A metabolite-derived protein modification integrates glycolysis with KEAP1-NRF2 signalling.

Mechanisms that integrate the metabolic state of a cell with regulatory pathways are necessary to maintain cellular homeostasis. Endogenous, intrinsically reactive metabolites can form functional, covalent modifications on proteins without the aid of enzymes1,2, and regulate cellular functions such as metabolism3-5 and transcription6. An important 'sensor' protein that captures specific metabolic information and transforms it into an appropriate response is KEAP1, which contains reactive cysteine residues that collectively act as an electrophile sensor tuned to respond to reactive species resulting from endogenous and xenobiotic molecules. Covalent modification of KEAP1 results in reduced ubiquitination and the accumulation of NRF27,8, which then initiates the transcription of cytoprotective genes at antioxidant-response element loci. Here we identify a small-molecule inhibitor of the glycolytic enzyme PGK1, and reveal a direct link between glycolysis and NRF2 signalling. Inhibition of PGK1 results in accumulation of the reactive metabolite methylglyoxal, which selectively modifies KEAP1 to form a methylimidazole crosslink between proximal cysteine and arginine residues (MICA). This posttranslational modification results in the dimerization of KEAP1, the accumulation of NRF2 and activation of the NRF2 transcriptional program. These results demonstrate the existence of direct inter-pathway communication between glycolysis and the KEAP1-NRF2 transcriptional axis, provide insight into the metabolic regulation of the cellular stress response, and suggest a therapeutic strategy for controlling the cytoprotective antioxidant response in several human diseases

Integrated Analysis of Multiple Microarray Datasets Identifies a Reproducible Survival Predictor in Ovarian Cancer

BACKGROUND: Public data integration may help overcome challenges in clinical implementation of microarray profiles. We integrated several ovarian cancer datasets to identify a reproducible predictor of survival. METHODOLOGY/PRINCIPAL FINDINGS: Four microarray datasets from different institutions comprising 265 advanced stage tumors were uniformly reprocessed into a single training dataset, also adjusting for inter-laboratory variation ("batch-effect"). Supervised principal component survival analysis was employed to identify prognostic models. Models were independently validated in a 61-patient cohort using a custom array genechip and a publicly available 229-array dataset. Molecular correspondence of high- and low-risk outcome groups between training and validation datasets was demonstrated using Subclass Mapping. Previously established molecular phenotypes in the 2(nd) validation set were correlated with high and low-risk outcome groups. Functional representational and pathway analysis was used to explore gene networks associated with high and low risk phenotypes. A 19-gene model showed optimal performance in the training set (median OS 31 and 78 months, p < 0.01), 1(st) validation set (median OS 32 months versus not-yet-reached, p = 0.026) and 2(nd) validation set (median OS 43 versus 61 months, p = 0.013) maintaining independent prognostic power in multivariate analysis. There was strong molecular correspondence of the respective high- and low-risk tumors between training and 1(st) validation set. Low and high-risk tumors were enriched for favorable and unfavorable molecular subtypes and pathways, previously defined in the public 2(nd) validation set. CONCLUSIONS/SIGNIFICANCE: Integration of previously generated cancer microarray datasets may lead to robust and widely applicable survival predictors. These predictors are not simply a compilation of prognostic genes but appear to track true molecular phenotypes of good- and poor-outcome

A systematic approach to biomarker discovery; Preamble to "the iSBTc-FDA taskforce on immunotherapy biomarkers"

The International Society for the Biological Therapy of Cancer (iSBTc) has initiated in collaboration with the United States Food and Drug Administration (FDA) a programmatic look at innovative avenues for the identification of relevant parameters to assist clinical and basic scientists who study the natural course of host/tumor interactions or their response to immune manipulation. The task force has two primary goals: 1) identify best practices of standardized and validated immune monitoring procedures and assays to promote inter-trial comparisons and 2) develop strategies for the identification of novel biomarkers that may enhance our understating of principles governing human cancer immune biology and, consequently, implement their clinical application. Two working groups were created that will report the developed best practices at an NCI/FDA/iSBTc sponsored workshop tied to the annual meeting of the iSBTc to be held in Washington DC in the Fall of 2009. This foreword provides an overview of the task force and invites feedback from readers that might be incorporated in the discussions and in the final document

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

PARK7 Catalyzes Stereospecific Detoxification of Methylglyoxal Consistent with Glyoxalase and Not Deglycase Function

The protein PARK7 (also known as DJ-1) has been implicated in several diseases, with the most notable being Parkinson's disease. While several molecular and cellular roles have been ascribed to DJ-1, there is no real consensus on what its true cellular functions are and how the loss of DJ-1 function may contribute to the pathogenesis of Parkinson's disease. Recent reports have implicated DJ-1 in the detoxification of several reactive metabolites that are produced during glycolytic metabolism, with the most notable being the α-oxoaldehyde species methylglyoxal. While it is generally agreed that DJ-1 is able to metabolize methylglyoxal to lactate, the mechanism by which it does so is hotly debated with potential implications for cellular function. In this work, we provide definitive evidence that recombinant DJ-1 produced in human cells prevents the stable glycation of other proteins through the conversion of methylglyoxal or a related alkynyl dicarbonyl probe to their corresponding α-hydroxy carboxylic acid products. This protective action of DJ-1 does not require a physical interaction with a target protein, providing direct evidence for a glutathione-free glyoxalase and not a deglycase mechanism of methylglyoxal detoxification. Stereospecific liquid chromatography-mass spectrometry (LC-MS) measurements further uncovered the existence of nonenzymatic production of racemic lactate from MGO under physiological buffer conditions, whereas incubation with DJ-1 predominantly produces l-lactate. Collectively, these studies provide direct support for the stereospecific conversion of MGO to l-lactate by DJ-1 in solution with negligible or no contribution of direct protein deglycation

Widespread, Reversible Cysteine Modification by Methylglyoxal Regulates Metabolic Enzyme Function

Methylglyoxal (MGO), a reactive metabolite byproduct of glucose metabolism, is known to form a variety of posttranslational modifications (PTMs) on nucleophilic amino acids. For example, cysteine, the most nucleophilic proteinogenic amino acid, forms reversible hemithioacetal and stable mercaptomethylimidazole adducts with MGO. The high reactivity of cysteine toward MGO and the rate of formation of such modifications provide the opportunity for mechanisms by which proteins and pathways might rapidly sense and respond to alterations in levels of MGO. This indirect measure of alterations in glycolytic flux would thereby allow disparate cellular processes to dynamically respond to changes in nutrient availability and utilization. Here we report the use of quantitative LC–MS/MS-based chemoproteomic profiling approaches with a cysteine-reactive probe to map the proteome-wide landscape of MGO modification of cysteine residues. This approach led to the identification of many sites of potential functional regulation by MGO. We further characterized the role that such modifications have in a catalytic cysteine residue in a key metabolic enzyme and the resulting effects on cellular metabolism

Profiling Reactive Metabolites via Chemical Trapping and Targeted Mass Spectrometry

Metabolomic profiling studies aim to provide a comprehensive, quantitative, and dynamic portrait of the endogenous metabolites in a biological system. While contemporary technologies permit routine profiling of many metabolites, intrinsically labile metabolites are often improperly measured or omitted from studies due to unwanted chemical transformations that occur during sample preparation or mass spectrometric analysis. The primary glycolytic metabolite 1,3-bisphosphoglyceric acid (1,3-BPG) typifies this class of metabolites, and, despite its central position in metabolism, has largely eluded analysis in profiling studies. Here we take advantage of the reactive acylphosphate group in 1,3-BPG to chemically trap the metabolite with hydroxylamine during metabolite isolation, enabling quantitative analysis by targeted LC–MS/MS. This approach is compatible with complex cellular metabolome, permits specific detection of the reactive (1,3-) instead of nonreactive (2,3-) BPG isomer, and has enabled direct analysis of dynamic 1,3-BPG levels resulting from perturbations to glucose processing. These studies confirmed that standard metabolomic methods misrepresent cellular 1,3-BPG levels in response to altered glucose metabolism and underscore the potential for chemical trapping to be used for other classes of reactive metabolites

Consensus guidelines for the definition, detection and interpretation of immunogenic cell death

Cells succumbing to stress via regulated cell death (RCD) can initiate an adaptive immune response associated with immunological memory, provided they display sufficient antigenicity and adjuvanticity. Moreover, multiple intracellular and microenvironmental features determine the propensity of RCD to drive adaptive immunity. Here, we provide an updated operational definition of immunogenic cell death (ICD), discuss the key factors that dictate the ability of dying cells to drive an adaptive immune response, summarize experimental assays that are currently available for the assessment of ICD in vitro and in vivo, and formulate guidelines for their interpretation.Peer reviewe