Gene expression profiling for prognosis of breast cancer
- M van de Vijver1
© BioMed Central Ltd 2007
Received: 23 May 2007
Published: 19 June 2007
Tumor factors that can predict prognosis and response to specific therapies (for example, chemotherapy regimens) are of great potential benefit for tailored treatment of patients with invasive breast cancer. We have previously defined a gene expression profile of 70 genes that is predictive for a short interval to distant metastases (< 5 years) in lymph node negative (LN0) patients . We have subsequently validated the prognostic value of this 70-gene profile in a cohort of 295 stage I and II breast cancer patients younger than 53 years of age . To test whether gene expression profiling can be used in clinical practice, we have performed a study in 16 hospitals in The Netherlands. Female patients younger than 61 years presenting with primary operable cT1-2N0M0 breast carcinoma were eligible and entered into this prospective feasibility study. Fresh tumor samples in a standardized fashion were collected within 1–3 hours of primary surgery and sent in RNAlater® to the Netherlands Cancer Institute. The 70-gene signature (genomic profile) was obtained in node-negative patients with a representative tumor sample; node-positive patients were excluded. Between 2004 and 2006, 812 patients were enrolled and 427 (53%) genomic profiles were obtained. The remaining 385 (47%) patients were excluded mainly because of node-positive disease (22%). The logistics of obtaining fresh-frozen material from the tumor has gone very well in each of the participating hospitals. Approximately 50% of the tumors were shown to have a good prognosis signature.
Another area of research is to identify gene expression signatures associated with the response to chemotherapy. Within a single-institution prospective phase II trial, patients with locally advanced breast cancer received six courses of either doxorubicin-cyclo-phosphamide (AC) (n = 25) or doxorubicin-docetaxel (AD) (n = 24) containing neoadjuvant chemotherapy. Gene expression profiles were generated from core needle biopsies obtained before treatment and correlated with the response of the primary tumor to the chemotherapy administered . Additionally, pretreatment gene expression profiles were compared with those in tumors remaining after chemotherapy (n = 15).
Eleven (22%) of the 49 patients showed a (near) pathological complete remission of the primary tumor after treatment. No gene expression pattern correlating with response could be identified for all patients as well as for the AC-treated or AD-treated group separately. The comparison of the pretreatment biopsy and the tumor excised after chemotherapy revealed differences in gene expression in those tumors that showed a partial remission but not in tumors that did not respond to chemotherapy.
No gene expression profile predicting the response of primary breast carcinomas to AC-based or AD-based neoadjuvant chemotherapy could be detected in this study. We are currently expanding the series of patients in this neoadjuvant chemotherapy study.
We conclude that gene expression profiling is a method that has greatly accelerated the identification of prognostic and predictive factors in breast cancer and will lead to novel diagnostic tests that can be reliably implicated in clinical practice.
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