Developing transcriptomic biomarkers for TAVO412 utilizing next generation sequencing analyses of preclinical tumor...

Area of Science:

• Oncology
• Molecular Biology
• Pharmacology

Background:

• TAVO412 is a novel multi-specific antibody targeting EGFR, c-Met, and VEGF-A for solid tumor treatment.
• It inhibits tumor growth via multiple mechanisms, including blocking key signaling pathways and angiogenesis.
• TAVO412 has shown significant in vivo efficacy in diverse cancer models.

Purpose of the Study:

• To identify transcriptomic biomarkers for predicting anti-tumor response to TAVO412.
• To develop a predictive model for patient selection in precision medicine.
• To validate the biomarker's accuracy in preclinical cancer models.

Main Methods:

• Gene expression profiling of preclinical cancer models (CDX and PDX) was performed.
• A 21-gene signature was identified and correlated with TAVO412 efficacy.
• A Linear Prediction Score (LPS) model was developed to predict treatment response.

Main Results:

• The 21-gene biomarker accurately predicted TAVO412 efficacy in cell-derived xenograft (CDX) models with 78% accuracy.
• The predictive model demonstrated comparable accuracy when validated in patient-derived xenograft (PDX) models.
• The identified biomarker effectively distinguished between responders and non-responders.

Conclusions:

• A predictive transcriptomic biomarker for TAVO412 has been identified using next-generation sequencing.
• This biomarker facilitates precision medicine by optimizing patient selection for TAVO412 treatment.
• Leveraging preclinical data is crucial for developing effective predictive biomarkers.