Classifying the estrogen receptor status of breast cancers by expression profiles reveals a poor prognosis subpopulation exhibiting high expression of the ERBB2 receptor.
Recent work using expression profiling to computationally predict the estrogen receptor (ER) status of breast tumors has revealed that certain tumors are characterized by a high prediction uncertainty ('low-confidence'). We analyzed these 'low-confidence' tumors and determined that their 'uncertain' prediction status arises as a result of widespread perturbations in multiple genes whose expression is important for ER subtype discrimination. Patients with 'low-confidence' ER+ tumors exhibited a significantly worse overall survival (P=0.03) and shorter time to distant metastasis (P=0.004) compared with their 'high-confidence' ER+ counterparts, indicating that the 'high-' and 'low-confidence' binary distinction is clinically meaningful. We then discovered that elevated expression of the ERBB2 receptor is significantly correlated with a breast tumor exhibiting a 'low-confidence' prediction, and this association was subsequently validated across multiple independently derived breast cancer expression datasets employing a variety of different array technologies and patient populations. Although ERBB2 signaling has been proposed to inhibit the transcriptional activity of ER, a large proportion of the perturbed genes in the 'low-confidence'/ERBB2+ samples are not known to be estrogen responsive, and a recently described bioinformatic algorithm (DEREF) was used to demonstrate the absence of potential estrogen-response elements (EREs) in their promoters. We propose that a significant portion of ERBB2's effects on ER+ breast tumors may involve ER-independent mechanisms of gene activation, which may contribute to the clinically aggressive behavior of the 'low-confidence' breast tumor subtype.
National Cancer Centre, Singapore, Republic of Singapore.
Yu
Y
Kun
Lee Chee
LC
How
Tan Puay
TP
Hoon
Vladimir B
VB
Bajic
Tan Sin
TS
Lam
Amit
A
Aggarwal
Hong Ga
HG
Sze
Wee Siew
WS
Bok
Wong Chow
WC
Yin
Patrick
P
Tan
D000465:Algorithms; D001943:Breast Neoplasms / Q000175:diagnosis / Q000235:genetics / Q000378:metabolism*; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D009376:Neoplasms, Hormone-Dependent / Q000175:diagnosis*; D011379:Prognosis; D018719:Erb-b2 Receptor Tyrosine Kinases / Q000378:metabolism*; D013223:Statistics as Topic; D015996:Survival Rate; D015533:Transcriptional Activation
D018719:Erb-b2 Receptor Tyrosine Kinases