Background/Aims: Among different molecular candidates, there is growing data to support that long noncoding RNAs (lncRNAs) play a significant role in acute myeloid leukemia (AML). HOXA-AS2 is significantly overexpressed in a variety of tumors and associated with anti-cancer drug resistance, however, little is known regarding the expression and function of HOXA-AS2 in the chemoresistance of AML. In this study, we aimed to determine the role and molecular mechanism of HOXA-AS2 in adriamycin-based chemotherapy resistance in AML cells. Methods: Quantitative real-time PCR was used to detect HOXA-AS2 expression in the BM samples and ADR cell lines, U/A and T/A cells. Furthermore, the effects of HOXA-AS2 silencing on cell proliferation and apoptosis were assessed in vitro by CCK8 and flow cytometry, and on tumor growth in vivo. Furthermore, bioinformatics online programs predicted and luciferase reporter assay were used to validate the association of HOXA-AS2 and miR-520c-3p in AML. Results: In this study, we showed that HOXA-AS2 is significantly upregulated in BM samples from AML patients after treatment with adriamycin-based chemotherapy and in U/A and T/A cells. Knockdown of HOXA-AS2 inhibited ADR cell proliferation in vitro and in vivo and promoted apoptosis. Bioinformatics online programs predicted that HOXA-AS2 sponge miR-520c-3p at 3’-UTR with complementary binding sites, which was validated using luciferase reporter assay and anti-Ago2 RIP assay. HOXA-AS2 could negatively regulate the expression of miR-520c-3p in ADR cells. S100A4 was predicted as a downstream target of miR-520c-3p, which was confirmed by luciferase reporter assay. Conclusion: Our results suggest that HOXA-AS2 plays an important role in the resistance of AML cells to adriamycin. Thus, HOXA-AS2 may represent a therapeutic target for overcoming resistance to adriamycin-based chemotherapy in AML.

Background Hepatocellular carcinoma (HCC) is a common cancer and the leading cause is persistent hepatitis B virus (HBV) infection. We aimed to identify some core genes and pathways for HBV-related HCC. Methods Gene expression profiles of GSE62232, GSE121248, and GSE94660 were available from Gene Expression Omnibus (GEO). The GSE62232 and GSE121248 profiles were the analysis datasets and GSE94660 was the validation dataset. The GEO2R online tool and Venn diagram software were applied to analyze commonly differentially expressed genes between HBV-related HCC tissues and normal tissues. Then, functional enrichment analysis using Gene Ontology (GO) and the Kyoto Encyclopedia of Gene and Genome (KEGG) as well as the protein-protein interaction (PPI) network was conducted. The overall survival rates and the expression levels were detected by Kaplan-Meier plotter and Gene Expression Profiling Interactive Analysis (GEPIA). Next, gene set enrichment analysis (GSEA) was performed to verify the KEGG pathway analysis. Furthermore, quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) was performed to validate the levels of these three core genes in tumor tissues and adjacent non-tumor liver tissues from 12 HBV related HCC patients, HBV-associated liver cancer cell lines and normal liver cell lines, and HepG2 with p53 knockdown or deletion, respectively. Results Fifteen highly expressed genes associated with significantly worse prognoses were selected and CCNB1, CDK1, and RRM2 in the p53 signaling pathway were identified as core genes. GSEA results showed that samples highly expressing three core genes were all enriched in the p53 signaling pathway in a validation dataset (P < 0.0001). The expression of these three core genes in tumor tissue samples was higher than that in relevant adjacent non-tumor liver tissues (P < 0.0001). Furthermore, we also found that the above genes were highly expressed in liver cancer cell lines compared with normal liver cells. In addition, we found that the expression of these three core genes in p53 knockdown or knockout HCC cell lines was lower than that in negative control HCC cell lines (P < 0.05). Conclusions CCNB1, CDK1, and RRM2 were enriched in the p53 signaling pathway and could be potential biomarkers and therapeutic targets for HBV-related HCC.

Background: Patients with chronic hepatitis B (CHB) with severe acute exacerbation (SAE) are at a progression stage of acute-on-chronic liver failure (ACLF) but uniform models for predicting ACLF occurrence are lacking. We aimed to present a risk prediction model to early identify the patients at a high risk of ACLF and predict the survival of the patient.Methods: We selected the best variable combination using a novel recursive feature elimination algorithm to develop and validate a classification regression model and also an online application on a cloud server from the training cohort with a total of 342 patients with CHB with SAE and two external cohorts with a sample size of 96 and 65 patients, respectively.Findings: An excellent prediction model called the PATA model including four predictors, prothrombin time (PT), age, total bilirubin (Tbil), and alanine aminotransferase (ALT) could achieve an area under the receiver operating characteristic curve (AUC) of 0.959 (95% CI 0.941–0.977) in the development set, and AUC of 0.932 (95% CI 0.876–0.987) and 0.905 (95% CI 0.826–0.984) in the two external validation cohorts, respectively. The calibration curve for risk prediction probability of ACLF showed optimal agreement between prediction by PATA model and actual observation. After predictive stratification into different risk groups, the C-index of predictive 90-days mortality was 0.720 (0.675–0.765) for the PATA model, 0.549 (0.506–0.592) for the end-stage liver disease score model, and 0.648 (0.581–0.715) for Child–Turcotte–Pugh scoring system.Interpretation: The highlypredictive risk model and easy-to-use online application can accurately predict the risk of ACLF with a poor prognosis. They may facilitate risk communication and guidetherapeutic options.

No abstract

ObjectivesThe small noncoding RNAs (sncRNAs) including microRNAs and the noncanonical sncRNAs [i.e., tRNA-derived small RNAs (tsRNAs) and rRNA-derived small RNAs (rsRNAs)] are a vital class of gene regulators in response to a variety of diseases. We focus on an sncRNA signature enriched in hepatitis B virus (HBV)-related acute-on-chronic liver failure (ACLF) to develop a plasma exosome-based noninvasive biomarker for human ACLF.MethodsIn this work, sncRNAs related to HBV-ACLF were identified by small RNA sequencing (RNA-seq) in plasma exosomes collected from 3 normal subjects, 4 chronic hepatitis B (CHB) patients with flare, and 6 HBV-ACLF patients in the discovery cohort. Thereafter, the differentially expressed sncRNAs were further verified in a validation cohort (n = 313) using the newly developed molecular signature incorporating different mi/ts/rsRNAs (named as MTR-RNAs) through qRT-PCR assays. Subsequently, using the least absolute shrinkage and selection operator (LASSO) logistic regression (LR) model analysis, we developed an MTR-RNA classifier for early detection of ACLF.ResultsThe identified sncRNAs (hsa-miR-23b-3p, hsa-miR-223-3p, hsa-miR-339-5p, tsRNA-20, tsRNA-46, and rsRNA-249) were specifically differentially expressed in plasma exosomes of HBV-ACLF. The MTR-RNA signature (AUC = 0.787) containing the above sncRNAs distinguished HBV-ACLF cases among normal subjects with 71.67% specificity and 74.29% sensitivity, CHB patients with flare (AUC = 0.694, 85.71% sensitivity/59.5% specificity), and patients with CHB/cirrhosis (AUC = 0.785, 57.14% sensitivity/94.59% specificity). Notably, it revealed 100% specificity/94.80% sensitivity in detecting patients or normal people.ConclusionsOur as-constructed plasma-derived exosomal sncRNA signature can serve as a reliable biomarker for ACLF detection and also be adopted to be the pre−triage biomarker for selecting cases that can gain benefits from adjuvant treatment.

Acute myeloid leukemia (AML) is associated with a poor prognosis in elderly adults and currently lacks optimal treatment strategies. MicroRNAs (miRNAs or miRs) have increasingly been reported to be associated with AML progression; however, the mechanisms of action of miR-93 in AML with the involvement of disabled 2 (DAB2) are currently unknown. In the present study, miR-93 expression was assessed in patients with AML and in AML cell lines. The association between miR-93 expression and the pathological characteristics of patients with AML was analyzed. AML cells were then transfected to knockdown or overexpress miR-93 in order to elucidate its function in AML progression. The target gene of miR-93 was assessed using a dual-luciferase reporter gene assay. The expression levels of miR-93, DAB2 and phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) pathway-related proteins were measured and in vivo experiments were conducted to confirm the results. It was observed that miR-93 was highly expressed in patients with AML and in AML cells. The knockdown of miR-93 in HL-60 cells inhibited AML cell proliferation and resistance to apoptosis, while the overexpression of miR-93 in THP-1 cells led to contrasting results. Moreover, miR-93 targeted DAB2 to inactivate the PI3K/AKT pathway, and the overexpression of DAB2 reversed the effects of miR-93 on THP-1 cell growth. Tumor volume, tumor weight, and the positive expression of Ki67, survivin and p53 were increased in THP-1 cells overexpressing miR-93. On the whole, the present study demonstrates that miR-93 is highly expressed in AML cells, and that the suppression of miR-93 inhibits AML cell growth by targeting DAB2 and inhibiting the PI3K/AKT pathway.

Background Since December 2019, an outbreak of coronavirus disease 2019 (COVID-19) that began in Wuhan and rapidly spread globally. The speed and scope of spread of COVID-19 makes urgent of the defining clinical characteristics, serological and radiological changes of the affected patients. Method 7 patients with laboratory-confirmed COVID-19 who admitted to the Third affiliated hospital of Sun Yat-sen university Yuedong hospital from January 2020 to March 2020 were retrospectively enrolled and their clinical features, serological and radiological longitudinal changes were analyzed. Results Among the 7 patients, all (100%) had a clear epidemiological history. The most common symptoms were respiratory symptoms 6 (85.7%), and only 2 (28.6%) of the patients had fever at their first visit. The cohort included 4 (57.1%) common types and 3 (42.9%) severe types. Two (28.6%) common types patients developed to severe type in a short time. All of the 7 patients (100%) had abnormal liver function, normal renal function and normal procalcitonin. The detection time of specific antibody in 7 patients was 5~13d after symptoms. Before the specific antibody could be detected, the absolute value of lymphocytes decreased in 2 (28.6%) common type cases transferred to severe type cases accompanied with obvious progress in pulmonary imaging, and the phenomenon of decreased albumin and elevated globulin occurred in 6 patients (85.7%). The predominant pattern of lung lesions observed was bilateral (71.4%) and mainly near the pleura at the first diagnosis. Bilateral pulmonary involvement occurred in 6 cases (85.7%) during the course of disease. In 4 cases (57.1%) with obvious pulmonary lesions, the absolute value of lymphocytes decreased, albumin decreased and globulin increased during the course of the disease. Conclusion Serum specific antibodies can be detected within 2 weeks of onset. Close observation of the dynamic changes of absolute value of blood lymphocytes, serum albumin and globulin which were related to pulmonary imaging changes in patients will contribute to assessment of COVID-19.

No abstract