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Abstract Oncogenic drivers of progression of monoclonal gammopathy of undetermined significance (MGUS) to multiple myeloma (MM) such as c-MYC have downstream effects on intracellular metabolic pathways of clonal plasma cells (PCs). Thus, extracellular environments such as the bone marrow (BM) plasma likely have unique metabolite profiles that differ from patients with MGUS compared to MM. This study utilized an untargeted metabolite and targeted complex lipid profiling of BM plasma to identify significant differences in the relative metabolite levels between patients with MGUS and MM from an exploratory cohort. This was followed by verification of some of the metabolite differences of interest by targeted quantification of the metabolites using isotopic internal standards in the exploratory cohort as well as an independent validation cohort. Significant differences were noted in the amino acid profiles such as decreased branch chain amino acids (BCAAs) and increased catabolism of tryptophan to the active kynurenine metabolite 3-hydroxy-kynurenine between patients with MGUS and MM. A decrease in the total levels of complex lipids such as phosphatidylethanolamines (PE), lactosylceramides (LCER) and phosphatidylinositols (PI) were also detected in the BM plasma samples from MM compared to MGUS patients. Thus, metabolite and complex lipid profiling of the BM plasma identifies differences in levels of metabolites and lipids between patients with MGUS and MM. This may provide insight into the possible differences of the intracellular metabolic pathways of their clonal PCs.

Glioblastoma (GBM) is uniformly fatal with a 1-year median survival, despite best available treatment, including radiotherapy (RT). Impacts of prior RT on tumor recurrence are poorly understood but may increase tumor aggressiveness. Metabolic changes have been investigated in radiation-induced brain injury; however, the tumor-promoting effect following prior radiation is lacking. Since RT is vital to GBM management, we quantified tumor-promoting effects of prior RT on patient-derived intracranial GBM xenografts and characterized metabolic alterations associated with the protumorigenic microenvironment. Human xenografts (GBM143) were implanted into nude mice 24 hrs following 20 Gy cranial radiation vs. sham animals. Tumors in pre-radiated mice were more proliferative and more infiltrative, yielding faster mortality (p < 0.0001). Histologic evaluation of tumor associated macrophage/microglia (TAMs) revealed cells with a more fully activated ameboid morphology in pre-radiated animals. Microdialyzates from radiated brain at the margin of tumor infiltration contralateral to the site of implantation were analyzed by unsupervised liquid chromatography-mass spectrometry (LC-MS). In pre-radiated animals, metabolites known to be associated with tumor progression (i.e., modified nucleotides and polyols) were identified. Whole-tissue metabolomic analysis of pre-radiated brain microenvironment for metabolic alterations in a separate cohort of nude mice using 1H-NMR revealed a significant decrease in levels of antioxidants (glutathione (GSH) and ascorbate (ASC)), NAD+, Tricarboxylic acid cycle (TCA) intermediates, and rise in energy carriers (ATP, GTP). GSH and ASC showed highest Variable Importance on Projection prediction (VIPpred) (1.65) in Orthogonal Partial least square Discriminant Analysis (OPLS-DA); Ascorbate catabolism was identified by GC-MS. To assess longevity of radiation effects, we compared survival with implantation occurring 2 months vs. 24 hrs following radiation, finding worse survival in animals implanted at 2 months. These radiation-induced alterations are consistent with a chronic disease-like microenvironment characterized by reduced levels of antioxidants and NAD+, and elevated extracellular ATP and GTP serving as chemoattractants, promoting cell motility and vesicular secretion with decreased levels of GSH and ASC exacerbating oxidative stress. Taken together, these data suggest IR induces tumor-permissive changes in the microenvironment with metabolomic alterations that may facilitate tumor aggressiveness with important implications for recurrent glioblastoma. Harnessing these metabolomic insights may provide opportunities to attenuate RT-associated aggressiveness of recurrent GBM.

Abstract Background Links between colorectal cancer (CRC) and the gut microbiome have been established, but the specific microbial species and their role in carcinogenesis remain an active area of inquiry. Our understanding would be enhanced by better accounting for tumor subtype, microbial community interactions, metabolism, and ecology. Methods We collected paired colon tumor and normal-adjacent tissue and mucosa samples from 83 individuals who underwent partial or total colectomies for CRC. Mismatch repair (MMR) status was determined in each tumor sample and classified as either deficient MMR (dMMR) or proficient MMR (pMMR) tumor subtypes. Samples underwent 16S rRNA gene sequencing and a subset of samples from 50 individuals were submitted for targeted metabolomic analysis to quantify amino acids and short-chain fatty acids. A PERMANOVA was used to identify the biological variables that explained variance within the microbial communities. dMMR and pMMR microbial communities were then analyzed separately using a generalized linear mixed effects model that accounted for MMR status, sample location, intra-subject variability, and read depth. Genome-scale metabolic models were then used to generate microbial interaction networks for dMMR and pMMR microbial communities. We assessed global network properties as well as the metabolic influence of each microbe within the dMMR and pMMR networks. Results We demonstrate distinct roles for microbes in dMMR and pMMR CRC. Bacteroides fragilis and sulfidogenic Fusobacterium nucleatum were significantly enriched in dMMR CRC, but not pMMR CRC. These findings were further supported by metabolic modeling and metabolomics indicating suppression of B. fragilis in pMMR CRC and increased production of amino acid proxies for hydrogen sulfide in dMMR CRC. Conclusions Integrating tumor biology and microbial ecology highlighted distinct microbial, metabolic, and ecological properties unique to dMMR and pMMR CRC. This approach could critically improve our ability to define, predict, prevent, and treat colorectal cancers.

While the triple tracer isotope dilution method has enabled accurate estimation of carbohydrate turnover after a mixed meal, use of the simple carbohydrate glucose as the carbohydrate source limits its translational applicability to everyday meals that typically contain complex carbohydrates. Hence, utilizing the natural enrichment of [13C]polysaccharide in commercially available grains, we devised a novel tracer method to measure postprandial complex carbohydrate turnover and indices of insulin action and β-cell function and compared the parameters to those obtained after a simple carbohydrate containing mixed meal. We studied healthy volunteers after either rice (n = 8) or sorghum (n = 8) and glucose (n = 16) containing mixed meals and modified the triple tracer technique to calculate carbohydrate turnover. All meals were matched for calories and macronutrient composition. Rates of meal glucose appearance (2,658 ± 736 vs. 4,487 ± 909 μM·kg-1·2 h-1), endogenous glucose production (-835 ± 283 vs. -1,123 ± 323 μM·kg-1·2 h-1) and glucose disappearance (1,829 ± 807 vs. 3,606 ± 839 μM·kg-1·2 h-1) differed (P < 0.01) between complex and simple carbohydrate containing meals, respectively. Interestingly, there were significant increase in indices of insulin sensitivity (32.5 ± 3.5 vs. 25.6 ± 3.2 10-5 (dl·kg-1·min-2)/pM, P = 0.006) and β-cell responsivity (disposition index: 1,817 ± 234 vs. 1,236 ± 159 10-14 (dl·kg-1·min-2)/pM, P < 0.005) with complex than simple carbohydrate meals. We present a novel triple tracer approach to estimate postprandial turnover of complex carbohydrate containing mixed meals. We also report higher insulin sensitivity and β-cell responsivity with complex than with simple carbohydrates in mixed meals of identical calorie and macronutrient compositions in healthy adults. [ABSTRACT FROM AUTHOR]