↓ Skip to main content

Novel Biomarkers in the Continuum of Breast Cancer

Overview of attention for book
Attention for Chapter 6: Biomarkers for Predicting Response to Anti- HER2 Agents
Altmetric Badge

Citations

dimensions_citation
25 Dimensions

Readers on

mendeley
26 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Chapter title
Biomarkers for Predicting Response to Anti- HER2 Agents
Chapter number 6
Book title
Novel Biomarkers in the Continuum of Breast Cancer
Published in
Advances in experimental medicine and biology, January 2016
DOI 10.1007/978-3-319-22909-6_6
Pubmed ID
Book ISBNs
978-3-31-922908-9, 978-3-31-922909-6
Authors

Vinay Varadan, Maria Sandoval, Lyndsay N. Harris

Abstract

The HER2 receptor is amplified or overexpressed in approximately 20 % of all breast cancers, but despite significant efforts of the clinical research community and a growing number of anti-HER2 agents, a significant number of patients with HER2-positive breast cancer either progress or suffer disease relapse within 5-10 years. The development of robust biomarkers that predict response to anti-HER2 agents is therefore an important clinical need to prevent overtreatment and to enable earlier assignment of patients to more optimal therapies. Here we review some of the recent advances in the field by focusing on pathways mediating resistance to anti-HER2 therapies, and the role of the immune system and cancer stem cells in therapy response. We also review preoperative treatment strategies and research paradigms that show promise in identifying novel biomarkers of response while also enabling the delineation of the mechanisms underlying clinical benefit from anti-HER2 therapies.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 26 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 19%
Student > Master 4 15%
Student > Bachelor 3 12%
Student > Doctoral Student 2 8%
Other 2 8%
Other 7 27%
Unknown 3 12%
Readers by discipline Count As %
Medicine and Dentistry 8 31%
Biochemistry, Genetics and Molecular Biology 5 19%
Agricultural and Biological Sciences 3 12%
Computer Science 2 8%
Economics, Econometrics and Finance 1 4%
Other 4 15%
Unknown 3 12%