Chaperonin CCT controls extracellular vesicle production and cell metabolism through kinesin dynamics.

Cell proteostasis includes gene transcription, protein translation, folding of de novo proteins, post-translational modifications, secretion, degradation and recycling. By profiling the proteome of extracellular vesicles (EVs) from T cells, we have found the chaperonin complex CCT, involved in the correct folding of particular proteins. By limiting CCT cell-content by siRNA, cells undergo altered lipid composition and metabolic rewiring towards a lipid-dependent metabolism, with increased activity of peroxisomes and mitochondria. This is due to dysregulation of the dynamics of interorganelle contacts between lipid droplets, mitochondria, peroxisomes and the endolysosomal system. This process accelerates the biogenesis of multivesicular bodies leading to higher EV production through the dynamic regulation of microtubule-based kinesin motors. These findings connect proteostasis with lipid metabolism through an unexpected role of CCT.

Early administration of tofacitinib in COVID-19 pneumonitis: An open randomised controlled trial.

BACKGROUND: Controversies on sub-populations most sensitive to therapy and the best timing of starting the treatment still surround the use of immunomodulatory drugs in COVID-19. OBJECTIVES: We designed a multicentre open-label randomised controlled trial to test the effect of prompt adding of tofacitinib to standard therapy for hospitalised patients affected by mild/moderate COVID-19 pneumonitis. METHODS: Patients admitted to three Italian hospitals affected by COVID-19 pneumonitis not requiring mechanical ventilation were randomised to receive standard treatment alone or tofacitinib (10 mg/bid) for 2 weeks, starting within the first 24 h from admission. RESULTS: A total of 116 patients were randomised; 49 in the experimental arm completed the 14-day treatment period, 9 discontinued tofacitinib as the disease worsened and were included in the analysis, and 1 died of respiratory failure. All 58 control patients completed the study. Clinical and demographic characteristics were similar between the study groups. In the tofacitinib group, 9/58 (15.5%) patients progressed to noninvasive ventilation (CPAP) to maintain SO2 > 93%, invasive mechanical ventilation or death by day 14 was 15.5%, significantly less than in the control group (20/58, 34.4%, RR 0,45, RRR -55%, NNT 5; p = .018). No differences in severe adverse effect incidence had been observed across the groups. CONCLUSION: High-dose tofacitinib therapy in patients with COVID pneumonitis is safe and may prevent deterioration to respiratory failure.

TurboPutative: A web server for data handling and metabolite classification in untargeted metabolomics.

Untargeted metabolomics aims at measuring the entire set of metabolites in a wide range of biological samples. However, due to the high chemical diversity of metabolites that range from small to large and more complex molecules (i.e., amino acids/carbohydrates vs. phospholipids/gangliosides), the identification and characterization of the metabolome remain a major bottleneck. The first step of this process consists of searching the experimental monoisotopic mass against databases, thus resulting in a highly redundant/complex list of candidates. Despite the progress in this area, researchers are still forced to manually explore the resulting table in order to prioritize the most likely identifications for further biological interpretation or confirmation with standards. Here, we present TurboPutative (https://proteomics.cnic.es/TurboPutative/), a flexible and user-friendly web-based platform composed of four modules (Tagger, REname, RowMerger, and TPMetrics) that streamlines data handling, classification, and interpretability of untargeted LC-MS-based metabolomics data. Tagger classifies the different compounds and provides preliminary insights into the biological system studied. REname improves putative annotation handling and visualization, allowing the recognition of isomers and equivalent compounds and redundant data removal. RowMerger reduces the dataset size, facilitating the manual comparison among annotations. Finally, TPMetrics combines different datasets with feature intensity and relevant information for the researcher and calculates a score based on adduct probability and feature correlations, facilitating further identification, assessment, and interpretation of the results. The TurboPutative web application allows researchers in the metabolomics field that are dealing with massive datasets containing multiple putative annotations to reduce the number of these entries by 80%-90%, thus facilitating the extrapolation of biological knowledge and improving metabolite prioritization for subsequent pathway analysis. TurboPutative comprises a rapid, automated, and customizable workflow that can also be included in programmed bioinformatics pipelines through its RESTful API services. Users can explore the performance of each module through demo datasets supplied on the website. The platform will help the metabolomics community to speed up the arduous task of manual data curation that is required in the first steps of metabolite identification, improving the generation of biological knowledge.

Circulating miR-320b and miR-483-5p levels are associated with COVID-19 in-hospital mortality.

The stratification of mortality risk in COVID-19 patients remains extremely challenging for physicians, especially in older patients. Innovative minimally invasive molecular biomarkers are needed to improve the prediction of mortality risk and better customize patient management. In this study, aimed at identifying circulating miRNAs associated with the risk of COVID-19 in-hospital mortality, we analyzed serum samples of 12 COVID-19 patients by small RNA-seq and validated the findings in an independent cohort of 116 COVID-19 patients by qRT-PCR. Thirty-four significantly deregulated miRNAs, 25 downregulated and 9 upregulated in deceased COVID-19 patients compared to survivors, were identified in the discovery cohort. Based on the highest fold-changes and on the highest expression levels, 5 of these 34 miRNAs were selected for the analysis in the validation cohort. MiR-320b and miR-483-5p were confirmed to be significantly hyper-expressed in deceased patients compared to survived ones. Kaplan-Meier and Cox regression models, adjusted for relevant confounders, confirmed that patients with the 20% highest miR-320b and miR-483-5p serum levels had three-fold increased risk to die during in-hospital stay for COVID-19. In conclusion, high levels of circulating miR-320b and miR-483-5p can be useful as minimally invasive biomarkers to stratify older COVID-19 patients with an increased risk of in-hospital mortality.

Activation of amino acid metabolic program in cardiac HIF1-alpha-deficient mice.

HIF1-alpha expression defines metabolic compartments in the developing heart, promoting glycolytic program in the compact myocardium and mitochondrial enrichment in the trabeculae. Nonetheless, its role in cardiogenesis is debated. To assess the importance of HIF1-alpha during heart development and the influence of glycolysis in ventricular chamber formation, herein we generated conditional knockout models of Hif1a in Nkx2.5 cardiac progenitors and cardiomyocytes. Deletion of Hif1a impairs embryonic glycolysis without influencing cardiomyocyte proliferation and results in increased mitochondrial number and transient activation of amino acid catabolism together with HIF2α and ATF4 upregulation by E12.5. Hif1a mutants display normal fatty acid oxidation program and do not show cardiac dysfunction in the adulthood. Our results demonstrate that cardiac HIF1 signaling and glycolysis are dispensable for mouse heart development and reveal the metabolic flexibility of the embryonic myocardium to consume amino acids, raising the potential use of alternative metabolic substrates as therapeutic interventions during ischemic events.

ALDH4A1 is an atherosclerosis auto-antigen targeted by protective antibodies.

Cardiovascular disease (CVD) is the leading cause of mortality in the world, with most CVD-related deaths resulting from myocardial infarction or stroke. The main underlying cause of thrombosis and cardiovascular events is atherosclerosis, an inflammatory disease that can remain asymptomatic for long periods. There is an urgent need for therapeutic and diagnostic options in this area. Atherosclerotic plaques contain autoantibodies1,2, and there is a connection between atherosclerosis and autoimmunity3. However, the immunogenic trigger and the effects of the autoantibody response during atherosclerosis are not well understood3-5. Here we performed high-throughput single-cell analysis of the atherosclerosis-associated antibody repertoire. Antibody gene sequencing of more than 1,700 B cells from atherogenic Ldlr-/- and control mice identified 56 antibodies expressed by in-vivo-expanded clones of B lymphocytes in the context of atherosclerosis. One-third of the expanded antibodies were reactive against atherosclerotic plaques, indicating that various antigens in the lesion can trigger antibody responses. Deep proteomics analysis identified ALDH4A1, a mitochondrial dehydrogenase involved in proline metabolism, as a target antigen of one of these autoantibodies, A12. ALDH4A1 distribution is altered during atherosclerosis, and circulating ALDH4A1 is increased in mice and humans with atherosclerosis, supporting the potential use of ALDH4A1 as a disease biomarker. Infusion of A12 antibodies into Ldlr-/- mice delayed plaque formation and reduced circulating free cholesterol and LDL, suggesting that anti-ALDH4A1 antibodies can protect against atherosclerosis progression and might have therapeutic potential in CVD.

Decreased serum levels of the inflammaging marker miR-146a are associated with clinical non-response to tocilizumab in COVID-19 patients.

Current COVID-19 pandemic poses an unprecedented threat to global health and healthcare systems. The most amount of the death toll is accounted by old people affected by age-related diseases that develop a hyper-inflammatory syndrome. In this regard, we hypothesized that COVID-19 severity may be linked to inflammaging. Here, we examined 30 serum samples from patients enrolled in the clinical trial NCT04315480 assessing the clinical response to a single-dose intravenous infusion of the anti-IL-6 receptor drug Tocilizumab (TCZ) in COVID-19 patients with multifocal interstitial pneumonia. In these serum samples, as well as in 29 age- and gender-matched healthy control subjects, we assessed a set of microRNAs that regulate inflammaging, i.e. miR-146a-5p, miR-21-5p, and miR-126-3p, which were quantified by RT-PCR and Droplet Digital PCR. We showed that COVID-19 patients who did not respond to TCZ have lower serum levels of miR-146a-5p after the treatment (p = 0.007). Among non-responders, those with the lowest serum levels of miR-146a-5p experienced the most adverse outcome (p = 0.008). Our data show that a blood-based biomarker, such as miR-146a-5p, can provide clues about the molecular link between inflammaging and COVID-19 clinical course, thus allowing to better understand the use of biologic drug armory against this worldwide health threat.

ECM deposition is driven by caveolin-1-dependent regulation of exosomal biogenesis and cargo sorting.

The composition and physical properties of the extracellular matrix (ECM) critically influence tumor progression, but the molecular mechanisms underlying ECM layering are poorly understood. Tumor-stroma interaction critically depends on cell communication mediated by exosomes, small vesicles generated within multivesicular bodies (MVBs). We show that caveolin-1 (Cav1) centrally regulates exosome biogenesis and exosomal protein cargo sorting through the control of cholesterol content at the endosomal compartment/MVBs. Quantitative proteomics profiling revealed that Cav1 is required for exosomal sorting of ECM protein cargo subsets, including Tenascin-C (TnC), and for fibroblast-derived exosomes to efficiently deposit ECM and promote tumor invasion. Cav1-driven exosomal ECM deposition not only promotes local stromal remodeling but also the generation of distant ECM-enriched stromal niches in vivo. Cav1 acts as a cholesterol rheostat in MVBs, determining sorting of ECM components into specific exosome pools and thus ECM deposition. This supports a model by which Cav1 is a central regulatory hub for tumor-stroma interactions through a novel exosome-dependent ECM deposition mechanism.

Subclinical progression of systemic sclerosis-related cardiomyopathy.

AIMS: Cardiac involvement in patients with systemic sclerosis (SSc) is frequent and represents a negative prognostic factor. Recent studies have described subclinical heart involvement of both the right ventricle (RV) and left ventricle (LV) via speckle-tracking-derived global longitudinal strain (GLS). It is currently unknown if SSc-related cardiomyopathy progresses through time. Our aim was to assess the progression of subclinical cardiac involvement in patients with SSc via speckle-tracking-derived GLS. METHODS: This was a prospective longitudinal study enrolling 72 consecutive patients with a diagnosis of SSc and no structural heart disease nor pulmonary hypertension. A standard echocardiographic exam and GLS calculations were performed at baseline and at follow-up. RESULTS: Traditional echocardiographic parameters did not differ from baseline to 20-month follow-up. LV GLS, despite being already impaired at baseline, worsened significantly during follow-up (from -19.8 ± 3.5% to -18.7 ± 3.5%, p = .034). RV GLS impairment progressed through the follow-up period (from -20.9 ± 6.1% to -18.7 ± 5.4%, p = .013). The impairment was more pronounced for the endocardial layers of both LV (from -22.5 ± 3.9% to -21.4 ± 3.9%, p = .041) and RV (-24.2 ± 6.2% to -20.6 ± 5.9%, p = .001). A 1% worsening in RV GLS was associated with an 18% increased risk of all-cause death or major cardiovascular event (p = .03) and with a 55% increased risk of pulmonary hypertension (p = .043). CONCLUSION: SSC-related cardiomyopathy progresses over time and can be detected by speckle-tracking GLS. The highest progression towards reduced deformation was registered for the endocardial layers, which supports the hypothesis that microvascular dysfunction is the main determinant of heart involvement in SSc patients and starts well before overt pulmonary hypertension.

Metabolomic Analysis of Liver Tissues for Characterization of Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) causes more than half a million annual deaths worldwide. Understanding the mechanisms contributing to HCC development is highly desirable for improved surveillance, diagnosis, and treatment. Liver tissue metabolomics has the potential to reflect the physiological changes behind HCC development. Also, it allows identification of biomarker candidates for future evaluation in biofluids and investigation of racial disparities in HCC. Tumor and nontumor tissues from 40 patients were analyzed by both gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) platforms to increase the metabolome coverage. The levels of the metabolites extracted from solid liver tissue of the HCC area and adjacent non-HCC area were compared. Among the analytes detected by GC-MS and LC-MS with significant alterations, 18 were selected based on biological relevance and confirmed metabolite identification. These metabolites belong to TCA cycle, glycolysis, purines, and lipid metabolism and have been previously reported in liver metabolomic studies where high correlation with HCC progression is implied. We demonstrated that metabolites related to HCC pathogenesis can be identified through liver tissue metabolomic analysis. Additionally, this study has enabled us to identify race-specific metabolites associated with HCC.

Sequential Bone-Marrow Cell Delivery of VEGFA/S1P Improves Vascularization and Limits Adverse Cardiac Remodeling After Myocardial Infarction in Mice.

Microvascular dysfunction and resulting tissue hypoxia is a major contributor to the pathogenesis and evolution of cardiovascular diseases (CVD). Diverse gene and cell therapies have been proposed to preserve the microvasculature or boost angiogenesis in CVD, with moderate benefit. This study tested in vivo the impact of sequential delivery by bone-marrow (BM) cells of the pro-angiogenic factors vascular endothelial growth factor (VEGFA) and sphingosine-1-phosphate (S1P) in a myocardial infarction model. For that, mouse BM cells were transduced with lentiviral vectors coding for VEGFA or sphingosine kinase (SPHK1), which catalyzes S1P production, and injected them intravenously 4 and 7 days after cardiac ischemia-reperfusion in mice. Sequential delivery by transduced BM cells of VEGFA and S1P led to increased endothelial cell numbers and shorter extravascular distances in the infarct zone, which support better oxygen diffusion 28 days post myocardial infarction, as shown by automated 3D image analysis of the microvasculature. Milder effects were observed in the remote zone, together with increased proportion of capillaries. BM cells delivering VEGFA and S1P also decreased myofibroblast abundance and restricted adverse cardiac remodeling without major impact on cardiac contractility. The results indicate that BM cells engineered to deliver VEGFA/S1P angiogenic factors sequentially may constitute a promising strategy to improve micro-vascularization and oxygen diffusion, thus limiting the adverse consequences of cardiac ischemia.

Multi-omic Pathway and Network Analysis to Identify Biomarkers for Hepatocellular Carcinoma.

The threat of Hepatocellular Carcinoma (HCC) is a growing problem, with incidence rates anticipated to near double over the next two decades. The increasing burden makes discovery of novel diagnostic, prognostic, and therapeutic biomarkers distinguishing HCC from underlying cirrhosis a significant focus. In this study, we analyzed tissue and serum samples from 40 HCC cases and 25 patients with liver cirrhosis (CIRR) to better understand the mechanistic differences between HCC and CIRR. Through pathway and network analysis, we are able to take a systems biology approach to conduct multi-omic analysis of transcriptomic, glycoproteomic, and metabolomic data acquired through various platforms. As a result, we are able to identify the FXR/RXR Activation pathway as being represented by molecules spanning multiple molecular compartments in these samples. Specifically, serum metabolites deoxycholate and chenodeoxycholic acid and serum glycoproteins C4A/C4B, KNG1, and HPX are biomarker candidates identified from this analysis that are of interest for future targeted studies. These results demonstrate the integrative power of multi-omic analysis to prioritize clinically and biologically relevant biomarker candidates that can increase understanding of molecular mechanisms driving HCC and make an impact in patient care.

Global longitudinal strain measured by speckle tracking identifies subclinical heart involvement in patients with systemic sclerosis.

Background Systemic sclerosis is characterised by progressive cutaneous and organ fibrosis. Among all organs, a subclinical heart involvement is difficult to detect through conventional imaging. Design We evaluated whether speckle tracking-derived global longitudinal strain could help detect early subclinical systolic dysfunction in systemic sclerosis patients without overt clinical involvement. Methods A case-control, single-centre study on 52 systemic sclerosis patients and 52 age and gender-matched controls. Patients with structural heart disease, heart failure, atrial fibrillation and pulmonary hypertension were excluded. For every patient, standard echocardiographic and speckle tracking-derived variables for the systolic and diastolic function of the left ventricle and right ventricle were acquired. Results Traditional parameters of left and right systolic function did not differ between systemic sclerosis patients and controls (all P = ns). Left and right ventricular global longitudinal strain was significantly impaired in patients with systemic sclerosis when compared to controls (-19.2% vs. -21.1%; P = 0.009 and -18.2% vs. -22.3%; P = 0.012, respectively). Systemic sclerosis patients had a 2.5-fold increased risk of subclinical left ventricular systolic impairment (odds ratio 2.5, 95% confidence interval 1.1-5.5; P = 0.027) and a 3.3-fold increased risk of subclinical right ventricular systolic impairment when compared to controls (odds ratio 3.3, 95% confidence interval 1.4-7.7; P = 0.004). Alterations in the myocardial deformation pattern of systemic sclerosis patients were homogeneous in the right ventricle and eccentric in the left ventricle. Conclusions While traditional echocardiographic parameters are ineffective in detecting subclinical systolic impairment, reduced global longitudinal strain is common in patients with systemic sclerosis and significant for both ventricles. Global longitudinal strain could become a low-cost, non-invasive and reliable tool in order to detect early cardiac involvement in systemic sclerosis patients.

Inter-operator variability and source of errors in tumour response assessment for hepatocellular carcinoma treated with sorafenib.

OBJECTIVES: To assess the inter-operator concordance and the potential sources of discordance in defining response to sorafenib in hepatocellular carcinoma (HCC). METHODS: All patients who received sorafenib between September 2008 and February 2015 were scrutinised for this retrospective study. Images were evaluated separately by three radiologists with different expertise in liver imaging (operator 1, >10 years; operator 2, 5 years; operator 3, no specific training in liver imaging), according to: response evaluation radiological criteria in solid tumours (RECIST) 1.1, modified RECIST (mRECIST) and response evaluation criteria in cancer of the liver (RECICL). RESULTS: The overall response concordance between the more expert operators was good, irrespective of the criteria (RECIST 1.1, ĸ = 0.840; mRECIST, ĸ = 0.871; RECICL, ĸ = 0.819). Concordance between the less expert operator and the other colleagues was lower. The most evident discordance was in target lesion response assessment, with expert operators disagreeing mostly on lesion selection and less expert operators on lesion measurement. As a clinical correlate, overall survival was more tightly related with "progressive disease" as assessed by the expert compared to the same assessment performed by operator 3. CONCLUSIONS: Decision on whether a patient is a responder or progressor under sorafenib may vary among different operators, especially in case of a non-specifically trained radiologist. Regardless of the adopted criteria, patients should be evaluated by experienced radiologists to minimise variability in this critical instance. KEY POINTS: • Inter-operator variability in the assessment of response to sorafenib is poorly known. • The concordance between operators with expertise in liver imaging was good. • Target lesions selection was the main source of discordance between expert operators. • Concordance with non-specifically trained operator was lower, independently from the response criteria. • The non-specifically trained operator was mainly discordant in measurements of target lesions.

Identification of race-associated metabolite biomarkers for hepatocellular carcinoma in patients with liver cirrhosis and hepatitis C virus infection.

Disparities in hepatocellular carcinoma (HCC) incidence and survival have been observed between ethnic groups including African-Americans (AA) and European-Americans (EA). The evaluation of the changes in the levels of metabolites in samples stratified by race could provide a snapshot of ethnically diverse disease related pathways and identify reliable biomarkers. In this study, we considered AA and EA to investigate metabolites that may be associated with HCC in a race-specific manner. The levels of 46 metabolites in plasma samples, collected from patients recruited at MedStar Georgetown University Hospital, were analyzed by Agilent GC-qMS in selected ion monitoring (SIM) mode. A least absolute shrinkage and selection operator (LASSO) regression model was applied to select metabolites with significant changes in HCC vs. cirrhosis in three groups: (1) AA and EA combined; (2) AA separately; and (3) EA separately. In addition, metabolites that distinguish HCC cases from cirrhosis in these three groups were selected by excluding those without HCV infection. The performances of the metabolites selected by LASSO in each group were evaluated through a leave-one-out cross-validation. We identified race-specific metabolites that differentiated HCC cases from cirrhotic controls, yielding better area under the receiver operating characteristics (ROC) curve (AUC) compared to alpha-fetoprotein (AFP), the serological marker widely used for the diagnosis of HCC. This study sheds light on metabolites that could potentially be used as biomarkers for HCC by monitoring their levels in high-risk population of cirrhotic patients in a race-specific manner.

Discriminant biomarkers of acute respiratory distress syndrome associated to H1N1 influenza identified by metabolomics HPLC-QTOF-MS/MS platform.

Acute respiratory distress syndrome (ARDS) is a serious complication of influenza A (H1N1) virus infection. Its pathogenesis is unknown and biomarkers are lacking. Untargeted metabolomics allows the analysis of the whole metabolome in a biological compartment, identifying patterns associated with specific conditions. We hypothesized that LC-MS could help identify discriminant metabolites able to define the metabolic alterations occurring in patients with influenza A (H1N1) virus infection that developed ARDS. Serum samples from patients diagnosed with 2009 influenza A (H1N1) virus infection with (n = 25) or without (n = 32) ARDS were obtained on the day of hospital admission and analyzed by LC-MS/MS. Metabolite identification was determined by MS/MS analysis and analysis of standards. The specificity of the patterns identified was confirmed in patients without 2009 influenza A(H1N1) virus pneumonia (15 without and 17 with ARDS). Twenty-three candidate biomarkers were found to be significantly different between the two groups, including lysophospholipids and sphingolipids related to inflammation; bile acids, tryptophan metabolites, and thyroxine, related to the metabolism of the gut microflora. Confirmation results demonstrated the specificity of major alterations occurring in ARDS patients with influenza A (H1N1) virus infection.

Differences in liver stiffness values obtained with new ultrasound elastography machines and Fibroscan: A comparative study.

BACKGROUND AND AIMS: Whether Fibroscan thresholds can be immediately adopted for none, some or all other shear wave elastography techniques has not been tested. The aim of the present study was to test the concordance of the findings obtained from 7 of the most recent ultrasound elastography machines with respect to Fibroscan. METHODS: Sixteen hepatitis C virus-related patients with fibrosis ≥2 and having reliable results at Fibroscan were investigated in two intercostal spaces using 7 different elastography machines. Coefficients of both precision (an index of data dispersion) and accuracy (an index of bias correction factors expressing different magnitudes of changes in comparison to the reference) were calculated. RESULTS: Median stiffness values differed among the different machines as did coefficients of both precision (range 0.54-0.72) and accuracy (range 0.28-0.87). When the average of the measurements of two intercostal spaces was considered, coefficients of precision significantly increased with all machines (range 0.72-0.90) whereas of accuracy improved more scatteredly and by a smaller degree (range 0.40-0.99). CONCLUSIONS: The present results showed only moderate concordance of the majority of elastography machines with the Fibroscan results, preventing the possibility of the immediate universal adoption of Fibroscan thresholds for defining liver fibrosis staging for all new machines.

Metabolomic Characterization of Hepatocellular Carcinoma in Patients with Liver Cirrhosis for Biomarker Discovery.

Background: Metabolomics plays an important role in providing insight into the etiology and mechanisms of hepatocellular carcinoma (HCC). This is accomplished by a comprehensive analysis of patterns involved in metabolic alterations in human specimens. This study compares the levels of plasma metabolites in HCC cases versus cirrhotic patients and evaluates the ability of candidate metabolites in distinguishing the two groups. Also, it investigates the combined use of metabolites and clinical covariates for detection of HCC in patients with liver cirrhosis.Methods: Untargeted analysis of metabolites in plasma from 128 subjects (63 HCC cases and 65 cirrhotic controls) was conducted using gas chromatography coupled to mass spectrometry (GC-MS). This was followed by targeted evaluation of selected metabolites. LASSO regression was used to select a set of metabolites and clinical covariates that are associated with HCC. The performance of candidate biomarkers in distinguishing HCC from cirrhosis was evaluated through a leave-one-out cross-validation based on area under the receiver operating characteristics (ROC) curve.Results: We identified 11 metabolites and three clinical covariates that differentiated HCC cases from cirrhotic controls. Combining these features in a panel for disease classification using support vector machines (SVM) yielded better area under the ROC curve compared with alpha-fetoprotein (AFP).Conclusions: This study demonstrates the combination of metabolites and clinical covariates as an effective approach for early detection of HCC in patients with liver cirrhosis.Impact: Further investigation of these findings may improve understanding of HCC pathophysiology and possible implication of the metabolites in HCC prevention and diagnosis. Cancer Epidemiol Biomarkers Prev; 26(5); 675-83. ©2016 AACR.