A model of acquired autoresistance to a potent ErbB2 tyrosine kinase inhibitor and a therapeutic strategy to prevent its onset in breast cancer

The development of acquired resistance to ErbB2 tyrosine kinase inhibitors limits the clinical efficacy of this class of cancer therapeutics. Little is known about the mechanism(s) of acquired resistance to these agents. Here we establish a model of acquired resistance to N-{3-chloro-4-[(3-fluorobenzyl) oxy]phenyl}-6-[5-({[2 (methylsulfonyl)ethyl]amino}methyl)-2-furyl]-4-quinazolinamine (lapatinib), an inhibitor of ErbB2 and ErbB1 tyrosine kinases by chronically exposing lapatinib-sensitive ErbB2-overexpressing breast cancer cells to lapatinib, simulating the clinic where lapatinib is administered on a daily chronic basis. Analysis of baseline gene expression in acquired lapatinib-resistant and parental cells indicates estrogen receptor (ER) signaling involvement in the development of resistance. Using gene interference, we confirm that acquired resistance to lapatinib is mediated by a switch in cell survival dependence and regulation of a key antiapoptotic mediator from ErbB2 alone to codependence upon ER and ErbB2 rather than loss of ErbB2 expression or insensitivity of ErbB2 signaling to lapatinib. Increased ER signaling in response to lapatinib is enhanced by the activation of factors facilitating the transcriptional activity of ER, notably FOXO3a and caveolin-1. Importantly, we confirm that lapatinib induces ER signaling in tumor biopsies from patients with ErbB2-overexpressing breast cancers receiving lapatinib therapy. These findings provided the rationale for preventing the development of acquired resistance by simultaneously inhibiting both ER and ErbB2 signaling pathways. Establishing clinically relevant models of acquired resistance to ErbB2 kinase inhibitors will enhance therapeutic strategies to improve clinical outcomes for patients with ErbB2-overexpressing breast cancers

Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications

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