The coronavirus disease 2019 (COVID-19) pandemic poses a current world-wide public health threat. However, little is known about its hallmarks compared to other infectious diseases. Here, we report the single-cell transcriptional landscape of longitudinally collected peripheral blood mononuclear cells (PBMCs) in both COVID-19- and influenza A virus (IAV)-infected patients. We observed increase of plasma cells in both COVID-19 and IAV patients and XIAP associated factor 1 (XAF1)-, tumor necrosis factor (TNF)-, and FAS-induced T cell apoptosis in COVID-19 patients. Further analyses revealed distinct signaling pathways activated in COVID-19 (STAT1 and IRF3) versus IAV (STAT3 and NFκB) patients and substantial differences in the expression of key factors. These factors include relatively increase of interleukin ( IL ) 6R and IL6ST expression in COVID-19 patients but similarly increased IL-6 concentrations compared to IAV patients, supporting the clinical observations of increased proinflammatory cytokines in COVID-19 patients. Thus, we provide the landscape of PBMCs and unveil distinct immune response pathways in COVID-19 and IAV patients.

BackgroundOur previous study identified AKT1, AKT2 and AKT3 as unfavorable prognostic factors for patients with hepatocellular carcinoma (HCC). However, limited data are available on their exact mechanisms in HCC. Since microRNAs (miRNAs) are implicated in various human cancers including HCC, we aimed to screen miRNAs targeting AKTs and investigate their underlying mechanisms in HCC by integrating bioinformatics prediction, network analysis, functional assay and clinical validation.MethodsFive online programs of miRNA target prediction and RNAhybrid which calculate the minimum free energy (MFE) of the duplex miRNA:mRNA were used to screen optimized miRNA-AKT interactions. Then, miRNA-regulated protein interaction network was constructed and 5 topological features (‘Degree’, ‘Node-betweenness’, ‘Edge-betweenness’, ‘Closeness’ and ‘Modularity’) were analyzed to link candidate miRNA-AKT interactions to oncogenesis and cancer hallmarks. Further systematic experiments were performed to validate the prediction results.ResultsSix optimized miRNA-AKT interactions (miR-149-AKT1, miR-302d-AKT1, miR-184-AKT2, miR-708-AKT2, miR-122-AKT3 and miR-124-AKT3) were obtained by combining the miRNA target prediction and MFE calculation. Then, 103 validated targets for the 6 candidate miRNAs were collected from miRTarBase. According to the enrichment analysis on GO items and KEGG pathways, these validated targets were significantly enriched in many known oncogenic pathways for HCC. In addition, miRNA-regulated protein interaction network were divided into 5 functional modules. Importantly, AKT1 and its interaction with mTOR respectively had the highest node-betweenness and edge-betweenness, implying their bottleneck roles in the network. Further experiments confirmed that miRNA-149 directly targeted AKT1 in HCC by a miRNA luciferase reporter approach. Then, re-expression of miR-149 significantly inhibited HCC cell proliferation and tumorigenicity by regulating AKT1/mTOR pathway. Notably, miR-149 down-regulation in clinical HCC tissues was correlated with tumor aggressiveness and poor prognosis of patients.ConclusionThis comprehensive analysis identified a list of miRNAs targeting AKTs and revealed their critical roles in HCC malignant progression. Especially, miR-149 may function as a tumor suppressive miRNA and play an important role in inhibiting the HCC tumorigenesis by modulating the AKT/mTOR pathway. Our clinical evidence also highlight the prognostic potential of miR-149 in HCC. The newly identified miR-149/AKT/mTOR axis might be a promising therapeutic target in the prevention and treatment of HCC.Electronic supplementary materialThe online version of this article (doi:10.1186/1476-4598-13-253) contains supplementary material, which is available to authorized users.

Background: SARS-CoV-2-caused coronavirus disease (COVID-19) is posing a large casualty. The features of COVID-19 patients with and without pneumonia, SARS-CoV-2 transmissibility in asymptomatic carriers, and factors predicting disease progression remain unknown. Methods: We collected information on clinical characteristics, exposure history, and laboratory examinations of all laboratory-confirmed COVID-19 patients admitted to PLA General Hospital. Cox regression analysis was applied to identify prognostic factors. The last follow-up was February 18, 2020. Results: We characterized 55 consecutive COVID-19 patients. The mean incubation was 8.42 (95% confidence interval [CI], 6.55-10.29) days. The mean SARS-CoV-2-positive duration from first positive test to conversion was 9.71 (95%CI, 8.21-11.22) days. COVID-19 course was approximately 2 weeks. Asymptomatic carriers might transmit SARS-CoV-2. Compared to patients without pneumonia, those with pneumonia were 15 years older and had a higher rate of hypertension, higher frequencies of having a fever and cough, and higher levels of interleukin-6 (14.61 vs. 8.06pg/mL, P=0.040), B lymphocyte proportion (13.0% vs.10.0%, P=0.024), low account (<190/µL) of CD8 + T cells (33.3% vs. 0, P=0.019). Multivariate Cox regression analysis indicated that circulating interleukin-6 and lactate independently predicted COVID-19 progression, with a hazard ratio (95%CI) of 1.052 (1.000-1.107) and 1.082 (1.013-1.155), respectively. During disease course, T lymphocytes were .CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.(which was not peer-reviewed) The copyright holder for this preprint .

AimTo screen novel markers for hepatocellular carcinoma (HCC) by a combination of expression profile, interaction network analysis and clinical validation.MethodsHCC significant molecules which are differentially expressed or had genetic variations in HCC tissues were obtained from five existing HCC related databases (OncoDB.HCC, HCC.net, dbHCCvar, EHCO and Liverome). Then, the protein-protein interaction (PPI) network of these molecules was constructed. Three topological features of the network ('Degree', 'Betweenness', and 'Closeness') and the k-core algorithm were used to screen candidate HCC markers which play crucial roles in tumorigenesis of HCC. Furthermore, the clinical significance of two candidate HCC markers growth factor receptor-bound 2 (GRB2) and GRB2-associated-binding protein 1 (GAB1) was validated.ResultsIn total, 6179 HCC significant genes and 977 HCC significant proteins were collected from existing HCC related databases. After network analysis, 331 candidate HCC markers were identified. Especially, GAB1 has the highest k-coreness suggesting its central localization in HCC related network, and the interaction between GRB2 and GAB1 has the largest edge-betweenness implying it may be biologically important to the function of HCC related network. As the results of clinical validation, the expression levels of both GRB2 and GAB1 proteins were significantly higher in HCC tissues than those in their adjacent nonneoplastic tissues. More importantly, the combined GRB2 and GAB1 protein expression was significantly associated with aggressive tumor progression and poor prognosis in patients with HCC.ConclusionThis study provided an integrative analysis by combining expression profile and interaction network analysis to identify a list of biologically significant HCC related markers and pathways. Further experimental validation indicated that the aberrant expression of GRB2 and GAB1 proteins may be strongly related to tumor progression and prognosis in patients with HCC. The overexpression of GRB2 in combination with upregulation of GAB1 may be an unfavorable prognostic factor for HCC.

BackgroundNucleolin, as a multifunctional protein, has been demonstrated to play an oncogenic role in human hepatocellular carcinoma (HCC). The aim of this study was to investigate the expression pattern of nucleolin in HCC and determine its correlation with tumor progression and prognosis.MethodsNucleolin expression at both mRNA and protein levels in HCC and adjacent nonneoplastic tissues were respectively detected by quantitative real time polymerase chain reaction (Q-PCR), immunohistochemistry and western blotting.ResultsNucleolin expression, at both mRNA and protein levels, was significantly higher in HCC tissues than in the adjacent nonneoplastic tissues (both P < 0.001). In addition, the elevated nucleolin expression was markedly correlated with advanced tumor stage (P = 0.001), high tumor grade (P = 0.02) and serum AFP level (P = 0.008). Moreover, HCC patients with high nucleolin expression had shorter 5-year disease-free survival and shorter 5-year overall survival than those with low expression (both P < 0.001). Furthermore, the Cox proportional hazards model showed that nucleolin expression was an independent poor prognostic factor for both 5-year disease-free survival (hazards ratio [HR] = 3.696, 95% confidence interval [CI] = 1.662-8.138, P = 0.01) and 5-year overall survival (HR = 3.872, CI = 1.681-8.392, P = 0.01) in HCC.ConclusionThese results showed that the markedly and consistently increasing expression of nucleolin may be associated with aggressive characteristics of HCC, and implied that nucleolin expression may serve as a promising biochemical marker for predicting the clinical outcome of patients with this malignancy.Virtual SlidesThe virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/13000_2014_175.