Dynamic transcription factor activity and networks during ErbB2 breast oncogenesis and targeted therapy

Area of Science:

• Molecular Biology
• Systems Biology
• Cancer Research

Background:

• Tissue development and disease progression involve dynamic regulatory factors over time.
• Existing omics approaches are limited by incomplete biological databases for identifying cellular processes.
• Understanding dynamic transcriptional regulation is crucial for dissecting complex biological systems.

Purpose of the Study:

• To present TRACER (Transcriptional Activity CEll aRrays) for simultaneous quantification of dynamic transcription factor activity.
• To introduce NTRACER, a computational algorithm for establishing dynamic regulatory networks based on TF activity.
• To identify key regulatory hubs in normal and abnormal tissue growth and elucidate therapeutic mechanisms.

Main Methods:

• TRACER was used to quantify the dynamic activity of numerous transcription factors (TFs) simultaneously in 3D.
• NTRACER algorithm facilitated cellular rewiring to establish dynamic regulatory networks based on TF reporter construct activity.
• Identified TF hubs and therapeutic mechanisms were validated in human breast cancer models.

Main Results:

• Identified ELK-1 and E2F1 as major regulatory hubs associated with normal and abnormal tissue growth, respectively.
• Elucidated the mechanism of action for the therapeutic lapatinib through the transcription factor GATA-1.
• Findings were confirmed in human ErbB2-positive breast cancer patients and cell lines with varying lapatinib sensitivity.

Conclusions:

• TRACER and NTRACER provide a powerful approach for dynamic analysis of transcription factor networks.
• This methodology enables the identification of critical regulators in tissue development and disease.
• The study offers insights into therapeutic strategies for ErbB2-positive breast cancer.