Abstract
ED08-03
To develop and clinically validate a breast cancer gene expression assay for use with tumor blocks that are routinely prepared following surgery, we used a multi-step approach of assay development, hypothesis testing, and validation. We sought to bring the rigor of drug development to the process for developing cancer diagnostics. Specifically, we sought to provide evidence from multiple well-designed clinical studies using a standardized assay system to enable physicians to use the information provided by the genomics of individual tumors to optimize the individualization of cancer care. First, we developed a new assay method to quantify the expression of hundreds of genes from three 10 micron sections of fixed, paraffin-embedded tumor tissue (1). Assay sensitivity, specificity, reproducibility were characterized and optimized for each gene. The assay was designed to be robust with regard to uncontrolled sources of variability, including fixation method and the duration of block storage. Studies were specifically performed to understand tumor heterogeneity and to develop criteria for selection of cases for manual microdissection. Second, we selected candidate genes from the published literature, genomic databases, pathway analysis, and from microarray expression profiling studies. Microarray studies are particularly useful for generating hypotheses for further testing. Third, we performed three clinical studies to examine 250 candidate genes in a total of 447 patients (Esteban et al, ASCO 2003; Cobleigh et al, ASCO 2003; Paik et al, San Antonio Breast Cancer Symposium 2003). Sixteen genes were identified that were consistently associated with the likelihood of breast cancer recurrence across the three studies. Based on the three studies, a multi-gene panel, consisting of 16 cancer-related genes and 5 reference genes, was selected and a "Recurrence Score" algorithm for predicting recurrence based on the expression of these 21 genes was designed. Fourth, the pre-specified 21 gene RT-PCR assay and Recurrence ScoreTM algorithm (Oncotype DXTM) was clinically validated in an independent multi-center study (2). In collaboration with the NSABP, we validated that the Recurrence Score is a predictor of the prospectively-defined endpoint of distant recurrence-free survival in 668 node-negative, ER positive, tamoxifen-treated patients in the NSABP B-14 Study. Moreover, the performance of the Recurrence Score exceeded standard measures, such as patient age, tumor size, and tumor grade. Finally, individual adjuvant treatment decisions are optimally informed if there is a very high confidence in the relationship of gene expression and prognosis, and even more importantly, if gene expression provides insight concerning treatment benefit. Five additional studies have been completed to study the relationship between the 21 gene assay and prognosis and to provide new information on the relationship between the Recurrence Score (and the genes that comprise) and treatment benefit. Esteva et al and Habel et al evaluated the relationship between gene expression and prognosis in a 149 patients cohort study, and in a multi-center study of 790 cases and controls, respectively (3,4). Gianni et al, in collaboration with Lajos Pusztai and colleagues, evaluated the relationship between gene expression as measured by the RT-PCR assay and pathologic complete response in patients treated with neoadjuvant chemotherapy (5). Paik et al performed additional studies of the NSABP B-14 patients treated with placebo, and the NSABP B-20 patients treated with chemotherapy to evaluate the relationship between the Oncotype DX assay and treatment benefit (6). The Oncotype DX assay not only quantifies the likelihood of distant recurrence, it also predicts the magnitude of treatment benefit for patients with node negative, hormone receptor positive breast cancer. The biology of individual tumors (as defined by this standardized RT-PCR assay) provides key independent information that is not captured by the standard measures used to guide treatment, such as patient age, tumor size, and tumor grade. Multiple well-designed clinical studies using a standardized assay system can successfully provide the evidence required by physicians to use the genomics of individual tumors to optimize the individualization of cancer care. References 1. Cronin M, Pho M, Dutta D, Stephans JC, Shak S, Kiefer MC, Esteban JM, Baker JB. Measurement of gene expression in archival paraffin-embedded tissues: development and performance of a 92-gene reverse transcriptase-polymerase chain reaction assay. Am J Pathol 2004; 164(1):35-42. 2. Paik S, Shak S, Tang G, Kim C, Baker J, Cronin M, Baehner FL, Walker MG, Watson D, Park T, Hiller W, Fisher ER, Wickerham DL, Bryant J, Wolmark N. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med 2004; 351(27):2817-2826. 3. Esteva FJ, Sahin AA, Cristofanilli M, Coombes K, Lee SJ, Baker J, Cronin M, Walker M, Watson D, Shak S, Hortobagyi GN. Prognostic role of a multigene reverse transcriptase-PCR assay in patients with node-negative breast cancer not receiving adjuvant systemic therapy. Clin Cancer Res 2005; 11(9):3315-3319. 4. Habel LA, Quesenberry CP, Jacobs MK, Blick NT, Greenberg D, Alexander C, Baker J, Walker M, Watson D, Shak S. A large case-control study of gene expression and breast cancer death in the Northern California Kaiser Permanente population. Breast Cancer Res 2006; 8:R25. 5. Gianni L, Zambetti M, Clark K, Baker J, Cronin M, Wu J, Mariani G, Rodriguez J, Carcangio M, Watson D, Valagussa P, Rouzier R, Symmans WF, Ross JS, Hortobagyi GN, Pusztai L, Shak S. Gene expression profiles in paraffin-embedded core biopsy tissue predict response to chemotherapy in women with locally advanced breast cancer. J Clin Oncol 2005; 23:7265-77. 6. Paik S, Shak S, Tang G, Kim C, Joo H, Baker J, Cronin M, Watson D, Bryant J, Costantino J, Wolmark N. Gene expression and benefit of chemotherapy in women with node-negative, estrogen receptor-positive breast cancer. J. Clin Oncol 2006; 10:3726-34.
[Fifth AACR International Conference on Frontiers in Cancer Prevention Research, Nov 12-15, 2006]