Biology-Informed Predictive Modeling and Resistance Monitoring in Trastuzumab Deruxtecan–Treated Metastatic Breast Cancer

**Background
**The antibody drug conjugate (ADC), Trastuzumab deruxtecan (T-DXd), produces meaningful responses in metastatic breast cancer (mBC), yet current biomarkers inadequately identify likely responders or elucidate resistance mechanisms. We developed a biology- informed survival model to predict T-DXd benefit in real-world data, assess treatment specificity, and characterize resistance evolution at time of progression.

Methods
We analyzed RNA-seq and clinical outcomes from 150 de-identified T-DXd–treated mBC patients in the Tempus real-world multimodal database. Baseline expression profiles were embedded into biology-structured biomodules using a large molecular foundation model trained on over 1-million transcriptomes, capturing processes relevant to ADC activity: DNA damage response (DDR), intracellular trafficking, cellular stress adaptation, and tumor microenvironment signaling. These biomodules informed a survival model trained to predict T-DXd–specific clinical benefit. Predictive specificity was evaluated in a matched cohort of T-DXd–eligible mBC patients treated with taxane-based chemotherapy and HER2-targeting therapy. Longitudinal tumor profiling from 15 patients with progressive disease were analyzed to monitor resistance evolution.

Results
The survival model predicted and identified biologically distinct benefit groups within the T-DXd cohort, with minimal separation observed in a control standard-of-care cohort, confirming treatment-specific predictive value (HR 2.22 [95% CI 1.14–4.35], p = 0.017). Predicted-benefit patients had longer rwTTNT (median = 345 vs 245 days), and no prognostic signal appeared in control cohorts (C-index = 0.51), suggesting predictive specificity. Longitudinal analysis of progressed patients revealed reproducible biological shifts at progression, including attenuation of programs associated with effective ADC engagement and upregulation of adaptive stress-response pathways. These molecular transitions correlated with clinical deterioration and earlier transition to subsequent therapy.

Conclusions
This study delineates the biology associated with durable T-DXd benefit and captures resistance evolution at progression in real-world patients. These findings highlight opportunities to refine patient selection and identify therapeutically actionable biology driving acquired resistance to T-DXd in the mBC setting.