In silico mouse study identifies tumor growth kinetics as biomarkers for the outcome of anti-angiogenic treatment

Angiogenesis is a crucial step in tumor progression, as this process allows tumors to recruit new blood vessels and obtain oxygen and nutrients to sustain growth. Therefore, inhibiting angiogenesis remains a viable strategy for cancer therapy. However, anti-angiogenic therapy has not proved to be effective in reducing tumor growth across a wide range of tumors, and no reliable predictive biomarkers have been found to determine the efficacy of anti-angiogenic treatment. Using our previously established computational model of tumor-bearing mice, we sought to determine whether tumor growth kinetic parameters could be used to predict the outcome of anti-angiogenic treatment. A model trained with datasets from six in vivo mice studies was used to generate a randomized in silico tumor-bearing mouse population. We analyzed tumor growth in untreated mice (control) and mice treated with an anti-angiogenic agent and determined the Kaplan-Meier survival estimates based on simulated tumor volume data. We found that the ratio between two kinetic parameters, k0 and k1, which characterize the tumors exponential and linear growth rates, as well as k1 alone, can be used as prognostic biomarkers of population survival outcome. Our work demonstrates a robust, quantitative approach for identifying tumor growth kinetic parameters as prognostic biomarkers and serves as a template that can be used to identify other biomarkers for anti-angiogenic treatment.