Mutational analysis of breast cancer: guiding personalized treatments.
The application of high throughput techniques to profile DNA, RNA and protein in breast cancer samples from hundreds of patients has profoundly increased our knowledge of the disease. However there remain many knowledge gaps that will require a long process of extended clinical correlation studies, deeper integrated 'omic analysis and functional annotation to address. This article reviews conclusions from recent breast cancer 'omics profiling' papers and considers pathways forward for extracting medically valuable information from large dimension data sets.
Division of Medical Oncology, Section of Breast Oncology, Washington University School of Medicine, Siteman Cancer Center, 660 South Euclid Ave, CB 8069, St Louis, MO 63110, USA. Electronic address: mellis@dom.wustl.edu.
Matthew J
MJ
Ellis
D000328:Adult; D000368:Aged; D018931:Antineoplastic Agents, Hormonal / Q000627:therapeutic use; D001943:Breast Neoplasms / Q000235:genetics* / Q000401:mortality / Q000628:therapy*; D003131:Combined Modality Therapy; D004252:DNA Mutational Analysis; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods*; D018734:Genes, erbB-2 / Q000235:genetics; D020022:Genetic Predisposition to Disease; D023281:Genomics; D006801:Humans; D008408:Mastectomy / Q000379:methods / Q000401:mortality; D008875:Middle Aged; D057285:Precision Medicine / Q000379:methods*; D011379:Prognosis; D018570:Risk Assessment; D017422:Sequence Analysis, DNA; D016019:Survival Analysis; D016896:Treatment Outcome
D018931:Antineoplastic Agents, Hormonal
Breast cancer; Genomics; Somatic mutation; Therapeutic road map; Whole genome sequencing