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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.
List of contents
1 Clinical Use of Aromatase Inhibitors in Breast Cancer: History and Present.-2 Structure, Regulation and Polymorphisms of the Aromatase Gene .-3 Structure, Function and Inhibition of Aromatase.-4 In Vivo Models of AI Resistance.-5 Ineffective inhibition of aromatase: a cause for AI resistance?.-6 Understanding the New Biology of Estrogen-Induced Apoptosis and its Application in Patient Care.-7 Ligand-independent signalling through estrogen receptor pathways in breast cancer.-8 Chromatin and epigenetic determinants of resistance to aromatase inhibitors.-9 Aromatase Inhibitor Resistance via Non-endocrine Signalling Pathways.-10 Prediction of Response to Aromatase Inhibitors in Breast Cancer.-11 Clinical Trials Combining Aromatase Inhibitors with Other Targeted Treatments.-12 Aromatase Inhibitors Beyond Breast Cancer: Endometrium vs Breast Puzzle and Other Issues.
About the author
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.
Summary
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.
