Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications¶
Why this mattered¶
This paper helped turn breast cancer taxonomy from a primarily histopathologic and receptor-based scheme into a molecular classification problem. By showing that genome-wide expression patterns could reproducibly separate tumors into biologically coherent groups, including basal-like, ERBB2-enriched, normal-like, and distinct luminal subtypes, Sørlie et al. made tumor heterogeneity visible at a systems level. The key shift was not merely that breast cancers differed in gene expression, but that those differences mapped onto recognizable clinical behavior, including survival differences among patients treated in a relatively uniform setting.
Its most important implication was that estrogen receptor-positive breast cancer was not one disease. The separation of luminal tumors into at least two subgroups gave molecular form to a clinical problem oncologists already faced: patients with superficially similar ER-positive tumors could have very different outcomes. After this paper, expression profiling could be used not only to describe tumors, but to stratify prognosis and suggest that treatment response might depend on subtype-specific biology rather than on single markers alone.
The study became part of the foundation for the “intrinsic subtype” framework that shaped later breast cancer research, including luminal A, luminal B, HER2-enriched, basal-like, and normal-like classifications. That framework influenced prognostic gene-expression assays, subtype-aware clinical trial design, and later genomic projects that integrated expression data with copy-number, mutation, methylation, and proteomic profiles. In retrospect, the paper mattered because it made molecular heterogeneity operational: it gave researchers and clinicians a vocabulary for linking tumor biology, prognosis, and therapeutic development in a way that subsequent precision oncology could build on.
Abstract¶
The purpose of this study was to classify breast carcinomas based on variations in gene expression patterns derived from cDNA microarrays and to correlate tumor characteristics to clinical outcome. A total of 85 cDNA microarray experiments representing 78 cancers, three fibroadenomas, and four normal breast tissues were analyzed by hierarchical clustering. As reported previously, the cancers could be classified into a basal epithelial-like group, an ERBB2-overexpressing group and a normal breast-like group based on variations in gene expression. A novel finding was that the previously characterized luminal epithelial/estrogen receptor-positive group could be divided into at least two subgroups, each with a distinctive expression profile. These subtypes proved to be reasonably robust by clustering using two different gene sets: first, a set of 456 cDNA clones previously selected to reflect intrinsic properties of the tumors and, second, a gene set that highly correlated with patient outcome. Survival analyses on a subcohort of patients with locally advanced breast cancer uniformly treated in a prospective study showed significantly different outcomes for the patients belonging to the various groups, including a poor prognosis for the basal-like subtype and a significant difference in outcome for the two estrogen receptor-positive groups.
Related¶
- cite → Molecular portraits of human breast tumours — The breast carcinoma study validates and refines the molecular breast-tumor subtypes introduced by the molecular portraits paper.
- cite → Molecular Classification of Cancer: Class Discovery and Class Prediction by Gene Expression Monitoring — The breast carcinoma study applies gene-expression-based class discovery and prediction to distinguish clinically relevant tumor subclasses.
- cite → Cluster analysis and display of genome-wide expression patterns — The breast carcinoma study uses hierarchical clustering and heatmap display methods from genome-wide expression pattern analysis.
- enables → The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups — The breast carcinoma subclass expression signatures provided clinically meaningful subtype concepts refined in the 2,000-tumor genomic architecture study.
- cite ← The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups — The 2012 METABRIC study extends the 2001 breast-cancer intrinsic gene-expression subtype framework by integrating genomic copy-number architecture with transcriptomic subgrouping.