SYNTHESIS-Breast: A prospective early-phase trial of a genetic-interaction- focused computational algorithm in

Aanika B Warner1, Britanny B Solarz1, Miroslava Belyov1

  • 1National Cancer Institute.

Research Square
|June 5, 2026
PubMed

Insights

This study explores off-label therapies for metastatic breast cancer using the ENLIGHT computational algorithm. It aims to generate data for future trials by identifying gene-expression-based treatments.

Area of Science:

  • Oncology
  • Computational Biology
  • Genomics

Background:

  • Metastatic breast cancer presents challenges for treatment selection.
  • Identifying novel, off-label therapeutic strategies is crucial.
  • Computational algorithms offer potential for personalized treatment discovery.

Purpose of the Study:

  • To adapt early-phase trial designs for identifying off-label therapies in metastatic breast cancer.
  • To utilize the ENLIGHT computational algorithm for treatment selection based on gene expression.
  • To generate preliminary data to inform future prospective trials.

Main Methods:

  • An exploratory trial design adapted for early-phase research.
  • Application of the ENLIGHT algorithm, which selects treatments via gene-expression-based synthetic lethality/rescue.
  • Inclusion of algorithm-specific adaptations such as a molecular tumor board and layered Simon two-stage designs.

Main Results:

  • The study is designed to identify potential off-label therapies.
  • Preliminary data will be generated for future clinical trials.
  • The ENLIGHT algorithm's application in a clinical trial setting will be evaluated.

Conclusions:

  • The SYNTHESIS-Breast trial will guide the application of the ENLIGHT algorithm.
  • This approach will facilitate future prospective trials for algorithm-driven cancer therapies.
  • The study contributes to advancing personalized medicine in metastatic breast cancer.

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