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  • © 2015

Resistance to Aromatase Inhibitors in Breast Cancer

Editors:

  • Brings together the current knowledge of molecular and translational aspects of AIs resistance in breast cancer
  • Provides mechanisms of physiological resistance and potential biomarkers that recognize or predict mechanisms of resistance
  • Explores acquired, adjuvant, pre-operative, and metastatic resistance
  • Includes supplementary material: sn.pub/extras

Part of the book series: Resistance to Targeted Anti-Cancer Therapeutics (RTACT, volume 8)

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Table of contents (12 chapters)

  1. Front Matter

    Pages i-xvi
  2. Structure, Function and Inhibition of Aromatase

    • Debashis Ghosh, Jessica Lo, Chinaza Egbuta
    Pages 33-61
  3. In Vivo Models of AI Resistance

    • Gauri Sabnis, Angela Brodie
    Pages 63-86
  4. Chromatin and Epigenetic Determinants of Resistance to Aromatase Inhibitors

    • Raffaella Maria Gadaleta, Luca Magnani
    Pages 145-168
  5. Aromatase Inhibitor Resistance via Non-endocrine Signalling Pathways

    • Abdul Aziz Bin Aiderus, Anita K. Dunbier
    Pages 169-190
  6. Prediction of Response to Aromatase Inhibitors in Breast Cancer

    • Alexey A. Larionov, William R. Miller
    Pages 191-228
  7. Back Matter

    Pages 287-288

About this book

Aromatase Inhibitors (AIs) treat postmenopausal estrogen receptor positive tumours, which constitute the majority of breast cancer patients. This comprehensive volume brings together the current knowledge from different relevant areas, including molecular mechanisms and translational aspects of drug resistance in AIs. Topics covered include research, experimental , and clinical data specifically focused on AI resistance in breast cancer. The volume will include three sections. The first section covers general knowledge about aromatase inhibitors, including regulation of aromatase genes, and structure and function of aromatase protein. The second section provides the detailed mechanisms of resistance to AIs, while the third section explores prediction of resistance and potential strategies to overcome resistance. Breast cancer is the most common female cancer and AIs significantly improve treatments outcomes compatibly to previously used endocrine treatments. However 10-15% of post-operative patients develop a relapse during adjuvant treatment with AIs; about 25-50% of the patients do not respond to AIs in neo-adjuvant or metastatic setting, and the majority of metastatic patients who initially respond develop resistance within 3 years. There is an important need to understand these mechanisms of resistance in order to develop methods of preventing or overcoming the resistance to AIs, which will ensure a more successful outcome in treating breast cancer.

Editors and Affiliations

  • Academic Laboratory of Medical Genetics, School of Clinical Medicine, Cancer Research UK Cambridge Institute, Statistics and Computational Biology Laboratory & University of Cambridge, Cambridge, United Kingdom

    Alexey Larionov

About the editor

Alexey Larionov, Ph.D. is a researcher at the Academic Laboratory of Medical Genetics and Statistics and Computational Biology Lab at the University of Cambridge. Dr Larionov is an expert in endocrine resistance in breast cancer, as well as whole exome sequencing data analysis. Dr. Larionov has received over 1019 citations.

Bibliographic Information

Buy it now

Buying options

eBook USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access