A systems approach to dissect actionable heterotypic interactions of lung cancer cells with their microenvironment

A significant advance in oncology is the advent of immunotherapies that target repressive interactions between tumor cells and T cells. These immunotherapies elicit sometimes dramatic as well as long-lasting tumor control. Similarly, targeting specific signaling pathways in cancer has become clinical routine in the past decade. Smoking-associated chronic inflammation and obstructive lung disease are risk factors for the development of lung cancer; thus, both are relevant comorbidities. They also often limit the therapeutic options for cancer patients due to high-er toxicity. However, if causally linked, in a holistic view, these comorbidities may also offer unexpected routes for mechanistically targeted therapies as these tumors may not only be adapted, but also addicted to certain aspects of the altered inflammatory states. Furthermore, it has long been known that metabolic disorders (e.g., adipositas) are associated with inflammatory processes in affected tissues, which in turn can fuel the process of malignant transformation.

In our consortium experts in the fields of inflammation, cancer genetics, metabolism, genetically engineered mouse models and computational biology work together to systematically characterize the relationship between cancer genome alterations, metabolic state and chronic inflammatory processes in order to derive holistic quantitative models of tumor initiation and progression. These insights will serve to derive novel strategies for a combined therapeutic approach to enhance tumor control in lung cancer.

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