Metabolomics analysis reveals novel serum metabolite alterations in cancer cachexia.

Background: Cachexia is a body wasting syndrome that significantly affects well-being and prognosis of cancer patients, without effective treatment. Serum metabolites take part in pathophysiological processes of cancer cachexia, but apart from altered levels of select serum metabolites, little is known on the global changes of the overall serum metabolome, which represents a functional readout of the whole-body metabolic state. Here, we aimed to comprehensively characterize serum metabolite alterations and analyze associated pathways in cachectic cancer patients to gain new insights that could help instruct strategies for novel interventions of greater clinical benefit. Methods: Serum was sampled from 120 metastatic cancer patients (stage UICC IV). Patients were grouped as cachectic or non-cachectic according to the criteria for cancer cachexia agreed upon international consensus (main criterium: weight loss adjusted to body mass index). Samples were pooled by cachexia phenotype and assayed using non-targeted gas chromatography-mass spectrometry (GC-MS). Normalized metabolite levels were compared using t-test (p < 0.05, adjusted for false discovery rate) and partial least squares discriminant analysis (PLS-DA). Machine-learning models were applied to identify metabolite signatures for separating cachexia states. Significant metabolites underwent MetaboAnalyst 5.0 pathway analysis. Results: Comparative analyses included 78 cachectic and 42 non-cachectic patients. Cachectic patients exhibited 19 annotable, significantly elevated (including glucose and fructose) or decreased (mostly amino acids) metabolites associating with aminoacyl-tRNA, glutathione and amino acid metabolism pathways. PLS-DA showed distinct clusters (accuracy: 85.6%), and machine-learning models identified metabolic signatures for separating cachectic states (accuracy: 83.2%; area under ROC: 88.0%). We newly identified altered blood levels of erythronic acid and glucuronic acid in human cancer cachexia, potentially linked to pentose-phosphate and detoxification pathways. Conclusion: We found both known and yet unknown serum metabolite and metabolic pathway alterations in cachectic cancer patients that collectively support a whole-body metabolic state with impaired detoxification capability, altered glucose and fructose metabolism, and substrate supply for increased and/or distinct metabolic needs of cachexia-associated tumors. These findings together imply vulnerabilities, dependencies and targets for novel interventions that have potential to make a significant impact on future research in an important field of cancer patient care.

Effects of Repeated Freeze and Thaw Cycles on the Genome-Wide DNA Methylation Profile of Isolated Genomic DNA.

The characterization of DNA methylation patterns to identify epigenetic markers for complex human diseases is an important and rapidly evolving part in biomedical research. DNA samples collected and stored in clinical biobanks over the past years are an important source for future epigenetic studies. Isolated gDNA is considered stable when stored at low temperatures for several years. However, the effect of multiple use and the associated repeated thawing of long-term stored DNA samples on DNA methylation patterns has not yet been investigated. In this study, we examined the influence of up to 10 freeze and thaw cycles on global DNA methylation by comparing genome-wide methylation profiles. DNA samples from 19 healthy volunteers were either frozen at -80°C or subjected to up to 10 freeze and thaw cycles. Genome-wide DNA methylation was analyzed after 0, 1, 3, 5, or 10 thaw cycles using the Illumina Infinium MethylationEPIC BeadChip. Evaluation of the global DNA methylation profile by beta-value density plots and multidimensional scaling plots revealed an expected clear participant-dependent variability, but a very low variability depending on the freeze and thaw cycles. In accordance, no significant difference in any of the methylated cytosine/guanine sites studied could be detected in the performed statistical analyses. Our results suggest that long-term frozen DNA samples are still suitable for epigenetic studies after multiple thaw cycles.

Transcriptomic landscapes of effective and failed liver regeneration in humans.

Background & Aims: Although extensive experimental evidence on the process of liver regeneration exists, in humans, validation is largely missing. However, liver regeneration is critically affected by underlying liver disease. Within this project, we aimed to systematically assess early transcriptional changes during liver regeneration in humans and further assess how these processes differ in people with dysfunctional liver regeneration. Methods: Blood samples of 154 patients and intraoperative tissue samples of 46 patients undergoing liver resection were collected and classified with regard to dysfunctional postoperative liver regeneration. Of those, a matched cohort of 21 patients were used for RNA sequencing. Samples were assessed for circulating cytokines, gene expression dynamics, intrahepatic neutrophil accumulation, and spatial transcriptomics. Results: Individuals with dysfunctional liver regeneration demonstrated an aggravated transcriptional inflammatory response with higher intracellular adhesion molecule-1 induction. Increased induction of this critical leukocyte adhesion molecule was associated with increased intrahepatic neutrophil accumulation and activation upon induction of liver regeneration in individuals with dysfunctional liver regeneration. Comparing baseline gene expression profiles in individuals with and without dysfunctional liver regeneration, we found that dual-specificity phosphatase 4 (DUSP4) expression, a known critical regulator of intracellular adhesion molecule-1 expression in endothelial cells, was markedly reduced in patients with dysfunctional liver regeneration. Mimicking clinical risk factors for dysfunctional liver regeneration, we found liver sinusoidal endothelial cells of two liver disease models to have significantly reduced baseline levels of DUSP4. Conclusions: Exploring the landscape of early transcriptional changes of human liver regeneration, we observed that people with dysfunctional regeneration experience overwhelming intrahepatic inflammation. Subclinical liver disease might account for DUSP4 reduction in liver sinusoidal endothelial cells, which ultimately primes the liver for an aggravated inflammatory response. Impact and implications: Using a unique human biorepository, focused on liver regeneration (LR), we explored the landscape of circulating and tissue-level alterations associated with both functional and dysfunctional LR. In contrast to experimental animal models, people with dysfunctional LR demonstrated an aggravated transcriptional inflammatory response, higher intracellular adhesion molecule-1 (ICAM-1) induction, intrahepatic neutrophil accumulation and activation upon induction of LR. Although inflammatory responses appear rapidly after liver resection, people with dysfunctional LR have exaggerated inflammatory responses that appear to be related to decreased levels of LSEC DUSP4, challenging existing concepts of post-resectional LR.

MIO: microRNA target analysis system for immuno-oncology.

SUMMARY: MicroRNAs have been shown to be able to modulate the tumor microenvironment and the immune response and hence could be interesting biomarkers and therapeutic targets in immuno-oncology; however, dedicated analysis tools are missing. Here, we present a user-friendly web platform MIO and a Python toolkit miopy integrating various methods for visualization and analysis of provided or custom bulk microRNA and gene expression data. We include regularized regression and survival analysis and provide information of 40 microRNA target prediction tools as well as a collection of curated immune related gene and microRNA signatures and processed TCGA data including estimations of infiltrated immune cells and the immunophenoscore. The integration of several machine learning methods enables the selection of prognostic and predictive microRNAs and gene interaction network biomarkers. AVAILABILITY AND IMPLEMENTATION: https://mio.icbi.at, https://github.com/icbi-lab/mio and https://github.com/icbi-lab/miopy. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Prediction and validation of murine MHC class I epitopes of the recombinant virus VSV-GP.

Oncolytic viruses are currently tested as a novel platform for cancer therapy. These viruses preferentially replicate in and kill malignant cells. Due to their microbial origin, treatment with oncolytic viruses naturally results in anti-viral responses and general immune activation. Consequently, the oncolytic virus treatment also induces anti-viral T cells. Since these can constitute the dominant activated T cell pool, monitoring of the anti-viral T cell response may aid in better understanding of the immune responses post oncolytic virotherapy. This study aimed to identify the anti-viral T cells raised by VSV-GP virotherapy in C57BL/6J mice, one of the most widely used models for preclinical studies. VSV-GP is a novel oncolytic agent that recently entered a clinical phase I study. To identify the VSV-GP epitopes to which mouse anti-viral T cells react, we used a multilevel adapted bioinformatics viral epitope prediction approach based on the tools netMHCpan, MHCflurry and netMHCstabPan, which are commonly used in neoepitope identification. Predicted viral epitopes were ranked based on consensus binding strength categories, predicted stability, and dissimilarity to the mouse proteome. The top ranked epitopes were selected and included in the peptide candidate matrix in order to use a matrix deconvolution approach. Using ELISpot, we showed which viral epitopes presented on C57BL/6J mouse MHC-I alleles H2-Db and H2-Kb trigger IFN-γ secretion due to T cell activation. Furthermore, we validated these findings using an intracellular cytokine staining. Collectively, identification of the VSV-GP T cell epitopes enables monitoring of the full range of anti-viral T cell responses upon VSV-GP virotherapy in future studies with preclinical mouse models to more comprehensively delineate anti-viral from anti-tumor T cell responses. These findings also support the development of novel VSV-GP variants expressing immunomodulatory transgenes and can improve the assessment of anti-viral immunity in preclinical models.