Aging and comprehensive molecular profiling in acute myeloid leukemia.

Acute myeloid leukemia (AML) is an aging-related and heterogeneous hematopoietic malignancy. In this study, a total of 1,474 newly diagnosed AML patients with RNA sequencing data were enrolled, and targeted or whole exome sequencing data were obtained in 94% cases. The correlation of aging-related factors including age and clonal hematopoiesis (CH), gender, and genomic/transcriptomic profiles (gene fusions, genetic mutations, and gene expression networks or pathways) was systematically analyzed. Overall, AML patients aged 60 y and older showed an apparently dismal prognosis. Alongside age, the frequency of gene fusions defined in the World Health Organization classification decreased, while the positive rate of gene mutations, especially CH-related ones, increased. Additionally, the number of genetic mutations was higher in gene fusion-negative (GF-) patients than those with GF. Based on the status of CH- and myelodysplastic syndromes (MDS)-related mutations, three mutant subgroups were identified among the GF- AML cohort, namely, CH-AML, CH-MDS-AML, and other GF- AML. Notably, CH-MDS-AML demonstrated a predominance of elderly and male cases, cytopenia, and significantly adverse clinical outcomes. Besides, gene expression networks including HOXA/B, platelet factors, and inflammatory responses were most striking features associated with aging and poor prognosis in AML. Our work has thus unraveled the intricate regulatory circuitry of interactions among different age, gender, and molecular groups of AML.

PRODeepSyn: predicting anticancer synergistic drug combinations by embedding cell lines with protein-protein interaction network.

Although drug combinations in cancer treatment appear to be a promising therapeutic strategy with respect to monotherapy, it is arduous to discover new synergistic drug combinations due to the combinatorial explosion. Deep learning technology holds immense promise for better prediction of in vitro synergistic drug combinations for certain cell lines. In methods applying such technology, omics data are widely adopted to construct cell line features. However, biological network data are rarely considered yet, which is worthy of in-depth study. In this study, we propose a novel deep learning method, termed PRODeepSyn, for predicting anticancer synergistic drug combinations. By leveraging the Graph Convolutional Network, PRODeepSyn integrates the protein-protein interaction (PPI) network with omics data to construct low-dimensional dense embeddings for cell lines. PRODeepSyn then builds a deep neural network with the Batch Normalization mechanism to predict synergy scores using the cell line embeddings and drug features. PRODeepSyn achieves the lowest root mean square error of 15.08 and the highest Pearson correlation coefficient of 0.75, outperforming two deep learning methods and four machine learning methods. On the classification task, PRODeepSyn achieves an area under the receiver operator characteristics curve of 0.90, an area under the precision-recall curve of 0.63 and a Cohen's Kappa of 0.53. In the ablation study, we find that using the multi-omics data and the integrated PPI network's information both can improve the prediction results. Additionally, the case study demonstrates the consistency between PRODeepSyn and previous studies.

A complete graph-based approach with multi-task learning for predicting synergistic drug combinations.

MOTIVATION: Drug combination therapy shows significant advantages over monotherapy in cancer treatment. Since the combinational space is difficult to be traversed experimentally, identifying novel synergistic drug combinations based on computational methods has become a powerful tool for pre-screening. Among them, methods based on deep learning have far outperformed other methods. However, most deep learning-based methods are unstable and will give inconsistent predictions even by simply changing the input order of drugs. In addition, the insufficient experimental data of drug combination screening limits the generalization ability of existing models. These problems prevent the deep learning-based models from being in service. RESULTS: In this article, we propose CGMS to address the above problems. CGMS models a drug combination and a cell line as a heterogeneous complete graph, and generates the whole-graph embedding to characterize their interaction by leveraging the heterogeneous graph attention network. Based on the whole-graph embedding, CGMS can make a stable, order-independent prediction. To enhance the generalization ability of CGMS, we apply the multi-task learning technique to train the model on drug synergy prediction task and drug sensitivity prediction task simultaneously. We compare CGMS's generalization ability with six state-of-the-art methods on a public dataset, and CGMS significantly outperforms other methods in the leave-drug combination-out scenario, as well as in the leave-cell line-out and leave-drug-out scenarios. We further present the benefit of eliminating the order dependency and the discrimination power of whole-graph embeddings, interpret the rationality of the attention mechanism, and verify the contribution of multi-task learning. AVAILABILITY AND IMPLEMENTATION: The code of CGMS is available via https://github.com/TOJSSE-iData/CGMS.

Improving dermal fibroblast-to-epidermis communications and aging wound repair through extracellular vesicle-mediated delivery of Gstm2 mRNA.

Skin aging is characterized by the disruption of skin homeostasis and impaired skin injury repair. Treatment of aging skin has long been limited by the unclear intervention targets and delivery techniques. Engineering extracellular vesicles (EVs) as an upgraded version of natural EVs holds great potential in regenerative medicine. In this study, we found that the expression of the critical antioxidant and detoxification gene Gstm2 was significantly reduced in aging skin. Thus, we constructed the skin primary fibroblasts-derived EVs encapsulating Gstm2 mRNA (EVsGstm2), and found that EVsGstm2 could significantly improve skin homeostasis and accelerate wound healing in aged mice. Mechanistically, we found that EVsGstm2 alleviated oxidative stress damage of aging dermal fibroblasts by modulating mitochondrial oxidative phosphorylation, and promoted dermal fibroblasts to regulate skin epidermal cell function by paracrine secretion of Nascent Polypeptide-Associated Complex Alpha subunit (NACA). Furthermore, we confirmed that NACA is a novel skin epidermal cell protective molecule that regulates skin epidermal cell turnover through the ROS-ERK-ETS-Cyclin D pathway. Our findings demonstrate the feasibility and efficacy of EVs-mediated delivery of Gstm2 for aged skin treatment and unveil novel roles of GSTM2 and NACA for improving aging skin.

Arsenic trioxide replacing or reducing chemotherapy in consolidation therapy for acute promyelocytic leukemia (APL2012 trial).

As all-trans retinoic acid (ATRA) and arsenic trioxide (ATO) are widely accepted in treating acute promyelocytic leukemia (APL), deescalating toxicity becomes a research hotspot. Here, we evaluated whether chemotherapy could be replaced or reduced by ATO in APL patients at different risks. After achieving complete remission with ATRA-ATO-based induction therapy, patients were randomized (1:1) into ATO and non-ATO groups for consolidation: ATRA-ATO versus ATRA-anthracycline for low-/intermediate-risk patients, or ATRA-ATO-anthracycline versus ATRA-anthracycline-cytarabine for high-risk patients. The primary end point was to assess disease-free survival (DFS) at 3 y by a noninferiority margin of -5%; 855 patients were enrolled with a median follow-up of 54.9 mo, and 658 of 755 patients could be evaluated at 3 y. In the ATO group, 96.1% (319/332) achieved 3-y DFS, compared to 92.6% (302/326) in the non-ATO group. The difference was 3.45% (95% CI -0.07 to 6.97), confirming noninferiority (P < 0.001). Using the Kaplan-Meier method, the estimated 7-y DFS was 95.7% (95% CI 93.6 to 97.9) in ATO and 92.6% (95% CI 89.8 to 95.4) in non-ATO groups (P = 0.066). Concerning secondary end points, the 7-y cumulative incidence of relapse (CIR) was significantly lower in ATO (2.2% [95% CI 1.1 to 4.2]) than in non-ATO group (6.1% [95% CI 3.9 to 9.5], P = 0.011). In addition, grade 3 to 4 hematological toxicities were significantly reduced in the ATO group during consolidation. Hence, ATRA-ATO in both chemotherapy-replacing and -reducing settings in consolidation is not inferior to ATRA-chemotherapy (https://www.clinicaltrials.gov/, NCT01987297).

Predicting anticancer synergistic drug combinations based on multi-task learning.

BACKGROUND: The discovery of anticancer drug combinations is a crucial work of anticancer treatment. In recent years, pre-screening drug combinations with synergistic effects in a large-scale search space adopting computational methods, especially deep learning methods, is increasingly popular with researchers. Although achievements have been made to predict anticancer synergistic drug combinations based on deep learning, the application of multi-task learning in this field is relatively rare. The successful practice of multi-task learning in various fields shows that it can effectively learn multiple tasks jointly and improve the performance of all the tasks. METHODS: In this paper, we propose MTLSynergy which is based on multi-task learning and deep neural networks to predict synergistic anticancer drug combinations. It simultaneously learns two crucial prediction tasks in anticancer treatment, which are synergy prediction of drug combinations and sensitivity prediction of monotherapy. And MTLSynergy integrates the classification and regression of prediction tasks into the same model. Moreover, autoencoders are employed to reduce the dimensions of input features. RESULTS: Compared with the previous methods listed in this paper, MTLSynergy achieves the lowest mean square error of 216.47 and the highest Pearson correlation coefficient of 0.76 on the drug synergy prediction task. On the corresponding classification task, the area under the receiver operator characteristics curve and the area under the precision-recall curve are 0.90 and 0.62, respectively, which are equivalent to the comparison methods. Through the ablation study, we verify that multi-task learning and autoencoder both have a positive effect on prediction performance. In addition, the prediction results of MTLSynergy in many cases are also consistent with previous studies. CONCLUSION: Our study suggests that multi-task learning is significantly beneficial for both drug synergy prediction and monotherapy sensitivity prediction when combining these two tasks into one model. The ability of MTLSynergy to discover new anticancer synergistic drug combinations noteworthily outperforms other state-of-the-art methods. MTLSynergy promises to be a powerful tool to pre-screen anticancer synergistic drug combinations.

The deubiquitinase USP36 promotes snoRNP group SUMOylation and is essential for ribosome biogenesis.

SUMOylation plays a crucial role in regulating diverse cellular processes including ribosome biogenesis. Proteomic analyses and experimental evidence showed that a number of nucleolar proteins involved in ribosome biogenesis are modified by SUMO. However, how these proteins are SUMOylated in cells is less understood. Here, we report that USP36, a nucleolar deubiquitinating enzyme (DUB), promotes nucleolar SUMOylation. Overexpression of USP36 enhances nucleolar SUMOylation, whereas its knockdown or genetic deletion reduces the levels of SUMOylation. USP36 interacts with SUMO2 and Ubc9 and directly mediates SUMOylation in cells and in vitro. We show that USP36 promotes the SUMOylation of the small nucleolar ribonucleoprotein (snoRNP) components Nop58 and Nhp2 in cells and in vitro and their binding to snoRNAs. It also promotes the SUMOylation of snoRNP components Nop56 and DKC1. Functionally, we show that knockdown of USP36 markedly impairs rRNA processing and translation. Thus, USP36 promotes snoRNP group SUMOylation and is critical for ribosome biogenesis and protein translation.

Dysregulated MDR1 by PRDM1/Blimp1 Is Involved in the Doxorubicin Resistance of Non-Germinal Center B-Cell-Like Diffuse Large B-Cell Lymphoma.

INTRODUCTION: The chemoresistance mechanism of diffuse large B-cell lymphoma (DLBCL) is still poorly understood, and patient prognosis remains unsatisfactory. This study aimed to investigate drug resistance mechanisms in non-germinal center B-cell-like (non-GCB) DLBCL. METHODS: Doxorubicin (DOX)-resistant OCI-Ly3 cells were generated through long-term incubation of cells in a medium with gradually increasing DOX concentrations. The expression levels of genes related to drug metabolism were determined using a functional gene grouping polymerase chain reaction (PCR) array. Drug-resistant proteins were identified using bioinformatics, and molecular association networks were subsequently generated. The association and mechanism of key genes were determined using a dual-luciferase reporter assay System and chromatin immunoprecipitation (ChIP). The expression of drug-resistant genes and target genes was then measured using Western blotting and immunohistochemistry. The correlation between gene expressions was analyzed using Spearman's rank correlation coefficient. RESULTS: Using the PCR array, MDR1 was identified as the key gene that regulates DOX resistance in OCI-Ly3/DOX-A100, a non-GCB DLBCL cell line. The dual-luciferase reporter assay system demonstrated that MDR1 transcription could be inhibited by PRDM1. ChIP results showed that PRDM1 had the ability to bind to the promoter region (-1,132 to -996) of MDR1. In OCI-Ly3/DOX cells, NF-κB activity and PRDM1 expression decreased with an increase in drug-resistant index, whereas MDR1 expression increased with enhanced drug resistance. Immunohistochemical analysis revealed that relative MDR1 expression was higher than that of PRDM1 in human DLBCL tissue samples. A negative correlation was observed between MDR1 and PRDM1. CONCLUSION: In non-GCB DLBCL cells, NF-κB downregulates PRDM1 and thereby promotes MDR1 transcription by terminating PRDM1-induced transcriptional inhibition of MDR1. Such a mechanism may explain the reason for disease recurrence in non-GCB DLBCL after R-CHOP or combined CHOP with bortezomib treatment. Our findings may provide a potential therapeutic strategy for reducing drug resistance in patients with DLBCL.

KIF18A knockdown reduces proliferation, migration, invasion and enhances radiosensitivity of esophageal cancer.

Kinesin family member 18A (KIF18A) is significantly overexpressed and is related to the poor prognosis of human cancers. However, the function of KIF18A in esophageal cancer (EC) is still unclear. Human EC cell lines were used in this study. KIF18A expression in human tissues was assessed using Gene Expression Profiling Interactive Analysis 2.0 (GEPIA2). The expressions of KIF18A or IGF2BP3 in EC cells were detected using qRT-PCR or WB. Cells were transfected using si-KIF18A, si-IGF2BP3, and plasmid IGF2BP3. The abilities of proliferation, migration, and invasion were detected by EdU, wound-healing, and transwell assay. The interaction between KIF18A and IGF2BP3 was predicted by starBase v3.0 and studied by RIP and RNA stability assay. Colony formation assay was used to reflect the changes of radiosensitivity in EC cells. KIF18A was upregulated in EC, and KIF18A knockdown inhibited EC cell proliferation, migration, invasion, and radioresistance. The prediction in starBase and RIP assay results showed that KIF18A mRNA could bind to IGF2BP3 protein in EC cells. RNA stability assay was performed to confirm that IGF2BP3 affects mRNA stability of KIF18A. Further studies also showed that IGF2BP3 could positively regulate KIF18A on proliferation, migration, invasion, and radioresistance. Our findings first revealed an oncogenic effect of KIF18A in human EC progression. KIF18A expression was associated with radioresistance of EC cells. The binding relationship between KIF18A and IGF2BP3 might influence the mRNA stability of KIF18A in EC cell lines.

Role of glutamine and its metabolite ammonia in crosstalk of cancer-associated fibroblasts and cancer cells.

Cancer-associated fibroblasts (CAFs), the most abundant cells in the tumor microenvironment, play an indispensable role in cancer initiation, progression, metastasis, and metabolism. The limitations of traditional treatments can be partly attributed to the lack of understanding of the role of the tumor stroma. For this reason, CAF targeting is gradually gaining attention, and many studies are trying to overcome the limitations of tumor treatment with CAF as a breakthrough. Glutamine (GLN) has been called a "nitrogen reservoir" for cancer cells because of its role in supporting anabolic processes such as fuel proliferation and nucleotide synthesis, but ammonia is a byproduct of the metabolism of GLN and other nitrogenous compounds. Moreover, in some studies, GLN has been reported as a fundamental nitrogen source that can support tumor biomass. In this review, we discuss the latest findings on the role of GLN and ammonia in the crosstalk between CAFs and cancer cells as well as the potential therapeutic implications of nitrogen metabolism.

Factors predicting the severity of acute pancreatitis in elderly patients.

BACKGROUND: Moderately severe acute pancreatitis (MSAP) and severe acute pancreatitis (SAP) are associated with organ failure (OF), which can be lethal. AIMS: This study determined the factors that predict the severity of AP at admission in elderly patients. METHODS: In this retrospective study, the data from elderly patients (> 60 years of age) admitted within 72 h of onset of symptoms without OF were collected. These data at admission were analyzed and correlated with the severity of AP. To identify the factors associated with more serious AP (i.e. MSAP and SAP), patients were divided into mild acute pancreatitis (MAP) and MSAP + SAP groups. RESULTS: A total of 198 patients [MAP group (n = 135) and MSAP + SAP group (n = 63)] were included. Biliary disease was the most common etiology. Respiratory failure was the most common OF. Logistic regression analyses indicated that idiopathic etiology (odds ratio [OR]: 3.029, 95% confidence interval [CI]: 1.017-9.022, p = 0.047), pre-existing pulmonary disease (OR: 7.104, CI 1.750-28.84, p = 0.006), increased hematocrit level (OR: 3.717, 95%CI 1.372-10.070, p = 0.010), serum calcium (OR: 0.023, 95%CI 0.001-0.371, p = 0.008), serum glucose (OR: 1.157, 95%CI 1.031-1.299, p = 0.013), arterial partial pressure of oxygen (PaO2) (OR: 0.914, 95%CI 0.874-0.956, p < 0.001), and pleural effusion (OR: 4.979, 95%CI 1.863-13.303, p = 0.001) were independent predictors of more serious AP. CONCLUSION: This study found that idiopathic etiology, pre-existing pulmonary diseases, increased hematocrit level or pleural effusion, higher serum glucose, and lower serum calcium or PaO2 at the time of admission independently correlated with more serious AP in the elderly patients.

FTRLIM: Distributed Instance Matching Framework for Large-Scale Knowledge Graph Fusion.

Instance matching is a key task in knowledge graph fusion, and it is critical to improving the efficiency of instance matching, given the increasing scale of knowledge graphs. Blocking algorithms selecting candidate instance pairs for comparison is one of the effective methods to achieve the goal. In this paper, we propose a novel blocking algorithm named MultiObJ, which constructs indexes for instances based on the Ordered Joint of Multiple Objects' features to limit the number of candidate instance pairs. Based on MultiObJ, we further propose a distributed framework named Follow-the-Regular-Leader Instance Matching (FTRLIM), which matches instances between large-scale knowledge graphs with approximately linear time complexity. FTRLIM has participated in OAEI 2019 and achieved the best matching quality with significantly efficiency. In this research, we construct three data collections based on a real-world large-scale knowledge graph. Experiment results on the constructed data collections and two real-world datasets indicate that MultiObJ and FTRLIM outperform other state-of-the-art methods.

Overexpression of ERBB4 rejuvenates aged mesenchymal stem cells and enhances angiogenesis via PI3K/AKT and MAPK/ERK pathways.

The age-related functional exhaustion limits potential efficacy of mesenchymal stem cells (MSC) in treating cardiovascular disease. Therefore, rejuvenation of aged MSC in the elderly population is of great interest. We have previously reported that Erb-B2 receptor tyrosine kinase 4 ( ERBB4) plays a critical role in regulating MSC survival under hypoxia. The aim of this study was to investigate whether ERBB4 rejuvenates aged MSC and how ERBB4 enhances therapeutic efficacy of aged MSC in treating myocardial infarction (MI). Compared with vector aged MSC (aged-MSC), ERBB4-engineered aged MSC (ER4-aged-MSC) conferred resistance to oxidative stress-induced cell death and ameliorated the senescent phenotype in vitro. Four weeks after MI, the ER4-aged-MSC group exhibited enhanced blood vessel density, reduced cardiac remodeling and apoptosis with improved heart function compared with the aged-MSC group. Overexpression of ERBB4 caused an increase in phosphorylated v-akt murine thymoma viral oncogene homolog 1 (AKT), and phosphorylated ERK expression under hypoxia. ER4-aged-MSC secreted higher levels of angiopoietin, epithelial neutrophil activating peptide 78, VEGF, and fibroblast growth factor 2, and enhanced tube formation in HUVEC. The impact of ERBB4 on protein expression, proangiogenesis, cell behavior, and cytokine secretion was abolished by inhibiting PI3K/AKT and MAPK/ERK signaling pathway.-Liang, X., Ding, Y., Lin, F., Zhang, Y., Zhou, X., Meng, Q., Lu, X., Jiang, G., Zhu, H., Chen, Y., Lian, Q., Fan, H., Liu, Z. Overexpression of ERBB4 rejuvenates aged mesenchymal stem cells and enhances angiogenesis via PI3K/AKT and MAPK/ERK pathways.

Low-dose decitabine priming with intermediate-dose cytarabine followed by umbilical cord blood infusion as consolidation therapy for elderly patients with acute myeloid leukemia: a phase II single-arm study.

BACKGROUND: Treatment of acute myeloid leukemia (AML) in elderly patients remains a great challenge. In this prospective single arm study (ChiCTR-OPC-15006492), we evaluated the efficacy and safety of a novel consolidation therapy with low-dose decitabine (LD-DAC) priming with intermediate-dose cytarabine (ID-Ara-C) followed by umbilical cord blood (UCB) infusion in elderly patients with AML. METHODS: A total of 25 patients with a median age of 64-years-old (60-74-years-old) who achieved complete remission (CR) after induction chemotherapy were enrolled in the study. RESULTS: The 2-year actual overall survival (OS) rate and leukemia-free survival (LFS) was 68.0 and 60.0%, respectively. The hematological and non-hematological toxicity were mild to moderate, and only one patient died in remission due to infection with possible acute graft versus host disease (aGVHD). Compared to a concurrent cohort of patients receiving conventional consolidation therapy, the study group tended to have an improved OS and LFS (p = 0.046 and 0.057, respectively), while the toxicity was comparable between the two groups. CONCLUSIONS: This study suggested the novel combination of LD-DAC, ID-Ara-C, and UCB infusion might be an optimal consolidation therapy for elderly patients with AML, and a prospective phase III randomized study is warranted to confirm this observation. TRIAL REGISTRATION: This single-arm phase II clinical trial in elderly AML patients was registered prospectively at www.chictr.org.cn (identifier: ChiCTR-OPC-15006492 ) on June 2, 2015.

miR-184 Inhibits Tumor Invasion, Migration and Metastasis in Nasopharyngeal Carcinoma by Targeting Notch2.

BACKGROUND/AIMS: A recent study found that dysregulated microRNA-184 (miR-184) is involved in the proliferation and survival of nasopharyngeal carcinoma (NPC). This study aimed to evaluate the detailed mechanisms of invasion, migration and metastasis of NPC cells. METHODS: Quantitative reverse-transcription PCR (qRT-PCR) and Western blot were used to confirm the expression levels of miR-184 and Notch2. NPC cell invasion and migration were subsequently examined using in vitro cell invasion and wound-healing assays, respectively. MicroRNA (miRNA) target gene prediction databases and dual-luciferase reporter assay were adopted to validate the target genes of miR-184. RESULTS: MiR-184 was downregulated in the NPC cell lines. The miR-184 inhibitor increased the number of invading NPC cells, whereas miR-184 mimics inhibited the invasive ability of such cells. The protein level of E-cadherin decreased, whereas those of N-cadherin and vimentin increased in the anti-miR-184 group. This result showed that miR-184 inhibited NPC cell invasion and metastasis by regulating EMT progression. MiRNA target gene prediction databases indicated the potential of Notch2 as a direct target gene of miR-184. Such a notion was then validated by results of dual-luciferase reporter assay. Notably, shRNANotch2 restrained the EMT and partially abrogated the inhibitory effects of miR-184 on EMT progression in NPC cells. CONCLUSION: MiR-184 functions as a tumour-suppressive miRNA targeting Notch2 and inhibits the invasion, migration and metastasis of NPC.

The severe cytokine release syndrome in phase I trials of CD19-CAR-T cell therapy: a systematic review.

CD19 chimeric antigen receptor (CAR) T cell therapy has shown impressive results in treating acute lymphoblastic leukemia (B-ALL), chronic lymphoblastic leukemia (B-CLL), and B-cell non-Hodgkin lymphoma (B-NHL) over the past few years. Meanwhile, the cytokine release syndrome (CRS), which could be moderate or even life-threatening, has emerged as the most significant adverse effect in the clinical course of this novel targeting immunotherapy. In this systematic review, we analyzed the incidence of severe CRS in 19 clinical trials selected from studies published between 2010 and 2017. The pooled severe CRS proportion was 29.3% (95% confidence interval [CI] 12.3-49.1%) in B-ALL, 38.8% (95%CI 12.9-67.6%) in B-CLL, and 19.8% (95%CI 4.2-40.8%) in B-NHL. In the univariate meta regression analysis, the proliferation of CD19-CAR-T cell in vivo was correlated with the severe CRS. Specifically, total infusion cell dose contributed to the severe CRS occurring in B-ALL patients but not in B-CLL or B-NHL patients. Tumor burden was strongly associated with the severity of CRS in B-ALL. Besides, post-HSCT CD19 CAR-T cell infusion represented lower severe CRS incidence. Further investigations into the risk factors of CRS in B-CLL and B-NHL are needed.

Arsenic trioxide at conventional dosage does not aggravate hemorrhage in the first-line treatment of adult acute promyelocytic leukemia.

OBJECTIVES: The arsenic trioxide (ATO) plus all-trans retinoic acid (ATRA) therapy has demonstrated a tremendous success in the first-line treatment of acute promyelocytic leukemia (APL). Actually, early death (ED) is currently thought as a major challenge in APL. ATO has been reported to inhibit platelet function in vitro, and whether it increases the ED rate by exacerbating the hemorrhagic symptoms remains to be investigated. METHODS: Effects of ATO on platelet aggregation and adhesion were evaluated in vitro and in thirty-two complete remission (CR) and four newly diagnosed APL patients. Furthermore, concentrations of plasma total arsenic were monitored in APL patients via ICP-MS. RESULTS: The inhibition of platelet function, either aggregation or adhesion, did occur in vitro when the concentration of ATO reached 2 µmol/L. However, in CR APL patients receiving ATO with normal platelet count, the platelets responded normally when being activated and so did those in the newly diagnosed patients with thrombocytopenia. Our data further showed that the conventional dosage of ATO reached a plasma concentration substantially below the required concentration to inhibit platelets. CONCLUSIONS: In the first-line treatment of APL, the use of ATO is safe and effective and does not compromise the hemostatic potential that may eventually increase ED rate.

Aldehyde dehydrogenase 2 deficiency negates chronic low-to-moderate alcohol consumption-induced cardioprotecion possibly via ROS-dependent apoptosis and RIP1/RIP3/MLKL-mediated necroptosis.

Previous studies evidenced the beneficial effects of low-to-moderate alcohol consumption on cardiovascular system by activation of mitochondrial aldehyde dehydrogenase 2 (ALDH2), a key enzyme metabolizing acetaldehyde to innocuous acetic acid, in diabetic mice. It remains questionable whether people with inactive ALDH2 would also benefit from the drinking habit. Present study was therefore designed to examine the influence of ALDH2 deficiency on low-to-moderate alcohol consumption related myocardial alternations. Wildtype (WT) and ALDH2 knockout (KO) mice were exposed to low-to-moderate alcohol (EtOH) challenge for 6weeks. Cardiac function and cell death related pathways were then measured. Although EtOH exposure did not further improve cardiac function or reduce reactive oxygen species (ROS) levels in WT mice, levels of high density lipoprotein-cholesterol (HDL-c) and expression of heme oxygenase-1 (HO-1) were significantly elevated in WT-EtOH group. However, EtOH exposure in KO mice depressed cardiac function as indicated by reduced left ventricular ejection fraction (EF) and increased myocardial fibrosis deposition as well as the excessive ROS accumulation. Above changes were related to altered cell demise (apoptosis and necroptosis), as shown by upregulated expression of cleaved caspase 9, cleaved caspase 3 and RIP1/RIP3/MLKL cascade. Our results thus suggest that ALDH2 is indispensable for the favorable cardiac effect of low-to-moderate alcohol consumption and ALDH2 deficiency may lead to unexpected cardiac dysfunctions via enhancing myocardial apoptosis and necroptosis.

Risk of Onset of Hematological Malignancies in Patients Infected with the Hepatitis B Virus: Results from a Large-Scale Retrospective Cohort Study in China.

The hepatitis B virus (HBV) is a major global issue, because an increased risk of hepatocellular carcinoma among patients infected with HBV is well established. Recently, it has been suggested that HBV is associated with other human cancers. However, the association between HBV and the risk of onset of hematological malignancies remains controversial. The aim of this large-scale retrospective cohort study was to evaluate the association between HBV infection and hematological malignancies. A retrospective analysis of 86,115 newly admitted patients at Shanghai Ruijin Hospital was performed. A cohort of patients previously exposed to HBV (n = 1,874) and a cohort of individuals without a positive test for anti-hepatitis B core antigen (anti-HBc; n = 45,118) were compared to assess the risk of hematological malignancies. Anti-HBc was positive in 61.2% cases and 54.3% controls (p = 0.0001). The risk of B cell non-Hodgkin's lymphoma, acute lymphoblastic leukemia, and multiple myeloma was higher in the HBV-infected cohort than in the non-HBV-infected cohort. In conclusion, patients infected with HBV have a substantially increased risk of hematological malignancies.