title: Genetic reclassification of histologic grade delineates new clinical subtypes of breast cancer.
abstract: Histologic grading of breast cancer defines morphologic subtypes informative of metastatic potential, although not without considerable interobserver disagreement and clinical heterogeneity particularly among the moderately differentiated grade 2 (G2) tumors. We posited that a gene expression signature capable of discerning tumors of grade 1 (G1) and grade 3 (G3) histology might provide a more objective measure of grade with prognostic benefit for patients with G2 disease. To this end, we studied the expression profiles of 347 primary invasive breast tumors analyzed on Affymetrix microarrays. Using class prediction algorithms, we identified 264 robust grade-associated markers, six of which could accurately classify G1 and G3 tumors, and separate G2 tumors into two highly discriminant classes (termed G2a and G2b genetic grades) with patient survival outcomes highly similar to those with G1 and G3 histology, respectively. Statistical analysis of conventional clinical variables further distinguished G2a and G2b subtypes from each other, but also from histologic G1 and G3 tumors. In multivariate analyses, genetic grade was consistently found to be an independent prognostic indicator of disease recurrence comparable with that of lymph node status and tumor size. When incorporated into the Nottingham prognostic index, genetic grade enhanced detection of patients with less harmful tumors, likely to benefit little from adjuvant therapy. Our findings show that a genetic grade signature can improve prognosis and therapeutic planning for breast cancer patients, and support the view that low- and high-grade disease, as defined genetically, reflect independent pathobiological entities rather than a continuum of cancer progression.
authors.affiliation: Genome Institute of Singapore, Singapore.
authors.forename: Anna V
authors.initials: AV
authors.lastname: Ivshina
authors.forename: Joshy
authors.initials: J
authors.lastname: George
authors.forename: Oleg
authors.initials: O
authors.lastname: Senko
authors.forename: Benjamin
authors.initials: B
authors.lastname: Mow
authors.forename: Thomas C
authors.initials: TC
authors.lastname: Putti
authors.forename: Johanna
authors.initials: J
authors.lastname: Smeds
authors.forename: Thomas
authors.initials: T
authors.lastname: Lindahl
authors.forename: Yudi
authors.initials: Y
authors.lastname: Pawitan
authors.forename: Per
authors.initials: P
authors.lastname: Hall
authors.forename: Hans
authors.initials: H
authors.lastname: Nordgren
authors.forename: John E L
authors.initials: JE
authors.lastname: Wong
authors.forename: Edison T
authors.initials: ET
authors.lastname: Liu
authors.forename: Jonas
authors.initials: J
authors.lastname: Bergh
authors.forename: Vladimir A
authors.initials: VA
authors.lastname: Kuznetsov
authors.forename: Lance D
authors.initials: LD
authors.lastname: Miller
mesh_terms: D000465:Algorithms; D001943:Breast Neoplasms / Q000145:classification / Q000235:genetics* / Q000401:mortality / Q000473:pathology; D005260:Female; D006801:Humans; D008207:Lymphatic Metastasis; D009367:Neoplasm Staging; D011379:Prognosis; D012307:Risk Factors