Genomics-based prognosis and therapeutic prediction in breast cancer.
Breast cancer is a heterogeneous disease. DNA microarray technology is being applied to breast cancer to identify new prognostic biomarkers, to predict response to therapy, and to discover targets for the development of novel therapies. New diagnostic assays based on global gene expression are being introduced into clinical practice or tested in large-scale clinical trials. This review focuses on translational studies using microarray analyses and discusses best practice features and pitfalls. We note that factors that predict metastatic disease are not necessarily the same factors that predict therapeutic response. We believe that the characterization and discernment of different systems among breast cancers is crucial for understanding drug sensitivity and resistance mechanisms and for guiding therapy.
Jeffrey
Stefanie S
SS
Department of Surgery, Stanford University School of Medicine, Stanford, California, 94305-5494, USA. ssj@stanford.edu
Lønning
Per Eystein
PE
Hillner
Bruce E
BE
D000970:Antineoplastic Agents / Q000494:pharmacology / Q000627:therapeutic use; D014408:Biomarkers, Tumor; D001943:Breast Neoplasms / Q000188:drug therapy / Q000235:genetics*; D004351:Drug Resistance; D005260:Female; D020869:Gene Expression Profiling; D023281:Genomics; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis; D011237:Predictive Value of Tests; D011379:Prognosis; D013629:Tamoxifen / Q000494:pharmacology / Q000627:therapeutic use
D000970:Antineoplastic Agents; D014408:Biomarkers, Tumor; D013629:Tamoxifen