CD69 controls the uptake of L-tryptophan through LAT1-CD98 and AhR-dependent secretion of IL-22 in psoriasis.

The activation marker CD69 is expressed by skin γδ T cells. Here we found that CD69 controlled the aryl hydrocarbon receptor (AhR)-dependent secretion of interleukin 22 (IL-22) by γδ T cells, which contributed to the development of psoriasis induced by IL-23. CD69 associated with the aromatic-amino-acid-transporter complex LAT1-CD98 and regulated its surface expression and uptake of L-tryptophan (L-Trp) and the intracellular quantity of L-Trp-derived activators of AhR. In vivo administration of L-Trp, an inhibitor of AhR or IL-22 abrogated the differences between CD69-deficient mice and wild-type mice in skin inflammation. We also observed LAT1-mediated regulation of AhR activation and IL-22 secretion in circulating Vγ9(+) γδ T cells of psoriatic patients. Thus, CD69 serves as a key mediator of the pathogenesis of psoriasis by controlling LAT1-CD98-mediated metabolic cues.

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.

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.

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.

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.

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.

Topic model-based mass spectrometric data analysis in cancer biomarker discovery studies.

BACKGROUND: A fundamental challenge in quantitation of biomolecules for cancer biomarker discovery is owing to the heterogeneous nature of human biospecimens. Although this issue has been a subject of discussion in cancer genomic studies, it has not yet been rigorously investigated in mass spectrometry based proteomic and metabolomic studies. Purification of mass spectometric data is highly desired prior to subsequent analysis, e.g., quantitative comparison of the abundance of biomolecules in biological samples. METHODS: We investigated topic models to computationally analyze mass spectrometric data considering both integrated peak intensities and scan-level features, i.e., extracted ion chromatograms (EICs). Probabilistic generative models enable flexible representation in data structure and infer sample-specific pure resources. Scan-level modeling helps alleviate information loss during data preprocessing. We evaluated the capability of the proposed models in capturing mixture proportions of contaminants and cancer profiles on LC-MS based serum proteomic and GC-MS based tissue metabolomic datasets acquired from patients with hepatocellular carcinoma (HCC) and liver cirrhosis as well as synthetic data we generated based on the serum proteomic data. RESULTS: The results we obtained by analysis of the synthetic data demonstrated that both intensity-level and scan-level purification models can accurately infer the mixture proportions and the underlying true cancerous sources with small average error ratios (<7 %) between estimation and ground truth. By applying the topic model-based purification to mass spectrometric data, we found more proteins and metabolites with significant changes between HCC cases and cirrhotic controls. Candidate biomarkers selected after purification yielded biologically meaningful pathway analysis results and improved disease discrimination power in terms of the area under ROC curve compared to the results found prior to purification. CONCLUSIONS: We investigated topic model-based inference methods to computationally address the heterogeneity issue in samples analyzed by LC/GC-MS. We observed that incorporation of scan-level features have the potential to lead to more accurate purification results by alleviating the loss in information as a result of integrating peaks. We believe cancer biomarker discovery studies that use mass spectrometric analysis of human biospecimens can greatly benefit from topic model-based purification of the data prior to statistical and pathway analyses.

Fingerprinting-based metabolomic approach with LC-MS to sleep apnea and hypopnea syndrome: a pilot study.

Sleep apnea and hypopnea syndrome (SAHS) is a multicomponent disorder, with associated cardiovascular and metabolic alterations, second in order of frequency among respiratory disorders. Sleep apnea is diagnosed with an overnight sleep test called a polysomnogram, which requires having the patient in hospital. In addition, a more clear classification of patients according to mild and severe presentations would be desirable. The aim of the present study was to assess the relative metabolic changes in SAHS to identify new potential biomarkers for diagnosis, able to evaluate disease severity to establish response to therapeutic interventions and outcomes. For this purpose, metabolic fingerprinting represents a valuable strategy to monitor, in a nontargeted manner, the changes that are at the base of the pathophysiological mechanism of SAHS. Plasma samples of 33 SAHS patients were collected after polysomnography and analyzed with LC coupled to MS (LC-QTOF-MS). After data treatment and statistical analysis, signals differentiating nonsevere and severe patients were detected. Putative identification of 14 statistically significant features was obtained and changes that can be related to the episodes of hypoxia/reoxygenation (inflammation) have been highlighted. Among them, the patterns of variation of platelet activating factor and lysophospholipids, together with some compounds related to differential activity of the gut microflora (bile pigments and pipecolic acid) open new lines of research that will benefit our understanding of the alterations, offering new possibilities for adequate monitoring of the stage of the disease.

Eplerenone attenuated cardiac steatosis, apoptosis and diastolic dysfunction in experimental type-II diabetes.

BACKGROUND: Cardiac steatosis and apoptosis are key processes in diabetic cardiomyopathy, but the underlying mechanisms have not been elucidated, leading to a lack of effective therapy. The mineralocorticoid receptor blocker, eplerenone, has demonstrated anti-fibrotic actions in the diabetic heart. However, its effects on the fatty-acid accumulation and apoptotic responses have not been revealed. METHODS: Non-hypertensive Zucker Diabetic Fatty (ZDF) rats received eplerenone (25 mg/kg) or vehicle. Zucker Lean (ZL) rats were used as control (n = 10, each group). After 16 weeks, cardiac structure and function was examined, and plasma and hearts were isolated for biochemical and histological approaches. Cultured cardiomyocytes were used for in vitro assays to determine the direct effects of eplerenone on high fatty acid and high glucose exposed cells. RESULTS: In contrast to ZL, ZDF rats exhibited hyperglycemia, hyperlipidemia, insulin-resistance, cardiac steatosis and diastolic dysfunction. The ZDF myocardium also showed increased mitochondrial oxidation and apoptosis. Importantly, eplerenone mitigated these events without altering hyperglycemia. In cultured cardiomyocytes, high-concentrations of palmitate stimulated the fatty-acid uptake (in detriment of glucose assimilation), accumulation of lipid metabolites, mitochondrial dysfunction, and apoptosis. Interestingly, fatty-acid uptake, ceramides formation and apoptosis were also significantly ameliorated by eplerenone. CONCLUSIONS: By blocking mineralocorticoid receptors, eplerenone may attenuate cardiac steatosis and apoptosis, and subsequent remodelling and diastolic dysfunction in obese/type-II diabetic rats.

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.

Combination of LC-MS- and GC-MS-based metabolomics to study the effect of ozonated autohemotherapy on human blood.

Ozonated autohemotherapy (O3-AHT) is a medical approach during which blood obtained from the patient is ozonated and injected back into the body. Despite an increasing number of evidence that O3-AHT is safe, this type of therapy remains controversial. To extend knowledge about the changes in blood evoked by O3-AHT, LC-MS- and GC-MS-based metabolic fingerprinting was used to compare plasma samples obtained from blood before and after the treatment with potentially therapeutic concentrations of ozone. The procedure was performed in PVC bags utilized for blood storage to study also possible interactions between ozone and plastic. By use of GC-MS, an increase in lactic acid and pyruvic acid was observed, which indicated an increased rate of glycolysis. With LC-MS, changes in plasma antioxidants were observed. Moreover, concentrations of lipid oxidation products (LOP) and lysophospholipids were increased after ozone treatment. This is the first report of increased LOPs metabolites after ozonation of blood. Seven metabolites detected by LC-QTOF-MS only in ozonated samples could be considered as novel biomarkers of oxidative stress. Several plasticizers have been detected by both techniques in blood stored in PVC bags. PVC is known to be an ozone resistant material, but ozonation of blood in PVC bags stimulates leaching of plasticizers into the blood.

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.

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.

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.

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.

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.

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.