Circadian tumor infiltration and function of CD8+ T cells dictate immunotherapy efficacy.

The quality and quantity of tumor-infiltrating lymphocytes, particularly CD8+ T cells, are important parameters for the control of tumor growth and response to immunotherapy. Here, we show in murine and human cancers that these parameters exhibit circadian oscillations, driven by both the endogenous circadian clock of leukocytes and rhythmic leukocyte infiltration, which depends on the circadian clock of endothelial cells in the tumor microenvironment. To harness these rhythms therapeutically, we demonstrate that efficacy of chimeric antigen receptor T cell therapy and immune checkpoint blockade can be improved by adjusting the time of treatment during the day. Furthermore, time-of-day-dependent T cell signatures in murine tumor models predict overall survival in patients with melanoma and correlate with response to anti-PD-1 therapy. Our data demonstrate the functional significance of circadian dynamics in the tumor microenvironment and suggest the importance of leveraging these features for improving future clinical trial design and patient care.

CD40 signal rewires fatty acid and glutamine metabolism for stimulating macrophage anti-tumorigenic functions.

Exposure of lipopolysaccharide triggers macrophage pro-inflammatory polarization accompanied by metabolic reprogramming, characterized by elevated aerobic glycolysis and a broken tricarboxylic acid cycle. However, in contrast to lipopolysaccharide, CD40 signal is able to drive pro-inflammatory and anti-tumorigenic polarization by some yet undefined metabolic programming. Here we show that CD40 activation triggers fatty acid oxidation (FAO) and glutamine metabolism to promote ATP citrate lyase-dependent epigenetic reprogramming of pro-inflammatory genes and anti-tumorigenic phenotypes in macrophages. Mechanistically, glutamine usage reinforces FAO-induced pro-inflammatory and anti-tumorigenic activation by fine-tuning the NAD+/NADH ratio via glutamine-to-lactate conversion. Genetic ablation of important metabolic enzymes involved in CD40-mediated metabolic reprogramming abolishes agonistic anti-CD40-induced antitumor responses and reeducation of tumor-associated macrophages. Together these data show that metabolic reprogramming, which includes FAO and glutamine metabolism, controls the activation of pro-inflammatory and anti-tumorigenic polarization, and highlight a therapeutic potential of metabolic preconditioning of tumor-associated macrophages before agonistic anti-CD40 treatments.

PERK is a critical metabolic hub for immunosuppressive function in macrophages.

Chronic inflammation triggers compensatory immunosuppression to stop inflammation and minimize tissue damage. Studies have demonstrated that endoplasmic reticulum (ER) stress augments the suppressive phenotypes of immune cells; however, the molecular mechanisms underpinning this process and how it links to the metabolic reprogramming of immunosuppressive macrophages remain elusive. In the present study, we report that the helper T cell 2 cytokine interleukin-4 and the tumor microenvironment increase the activity of a protein kinase RNA-like ER kinase (PERK)-signaling cascade in macrophages and promote immunosuppressive M2 activation and proliferation. Loss of PERK signaling impeded mitochondrial respiration and lipid oxidation critical for M2 macrophages. PERK activation mediated the upregulation of phosphoserine aminotransferase 1 (PSAT1) and serine biosynthesis via the downstream transcription factor ATF-4. Increased serine biosynthesis resulted in enhanced mitochondrial function and α-ketoglutarate production required for JMJD3-dependent epigenetic modification. Inhibition of PERK suppressed macrophage immunosuppressive activity and could enhance the efficacy of immune checkpoint programmed cell death protein 1 inhibition in melanoma. Our findings delineate a previously undescribed connection between PERK signaling and PSAT1-mediated serine metabolism critical for promoting immunosuppressive function in M2 macrophages.

Microenvironment-driven metabolic adaptations guiding CD8+ T cell anti-tumor immunity.

The metabolic stress occurring in the tumor microenvironment (TME) hampers T cell anti-tumor immunity by disturbing T cell metabolic and epigenetic programs. Recent studies are making headway toward identifying strategies to unleash T cell activities by targeting T cell metabolism. Furthermore, efforts have been made to improve the efficacy of immune checkpoint blockade and adoptive cell transfer therapies. However, distinct treatment outcomes across different cancers raise the question of whether our understanding of the features of CD8+ T cells within the TME are universal, regardless of their tissue of origin. Here, we review the common and distinct environmental factors affecting CD8+ T cells across tumors. Moreover, we discuss how distinct tissue-specific niches are interpreted by CD8+ T cells based on studies on tissue-resident memory T (Trm) cells and how these insights can pave the way for a better understanding of the metabolic regulation of CD8+ T cell differentiation and anti-tumor immunity.

Development and validation of machine learning-based risk prediction models of oral squamous cell carcinoma using salivary autoantibody biomarkers.

INTRODUCTION: The incidence of oral cavity squamous cell carcinoma (OSCC) continues to rise. OSCC is associated with a low average survival rate, and most patients have a poor disease prognosis because of delayed diagnosis. We used machine learning techniques to predict high-risk cases of OSCC by using salivary autoantibody levels and demographic and behavioral data. METHODS: We collected the salivary samples of patients recruited from a teaching hospital between September 2008 and December 2012. Ten salivary autoantibodies, sex, age, smoking, alcohol consumption, and betel nut chewing were used to build prediction models for identifying patients with a high risk of OSCC. The machine learning algorithms applied in the study were logistic regression, random forest, support vector machine with the radial basis function kernel, eXtreme Gradient Boosting (XGBoost), and a stacking model. We evaluated the performance of the models by using the area under the receiver operating characteristic curve (AUC), with simulations conducted 100 times. RESULTS: A total of 337 participants were enrolled in this study. The best predictive model was constructed using a stacking algorithm with original forms of age and logarithmic levels of autoantibodies (AUC = 0.795 ± 0.055). Adding autoantibody levels as a data source significantly improved the prediction capability (from 0.698 ± 0.06 to 0.795 ± 0.055, p < 0.001). CONCLUSIONS: We successfully established a prediction model for high-risk cases of OSCC. This model can be applied clinically through an online calculator to provide additional personalized information for OSCC diagnosis, thereby reducing the disease morbidity and mortality rates.

Proteomic Profiling of Paired Interstitial Fluids Reveals Dysregulated Pathways and Salivary NID1 as a Biomarker of Oral Cavity Squamous Cell Carcinoma.

Patients with oral cavity squamous cell carcinoma (OSCC) are frequently first diagnosed at an advanced stage, leading to poor prognosis and high mortality rates. Early detection of OSCC using body fluid-accessible biomarkers may improve the prognosis and survival rate of OSCC patients. As tumor interstitial fluid is a proximal fluid enriched with cancer-related proteins, it is a useful reservoir suitable for the discovery of cancer biomarkers and dysregulated biological pathways in tumor microenvironments. Thus, paired interstitial fluids of tumor (TIF) and adjacent noncancerous (NIF) tissues from 10 OSCC patients were harvested and analyzed using one-dimensional gel electrophoresis coupled with liquid chromatography-tandem mass spectrometry (GeLC-MS/MS). Using label-free spectral counting-based quantification, 113 proteins were found to be up-regulated in the TIFs compared with the NIFs. The gene set enrichment analysis (GSEA) revealed that the differentially expressed TIF proteins were highly associated with aminoacyl tRNA biosynthesis pathway. The elevated levels of 4 proteins (IARS, KARS, WARS, and YARS) involved in the aminoacyl tRNA biosynthesis were verified in the OSCC tissues with immunohistochemistry (IHC). In addition, nidogen-1 (NID1) was selected for verification as an OSCC biomarker. Salivary level of NID1 in OSCC patients (n = 48) was significantly higher than that in the healthy individuals (n = 51) and subjects with oral potentially malignant disorder (OPMD; n = 53). IHC analysis showed that NID1 level in OSCC tissues was increased compared with adjacent noncancerous epithelium (n = 222). Importantly, the elevated NID1 level was correlated with the advanced stages of OSCC, as well as the poor survival of OSCC patients. Collectively, the results suggested that TIF analysis facilitates understanding of the OSCC microenvironment and that salivary NID1 may be a useful biomarker for OSCC.

Combined serum biomarkers in the noninvasive diagnosis of complicated parapneumonic effusions and empyema.

BACKGROUND: We previously demonstrated that the pleural levels of proteins (neutrophil gelatinase-associated lipocalin/NGAL, calprotectin, bactericidal permeability-increasing/BPI, azurocidin 1/AZU-1) were valuable markers for identifying complicated PPE (CPPE). Herein, this study was performed to evaluate whether these proteins are useful as serological markers for identifying CPPE and empyema. METHODS: A total of 137 participates were enrolled in this study. The levels of NGAL, calprotectin, BPI and AZU-1 were measured in serum and pleural fluid by enzyme-linked immunosorbent assay. We also characterized the diagnostic values of these markers between different groups. RESULTS: The serum levels of NGAL, calprotectin, and BPI in PPE patients were significantly higher than those in transudates, noninfectious exudates, and healthy controls. The area under the curve (AUC) values of NGAL, calprotectin, and BPI for distinguishing PPE from transudates or noninfectious exudates were around 0.861 to 0.953. In PPE group, serum NGAL and calprotectin levels were significantly elevated in patients with CPPE and empyema than in those with UPPE, whereas the serum BPI levels were similar between these two groups. In CPPE and empyema patients, the serum NGAL showed a positive correlation with the pleural fluid NGAL (r = 0.417, p <  0.01). When combined with serum CRP, the sensitivity and specificity of serum calprotectin for identifying CPPE and empyema were the highest at 73.52% and 80.55%, respectively. CONCLUSIONS: We concluded that serum calprotectin and NGAL were adjuvant serological markers for CPPE and empyema diagnosis. Patients present with pneumonia and pleural effusion signs in the chest x-ray and the combination of serum calprotectin and CRP constitutes a more highly sensitive and specific assay for identifying CPPE and empyema.

Exploration of influenza A virus PA protein-associated cellular proteins discloses its impact on mitochondrial function.

Influenza A virus can infect respiratory tracts and may cause severe illness in humans. Proteins encoded by influenza A virus can interact with cellular factors and dysregulate host biological processes to support viral replication and cause pathogenicity. The influenza viral PA protein is not only a subunit of influenza viral polymerase but also a virulence factor involved in pathogenicity during infection. To explore the role of the influenza virus PA protein in regulating host biological processes, we performed immunoprecipitation and LC‒MS/MS to globally identify cellular factors that interact with the PA proteins of the influenza A H1N1, 2009 pandemic H1N1, and H3N2 viruses. The results demonstrated that proteins located in the mitochondrion, proteasome, and nucleus are associated with the PA protein. We further discovered that the PA protein is partly located in mitochondria by immunofluorescence and mitochondrial fractionation and that overexpression of the PA protein reduces mitochondrial respiration. In addition, our results revealed the interaction between PA and the mitochondrial matrix protein PYCR2 and the antiviral role of PYCR2 during influenza A virus replication. Moreover, we found that the PA protein could also trigger autophagy and disrupt mitochondrial homeostasis. Overall, our research revealed the impacts of the influenza A virus PA protein on mitochondrial function and autophagy.

Immunoediting instructs tumor metabolic reprogramming to support immune evasion.

Immunoediting sculpts immunogenicity and thwarts host anti-tumor responses in tumor cells during tumorigenesis; however, it remains unknown whether metabolic programming of tumor cells can be guided by immunosurveillance. Here, we report that T cell-mediated immunosurveillance in early-stage tumorigenesis instructs c-Myc upregulation and metabolic reprogramming in tumor cells. This previously unexplored tumor-immune interaction is controlled by non-canonical interferon gamma (IFNγ)-STAT3 signaling and supports tumor immune evasion. Our findings uncover that immunoediting instructs deregulated bioenergetic programs in tumor cells to empower them to disarm the T cell-mediated immunosurveillance by imposing metabolic tug-of-war between tumor and infiltrating T cells and forming the suppressive tumor microenvironment.

Metabolic programs tailor T cell immunity in viral infection, cancer, and aging.

Productive T cell responses to infection and cancer rely on coordinated metabolic reprogramming and epigenetic remodeling among the immune cells. In particular, T cell effector and memory differentiation, exhaustion, and senescence/aging are tightly regulated by the metabolism-epigenetics axis. In this review, we summarize recent advances of how metabolic circuits combined with epigenetic changes dictate T cell fate decisions and shape their functional states. We also discuss how the metabolic-epigenetic axis orchestrates T cell exhaustion and explore how physiological factors, such as diet, gut microbiota, and the circadian clock, are integrated in shaping T cell epigenetic modifications and functionality. Furthermore, we summarize key features of the senescent/aged T cells and discuss how to ameliorate vaccination- and COVID-induced T cell dysfunctions by metabolic modulations. An in-depth understanding of the unexplored links between cellular metabolism and epigenetic modifications in various physiological or pathological contexts has the potential to uncover novel therapeutic strategies for fine-tuning T cell immunity.

Development of a salivary autoantibody biomarker panel for diagnosis of oral cavity squamous cell carcinoma.

Oral cavity squamous cell carcinoma (OSCC) is a destructive disease with increasing incidence. OSCC is usually diagnosed at an advanced stage, which leads to poor outcomes of OSCC patients. Currently, there is a lack of biomarkers with sufficient effectiveness in early diagnosis of OSCC. To ameliorate OSCC screening, we evaluated the performances of salivary autoantibodies (auto-Abs) to nine proteins (ANXA2, CA2, ISG15, KNG1, MMP1, MMP3, PRDX2, SPARC, and HSPA5) as OSCC biomarkers. A multiplexed immunoassay using a fluorescence bead-based suspension array system was established for simultaneous assessment of the salivary levels of the above nine auto-Abs and a known OSCC-associated auto-Ab, anti-p53. Compared to healthy individuals (n = 140), the salivary levels of nine auto-Abs were significantly elevated in OSCC patients (n = 160). Notably, the salivary levels of the 10 auto-Abs in the early-stage OSCC patients (n = 102) were higher than that in the healthy group. Most importantly, utilizing a marker panel consisting of anti-MMP3, anti-PRDX2, anti-SPARC, and anti-HSPA5 for detection of early-stage OSCC achieved a sensitivity of 63.8% with a specificity of 90%. Collectively, herein we established a multiplex auto-Ab platform for OSCC screening, and demonstrated a four-auto-Ab panel which shows clinical applicability for early diagnosis of OSCC.

Machine Learning Based Risk Prediction Models for Oral Squamous Cell Carcinoma Using Salivary Biomarkers.

Tumor-associated autoantibodies can be used as biomarkers for detecting different types of cancers. Our objective was to use machine learning techniques to predict high-risk cases of oral squamous cell carcinoma (OSCC) with salivary autoantibodies. The optimal model was using eXtreme Gradient Boosting (XGBoost) with the area under the receiver operating characteristic curve (AUC) of 0.765 (p < 0.01). Thus, applying machine learning model to early detect high-risk cases of OSCC could assist the clinic treatment and prognosis.

Pleural cytokines MIF and MIP-3α as novel biomarkers for complicated parapneumonic effusions and empyema.

Patients with complicated parapneumonic effusion (CPPE)/empyema have high morbidity and mortality, particularly when adequate management is delayed. We aimed to investigate novel dysregulated cytokines that can be used as biomarkers for infectious pleural effusions, especially for CPPE/empyema. Expression of 40 cytokines in parapneumonic effusions (PPE) was screened in the discovery phase, involving 63 patients, using a multiplex immunobead-based assay. Six cytokines were subsequently validated by enzyme-linked immunosorbent assays (ELISAs). We then used ELISA to further evaluate the diagnostic values and cutoff values of these cytokines as potential biomarkers in an expanded group that included 200 patients with uncomplicated parapneumonic effusion (UPPE), CPPE, empyema, transudates, other exudates, and malignant pleural effusion (MPE). The pleural levels of four cytokines (MIF, MIP-3α, IL-1ß, ENA-78) were highest and significantly increased in CPPE/empyema compared with those in other etiologies. According to receiver operating characteristic curve analysis, the four cytokines (MIF, MIP-3α, IL-1ß, and ENA-78) had areas under the curve (AUCs) greater than 0.710 for discriminating parapneumonic pleural effusion from noninfectious pleural effusions. In a comparison of nonpurulent CPPE with UPPE, logistic regression analysis revealed that pleural fluid MIF ≥ 12 ng/ml and MIP-3α ≥ 4.3 ng/ml had the best diagnostic value; MIF also displayed the highest odds ratio of 663 for nonpurulent CPPE, with 97.5% specificity, 94.44% sensitivity, and an AUC of 0.950. In conclusion, our results show that elevated MIF and MIP-3α may be used as novel biomarkers for PPE diagnosis, particularly in patients with CPPE/empyema; the findings indicate that dysregulated cytokine expression may provide clues about the pathogenesis of pleural infection.

Novel plasma metabolite markers of attention-deficit/hyperactivity disorder identified using high-performance chemical isotope labelling-based liquid chromatography-mass spectrometry.

OBJECTIVES: Metabolites are the intermediate and final products of biological processes and ultimately reflect the responses of these processes to genetic regulation and environmental perturbations, including those involved in attention deficit/hyperactivity disorder (ADHD). METHODS: We identified a quantitative profile of plasma metabolites in 58 ADHD patients (mean age 9.0 years, 77.6% males) and 38 healthy control subjects (mean age 10.2 years, 55.3% males) using the high-performance chemical isotope labelling (CIL)-based liquid chromatography-mass spectrometry (LC-MS). Using a volcano plot and orthogonal projections to latent structure-discriminant analysis (OPLS-DA), we determined nine metabolites with differentially expressed levels in ADHD plasma samples. RESULTS: Compared to the control group, the plasma levels of guanosine, O-phosphoethanolamine, phenyl-leucine, hypoxanthine, 4-aminohippuric acid, 5-hydroxylysine, and L-cystine appeared increased in the ADHD patients, whilegentisic acid and tryptophyl-phenylalanine were down-regulated in the patients with ADHD. We found that the plasma levels of all nine metabolites were able to discriminate the ADHD group from the control group. Levels of O-phosphoethanolamine, 4-aminohippuric acid, 5-hydroxylysine, L-cystine, tryptophyl-phenylalanine, and gentisic acid were significantly correlated with clinical ADHD symptoms. CONCLUSIONS: This study is the first to use the CIL-based LC-MS to profile ADHD plasma metabolites, and we identified nine novel metabolite biomarkers of ADHD.

Significant association of serum autoantibodies to TYMS, HAPLN1 and IGFBP5 with early stage canine malignant mammary tumours.

Canine mammary tumours (CMTs) are the most prevalent neoplasms in female dogs. Despite the high incidence of such tumours, a lack of easily accessible biomarkers still impedes early diagnosis of malignant CMTs. Herein we identify thymidylate synthetase (TYMS), hyaluronan and proteoglycan link protein 1 (HAPLN1) and insulin-like growth factor-binding protein 5 (IGFBP5) as CMT antigens eliciting corresponding autoantibodies in CMT cases. We establish enzyme-linked immunosorbent assays (ELISAs) to detect autoantibodies to TYMS (TYMS-AAb), HAPLN1 (HAPLN1-AAb) and IGFBP5 (IGFBP5-AAb) in sera from 81 dogs with malignant CMTs (41 in Stage I), 24 with benign CMTs and 35 healthy controls. Levels of all the three autoantibodies are elevated in the malignant group compared with the healthy or the benign group; notably, the elevated autoantibody levels significantly correlate with the stage-I CMTs. For discriminating malignant CMTs from healthy control, the area under curve (AUC) of TYMS-AAb is 0.694 with specificity of 82.9% and sensitivity of 50.6%. The AUC of utilising HAPLN1-AAb for distinguishing the stage-I CMTs from healthy controls is 0.711 with specificity of 77.1% and sensitivity of 58.5%. In differentiating malignant CMTs from the benign, the AUC of IGFBP5-AAb reaches 0.696 with specificity of 70.8% and sensitivity of 67.9%, and a combination of IGFBP5-AAb and TYMS-AAb increases the AUC to 0.72. Finally, the AUC of combined HAPLN1-AAb and IGFBP5-AAb in discriminating the stage-I CMTs from the benign achieves 0.731. Collectively, this study highlights a significant association of the three serum autoantibodies with early stage malignant CMTs.

Metabolomic profiling of parapneumonic effusion reveals a regulatory role of dipeptides in interleukin-8 production in neutrophil-like cells.

Bacterial pneumonia is a lethal condition, and approximately 40% of bacterial pneumonia patients experience parapneumonic effusion (PPE). Based on the severity of inflammation, PPEs can be categorized as early-stage uncomplicated PPE (UPPE), advanced-stage complicated PPE (CPPE) and, most seriously, thoracic empyema. Appropriate antibiotic treatment at the early stage of PPE can prevent PPE progression and reduce mortality, indicating that understanding PPE generation and components can help researchers develop corresponding treatment strategies for PPE. To this end, metabolomes of 73 PPE (38 UPPE and 35 CPPE samples) and 30 malignant pleural effusion (MPE) samples were profiled with differential 12C2-/13C2-isotope dansylation labeling-based mass spectrometry. We found that PPE is characterized by elevated levels of dipeptides, especially for PPEs at advanced stages. Furthermore, with integrated proteomic and transcriptomic analyses of PPEs, the levels of dipeptides were strongly associated with the production of interleukin-8 (IL-8), an inflammation-associated cytokine. The production of IL-8 indeed increased upon the treatment of HL-60-derived neutrophilic cells with dipeptides, Gly-Val and Gly-Tyr. Our findings help to elucidate the metabolic perturbations present in PPE and indicate for the first time that dipeptides may be involved in the immune regulation observed during PPE progression.

Integrated analyses utilizing metabolomics and transcriptomics reveal perturbation of the polyamine pathway in oral cavity squamous cell carcinoma.

Oral cavity squamous cell carcinoma (OSCC), the most common malignancy of the oral cavity, is associated with poor prognosis and high mortality worldwide. Moreover, knowledge of the metabolic alterations that occur in OSCC is still limited. In the present study, we used a quantitative metabolomic approach with chemical isotope labeling (CIL) to analyze alterations in the metabolite levels in paired cancerous (T) and adjacent noncancerous (AN) tissues from 31 OSCC patients. Using volcano plot and orthogonal projections to latent structure-discriminant analysis (OPLS-DA), we uncovered 99 dysregulated metabolites in OSCC and verified the identities of seven metabolites via comparison with authenticated standards. From these seven metabolites, we constructed a 3-marker panel, consisting of putrescine, glycyl-leucine, and phenylalanine, using a support vector machine (SVM) model that can discriminate T from AN with high sensitivity and specificity based on receiver operator characteristic (ROC) analysis. Furthermore, by integrating the metabolomics profiles with transcriptomics data obtained from the same sample set, we revealed the dysregulation of the polyamine pathway in OSCC. Our findings provide insights into the metabolic perturbations present in OSCC and have uncovered potential metabolic biomarkers and therapeutic targets for use in the treatment of OSCC.