State of the science: molecular classifications of breast cancer for clinical diagnostics.
Over the past few years, the study of genomics has embarked on developing gene expression-based classifications for tumors-an initiative that promises to revolutionize cancer medicine. High-throughput genomic platforms, such as microarray and SAGE, have found gene expression signatures that correlate to important clinical parameters used in current staging and are providing additional information that will improve standard of care. Although implementing a molecular taxonomy for prognosis and treatment would likely benefit cancer patients, there remain significant obstacles to using these assays within the current diagnostic framework. Since most genomic assays are being performed from fresh tissue, there is a need to either change the practice of formalin-fixing and paraffin-embedding tissue or adapting the assays for use on degraded RNA specimens. To date, even the most mature data sets, such as molecular classifications for breast cancer, still fall short of the number of patients needed to generalize the results to treating large populations. To implement these assays in large scale, there will need to be standardization of sample procurement, preparation, and analysis. Certainly, the greatest improvements in patient care will come through tailored therapies as genomics is coupled with clinical trials that randomize cohorts to different treatments. This manuscript reviews the current standards of care, presents progress that is being made in the development of genomic assays for breast cancer and discusses options for implementing these new tests into the clinical setting.
Robison
John E
JE
Department of Pathology, University of Utah, Salt Lake City, UT 84112, USA.
Perreard
Laurent
L
Bernard
Philip S
PS
D014408:Biomarkers, Tumor / Q000032:analysis; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000235:genetics* / Q000401:mortality; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D023281:Genomics; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis; D011237:Predictive Value of Tests; D020133:Reverse Transcriptase Polymerase Chain Reaction; D015996:Survival Rate
D014408:Biomarkers, Tumor