
Gene-expression profiling with the use of DNA microarrays allows measurement of thousands of messenger RNA (mRNA) transcripts in a single experiment. Results of such studies have confirmed that breast cancer is not a single disease with variable morphologic features and biomarkers but, rather, a group of molecularly distinct neoplastic disorders. Profiling results also support the hypothesis that estrogen-receptor (ER)–negative and ER-positive breast cancers originate from distinct cell types and point to biologic processes that govern metastatic progression. Moreover, such profiling has uncovered molecular signatures that could influence clinical care. In this review, we summarize the results of gene-expression studies that hold the most promise to accelerate the transition between empirical and molecular medicine.
Genetic Markers, Genetic Markers -- physiology, Breast Neoplasms -- drug therapy, Gene Expression, Antineoplastic Agents, Breast Neoplasms, Breast Neoplasms -- metabolism, Receptors, Humans, erbB-2, Oligonucleotide Array Sequence Analysis, Gene Expression Profiling, Médecine pathologie humaine, Breast Neoplasms -- genetics, Sciences bio-médicales et agricoles, Genes, erbB-2, Prognosis, Cancérologie, Treatment Outcome, Genes, Receptors, Estrogen, Estrogen -- analysis, Antineoplastic Agents -- therapeutic use, Breast Neoplasms -- pathology, Female
Genetic Markers, Genetic Markers -- physiology, Breast Neoplasms -- drug therapy, Gene Expression, Antineoplastic Agents, Breast Neoplasms, Breast Neoplasms -- metabolism, Receptors, Humans, erbB-2, Oligonucleotide Array Sequence Analysis, Gene Expression Profiling, Médecine pathologie humaine, Breast Neoplasms -- genetics, Sciences bio-médicales et agricoles, Genes, erbB-2, Prognosis, Cancérologie, Treatment Outcome, Genes, Receptors, Estrogen, Estrogen -- analysis, Antineoplastic Agents -- therapeutic use, Breast Neoplasms -- pathology, Female
| citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1K | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 0.1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 0.1% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 0.01% |
