Luca Gianni

Gene Expression Profiles in Paraffin-Embedded Core Biopsy Tissue Predict Response to Chemotherapy in Women With Locally Advanced Breast Cancer

PURPOSE We sought to identify gene expression markers that predict the likelihood of chemotherapy response. We also tested whether chemotherapy response is correlated with the 21-gene Recurrence Score assay that quantifies recurrence risk. METHODS Patients with locally advanced breast cancer received neoadjuvant paclitaxel and doxorubicin. RNA was extracted from the pretreatment formalin-fixed paraffin-embedded core biopsies. The expression of 384 genes was quantified using reverse transcriptase polymerase chain reaction and correlated with pathologic complete response (pCR). The performance of genes predicting for pCR was tested in patients from an independent neoadjuvant study where gene expression was obtained using DNA microarrays. RESULTS Of 89 assessable patients (mean age, 49.9 years; mean tumor size, 6.4 cm), 11 (12%) had a pCR. Eighty-six genes correlated with pCR (unadjusted P < .05); pCR was more likely with higher expression of proliferation-related genes and immune-related genes, and with lower expression of estrogen receptor (ER) -related genes. In 82 independent patients treated with neoadjuvant paclitaxel and doxorubicin, DNA microarray data were available for 79 of the 86 genes. In univariate analysis, 24 genes correlated with pCR with P < .05 (false discovery, four genes) and 32 genes showed correlation with P < .1 (false discovery, eight genes). The Recurrence Score was positively associated with the likelihood of pCR (P = .005), suggesting that the patients who are at greatest recurrence risk are more likely to have chemotherapy benefit. CONCLUSION Quantitative expression of ER-related genes, proliferation genes, and immune-related genes are strong predictors of pCR in women with locally advanced breast cancer receiving neoadjuvant anthracyclines and paclitaxel.

Technology insight: Emerging techniques to predict response to preoperative chemotherapy in breast cancer.

During the past decade, several high-throughput analytical methods have been developed, and most of these are being explored as potential diagnostic tools. Gene expression profiling with DNA microarrays or with multiplex polymerase chain reaction are the methods closest to being of clinical use. Prediction of clinically meaningful response to particular chemotherapy regimens or drugs remains a persistent challenge. There are established clinical and histopathologic predictors of prognosis for breast cancer, but there is no test to assist in selecting the optimal chemotherapy regimen for patients. Here we review recent advances in the application of gene expression profiling to chemotherapy response prediction.