Using modern molecular markers to tailor breast cancer treatment: a new era for personalized medicine

Abstract

Breast cancer is well known as a heterogeneous disease; the traditional morphological and pathologic anatomical classification cannot accurately predict its biological and clinical behavior, prognosis or response to treatment. Defining and understanding the ‘omics’ (the term used to characterize sets of biologic molecules, e.g., DNA, RNA, proteins and metabolites) and pathway changes associated with individual tumors and their treatment can identify patient subsets and be used to tailor treatment regimens. Since the advent of such multidisciplinary initiatives, it has been a tremendously exciting time for oncology, and an opportunity for transforming clinical and translational research to deliver more effective and personalized cancer therapies faster has emerged. Personalized medicine is the new term for the 21st century approach: but what does it mean for breast cancer? Nowadays, it is not only important to identify the clinical stage, but also to use biologic or molecular markers that determine outcome (i.e., prognosis) and therapy (i.e., prediction); customarily, we determine the receptor status, including Ki67 proliferation index, p53 proto-oncogene, uPA/PAI-1 invasion factor and other selected markers that can partially help to determine prognosis and identify prediction for systemic therapy. The biomarkers are examined for their presence or absence and whether gene amplification has occured; occasionally, mutation is also checked for (e.g., p53) [1]. One of the most remarkable, fast-paced advances in breast cancer research has been the development of techniques for sequencing, identifying and profiling molecular and gene expression signatures [2]. Serial analyses of gene expression, as well as oligonucleotide and cDNA arrays, have been applied by several groups such as The Cancer Genome Atlas and the International Cancer Genome Consortium, and have led to the active sequencing and identification of thousands of cancer-related genes, transcriptomes and critical pathways that have subsequently been validated as prognostic and therapeutic targets and are in clinical use [3]. The first and most widely used test using these techniques is the 21-gene recurrence score (OncoType Dx), which was developed from an original database of the 250 most widely described genes related