Some breast cancers have been shown to contain a small fraction of cells characterized by CD44 ⁺ /CD24 ^−/low cell-surface antigen profile that have high tumor-initiating potential. In addition, breast cancer cells propagated in vitro as mammospheres (MSs) have also been shown to be enriched for cells capable of self-renewal. In this study, we have defined a gene expression signature common to both CD44 ⁺ /CD24 ^−/low and MS-forming cells. To examine its clinical significance, we determined whether tumor cells surviving after conventional treatments were enriched for cells bearing this CD44 ⁺ /CD24 ^−/low -MS signature. The CD44 ⁺ /CD24 ^−/low -MS signature was found mainly in human breast tumors of the recently identified “claudin-low” molecular subtype, which is characterized by expression of many epithelial-mesenchymal-transition (EMT)-associated genes. Both CD44 ⁺ /CD24 ^−/low -MS and claudin-low signatures were more pronounced in tumor tissue remaining after either endocrine therapy (letrozole) or chemotherapy (docetaxel), consistent with the selective survival of tumor-initiating cells posttreatment. We confirmed an increased expression of mesenchymal markers, including vimentin ( VIM ) in cytokeratin-positive epithelial cells metalloproteinase 2 ( MMP 2), in two separate sets of postletrozole vs. pretreatment specimens. Taken together, these data provide supporting evidence that the residual breast tumor cell populations surviving after conventional treatment may be enriched for subpopulations of cells with both tumor-initiating and mesenchymal features. Targeting proteins involved in EMT may provide a therapeutic strategy for eliminating surviving cells to prevent recurrence and improve long-term survival in breast cancer patients.

Background: Currently real time PCR is the most precise method by which to measure gene expression. The method generates a large amount of raw numerical data and processing may notably influence final results. The data processing is based either on standard curves or on PCR efficiency assessment. At the moment, the PCR efficiency approach is preferred in relative PCR whilst the standard curve is often used for absolute PCR. However, there are no barriers to employ standard curves for relative PCR. This article provides an implementation of the standard curve method and discusses its advantages and limitations in relative real time PCR. Results: We designed a procedure for data processing in relative real time PCR. The procedure completely avoids PCR efficiency assessment, minimizes operator involvement and provides a statistical assessment of intra-assay variation. The procedure includes the following steps. (I) Noise is filtered from raw fluorescence readings by smoothing, baseline subtraction and amplitude normalization. (II) The optimal threshold is selected automatically from regression parameters of the standard curve. (III) Crossing points (CPs) are derived directly from coordinates of points where the threshold line crosses fluorescence plots obtained after the noise filtering. (IV) The means and their variances are calculated for CPs in PCR replicas. (V) The final results are derived from the CPs' means. The CPs' variances are traced to results by the law of error propagation. A detailed description and analysis of this data processing is provided. The limitations associated with the use of parametric statistical methods and amplitude normalization are specifically analyzed and found fit to the routine laboratory practice. Different options are discussed for aggregation of data obtained from multiple reference genes. Conclusion: A standard curve based procedure for PCR data processing has been compiled and validated. It illustrates that standard curve design remains a reliable and simple alternative to the PCR-efficiency based calculations in relative real time PCR.

Background: The tissue-specific translation elongation factor eEF1A2 was recently shown to be a potential oncogene that is overexpressed in ovarian cancer. Although there is no direct evidence for an involvement of eEF1A2 in breast cancer, the genomic region to which EEF1A2 maps, 20q13, is frequently amplified in breast tumours. We therefore sought to establish whether eEF1A2 expression might be upregulated in breast cancer. Methods: eEF1A2 is highly similar (98%) to the near-ubiquitously expressed eEF1A1 (formerly known as EF1-α) making analysis with commercial antibodies difficult. We have developed specific anti-eEF1A2 antibodies and used them in immunohistochemical analyses of tumour samples. We report the novel finding that although eEF1A2 is barely detectable in normal breast it is moderately to strongly expressed in two-thirds of breast tumours. This overexpression is strongly associated with estrogen receptor positivity. Conclusion: eEF1A2 should be considered as a putative oncogene in breast cancer that may be a useful diagnostic marker and therapeutic target for a high proportion of breast tumours. The oncogenicity of eEF1A2 may be related to its role in protein synthesis or to its potential non-canonical functions in cytoskeletal remodelling or apoptosis.

Purpose: Aromatase inhibitors (AIs) have an established role in the treatment of breast cancer. Response rates are only 50% to 70% in the neoadjuvant setting and lower in advanced disease. Accurate biomarkers are urgently needed to predict response in these settings and to determine which individuals will benefit from adjuvant AI therapy.Patients and Methods: Pretreatment and on-treatment (after 2 weeks and 3 months) biopsies were obtained from 89 postmenopausal women who had estrogen receptor–alpha positive breast cancer and were receiving neoadjuvant letrozole for transcript profiling. Dynamic clinical response was assessed with use of three-dimensional ultrasound measurements.Results: The molecular response to letrozole was characterized and a four-gene classifier of clinical response was established (accuracy of 96%) on the basis of the level of two genes before treatment (one gene [IL6ST] was associated with immune signaling, and the other [NGFRAP1] was associated with apoptosis) and the level of two proliferation genes (ASPM, MCM4) after 2 weeks of therapy. The four-gene signature was found to be 91% accurate in a blinded, completely independent validation data set of patients treated with anastrozole. Matched 2-week on-treatment biopsies were associated with improved predictive power as compared with pretreatment biopsies alone. This signature also significantly predicted recurrence-free survival (P = .029) and breast cancer –specific survival (P = .009). We demonstrate that the test can also be performed with use of quantitative polymerase chain reaction or immunohistochemistry.Conclusion: A four-gene predictive model of clinical response to AIs by 2 weeks has been generated and validated. Deregulated immune and apoptotic responses before treatment and cell proliferation that is not reduced 2 weeks after initiation of treatment are functional characteristics of breast tumors that do not respond to AIs.

Background: Aromatase inhibitors such as anastrozole and letrozole are highly effective suppressants of estrogen synthesis in postmenopausal women and are the most effective endocrine treatments for hormone receptor positive breast cancer in such women. Little is known of the molecular effects of these agents on human breast carcinomas in vivo. Methods: We randomly assigned primary estrogen receptor positive breast cancer patients to treatment with anastrozole or letrozole for 2 weeks before surgery. Expression profiling using cDNA arrays was conducted on pretreatment and post-treatment biopsies. Sample pairs from 34 patients provided sufficient RNA for analysis. Results: Profound changes in gene expression were seen with both aromatase inhibitors, including many classical estrogen-dependent genes such as TFF1, CCND1, PDZK1 and AGR2, but also many other genes that are likely to represent secondary responses; decrease in the expression of proliferation-related genes were particularly prominent. Many upregulated genes are involved in extracellular matrix remodelling, including collagens and members of the small leucine-rich proteoglycan family (LUM, DCN, and ASPN). No significant differences were seen between letrozole and anastrozole in terms of molecular effects. The gene changes were integrated into a Global Index of Dependence on Estrogen (GIDE), which enumerates the genes changing by at least twofold with therapy. The GIDE varied markedly between tumours and related significantly to pretreatment levels of HER2 and changes in immunohistochemically detected Ki67. Conclusion: Our findings identify the transcriptional signatures associated with aromatase inhibitor treatment of primary breast tumours. Larger datasets using this approach should enable identification of estrogen-dependent molecular changes, which are the determinants of benefit or resistance to endocrine therapy.

The aim of the study was to identify changes in tumour expression profiling associated with short-term therapy of breast cancer patients with letrozole. Microarray analysis was performed on RNA extracted from paired tumour core biopsies taken before and after 14 days of treatment with letrozole (2.5 mg/daily) in 58 patients. Changes in expression profile were identified by three different approaches on the basis of frequency of changes, magnitude of changes and significance analysis of microarray. No single gene was consistently changed by therapy in all cases. Fifty-two genes, however, were downregulated and 36 upregulated in at least 45 of the 58 cases. In terms of quantitative change, 46 genes showed at least a median 1.5-fold change in expression. Significance analysis of microarray identified 62 genes that were significantly changed by therapy (P<0.0001, 56 downregulated and six upregulated). All three approaches showed that greater numbers of genes were downregulated rather than upregulated. Merging data produced a total of 143 genes, which were subject to gene ontology and cluster analysis. The ontology of the 91 downregulated genes showed that they were functionally associated with cell cycle progression, particularly mitosis. In contrast, upregulated genes were associated with organ development, connective tissue extracellular matrix regulation and inflammatory response. Cluster analysis segregated the patients into four groups differing in patterns of gene expression. Genes have been identified which either change markedly or consistently in breast cancer after 14 days treatment with letrozole. These are new important data in understanding letrozole's molecular mechanism of action in breast cancers.