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Transcriptomic Maps of Colorectal Liver Metastasis: Machine Learning of Gene Activation Patterns and Epigenetic Trajectories in Support of Precision Medicine
Liver metastasis is a significant factor contributing to mortality associated with colorectal cancer. Establishing the biological mechanisms of metastasis is crucial for refining diagnostics and identifying therapeutic windows for interventions. Currently, little is known of the processes that govern the development of liver metastases, the role of the tumor microenvironment, the role of epigenetics, and potential treatment-induced shaping effects. Machine learning-based bioinformatics has provided an important methodical option to decipher fine-granular details of the transcriptomic landscape of tumor heterogeneity and the underlying molecular mechanisms. Our molecular portrayal method has potential implications for treatment decisions, which may require personalized diagnostics.