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Deciphering the Structural Effects of Activating EGFR Somatic Mutations with Molecular Dynamics Simulation

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ESR1 activating mutations: From structure to clinical application.

Albert Grinshpun¹, Vincent Chen¹, Zachary M Sandusky²

¹Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, United States of America; Breast Oncology Center, Dana-Farber Cancer Center, Boston, MA, United States of America.

Biochimica Et Biophysica Acta. Reviews on Cancer

|November 6, 2022

Summary

This summary is machine-generated.

Activating ESR1 mutations in estrogen receptor-positive breast cancer emerge during hormone therapy. These mutations impact cancer progression and treatment response, offering potential as therapeutic targets and biomarkers.

Keywords:

Breast cancer ESR1 mutation Endocrine resistance Endocrine treatment Estrogen receptor Structure

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Published on: August 24, 2017

Area of Science:

Oncology
Molecular Biology
Endocrinology

Background:

Estrogen receptor-positive breast cancer is the most common subtype.
Estrogen receptor alpha (ER) drives tumorigenesis and progression in these cancers.
ER is a key target for endocrine therapy and a predictive biomarker.

Purpose of the Study:

To review the structure, functional consequences, and clinical implications of activating ESR1 mutations.
To discuss the evolving understanding of these mutations in advanced breast cancer.

Main Methods:

Literature review of studies on ESR1 mutations.
Analysis of functional consequences on ER transcription and tumor behavior.
Evaluation of clinical significance and biomarker potential.

Main Results:

Activating ESR1 mutations arise after prolonged endocrine therapy, particularly with aromatase inhibitors.
These mutations lead to ligand-independent ER transcriptional activity.
Mutations influence metastatic propensity and the tumor microenvironment.

Conclusions:

Activating ESR1 mutations are clinically significant in advanced ER-positive breast cancer.
These mutations represent potential therapeutic targets and dynamic biomarkers.
Further research is needed to fully understand their multimodal effects.