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Unveiling the Tumor Microenvironment by Machine Learning to Develop New Immunotherapeutic Strategies (Volume I.B)
The tumor microenvironment (TME) plays a critical role in tumor proliferation, progression, and therapeutic responses. TME is a complex network of cancer cells, stromal cells, and, most importantly, infiltrating immune cells. Cancer cells regulate numerous biological functions through direct or indirect interaction with TME components. Emerging evidence suggests that TME crucially influences the response to both chemotherapy and immunotherapy. As scientific research has entered the big data era with the fast development of high-throughput sequencing technologies, machine learning has been gradually widely applied to extract important knowledge from big data bioinformatics. Thus, characterizing the TME landscape in cancer and identifying different immune-related TME phenotypes using machine learning-based bioinformatics analyses, in vitro experiments, and in vivo experiments are of great interest and significance.
Pharmacogenomics and Personalized Medicine
Pharmacogenomics is one of the emerging approaches to precision medicine, tailoring drug selection and dosing to the patient’s genetic features. In recent years, several pharmacogenetic guidelines have been published by international scientific consortia, but the uptake in clinical practice is still poor. Many coordinated international efforts are ongoing in order to overcome the existing barriers to pharmacogenomic implementation. On the other hand, existing validated pharmacogenomic markers can explain only a minor part of the observed clinical variability in the therapeutic outcome. New investigational approaches are warranted, including a study of the pharmacogenomic role of the immune...
