Hunt for the tipping point during endocrine resistance process in breast cancer by dynamic network biomarkers

Rui Liu1, Jinzeng Wang2,3, Masao Ukai4,5

  • 1School of Mathematics, South China University of Science and Technology, Guangzhou, China.

Insights

This study introduces a dynamic network biomarker (DNB) method to identify the tipping point for endocrine resistance in cancer. DNB genes were found to be crucial in developing drug resistance and predicting poor patient survival.

Area of Science:

  • Oncology
  • Systems Biology
  • Genomics

Background:

  • Acquired drug resistance is a primary cause of cancer therapy failure.
  • Identifying the onset and molecular drivers of endocrine resistance remains challenging.

Purpose of the Study:

  • To apply the dynamic network biomarker (DNB) method to quantitatively identify the tipping point of endocrine resistance.
  • To detect key molecules and genes associated with the development of drug resistance.

Main Methods:

  • Analysis of time-course mRNA sequencing data from tamoxifen-treated MCF-7 cells.
  • Application of the dynamic network biomarker (DNB) method to identify tipping points and key genes.
  • Survival analysis using clinical datasets to validate DNB gene associations.

Main Results:

  • Identified the tipping point of endocrine resistance and associated leading molecules in ER-positive breast cancer cells.
  • Revealed an interplay between gene mutations and DNB genes in driving transcriptional changes and resistance.
  • Validated DNB genes as predictors of poor survival in breast cancer patients.

Conclusions:

  • The DNB method can detect pre-resistance states and early signs of endocrine resistance.
  • This predictive approach may improve treatment scheduling for drug-resistant cancers.
  • Understanding DNB genes offers insights into mechanisms of acquired drug resistance.

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