Background Malignant tumours seriously threaten human life and health, and effective treatments for cancer are still being explored. The ability of SHC SH2 domain-binding protein 1 (SHCBP1) to induce cell cycle disturbance and inhibit tumour growth has been increasingly studied, but its dynamic role in the tumour cell cycle and corresponding effects leading to mitotic catastrophe and DNA damage have rarely been studied. Results In this paper, we found that the nucleoprotein SHCBP1 exhibits dynamic spatiotemporal expression during the tumour cell cycle, and SHCBP1 knockdown slowed cell cycle progression by inducing spindle disorder, as reflected by premature mitotic entry and multipolar spindle formation. This dysfunction was caused by G2/M checkpoint impairment mediated by downregulated WEE1 kinase and NEK7 (a member of the mammalian NIMA-related kinase family) expression and upregulated centromere/kinetochore protein Zeste White 10 (ZW10) expression. Moreover, both in vivo and in vitro experiments confirmed the significant inhibitory effects of SHCBP1 knockdown on tumour growth. Based on these findings, SHCBP1 knockdown in combination with low-dose DNA-damaging agents had synergistic tumouricidal effects on tumour cells. In response to this treatment, tumour cells were forced into the mitotic phase with considerable unrepaired DNA lesions, inducing mitotic catastrophe. These synergistic effects were attributed not only to the abrogation of the G2/M checkpoint and disrupted spindle function but also to the impairment of the DNA damage repair system, as demonstrated by mass spectrometry-based proteomic and western blotting analyses. Consistently, patients with low SHCBP1 expression in tumour tissue were more sensitive to radiotherapy. However, SHCBP1 knockdown combined with tubulin-toxic drugs weakened the killing effect of the drugs on tumour cells, which may guide the choice of chemotherapeutic agents in clinical practice. Conclusion In summary, we elucidated the role of the nucleoprotein SHCBP1 in tumour cell cycle progression and described a novel mechanism by which SHCBP1 regulates tumour progression and through which targeting SHCBP1 increases sensitivity to DNA-damaging agent therapy, indicating its potential as a cancer treatment. Graphical Abstract

Multiple studies showed that metabolic disorders play a critical role in respiratory infectious diseases, including COVID-19. Metabolites contained in small extracellular vesicles (sEVs) are different from those in plasma at the acute stage, while the metabolic features of plasma sEVs of COVID-19 survivors remain unknown. Here, we used a nanopore membrane-based microfluidic chip for plasma sEVs separation, termed ExoSEC, and compared the sEVs obtained by UC, REG, and ExoSEC in terms the time, cost, purity, and metabolic features. The results indicated the ExoSEC was much less costly, provided higher purity by particles/proteins ratio, and achieved 205-fold and 2-fold higher sEVs yield, than UC and REG, respectively. Moreover, more metabolites were identified and several signaling pathways were significantly enriched in ExoSEC-sEVs compared to UC-sEVs and REG-sEVs. Furthermore, we detected 306 metabolites in plasma sEVs using ExoSEC from recovered asymptomatic (RA), moderate (RM), and severe/critical COVID-19 (RS) patients without underlying diseases 3 months after discharge. Our study demonstrated that COVID-19 survivors, especially RS, experienced significant metabolic alteration and the dysregulated pathways mainly involved fatty acid biosynthesis, phenylalanine metabolism, etc. Metabolites of the fatty acid biosynthesis pathway bore a significantly negative association with red blood cell counts and hemoglobin, which might be ascribed to hypoxia or respiratory failure in RM and RS but not in RA at the acute stage. Our study confirmed that ExoSEC could provide a practical and economical alternative for high throughput sEVs metabolomic study.

The coronavirus disease 2019 (COVID-19), which affects multiple organs, is causing an unprecedented global public health crisis. Most COVID-19 patients recover gradually upon appropriate interventions. Viruses were reported to utilize the small extracellular vesicles (sEVs), containing a cell-specific cargo of proteins, lipids, and nucleic acids, to escape the attack from the host’s immune system. This study aimed to examine the sEVs lipid profile of plasma of recovered COVID-19 patients (RCs). Plasma sEVs were separated from 83 RCs 3 months after discharge without underlying diseases, including 18 recovered asymptomatic patients (RAs), 32 recovered moderate patients (RMs), and 33 recovered severe and critical patients (RSs), and 19 healthy controls (HCs) by Total Exosome Isolation Kit. Lipids were extracted from sEVs and then subjected to targeted liquid chromatography-mass spectrometry. The size, concentration, and distribution of sEVs did not differ in RCs and HCs as validated by transmission electron microscopy, nanoparticle tracking analysis, and immunoblot analysis. Fifteen subclasses of 508 lipids were detected in plasma sEVs from HCs, RAs, RMs, and RSs, such as phosphatidylcholines (PCs) and diacylglycerols (DAGs), etc. Total lipid intensity displayed downregulation in RCs compared with HCs. The relative abundance of DAGs gradually dropped, whereas PCs, lysophosphatidylcholines, and sphingomyelins were higher in RCs relative to HCs, especially in RSs. 88 lipids out of 241 in sEVs of RCs were significantly different and a conspicuous increase was revealed with disease status. The sEVs lipids alternations were found to be significantly correlated with the clinical indices in RCs and HCs, suggesting that the impact of COVID-19 on lipid metabolism lingered for a long time. The lipid abnormalities bore an intimate link with glycerophospholipid metabolism and glycosylphosphatidylinositol anchor biosynthesis. Furthermore, the lipidomic analysis showed that RCs were at higher risk of developing diabetes and sustaining hepatic impairment. The abnormality of immunomodulation in RCs might still exist. The study may offer new insights into the mechanism of organ dysfunction and help identify novel therapeutic targets in the RCs.

To explore the recovery of renal function in severely ill coronavirus disease (COVID-19) survivors and determine the plasma metabolomic profile of patients with different renal outcomes 3 months after discharge, we included 89 severe COVID-19 survivors who had been discharged from Wuhan Union Hospital for 3 months. All patients had no underlying kidney disease before admission. At patient recruitment, renal function assessment, laboratory examination, chest computed tomography (CT) were performed. Liquid chromatography-mass spectrometry was used to detect metabolites in the plasma. We analyzed the longitudinally change in the estimated glomerular filtration rate (eGFR) based on serum creatinine and cystatin-c levels using the CKD-EPI equation and explored the metabolomic differences in patients with different eGFR change patterns from hospitalization to 3 months after discharge. Lung CT showed good recovery; however, the median eGFR significantly decreased at the 3-month follow-up. Among the 89 severely ill COVID-19 patients, 69 (77.5%) showed abnormal eGFR (<90 mL/min per 1.73 m2) at 3 months after discharge. Age (odds ratio [OR] = 1.26, 95% confidence interval [CI] = 1.08-1.47, p = 0.003), body mass index (OR = 1.97, 95% CI = 1.20-3.22, p = 0.007), and cystatin-c level (OR = 1.22, 95% CI = 1.07-1.39, p = 0.003) at discharge were independent risk factors for post-discharge abnormal eGFR. Plasma metabolomics at the 3-months follow-up revealed that β-pseudouridine, uridine, and 2-(dimethylamino) guanosine levels gradually increased with an abnormal degree of eGFR. Moreover, the kynurenine pathway in tryptophan metabolism, vitamin B6 metabolism, cysteine and methionine metabolism, and arginine biosynthesis were also perturbed in survivors with abnormal eGFR.

More and more patients suffered from Coronavirus disease 2019 (COVID-19) have got recovery gradually due to suitable intervention. Increasing data mainly studies the clinical characteristics of recovered COVID-19 patients, and their molecular changes especially proteome changes also play the same important role in understanding of biological characteristics of recovered COVID-19 patients as clinical characteristics do. In our study, we reported the whole lung-ground glass-CT value-average of mild/severe recovered patients 3 months after discharge without underlying diseases was significantly lower than that of healthy subjects. Then we isolated the extracellular vesicles (EVs) of plasma from 19 healthy subjects and 67 recovered COVID-19 patients. Mass Spectrometry was used to catalogue the proteins of these EVs compared to a defined group of controls. Identified 174 proteins were differentially expressed in the EVs of COVID-19 patients compared with healthy subjects, which involved in lipid metabolic process, response to cellular, and response to stress oxygen-containing compound. Besides, we identified several protein of plasma EVs in recovered patients associated with coagulation activity, inflammatory reaction, immune response, and low organ function. In addition, proteins correlating with clinical index such as alkaline phosphatase (ALP) and alanine aminotransferase (ALT) were also detected. Moreover, we also identified many unique or characteristic associations found in the recovered COVID-19 patients, which especially involved the kidney, serum electrolyte levels, and inflammation functions. This finding suggests that monitoring the situation of recovered patients might be useful, especially the indexes of coagulation, inflammation, immunity, and organ function, which can prevent bleeding, reinfection and organ dysfunction.

This study aimed to explore the associations between cerebral white matter (WM) alterations, mental health status, and metabolism in recovered COVID-19 patients. We included 28 recovered COVID-19 patients and 27 healthy controls between April 2020 and June 2020. Demographic data, the mental health scores, diffusion-tensor imaging (DTI) data, and plasma metabolomics were collected and compared between the two groups. Tract-based spatial statistics and graph theory approaches were used for DTI data analysis. Untargeted metabolomics analysis of the plasma was performed. Correlation analyses were performed between these characteristics. Recovered COVID-19 patients showed decreased fractional anisotropy, increased mean diffusivity and radial diffusivity values in widespread brain regions, and significantly lower global efficiency, longer shortest path length, and less nodal local efficiency in superior occipital gyrus (all, P < 0.05, Bonferroni corrected). Our results also demonstrated significantly different plasma metabolic profiling in recovered COVID-19 patients even at 3 months after their hospital discharge, which was mainly related to purine pathways, amino acids, lipids, and amine metabolism. Certain regions with cerebral WM alterations in the recovered patients showed significant correlations with different metabolites and the mental health scores. We observed multiple alterations in both WM integrity and plasma metabolomics that may explain the deteriorated mental health of recovered COVID-19 patients. These findings may provide potential biomarkers for the mental health evaluation for the recovered COVID-19 patients and potential targets for novel therapeutics.

Background Elucidation of the molecular mechanisms involved in the pathogenesis of coronavirus disease 2019 (COVID-19) may help to discover therapeutic targets. Methods To determine the metabolomic profile of circulating plasma from COVID-19 survivors with pulmonary sequelae 3 months after discharge, a random, outcome-stratified case-control sample was analyzed. We enrolled 103 recovered COVID-19 patients as well as 27 healthy donors, and performed pulmonary function tests, computerized tomography (CT) scans, laboratory examinations, and liquid chromatography-mass spectrometry. Results Plasma metabolite profiles of COVID-19 survivors with abnormal pulmonary function were different from those of healthy donors or subjects with normal pulmonary function. These alterations were associated with disease severity and mainly involved amino acid and glycerophospholipid metabolic pathways. Furthermore, increased levels of triacylglycerols, phosphatidylcholines, prostaglandin E2, arginine, and decreased levels of betain and adenosine were associated with pulmonary CO diffusing capacity and total lung capacity. The global plasma metabolomic profile differed between subjects with abnormal and normal pulmonary function. Conclusions Further metabolite-based analysis may help to identify the mechanisms underlying pulmonary dysfunction in COVID-19 survivors, and provide potential therapeutic targets in the future.

It has been reported that melatonin can relieve the symptoms of chronic obstructive pulmonary disease (COPD) by improving sleep quality, that is to say, the pineal secreted hormone melatonin has a protective effect in the pathogenesis of COPD, but its underlying mechanism remains unclear. In this study, we recruited 73 people into control (n = 22), stable COPD (n = 20), and acute exacerbation of COPD (n = 31) groups to detect the serum melatonin levels. Then, through the mouse model, we employed a systematic study based on the metabolomic and transcriptomic analyses to investigate the molecular mechanisms involved in the progression of the disease. Circulating melatonin in acute exacerbation of COPD patients was decreased compared with that in healthy donors and stable COPD patients. The serum melatonin level was positively correlated with lung function parameters, such as FEV1, FEV1/FVC, and FEV1% predicted in acute exacerbation of COPD patients. Animal experiments showed that melatonin can not only alleviate chronic lipopolysaccharide (LPS)-induced mouse lung destruction and chronic lung inflammation but also reduce necroptosis (RIP1/RIP3/MLKL), a programmed cell death process in bronchial epithelial cells. The protective effect of melatonin on chronic lung inflammation was further suggested to be dependent on targeting its membrane receptor MT1/MT2. In addition, transcriptomic and metabolomic profiling in the lungs of mice indicated that LPS can induce perturbations of the mainstream metabolites associated with amino acid and energy metabolism. Melatonin may reduce the necroptosis by modifying the disordered pathways of alanine, aspartate, and glutamate metabolism caused by LPS. This study suggests that melatonin may act as a potential therapeutic agent for alleviating the chronic inflammation associated with COPD.

Background: It remains unclear whether discharged COVID-19 patients have fully recovered from severe complications, including the differences in the post-infection metabolomic profiles of patients with different disease severities. Methods: COVID-19-recovered patients, who had no previous underlying diseases and were discharged from Wuhan Union Hospital for 3 months, and matched healthy controls (HCs) were recruited in this prospective cohort study. We examined the blood biochemical indicators, cytokines, lung computed tomography scans, including 39 HCs, 18 recovered asymptomatic (RAs), 34 recovered moderate (RMs), and 44 recovered severe/ critical patients (RCs). A liquid chromatography-mass spectrometry-based metabolomics approach was employed to profile the global metabolites of fasting plasma of these participants. Results: Clinical data and metabolomic profiles suggested that RAs recovered well, but some clinical indicators and plasma metabolites in RMs and RCs were still abnormal as compared with HCs, such as decreased taurine, succinic acid, hippuric acid, some indoles, and lipid species. The disturbed metabolic pathway mainly involved the tricarboxylic cycle, purine, and glycerophospholipid metabolism. Moreover, metabolite alterations differ between RMs and RCs when compared with HCs. Correlation analysis revealed that many differential metabolites were closely associated with inflammation and the renal, pulmonary, heart, hepatic, and coagulation system functions. Conclusion: We uncovered metabolite clusters pathologically relevant to the recovery state in discharged COVID-19 patients which may provide new insights into the pathogenesis of potential organ damage in recovered patients.

Background: The ongoing outbreak of novel coronavirus disease (COVID-19), which started in Wuhan, China in December 2019 has developed into a global pandemic. Among critical patients, death seems likely once a composite end point event (CEPE), such as acute respiratory distress syndrome (ARDS) requiring mechanical ventilation, other organ failure needing an admission to the intensive care unit (ICU) or shock occur. However, until now, little is known about the change pattern of critical cases, the crucial turning points and high-risk period before the CEPEs occur.Methods: In this observational multicenter study, we examined 411 severe and critical COVID-19 patients admitted from Jan 12 to Feb 20, 2020, and their outcomes were followed up until Mar 16, 2020. These patients were divided into two groups (Group 1: critical patients who developed CEPE; Group 2: severe patients without CEPE and discharged). In order to predict the likelihood of CEPE during hospital stay, a baseline nomogram, based on multivariate logistic regression analysis, was constructed and validated. The linear mixed model (LMM) was used in critical patients to identify the burning point and the burning-point-related indicators (included in an early warning system), and their weights were calculated on the basis of their standardized changes after normalization.Findings: We constructed a baseline nomogram containing five independent risk factors (blood urea nitrogen [BUN]>5·3mmol/L, D-dimer>0·97μg/ml, lactate dehydrogenase [LDH]>354U/L, C reactive protein [CRP]>21·4mg/ml, and direct bilirubin [DBIL]>4·6mmol/L) to identify high-risk patients who might develop CEPE. In the patients, the receiver operating characteristic (ROC) values in the training set and the validation set were 0·919 and 0·864 respectively. Importantly, we identified a burning point, from which some indicators started to change dramatically and CEPE is about five days away. Six most significant laboratory indicators (CRP, BUN, DBIL, platelet [PLT], neutrophil-to-lymphocyte ratio [NLR], and LDH) were selected as burning-point indicators and were integrated into the early warning system. Their continuous change estimates were 13·22 mg/L, 1·03 mmol/L, 0·77 mmol/L, -6·05 x109/L, 8·57, 128·0U/L respectively, and weights of them were 37·71%, 15·28%, 15·09%, 12·04%, 11·73%, and 8·14% respectively. The time interval between the burning point and CEPE was deemed a high-risk period of CEPE.Interpretation: The baseline nomogram model can be employed at admission to identify the high-risk patients who might develop CEPE. During hospitalization, by monitoring the changes in the burning point indicators in the early warning system, clinicians can combine their respective weights to determine whether the patient has crossed the burning point. If so, CEPE will occur within five days. Hopefully, by using this early warning system, clinicians could intervene proactively before a CEPE develops, thereby avoiding irreversible disease progression and minimizing the likelihood of fatality.Funding Statement: This paper was supported in part by the National Natural Science Special Foundation of China for COVID-19(NO.82041018), the Independent Innovation Research Fund for Huazhong University of Science and Technology (2020kfyXGYJ).Declaration of Interests: The authors declare no competing interests.Ethics Approval Statement: This study was approved by the institutional review board of Medical Ethics Committee of Union Hospital, Tongji Medical College, Huazhong University of Science and Technology (NO.0036). Written informed consent was exempted by the Ethics Committee of the designated hospital for this emerging infectious disease based in Union Hospital, Wuhan, China.

Acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) are life-threatening clinical conditions predominantly arising from uncontrolled inflammatory reactions. It has been found that the administration of astaxanthin (AST) can exert protective effects against lipopolysaccharide (LPS)-induced ALI; however, the robust genetic signatures underlying LPS induction and AST treatment remain obscure. Here we performed a statistical meta-analysis of five publicly available gene expression datasets from LPS-induced ALI mouse models, conducted RNA-sequencing (RNA-seq) to screen differentially expressed genes (DEGs) in response to LPS administration and AST treatment, and integrative analysis to determine robust genetic signatures associated with LPS-induced ALI onset and AST administration. Both the meta-analyses and our experimental data identified a total of 198 DEGs in response to LPS administration, and 11 core DEGs (Timp1, Ly6i, Cxcl13, Irf7, Cxcl5, Ccl7, Isg15, Saa3, Saa1, Tgtp1, and Gbp11) were identified to be associated with AST therapeutic effects. Further, the 11 core DEGs were verified by quantitative real-time PCR (qRT-PCR) and immunohistochemistry (IHC), and functional enrichment analysis revealed that these genes are primarily associated with neutrophils and chemokines. Collectively, these findings unearthed the robust genetic signatures underlying LPS administration and the molecular targets of AST for ameliorating ALI/ARDS which provide directions for further research.

ABSTRACTPleural effusion is a common respiratory disease worldwide; however, rapid and accurate diagnoses of tuberculosis pleural effusion (TPE) and malignancy pleural effusion (MPE) remain challenging. Although extracellular vesicles (EVs) have been confirmed as promising sources of disease biomarkers, little is known about the metabolite compositions of its subpopulations and their roles in the diagnosis of pleural effusion. Here, we performed metabolomics and lipidomics analysis to investigate the metabolite characteristics of two EV subpopulations derived from pleural effusion by differential ultracentrifugation, namely large EVs (lEVs, pelleted at 20,000 × g) and small EVs (sEVs, pelleted at 110,000 × g), and assessed their metabolite differences between tuberculosis and malignancy. A total of 579 metabolites, including amino acids, acylcarnitines, organic acids, steroids, amides and various lipid species, were detected. The results showed that the metabolic profiles of lEVs and sEVs overlapped with and difference from each other but significantly differed from those of pleural effusion. Additionally, different type of vesicles and pleural effusion showed unique metabolic enrichments. Furthermore, lEVs displayed more significant and larger metabolic alterations between the tuberculosis and malignancy groups, and their differential metabolites were more closely related to clinical parameters than those of sEV. Finally, a panel of four biomarker candidates, including phenylalanine, leucine, phosphatidylcholine 35:0, and sphingomyelin 44:3, in pleural lEVs was defined based on the comprehensive discovery and validation workflow. This panel showed high performance for distinguishing TPE and MPE, particularly in patients with delayed or missed diagnosis, such as the area under the receiver‐operating characteristic curve (AUC) >0.95 in both sets. We conducted comprehensive metabolic profiling analysis of EVs, and further explored the metabolic reprogramming of tuberculosis and malignancy at the level of metabolites in lEVs and sEVs, providing insight into the mechanism of pleural effusion, and identifying novel biomarkers for diagnosing TPE and MPE.

Forkhead box M1 (FOXM1), a transcriptional regulator of G1/S and G2/M transition and M phase progression in the cell cycle, plays a principal role in many physiological and pathological processes. A growing number of studies have focused on the relationship between abnormal FOXM1 expression and pulmonary diseases, such as lung cancer, chronic obstructive pulmonary disease (COPD), asthma, acute lung injury (ALI), pulmonary fibrosis, and pulmonary arterial hypertension (PAH). These studies indicate that the FOXM1 regulatory network is a major predictor of poor outcomes, especially in lung cancer, and provide novel insight into various pulmonary diseases. For the first time, this review summarizes the mechanistic relationship between FOXM1 dysregulation and pulmonary diseases, the benefits of targeting abnormal FOXM1 expression, and the questions that remain to be addressed in the future.

The interleukin-(IL)-1 subfamily consists of IL-1α, IL-1β, IL-1 receptor antagonist IL-1Ra and IL-33. These cytokines are the main members of the IL-1 family and have been widely recognized as having significant roles in pro-inflammatory and immunomodulatory actions. Mounting evidence has revealed that these cytokines also play key roles in the regulation of glycolysis, which is an important metabolic pathway in most organisms that provides energy. Dysregulation of glycolysis is associated with various diseases, including type 2 diabetes, rheumatoid arthritis (RA) and cancer. We reviewed studies addressing the important roles of IL-1 subfamily cytokines, with particular focus on their ability to regulate glycolysis in disease states. In this review, we summarize the potential roles of IL-1 subfamily members in glycolysis in disease states and address the underlying mechanisms. Furthermore, we discuss the potential of these cytokines as therapeutic targets in clinical applications to provide insight into possible therapeutic strategies for treatment, especially for cancers.

Adrenergic receptors (ARs), especially β-ARs, are constitutively expressed in most mammalian cells and are associated with various malignancies including lung cancer. Epidemiologic studies have reported that activation of β-AR signalling promotes the development and progression of lung cancer and that pharmacological interference by β-AR blockers could partially reverse lung cancer progression. In this review, we mainly focus on the role of β-ARs in lung cancer and then reveal the possible application of AR blockers in anti-tumour therapy for lung cancer.