Meet Inspiring Speakers and Experts at our 3000+ Global Conference Series Events with over 1000+ Conferences, 1000+ Symposiums
and 1000+ Workshops on Medical, Pharma, Engineering, Science, Technology and Business.

Explore and learn more about Conference Series : World's leading Event Organizer

Back

Hiltrud Brauch

Hiltrud Brauch

Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Germany

Title: Endocrine treatment of breast cancer: Current concepts to predict and prevent relapse

Biography

Biography: Hiltrud Brauch

Abstract

Standard-of-care in endocrine treatment is the blockade of estrogen signaling via long-term estrogen deprivation. Tamoxifen, a selective ER modulator blocks 17ß-estradiol binding to stop tumor growth, and aromatase inhibitors (AI) block the aromatase enzyme to prevent conversion of androgens to estrogens. Despite their effectiveness one third of the patients develop recurrences leading to disease progression and death. Tamoxifen failure is attributed to a lack of bioactivation towards its active metabolite endoxifen that is mainly mediated by the polymorphic CYP2D6 enzyme for which distinct genetically determined functional variants are present in the general population. Inter-individual differences in CYP2D6 enzyme activities are grouped into the phenotypes ultra-rapid (UM), extensive (EM), intermediate (IM) and poor (PM) metabolizers. EM patients have high levels of endoxifen and are likely to benefit whereas PM patients have low endoxifen levels and a significant risk to relapse. Therefore, CYP2D6 polymorphism and plasma endoxifen levels may serve as tamoxifen outcome predictors however findings from others do not support this view. I will discuss the controversy and suggest a way forward towards the improvement of tamoxifen outcome. With regards to AI treatment, long-term estrogen deprivation leads to the reconfiguration of survival signaling in that reconfigured tumor cells eventually become sensitive towards estrogen, a mechanism known as E2-inducible apoptosis. While this is being explored in clinical trials I will show that distinct microRNA patterns characterize AI resistance and discuss their potential as biomarkers to identify patients at risk for relapse and those susceptible to E2-inducible apoptosis towards the prevention of relapse.