S. Benzekry

Machine-learning and mechanistic modeling of primary and metastatic breast cancer growth after neoadjuvant targeted therapy

This paper develops a mathematical model and applies machine learning to predict neoadjuvant treatment response in breast cancer, finding limited predictive power of biomarkers for metastatic outcomes.

Acquired resistance to PD-L1 inhibition is associated with an enhanced type I IFN-stimulated secretory program in tumor cells

This study identifies an IFN-stimulated secretory program in PD-L1-resistant tumors that promotes immune evasion and shows that targeting this program can inhibit tumor growth.

Macro-scale models for fluid flow in tumour tissues: impact of microstructure properties

The paper develops macro-scale fluid flow models for tumour tissues, showing how microstructure properties affect vascular and interstitial flow dynamics.

Machine learning and mechanistic modeling for prediction of metastatic relapse in breast cancer

This paper develops a mechanistic model to predict metastatic relapse in breast cancer using clinicopathological data and compares its performance to existing statistical and machine learning methods.

A multi-layered systems approach for renal cell carcinoma

A multi-layered systems approach identifies prognostic and predictive biomarkers for renal cell carcinoma aggressiveness through in vivo models and integrative analysis.

Quantitative mathematical modeling of clinical brain metastasis dynamics in non-small cell lung cancer

The paper develops a mathematical model to predict brain metastasis dynamics in NSCLC using clinical data and estimates tumor age and latency phases.

A reduced Gompertz model for predicting tumor age using a population approach

The paper develops a reduced Gompertz model to predict tumor age using a population approach and Bayesian inference, showing improved accuracy and precision compared to traditional methods.

Optimal Scheduling of Bevacizumab and Pemetrexed/Cisplatin Dosing in Non-Small Cell Lung Cancer

The paper predicts optimal dosing gaps for BEV-PEM/CIS in mice and humans to maximize efficacy while minimizing toxicity.

Mathematical modeling of tumor-tumor distant interactions supports a systemic control of tumor growth

The paper uses mathematical models and experiments to show that tumor growth is suppressed when two tumors coexist, supporting a proliferation inhibition mechanism over competition or angiogenesis inhibition.