L. Rocha, H.; Aguilar, B.; Getz, M.; Shmulevich, I.; Macklin, P.

Metastasis is the leading cause of death in patients with cancer. Among the targets of this spread, the lung is one of the most frequent targets of metastasis. In the scientific community, many studies have been developed to study the process of cancer dissemination in the lung. We investigated this process by creating a multiscale mathematical model to study the interactions between the immune system and the progression of micrometastases in the lung. We analyzed the parameter space of the model using high-throughput computing resources to generate over 100,000 virtual patient trajectories. We demonstrated that the model could recapitulate a wide variety of virtual patient trajectories, uncontrolled growth, and partial and complete immune response to tumor growth. We classified the patients and identified key patient parameters that regulate immunosurveillance. We highlight the lessons derived from this analysis and outline the primary challenges in building cancer patient digital twins. These digital twins would enable clinicians to systematically dissect the complexity of cancer in each individual patient, simulate treatment outcomes, and ultimately select the most suitable treatment.