Serial expression analysis of breast tumors during neoadjuvant chemotherapy reveals changes in cell cycle and immune pathways associated with recurrence and response.

INTRODUCTION: The molecular biology involving neoadjuvant chemotherapy (NAC) response is poorly understood. To elucidate the impact of NAC on the breast cancer transcriptome and its association with clinical outcome, we analyzed gene expression data derived from serial tumor samples of patients with breast cancer who received NAC in the I-SPY 1 TRIAL. METHODS: Expression data were collected before treatment (T1), 24-96 hours after initiation of chemotherapy (T2) and at surgery (TS). Expression levels between T1 and T2 (T1 vs. T2; n = 36) and between T1 and TS (T1 vs. TS; n = 39) were compared. Subtype was assigned using the PAM50 gene signature. Differences in early gene expression changes (T2 - T1) between responders and nonresponders, as defined by residual cancer burden, were evaluated. Cox proportional hazards modeling was used to identify genes in residual tumors associated with recurrence-free survival (RFS). Pathway analysis was performed with Ingenuity software. RESULTS: When we compared expression profiles at T1 vs. T2 and at T1 vs. TS, we detected significantly altered expression of 150 and 59 transcripts, respectively. We observed notable downregulation of proliferation and immune-related genes at T2. Lower concordance in subtype assignment was observed between T1 and TS (62 %) than between T1 and T2 (75 %). Analysis of early gene expression changes (T2 - T1) revealed that decreased expression of cell cycle inhibitors was associated with poor response. Increased interferon signaling (TS - T1) and high expression of cell proliferation genes in residual tumors (TS) were associated with reduced RFS. CONCLUSIONS: Serial gene expression analysis revealed candidate immune and proliferation pathways associated with response and recurrence. Larger studies incorporating the approach described here are warranted to identify predictive and prognostic biomarkers in the NAC setting for specific targeted therapies. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT00033397 . Registered 9 Apr 2002.

Expression profiling of circulating tumor cells in metastatic breast cancer.

Circulating tumor cells (CTCs) are prognostic in all stages of breast cancer. However, since they are extremely rare, little is known about the molecular nature of these cells. We report a novel strategy for the isolation and expression profiling of pure populations of CTCs derived from peripheral blood. We developed a method to isolate CTCs based on immunomagnetic capture followed by fluorescence-activated cell sorting (IE/FACS). After assay validation using the BT474 cell line spiked into blood samples in vitro, RNA from CTCs isolated from the blood of five metastatic breast cancer (MBC) patients was linearly amplified and subjected to gene expression profiling via cDNA microarrays. We isolated a range of 9-993 captured CTCs from five MBC patients' blood and profiled their RNA in comparison to a diverse panel of primary breast tumors (n = 55). Unsupervised hierarchical clustering revealed that CTC profiles clustered with more aggressive subtypes of primary breast tumors and were readily distinguishable from peripheral blood (PB) and normal epithelium. Differential expression analysis revealed CTCs to have downregulated apoptosis, and they were distinguishable from PB by the relative absence of immune-related signals. As expected, CTCs from MBC had significantly higher risk of recurrence scores than primary tumors (p = 0.0073). This study demonstrates that it is feasible to isolate CTCs from PB with high purity through IE/FACS and profile them via gene expression analysis. Our approach may inform the discovery of therapeutic predictors and be useful for real-time identification of emerging resistance mechanisms in MBC patients.

Cellular and gene expression responses involved in the rapid growth inhibition of human cancer cells by RNA interference-mediated depletion of telomerase RNA.

Inhibition of the up-regulated telomerase activity in cancer cells has previously been shown to slow cell growth but only after prior telomere shortening. Previously, we have reported that, unexpectedly, a hairpin short interfering RNA specifically targeting human telomerase RNA rapidly inhibits the growth of human cancer cells independently of p53 or telomere length and without bulk telomere shortening (Li, S., Rosenberg, J. E., Donjacour, A. A., Botchkina, I. L., Hom, Y. K., Cunha, G. R., and Blackburn, E. H. (2004) Cancer Res. 64, 4833-4840). Here we have demonstrated that such telomerase RNA knockdown in cancer cells does not cause telomere uncapping but rather induces changes in the global gene expression profile indicative of a novel response pathway, which includes suppression of specific genes implicated in angiogenesis and metastasis, and is distinct from the expression profile changes induced by telomere-uncapping mutant template telomerase RNAs. These cellular responses to depleting telomerase in human cancer cells together suggest that cancer cells are "telomerase-addicted" and uncover functions of telomerase in tumor growth and progression in addition to telomere maintenance.

The gene expression signatures of melanoma progression.

Because of the paucity of available tissue, little information has previously been available regarding the gene expression profiles of primary melanomas. To understand the molecular basis of melanoma progression, we compared the gene expression profiles of a series of nevi, primary melanomas, and melanoma metastases. We found that metastatic melanomas exhibit two dichotomous patterns of gene expression, which unexpectedly reflect gene expression differences already apparent in comparing laser-capture microdissected radial and vertical phases of a large primary melanoma. Unsupervised hierarchical clustering accurately separated nevi and primary melanomas. Multiclass significance analysis of microarrays comparing normal skin, nevi, primary melanomas, and the two types of metastatic melanoma identified 2,602 transcripts that significantly correlated with sample class. These results suggest that melanoma pathogenesis can be understood as a series of distinct molecular events. The gene expression signatures identified here provide the basis for developing new diagnostics and targeting therapies for patients with malignant melanoma.