Radiation dose dependent positive correlations between plasma and liver metabolites for whole liver irradiation for the combined radiation levels of 0, 10 or 50 Gy.

<p>The Spearman’s correlation coefficient, is defined in Methods.</p><p>Radiation dose dependent positive correlations between plasma and liver metabolites for whole liver irradiation for the combined radiation levels of 0, 10 or 50 Gy.</p

Plasma metabolites key to group separation predicted by Random Forest classification.

<p>The top 30 plasma metabolites important for increasing class separation as determined by the Random Forest approach. Bradykinin was seen as most important for class separation, however, smaller peptides also showed class discrimination, such as L-aspartyl-L-phenylalanine, and alanyl-alanine. Energy metabolism, as reflected by the presence of riboflavin as a biomarker, was indicated. Metabolites suggesting multiple organ interactions, i.e. kidney/liver/GI tract/microbiome were indicated (see text).</p

Purine Metabolism changes in response to liver irradiation.

<p>A general increase in purine metabolism intermediates may suggest increased breakdown of nucleotides in response to radiation perhaps as a mechanism to support repair after cell injury. Metabolites highlighted in green were decreased after liver irradiation relative to control while metabolites highlighted in red were increased.</p

Liver metabolites key to group separation predicted by PLS-DA assessed using variable influence on projections (VIPs).

<p>Liver PLS-DA VIPs identified potential biomarkers and exhibited strong overlap with metabolites important for classification using the Random Forest approach. VIP values greater than 1 delineated metabolites most important for cluster classification. An asterisk indicates metabolites in the purine synthesis pathway while a 'P' indicates the pentose phosphate pathway. Both purines and pentose phosphate metabolites were highly important for liver group classification, reinforcing Random Forest findings, and might be determinants of the liver radiation response.</p

PLS-DA classifier correctly classifies 100% of liver samples and 86% of plasma samples.

<p>PLS-DA classifier correctly classifies 100% of liver samples and 86% of plasma samples.</p

Decision Tree for metabolite validation.

<p>The decision tree approach that was used to confirm important metabolite signatures in the WLI experiments is illustrated. Consistently altered metabolites between groups were determined first by comparison of the 50 Gy vs. 0 Gy data sets, then by validation of the metabolite in the 50 Gy vs untreated data sets. If the metabolite was still unconfirmed, it was tested as being significant in the 10Gy vs. 0 Gy plasma or liver data set, or the 10 Gy vs. untreated data sets.</p

Radiation dose dependent positive correlations between plasma and liver metabolites for whole liver irradiation for the combined radiation levels of 0, 10 or 50 Gy.

<p>The Spearman’s correlation coefficient, is defined in Methods.</p><p>Radiation dose dependent positive correlations between plasma and liver metabolites for whole liver irradiation for the combined radiation levels of 0, 10 or 50 Gy.</p

Integrative Metabolic Signatures for Hepatic Radiation Injury

<div><p>Background</p><p>Radiation-induced liver disease (RILD) is a dose-limiting factor in curative radiation therapy (RT) for liver cancers, making early detection of radiation-associated liver injury absolutely essential for medical intervention. A metabolomic approach was used to determine metabolic signatures that could serve as biomarkers for early detection of RILD in mice.</p><p>Methods</p><p>Anesthetized C57BL/6 mice received 0, 10 or 50 Gy Whole Liver Irradiation (WLI) and were contrasted to mice, which received 10 Gy whole body irradiation (WBI). Liver and plasma samples were collected at 24 hours after irradiation. The samples were processed using Gas Chromatography/Mass Spectrometry and Liquid Chromatography/Mass Spectrometry.</p><p>Results</p><p>Twenty four hours after WLI, 407 metabolites were detected in liver samples while 347 metabolites were detected in plasma. Plasma metabolites associated with 50 Gy WLI included several amino acids, purine and pyrimidine metabolites, microbial metabolites, and most prominently bradykinin and 3-indoxyl-sulfate. Liver metabolites associated with 50 Gy WLI included pentose phosphate, purine, and pyrimidine metabolites in liver. Plasma biomarkers in common between WLI and WBI were enriched in microbial metabolites such as 3 indoxyl sulfate, indole-3-lactic acid, phenyllactic acid, pipecolic acid, hippuric acid, and markers of DNA damage such as 2-deoxyuridine. Metabolites associated with tryptophan and indoles may reflect radiation-induced gut microbiome effects. Predominant liver biomarkers in common between WBI and WLI were amino acids, sugars, TCA metabolites (fumarate), fatty acids (lineolate, n-hexadecanoic acid) and DNA damage markers (uridine).</p><p>Conclusions </p><p>We identified a set of metabolomic markers that may prove useful as plasma biomarkers of RILD and WBI. Pathway analysis also suggested that the unique metabolic changes observed after liver irradiation was an integrative response of the intestine, liver and kidney.</p></div

Pentose Phosphate Pathway changes in response to liver irradiation.

<p>The pentose phosphate pathway generates NADPH, ribose 5-phosphate, and intermediates of the glycolytic pathway. The NADPH is utilized for reductive pathways, such as fatty acid biosynthesis and the glutathione defense system against injury by reactive oxygen species. Ribose 5-phosphate provides the sugar for nucleotide synthesis. Increased levels of pentose phosphate intermediates may indicate altered glucose and/or nucleotide metabolism.</p

Plasma metabolites key to group separation predicted by PLS-DA assessed using variable influence on projections (VIPs).

<p>The most significant known hits for plasma VIPs included: bradykinin, niacinamide, riobflavine, 3-indoxyl-sulfate, and 3-hydroxycinnamic acid. Levels of plasma bradykinin increased more than 25-fold following high dose irradiation. Based on its vasodilator effects, bradykinin may help increase permeability in vasculature damaged by radiation. As in the previous figures, VIP values greater than 1 delineated metabolites most important for cluster classification.</p