21
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Changes in expression of oestrogen regulated and proliferation genes with neoadjuvant treatment highlight heterogeneity of clinical resistance to the aromatase inhibitor, letrozole

      research-article
      1 , 2 , ,   3
      Breast Cancer Research : BCR
      BioMed Central

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Introduction

          Clinical resistance is a major factor limiting benefits to endocrine therapy. Causes of resistance may be diverse and the mechanism of resistance in individual breast cancers is usually unknown. The present study illustrates how changes in the expression of proliferation and oestrogen-regulated genes occurring during neoadjuvant treatment with the aromatase inhibitor, letrozole, may define distinctive tumour subgroups and suggest different mechanisms of resistance in clinically endocrine resistant breast cancers.

          Methods

          Postmenopausal women with large primary oestrogen-receptor (ER)-rich breast cancers were treated neoadjuvantly with letrozole (2.5 mg daily) for three months. Clinical response was determined by ultrasound changes in tumour volume. Tumour ribonucleic acid (RNA) from biopsies taken before, after 14 days and after three months of treatment was hybridized on Affymetrix U133A chips. Changes in expression of KIAA0101, TFF3, SERPINA3, IRS-1 and TFF1 were taken as markers of oestrogen regulation and those in CDC2, CKS-2, Cyclin B1, Thymidine Synthetase and PCNA as markers of proliferation.

          Results

          Fifteen tumours with < 50% volume reduction over three months of treatment were classified as being clinically non-responsive. Gene expression changes after 14 days of treatment with letrozole revealed different patterns of change in oestrogen regulated and proliferation genes in individual resistant tumours. Tumours could be separated into three different subgroups as follows: i) nine cases in which both proliferation and oestrogen signalling signatures were generally reduced on treatment (ii) four cases in which both signatures were generally unaffected or increased with treatment and (iii) two cases in which expression of the majority of oestrogen-regulated genes decreased whereas proliferation genes remained unchanged or increased. In 14 out of 15 tumours, RNA profiles were also available after three months of treatment. Patterns of change observed after 14 days were maintained or accentuated at three months in nine tumours but changes in patterns were apparent in the remaining five cancers.

          Conclusions

          Different dynamic patterns of expression of oestrogen-regulated and proliferation genes were observed in tumours clinically resistant to neoadjuvant letrozole, thus illustrating heterogeneity of resistance and discriminating molecular sub-classes of resistant tumours. Molecular phenotyping might help to direct circumventing therapy suggesting the targeting of specific pathways in different tumour subtypes.

          Related collections

          Most cited references32

          • Record: found
          • Abstract: found
          • Article: not found

          Biological determinants of endocrine resistance in breast cancer.

          Endocrine therapies targeting oestrogen action (anti-oestrogens, such as tamoxifen, and aromatase inhibitors) decrease mortality from breast cancer, but their efficacy is limited by intrinsic and acquired therapeutic resistance. Candidate molecular biomarkers and gene expression signatures of tamoxifen response emphasize the importance of deregulation of proliferation and survival signalling in endocrine resistance. However, definition of the specific genetic lesions and molecular processes that determine clinical endocrine resistance is incomplete. The development of large-scale computational and genetic approaches offers the promise of identifying the mediators of endocrine resistance that may be exploited as potential therapeutic targets and biomarkers of response in the clinic.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found
            Is Open Access

            A standard curve based method for relative real time PCR data processing

            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.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Profiling of estrogen up- and down-regulated gene expression in human breast cancer cells: insights into gene networks and pathways underlying estrogenic control of proliferation and cell phenotype.

              Estrogens are known to regulate the proliferation of breast cancer cells and to alter their cytoarchitectural and phenotypic properties, but the gene networks and pathways by which estrogenic hormones regulate these events are only partially understood. We used global gene expression profiling by Affymetrix GeneChip microarray analysis, with quantitative PCR verification in many cases, to identify patterns and time courses of genes that are either stimulated or inhibited by estradiol (E2) in estrogen receptor (ER)-positive MCF-7 human breast cancer cells. Of the >12,000 genes queried, over 400 showed a robust pattern of regulation, and, notably, the majority (70%) were down-regulated. We observed a general up-regulation of positive proliferation regulators, including survivin, multiple growth factors, genes involved in cell cycle progression, and regulatory factor-receptor loops, and the down-regulation of transcriptional repressors, such as Mad4 and JunB, and of antiproliferative and proapoptotic genes, including B cell translocation gene-1 and -2, cyclin G2, BCL-2 antagonist/killer 1, BCL 2-interacting killer, caspase 9, and TGFbeta family growth inhibitory factors. These together likely contribute to the stimulation of proliferation and the suppression of apoptosis by E2 in these cells. Of interest, E2 appeared to modulate its own activity through the enhanced expression of genes involved in prostaglandin E production and signaling, which could lead to an increase in aromatase expression and E2 production, as well as the decreased expression of several nuclear receptor coactivators that could impact ER activity. Our studies highlight the diverse gene networks and metabolic and cell regulatory pathways through which this hormone operates to achieve its widespread effects on breast cancer cells.
                Bookmark

                Author and article information

                Journal
                Breast Cancer Res
                Breast Cancer Research : BCR
                BioMed Central
                1465-5411
                1465-542X
                2010
                20 July 2010
                : 12
                : 4
                : R52
                Affiliations
                [1 ]Breast Research Group, University of Edinburgh, Western General Hospital, Crewe Road South, Edinburgh EH4 2XU, UK
                [2 ]Current address: 2 Stoneycroft Road, South Queensferry, EH30 9HX, West Lothian, UK
                [3 ]Edinburgh Breakthrough Breast Research Unit, Edinburgh University, Western General Hospital, Crewe Road South, Edinburgh EH4 2XU, UK
                Article
                bcr2611
                10.1186/bcr2611
                2949641
                20646288
                dcec9caa-f5f9-4ab4-9046-6706f0668c71
                Copyright ©2010 Miller et al.; licensee BioMed Central Ltd.

                This is an open access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 29 January 2010
                : 25 May 2010
                : 20 July 2010
                Categories
                Research Article

                Oncology & Radiotherapy
                Oncology & Radiotherapy

                Comments

                Comment on this article