Is it time to ReSET the standard for estrogen receptor testing in breast cancer

More than 35 years ago, early clinical studies suggested that tumor estrogen receptor (ER) content predicted response to hormone therapy in metastatic breast cancer. Thus, ER represents one of the first predictive markers for a targeted therapy, the antiestrogen tamoxifen. Large overviews of randomized clinical trials have confirmed that hormone therapy is ineffective in invasive breast cancers that lack ER expression, so ER status is an excellent negative predictive factor. Although it has been suggested that clinical responses can be seen in women whose tumors express ER in as few as 1% of cells, ER expression alone is a relatively poor predictor of which tumors will respond to hormone therapy. In addition, despite several decades of ER biomarker research, recent guidelines for immunohistochemistry (IHC) testing for ER and progesterone receptor (PR) in breast cancer note that they are inaccurately assessed in up to 20% of tumors. Of most concern here is the false-negative rate, which might lead to inappropriate withholding of a minimally toxic and potentially curative hormone therapy. There was early recognition that ER expression alone might not be a perfect positive predictive factor for response to hormone therapy, because levels of ER alone do not actually indicate if the ER is active or not. This led to the idea that ER-regulated genes might serve as a biomarker of ER activity; the estrogen-regulated PR was the initial candidate. However, despite the attractiveness of this hypothesis, as well as support from prospective trials validating PR as a predictive marker, other studies have failed to reproduce this finding. The last 20 years have seen great strides in our understanding of the molecular basis of ER activity in normal reproduction and development and in breast cancer. The ER protein binds the steroid hormone estradiol and regulates the transcription of a large network of genes. The advent of new molecular technologies such as gene expression microarrays, chromatin immunoprecipitation, massively parallel sequencing, and others have refined our ability to define a large number of ER target genes. In particular, early microarray analysis of human breast cancers identified an ERpositive subset of luminal breast cancer, which expresses a panel of genes in concert with ER expression. Armed with these technical advances, several groups have recently tried to use a network of estrogen-regulated genes to better predict response to hormone therapy. In this issue of Journal of Clinical Oncology, Symmans et al postulate that expression of genes correlated with ER may better predict patient outcome in response to hormone therapy than ER expression alone. They used microarray analysis to identify genes whose expression either positively or negatively correlated with ER in a discovery cohort of 437 human breast cancers to develop a genomic index for sensitivity to endocrine therapy (SET index). The SET index includes 106 genes that are positively correlated and 59 genes that are negatively correlated with ER expression. It is comforting that many of these genes are known as classic estrogen-regulated genes, including GATA-3, IGF-IR, IRS1, TFF1, ErbB4, MYB, and others. The authors then used a validation cohort of 245 patients to develop cutoff points for the SET index to define three endocrine sensitivity classes. In this cohort, the SET index, but not ER mRNA expression, was associated with distant relapse and death in the setting of adjuvant tamoxifen, perhaps indicating superiority of the SET index over ER mRNA alone. Importantly, the study team then evaluated the association of the predefined categories of the SET index with outcome (distant relapse-free survival) in several different cohorts of patients who received adjuvant tamoxifen (N 310) or chemoendocrine therapy (N 131) or patients who received no treatment (N 209 and N 134) as a second independent validation. In aggregate, these analyses show that continuous SET index, but not ER transcript, was again associated with the hazard ratio for distant relapse or death within 10 years. Of note, the SET index was even more predictive of distant relapse-free survival in patients treated with chemoendocrine therapy. Finally, the SET index was not associated with outcome in patients with ER-positive tumors who did not receive therapy. Together, these findings suggest that the SET index is predictive of benefit from endocrine therapy but that it does not predict for prognosis. This result is different from many other previously reported gene signatures, which are largely prognostic of outcome in the absence of therapy. This difference may result from the unique filtering approach used by Symmans et al whereby they removed probe sets that were associated with proliferation. Of course, as these data are not derived from a randomized trial, comparisons of data from patients who received treatment and patients who did not receive treatment are fraught with danger given that the reasons for lack of treatment in patients with ER-positive tumors may have affected the ability of the SET index to indicate prognosis. An immediate question regarding the SET index is its performance compared with other standard assays and other reported multigene assays to predict hormone response. There have been several reports of genes differentially expressed in tumors recurring on tamoxifen, estrogen-induced genes in culture, and clusters of JOURNAL OF CLINICAL ONCOLOGY E D I T O R I A L S VOLUME 28 NUMBER 27 SEPTEMBER 2