Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis.
BACKGROUND
Histologic grade in breast cancer provides clinically important prognostic information. However, 30%-60% of tumors are classified as histologic grade 2. This grade is associated with an intermediate risk of recurrence and is thus not informative for clinical decision making. We examined whether histologic grade was associated with gene expression profiles of breast cancers and whether such profiles could be used to improve histologic grading.


METHODS
We analyzed microarray data from 189 invasive breast carcinomas and from three published gene expression datasets from breast carcinomas. We identified differentially expressed genes in a training set of 64 estrogen receptor (ER)-positive tumor samples by comparing expression profiles between histologic grade 3 tumors and histologic grade 1 tumors and used the expression of these genes to define the gene expression grade index. Data from 597 independent tumors were used to evaluate the association between relapse-free survival and the gene expression grade index in a Kaplan-Meier analysis. All statistical tests were two-sided.


RESULTS
We identified 97 genes in our training set that were associated with histologic grade; most of these genes were involved in cell cycle regulation and proliferation. In validation datasets, the gene expression grade index was strongly associated with histologic grade 1 and 3 status; however, among histologic grade 2 tumors, the index spanned the values for histologic grade 1-3 tumors. Among patients with histologic grade 2 tumors, a high gene expression grade index was associated with a higher risk of recurrence than a low gene expression grade index (hazard ratio = 3.61, 95% confidence interval = 2.25 to 5.78; P < .001, log-rank test).


CONCLUSIONS
Gene expression grade index appeared to reclassify patients with histologic grade 2 tumors into two groups with high versus low risks of recurrence. This approach may improve the accuracy of tumor grading and thus its prognostic value.
Sotiriou
Christos
C
Functional Genomics and Translational Research Unit, Université Libre de Bruxelles, Brussels, Belgium. christos.sotiriou@bordet.be
Wirapati
Pratyaksha
P
Loi
Sherene
S
Harris
Adrian
A
Fox
Steve
S
Smeds
Johanna
J
Nordgren
Hans
H
Farmer
Pierre
P
Praz
Viviane
V
Haibe-Kains
Benjamin
B
Desmedt
Christine
C
Larsimont
Denis
D
Cardoso
Fatima
F
Peterse
Hans
H
Nuyten
Dimitry
D
Buyse
Marc
M
Van de Vijver
Marc J
MJ
Bergh
Jonas
J
Piccart
Martine
M
Delorenzi
Mauro
M
D001943:Breast Neoplasms / Q000737:chemistry / Q000235:genetics* / Q000473:pathology*; D002453:Cell Cycle; D049109:Cell Proliferation; D018572:Disease-Free Survival; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D008207:Lymphatic Metastasis; D008432:Mathematical Computing; D008875:Middle Aged; D015999:Multivariate Analysis; D020411:Oligonucleotide Array Sequence Analysis; D011379:Prognosis; D016016:Proportional Hazards Models; D011960:Receptors, Estrogen / Q000032:analysis; D012307:Risk Factors
D011960:Receptors, Estrogen