MyD88 provides a protective role in long-term radiation-induced lung injury

PURPOSE: The role of innate immune regulators is investigated in injury sustained from irradiation as in the clinic for cancer treatment or from a nuclear incident. The protective benefits of flagellin signaling through Toll-like receptors (TLR) in an irradiation setting warrant study of a key intracellular adaptor of TLR signaling, namely Myeloid differentiation primary response factor 88 (MyD88). The role of MyD88 in regulating innate immunity and Nuclear factor kappa-B (NF-κB)-activated responses targets this critical factor for influencing injury and recovery as well as maintaining immune homeostasis. MATERIALS AND METHODS: To examine the role of MyD88, we examined immune cells and factors during acute pneumonitic and fibrotic phases in Myd88 -deficient animals receiving thoracic gamma (γ)-irradiation. RESULTS: We found that MyD88 supports survival from radiation-induced injury through the regulation of inflammatory factors that aid in recovery from irradiation. The absence of MyD88 resulted in unresolved pulmonary infiltrate and enhanced collagen deposition plus elevated type 2 helper T cell (Th2) cytokines in long-term survivors of irradiation. CONCLUSIONS: These results based only on a gene deletion model suggest that alterations of MyD88-dependent inflammatory processes impact chronic lung injury. Therefore, MyD88 may contribute to attenuating long-term radiation-induced lung injury and protecting against fibrosis

Predicting outcomes in radiation oncology-multifactorial decision support systems

With the emergence of individualized medicine and the increasing amount and complexity of available medical data, a growing need exists for the development of clinical decision-support systems based on prediction models of treatment outcome. In radiation oncology, these models combine both predictive and prognostic data factors from clinical, imaging, molecular and other sources to achieve the highest accuracy to predict tumour response and follow-up event rates. In this Review, we provide an overview of the factors that are correlated with outcome-including survival, recurrence patterns and toxicity-in radiation oncology and discuss the methodology behind the development of prediction models, which is a multistage process. Even after initial development and clinical introduction, a truly useful predictive model will be continuously re-evaluated on different patient datasets from different regions to ensure its population-specific strength. In the future, validated decision-support systems will be fully integrated in the clinic, with data and knowledge being shared in a standardized, instant and global manner