Lipidomic dysregulation within the lung parenchyma following whole-thorax lung irradiation: Markers of injury, inflammation and fibrosis detected by MALDI-MSI

Abstract

Radiation-induced lung injury (RILI) is a delayed effect of acute radiation exposure that can limit curative cancer treatment therapies and cause lethality following high-dose whole-thorax lung irradiation (WTLI). To date, the exact mechanisms of injury development following insult remain ill-defined and there are no FDA approved pharmaceutical agents or medical countermeasures. Traditionally, RILI development is considered as three phases, the clinically latent period, the intermediate acute pneumonitis phase and the later fibrotic stage. Utilizing matrix-assisted laser desorption ionization mass spectrometry imaging, we identified a number of lipids that were reflective of disease state or injury. Lipids play central roles in metabolism and cell signaling, and thus reflect the phenotype of the tissue environment, making these molecules pivotal biomarkers in many disease processes. We detected decreases in specific surfactant lipids irrespective of the different pathologies that presented within each sample at 180 days post whole-thorax lung irradiation. We also detected regional increases in ether-linked phospholipids that are the precursors of PAF, and global decreases in lipids that were reflective of severe fibrosis. Taken together our results provide panels of lipids that can differentiate between naïve and irradiated samples, as well as providing potential markers of inflammation and fibrosis.

Oxidized Phospholipids in Healthy and Diseased Lung Endothelium

“…By employing hydrophilic liquid chromatography coupled to MS, Colombo et al showed that phospholipidomic profile significantly varies among hydrogen peroxide, glucose, or hydroxynonenal-induced stress conditions in bovine aortic EC [140]. Lipidomic analysis can be utilized to determine the pathologic states and thus can be used as a biomarker platform, as exemplified in a study showing the disease-specific differential lipid profiles [141]. Similarly, oxidative phospholipidomics analysis of lipids have identified oxygenated cardiolipins and phosphatidylethanolamines as predictive biomarkers of apoptotic and ferroptic cell death, respectively [142].…”

Acute Proteomic Changes in the Lung After WTLI in a Mouse Model: Identification of Potential Initiating Events for Delayed Effects of Acute Radiation Exposure

“…This type of proteomic approach also provides complementary information from a systems biology perspective to our metabolomic efforts to characterize radiation-induced lung injury where changes in metabolites are often the result of alterations in protein function or abundance (Jones et al 2014). Previously, the Medical Countermeasures Against Radiological Threat (MCART) has used discovery and targeted metabolomics towards identifying potential biomarkers of radiation-induced lung injury, used mass spectrometry imaging to both identify and localize biomarker candidates and medical countermeasures in the non-human primate lung, and identified biomarker candidates with pharmacodynamic utility (Jones et al 2014;Carter et al 2015;Carter et al 2016;Carter et al 2017;Jones et al 2017a;Jones et al 2017b). This current study sought to use an untargeted systems biology approach to identify acute molecular events that could potentially be initiating events for radiation-induced lung injury.…”

Characterizing the Natural History of Acute Radiation Syndrome of the Gastrointestinal Tract: Combining High Mass and Spatial Resolution Using MALDI-FTICR-MSI

“…The MCART consortium has developed and characterized animal models that define the incidence, latency, severity and onset of GI-ARS, H-ARS, and MOI involving the kidney, lung, and heart (Farese et al 2012;Jackson et al 2012;Plett et al 2012;Garofalo et al 2014;de Faria et al 2015;Farese et al 2015;Medhora et al 2015;Zhang et al 2015;Cohen et al 2017). Histological, clinical, and analytical techniques were used to interrogate mechanisms of action (MoA) and identify biomarkers of radiation injury following all-cause mortality (Booth et al 2012a;Chua et al 2012;MacVittie et al 2012a;Jones et al 2014a;Jones et al 2014b;Carter et al 2015;Farese et al 2015;Jones et al 2015;Zhang et al 2015;Carter et al 2016;Carter et al 2017;Cohen et al 2017;Jones et al 2017). While these studies have provided vital mechanistic 'pieces of the puzzle' and identified panels of biomarkers that can be used to assess injury and efficacy of a MCM, they cannot inform on the natural history of injury development.…”