Browsing by Subject "ENDOCRINE THERAPY"

Sort by: Order: Results:

Now showing items 1-2 of 2
  • Varga, Zsuzsanna; Lebeau, Annette; Bu, Hong; Hartmann, Arndt; Penault-Llorca, Frederique; Guerini-Rocco, Elena; Schraml, Peter; Symmans, Fraser; Stoehr, Robert; Teng, Xiaodong; Turzynski, Andreas; von Wasielewski, Reinhard; Guertler, Claudia; Laible, Mark; Schlombs, Kornelia; Joensuu, Heikki; Keller, Thomas; Sinn, Peter; Sahin, Ugur; Bartlett, John; Viale, Giuseppe (2017)
    Background: Accurate determination of the predictive markers human epidermal growth factor receptor 2 (HER2/ERBB2), estrogen receptor (ER/ESR1), progesterone receptor (PgR/PGR), and marker of proliferation Ki67 (MKI67) is indispensable for therapeutic decision making in early breast cancer. In this multicenter prospective study, we addressed the issue of inter- and intrasite reproducibility using the recently developed reverse transcription-quantitative real-time polymerase chain reaction-based MammaTyper (R) test. Methods: Ten international pathology institutions participated in this study and determined messenger RNA expression levels of ERBB2, ESR1, PGR, and MKI67 in both centrally and locally extracted RNA from formalin-fixed, paraffin-embedded breast cancer specimens with the MammaTyper (R) test. Samples were measured repeatedly on different days within the local laboratories, and reproducibility was assessed by means of variance component analysis, Fleiss' kappa statistics, and interclass correlation coefficients (ICCs). Results: Total variations in measurements of centrally and locally prepared RNA extracts were comparable; therefore, statistical analyses were performed on the complete dataset. Intersite reproducibility showed total SDs between 0.21 and 0.44 for the quantitative single-marker assessments, resulting in ICC values of 0.980-0.998, demonstrating excellent agreement of quantitative measurements. Also, the reproducibility of binary single-marker results (positive/negative), as well as the molecular subtype agreement, was almost perfect with kappa values ranging from 0.90 to 1.00. Conclusions: On the basis of these data, the MammaTyper (R) has the potential to substantially improve the current standards of breast cancer diagnostics by providing a highly precise and reproducible quantitative assessment of the established breast cancer biomarkers and molecular subtypes in a decentralized workup.
  • Khan, Sofia; Fagerholm, Rainer; Kadalayil, Latha; Tapper, William; Aittomäki, Kristiina; Liu, Jianjun; Blomqvist, Carl; Eccles, Diana; Nevanlinna, Heli (2018)
    The majority of breast cancers are driven by the female hormone oestrogen via oestrogen receptor (ER) alpha. ER-positive patients are commonly treated with adjuvant endocrine therapy, however, resistance is a common occurrence and aside from ER-status, no unequivocal predictive biomarkers are currently in clinical use. In this study, we aimed to identify constitutional genetic variants influencing breast cancer survival among ER-positive patients and specifically, among endocrine-treated patients. We conducted a meta-analysis of three genome-wide association studies comprising in total 3,136 patients with ER-positive breast cancer of which 2,751 had received adjuvant endocrine therapy. We identified a novel locus (rs992531 at 8p21.2) associated with reduced survival among the patients with ER-positive breast cancer (P = 3.77 x 10(-8)). Another locus (rs7701292 at 5q21.3) was associated with reduced survival among the endocrine-treated patients (P = 2.13 x 10(-8)). Interaction analysis indicated that the survival association of rs7701292 is treatment-specific and independent of conventional prognostic markers. In silico functional studies suggest plausible biological mechanisms for the observed survival associations and a functional link between the putative target genes of the rs992531 and rs7701292 (RHOBTB2 and RAB9P1, respectively). We further explored the genetic interaction between rs992531 and rs7701292 and found a significant, treatment-specific interactive effect on survival among ER-positive, endocrine-treated patients (hazard ratio = 6.97; 95% confidence interval, 1.79-27.08, P-interaction = 0.036). This is the first study to identify a genetic interaction that specifically predicts treatment outcome. These findings may provide predictive biomarkers based on germ line genotype informing more personalized treatment selection.