Abstract
During the past decade, genomic microarrays have been applied with some success to the molecular profiling of breast tumours, which has resulted in a much more detailed classification scheme as well as in the identification of potential gene signature sets. These gene sets have been applied to both the prognosis and prediction of outcome to treatment and have performed better than the current clinical criteria. One of the main limitations of microarray analysis, however, is that frozen tumour samples are required for the assay. This imposes severe limitations on access to samples and precludes large scale validation studies from being conducted. Quantitative reverse transcriptase polymerase chain reaction (qRT-PCR), on the other hand, can be used with degraded RNAs derived from formalin-fixed paraffin-embedded (FFPE) tumour samples, the most important and abundant source of clinical material available. More recently, the novel DASL (cDNA-mediated Annealing, Selection, extension and Ligation) assay has been developed as a high throughput gene expression profiling system specifically designed for use with FFPE tumour tissue samples.However, we do not believe that genomics is adequate as a sole prognostic and predictive platform in breast cancer. The key proteins driving oncogenesis, for example, can undergo post-translational modifications; moreover, if we are ever to move individualization of therapy into the practical world of blood-based assays, serum proteomics becomes critical. Proteomic platforms, including tissue micro-arrays (TMA) and protein chip arrays, in conjunction with surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF/MS), have been the technologies most widely applied to the characterization of tumours and serum from breast cancer patients, with still limited but encouraging results.This review will focus on these genomic and proteomic platforms, with an emphasis placed on the utilization of FFPE tumour tissue samples and serum, as they have been applied to the study of breast cancer for the discovery of gene signatures and biomarkers for the early diagnosis, prognosis and prediction of treatment outcome. The ultimate goal is to be able to apply a systems biology approach to the information gleaned from the combination of these techniques in order to select the best treatment strategy, monitor its effectiveness and make changes as rapidly as possible where needed to achieve the optimal therapeutic results for the patient.
Highlights
In the United States it is estimated that approximately 213,000 new cases of invasive breast cancer will be diagnosed in 2006 and 41,000 women are expected to die from this disease [1]
A tissue micro-arrays (TMA) study [51], using tumour samples from 200 breast cancer patients, was conducted that focused on histone deacetylases (HDACs)-1 and HDAC-3, from HDAC class I, since these play a role in proliferation and cell survival of mammary tumour cells and can interact either directly or indirectly with the steroid hormone receptors estrogen receptor (ER) and progesterone receptor- (PGR) as well as the tumour suppressor p53 [[52,53,54]]
formalin-fixed paraffin-embedded (FFPE) tumour tissue samples are, the most important and abundant source of material available from randomized clinical trials that will allow for well-controlled hypothesis testing to be conducted
Summary
In the United States it is estimated that approximately 213,000 new cases of invasive breast cancer will be diagnosed in 2006 and 41,000 women are expected to die from this disease [1]. One of the main objectives for the use of TMA technology is to identify prognostically relevant groups of breast cancer patients and, in conjunction with data from other molecular profiling studies, come up with an optimal panel of biomarkers that can be validated in independent sample sets. The goal, is to use FFPE tumour tissue samples in conjunction with the DASL platform to potentially identify differential signature gene sets that can be used for diagnosis, prognosis and/or monitoring of disease This technology is just beginning to be applied to cancer research and as its use becomes more widespread it has the potential to have an important impact on translational breast cancer research. Applying this systems biology approach to breast cancer has the potential to more rapidly lead to early diagnosis and the individualization of treatment
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
