. The perspectives and challenges of this copy number changes-based approach with emphasis on tumor banks potential clinical implications are discussed in this editorial article.

(Citation: Gastric & Breast Cancer 2012; 11(3): 108-110)

Back

Full Text

PDF Version