The Technology
Immunotherapy has revolutionized cancer treatment, but patient response remains unpredictable, with success rates varying significantly across different cancer types. This technology introduces a metabolic biomarker platform derived from single-cell RNA sequencing of tumor-infiltrating immune cells. By analyzing over one million immune cells across diverse cancers, a unique metabolic gene signature was identified, accurately distinguishing responders from non-responders to immune checkpoint inhibitors (AUC = 0.8–0.92). This platform not only predicts patient response but also provides valuable insights into immune cell metabolic states associated with treatment resistance, enabling more informed clinical decisions and better patient stratification.
Advantages
- Accurate Prediction: High accuracy across melanoma, lung, and breast cancers.
- Broad Applicability: Effective across various cancer types and immune therapies.
- Actionable Insights: Identifies metabolic vulnerabilities linked to therapy resistance.
- Personalized Therapy: Facilitates optimized treatment plans for individual patients.
- Diagnostic Integration: Potential for companion diagnostic tools to guide treatment selection.
Applications and Opportunities
- Clinical Decision Support: Integration into clinical workflows to guide immunotherapy decisions.
- Patient Stratification: Identifying responders and non-responders for checkpoint inhibitor therapies.
- Drug Development: Development of therapies targeting specific metabolic pathways associated with resistance.
- Companion Diagnostics: Commercialization as a diagnostic assay for precision oncology.
Business Development Contacts