Estrogen Receptor-Low Positive (ER-Low) Breast Cancer: A Unique Clinical and Pathological Entity

Area of Science:

• Oncology
• Pathology
• Biomedical Engineering

Background:

• ER-low breast cancer (1-9% ER expression) is a distinct subtype.
• It exhibits molecular and clinical similarities to triple-negative breast cancer.
• Accurate ER assessment is challenging due to methodological variability.

Purpose of the Study:

• To review current insights into ER-low breast cancer.
• To discuss evolving therapeutic strategies.
• To explore the role of AI in managing this subtype.

Main Methods:

• Literature review of pathological and clinical data.
• Analysis of treatment responses, including chemotherapy and chemo-immunotherapy.
• Evaluation of emerging artificial intelligence tools for ER quantification.

Main Results:

• ER-low tumors demonstrate sensitivity to chemotherapy and chemo-immunotherapy.
• These tumors share aggressive behavior and molecular signatures with triple-negative breast cancer.
• AI tools, including digital pathology and deep learning, show potential for improved ER assessment and patient stratification.

Conclusions:

• ER-low breast cancer requires tailored management strategies.
• Chemotherapy and chemo-immunotherapy are promising treatment options.
• AI-driven approaches offer future potential for personalized treatment optimization.