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Trawling for genes that predict response to breast cancer adjuvant therapy.

Randomized clinical trials often set the standard of care for the treatment of early-stage breast cancer. However, the low event rates in these studies often require large sample sizes and long-term follow-up to demonstrate significant improvements in outcomes. This has translated into a glacial timeline for progress that can frustrate both patients and physicians. As progress is made toward the goal of a cure for all patients, the stepwise approach of comparing standard therapy with standard therapy plus something new has generated trials involving large populations, with the possibility of massive overtreatment and ballooning health care costs. How can we focus on the decreasing minority of women who are not cured with standard multimodality breast cancer therapy, while not imposing on the majority who are? The key to this problem lies in the development of tools to individualize treatment so that treatment plans can be carefully matched to both the risk of relapse and the responsiveness of the tumor. To achieve this goal, we need effective biomarkers to replace the old standards of stage, grade, and hormone receptor status. Genomic profiling, therefore, is central to our current vision of individually tailored therapy; confidence is rising that we will be able to track down the constellations of genes that orchestrate patient fate. 1 Recent gene expression profiling studies have clearly shown that we can differentiate between tumors with limited potential for systemic spread and those that are disconcertingly metastatic even at a very early stage. 2 The goal for new prognostic tools is a triage strategy—treating according to risk to produce the same overall outcome but with fewer patients receiving unnecessary therapy. While avoiding toxicity and expense is a laudable goal, predicting outcome without systemic intervention (prognosis) will not greatly increase the overall number of patients cured of their breast cancer. For this, we must understand the biology underlying responsiveness to systemic therapy and develop new and effective treatments through predictive strategies. The article by Ayers et al 3 in this issue of the Journal of Clinical Oncology provides an opportunity to discuss progress in this area and to consider ways to improve our approaches to clinical trial designs that focus on predictive biomarker analysis. The goal of this study was to examine the feasibility of developing a multigene predictor of pathologic complete response (pCR) to sequential weekly paclitaxel, fluorouracil, doxorubicin, and cyclophosphamide (T/FAC) neoadjuvant chemotherapy for breast cancer. The specimens were collected from 42 patients. The first 24 samples were used to develop a multigene predictor for pCR, and the remaining 19 were used to validate the results of the predictor. The model successfully identified only three of seven instances of pCR, based on the expression pattern of the primary tumor before treatment. The study therefore fell short of presenting a definitive result, concluding that transcriptional profiling has “the potential to identify a gene expression pattern in breast that may lead to clinically useful predictors of pCR to T/FAC neoadjuvant therapy.” Is this really the case, or are there formidable barriers that we must resolve before any real progress can be made? Unquestionably, the article serves to illustrate the scientific advantages of treating patients with systemic agents while the primary tumor is intact so that antitumor efficacy can be monitored and the molecular and cellular basis for response can be carefully investigated. pCR as an end point has been validated by large randomized trials that have shown a statistically robust relationship between the ability to eradicate the primary breast cancer and the risk of relapse and death from the disease. 4 However, pCR is not a perfect surrogate for cure, as patients in this category are still at substantial risk for metastatic disease, albeit with a reduced frequency. Perhaps the most significant advantage for primary systemic therapy, aside from improvements in surgical outcomes, is the efficiency of this approach as a drug development strategy. There are an increasing number of