Breast cancer prognostication and prediction in the postgenomic era

Expanding knowledge, together with implementation of new techniques, has fuelled the area of translational medical research aiming at improving prognostication as well as prediction in cancer therapy. At the same time, new discoveries have revealed a biological complexity we were unaware of only a decade ago. Thus, we are faced with novel challenges with respect to how we may explore issues such as prognostication and predict drug resistance in vivo. While microarray analysis exploring expression of thousands of genes in concert represents a major methodological advancement, discoveries such as the finding of different mechanisms of epigenetic silencing, intronic mutations, that most gene transcripts in the human genome are subject to alternative splicing and that hypersplicing seems to be a tumour-related phenomenon, exemplifies a complex pathology that may not be explored with use of single analytical methods only. This paper discusses clinical settings for studying drug resistance in vivo together with a discussion of contemporary biology in this field. Notably, each individual parameter which has been found correlated to drug resistance in vivo so far represents either a direct drug target or a factor involved in DNA repair or apoptosis. On the basis of these findings, we suggest drug resistance may be explored on the basis of upfront biological hypotheses.