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Updated: Dec 13, 2025

Generation of Heterogeneous Drug Gradients Across Cancer Populations on a Microfluidic Evolution Accelerator for Real-Time Observation
Published on: September 19, 2019
Predicting Cancer Evolution Using Cell State Dynamics
1Centre for Molecular Medicine Norway, University of Oslo, Oslo, Norway. marieke.kuijjer@ncmm.uio.no.
Abstract:
One of the biggest challenges in cancer is predicting its initiation and course of progression. In this issue of Cancer Research, Rockne and colleagues use state transition theory to predict how peripheral mononuclear blood cells in mice transition from a healthy state to acute myeloid leukemia. They found that critical transcriptomic perturbations could predict initiation and progression of the disease. This is an important step toward accurately predicting cancer evolution, which may eventually facilitate early diagnosis of cancer and disease recurrence, and which could potentially inform on timing of therapeutic interventions.See related article by Rockne et al., 3157.
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