A205 PEMBROLIZUMAB ASSOCIATED SCLEROSING CHOLANGITIS RESPONDS TO COMBINATION OF STEROIDS AND MYCOPHENOLIC ACID: A CASE REPORT

Background

Pembrolizumab is a check point inhibitor that targets programmed cell death receptor ligand 1 (PD-L1). However, check-point inhibitors are associated with its characteristic adverse event know as immune related adverse events that can affect a myriad of organ systems. In the hepatobiliary system, the most commonly described iRAE is hepatitis/hepatotoxicity and latest oncology guidelines offer recommendations on treatment and followup of immunotherapy related hepatitis (1). However, a more rare presentation of iRAE, that have only been described as case reports or case series, is secondary cholangitis. We report one of such a case.

Aims

Case report

Methods

Case report

Results

The patient is a 55 year-old Caucasian female know for lung adenocarcinoma presented to the emergency room on May 5th, 2020, having received her 8th cycle of pembrolizumab. Her blood works mildly elevated transaminitis; ALT 78 U/L, AST 11 U/L, alkaline phosphate of 130 U/L, and total bilirubin of 3.5 umol/L.

MRI of the abdomen showed a normal appearing liver without focal parenchymal lesion, no biliary stones or obstructing masses, dilated common bile duct at 11 mm with small pericholecystic free fluid, and normal gall badder thickness of 2 mm. There was also notion of minimally prominent intrahepatic biliary radicles seen within the CBD.

Etiology workup of cholestatic transaminitis was negative. A diagnosis of immunotherapy related sclerosing cholangitis was posed and the patient was treated with MMF and prednisone with good response.

Conclusions

Discussion

This patient seems to have developed immunotherapy mediated cholangitis. Liver biopsy when performed in liver injury tend to show lobular hepatitis, with liver parenchyma infiltrated with lymphocytes and focal necrosis with acidophilic bodies. However, there seems to be another, less frequent pattern of injury described with pembrolizumab and associated with cholangiopathy, resembling primary biliary cholangitis. It is characterized with portal tracts enlarged with fibrosis and inflammatory cells infiltration; infiltrating cells are lymphocytes (2). Biliary epithelium with fibrosis with CD8+ T cells infiltration seem to be recurrently reported in case reports. (3, 4).

Other cases have been describe in the literature. In many cases, steroid therapy was attempted, but response rates seem to be inconsistent. Nivolumab related cholangitis have been also been described and characterized by extra hepatic bile duct dilatation along with negative immunological markers such as ANA and IgG4 in patients with non-small cell lung cancer, and seems to respond only moderately to steroid therapy (6). Retrospective data of nivolumab related cholangiopathy seems to suggest that there is favourable response to the combination of MMF and steroid therapy (7).

Funding Agencies

None

Utility of Contrast-Enhanced T2 FLAIR for Imaging Brain Metastases Using a Half-dose High-Relaxivity Contrast Agent

BACKGROUND AND PURPOSE

Efficient detection of metastases is important for patient' treatment. This prospective study was to explore the clinical value of contrast-enhanced T2 FLAIR in imaging brain metastases using half-dose gadobenate dimeglumine.

MATERIALS AND METHODS

In vitro signal intensity of various gadolinium concentrations was explored by spin-echo T1-weighted imaging and T2 FLAIR. Then, 46 patients with lung cancer underwent nonenhanced T2 FLAIR before administration of half-dose gadobenate dimeglumine and 3 consecutive contrast-enhanced T2 FLAIR sequences followed by 1 spin-echo T1WI after administration of half-dose gadobenate dimeglumine. After an additional dose of 0.05 mmol/kg, 3D brain volume imaging was performed. All brain metastases were classified as follows: solid-enhancing, ≥ 5 mm (group A); ring-enhancing, ≥ 5 mm (group B); and lesion diameter of <5 mm (group C). The contrast ratio of the lesions on 3 consecutive phases of contrast-enhanced T2 FLAIR was measured, and the percentage increase of contrast-enhanced T2 FLAIR among the 3 groups was compared.

RESULTS

In vitro, the maximal signal intensity was achieved in T2 FLAIR at one-eighth to one-half of the contrast concentration needed for maximal signal intensity in T1WI. In vivo, the mean contrast ratio values of metastases on contrast-enhanced T2 FLAIR for the 3 consecutive phases ranged from 63.64% to 83.05%. The percentage increase (PI) values of contrast-enhanced T2 FLAIR were as follows: PI_A < PI_B (P = .001) and PI_A < PI_C (P < .001). The degree of enhancement of brain metastases on contrast-enhanced T2 FLAIR was lower than on 3D brain volume imaging (P < .001) in group A, and higher than on 3D brain volume imaging (P < .001) in group C.

CONCLUSIONS

Small or ring-enhancing metastases can be better visualized on delayed contrast-enhanced T2 FLAIR using a half-dose high-relaxivity contrast agent.

The Tox21 10K Compound Library: Collaborative Chemistry Advancing Toxicology

Since 2009, the Tox21 project has screened ∼8500 chemicals in more than 70 high-throughput assays, generating upward of 100 million data points, with all data publicly available through partner websites at the United States Environmental Protection Agency (EPA), National Center for Advancing Translational Sciences (NCATS), and National Toxicology Program (NTP). Underpinning this public effort is the largest compound library ever constructed specifically for improving understanding of the chemical basis of toxicity across research and regulatory domains. Each Tox21 federal partner brought specialized resources and capabilities to the partnership, including three approximately equal-sized compound libraries. All Tox21 data generated to date have resulted from a confluence of ideas, technologies, and expertise used to design, screen, and analyze the Tox21 10K library. The different programmatic objectives of the partners led to three distinct, overlapping compound libraries that, when combined, not only covered a diversity of chemical structures, use-categories, and properties but also incorporated many types of compound replicates. The history of development of the Tox21 "10K" chemical library and data workflows implemented to ensure quality chemical annotations and allow for various reproducibility assessments are described. Cheminformatics profiling demonstrates how the three partner libraries complement one another to expand the reach of each individual library, as reflected in coverage of regulatory lists, predicted toxicity end points, and physicochemical properties. ToxPrint chemotypes (CTs) and enrichment approaches further demonstrate how the combined partner libraries amplify structure-activity patterns that would otherwise not be detected. Finally, CT enrichments are used to probe global patterns of activity in combined ToxCast and Tox21 activity data sets relative to test-set size and chemical versus biological end point diversity, illustrating the power of CT approaches to discern patterns in chemical-activity data sets. These results support a central premise of the Tox21 program: A collaborative merging of programmatically distinct compound libraries would yield greater rewards than could be achieved separately.

The Tox21 10K Compound Library: Collaborative Chemistry Advancing Toxicology

Since 2009, the Tox21 project has screened ∼8500 chemicals in more than 70 high-throughput assays, generating upward of 100 million data points, with all data publicly available through partner websites at the United States Environmental Protection Agency (EPA), National Center for Advancing Translational Sciences (NCATS), and National Toxicology Program (NTP). Underpinning this public effort is the largest compound library ever constructed specifically for improving understanding of the chemical basis of toxicity across research and regulatory domains. Each Tox21 federal partner brought specialized resources and capabilities to the partnership, including three approximately equal-sized compound libraries. All Tox21 data generated to date have resulted from a confluence of ideas, technologies, and expertise used to design, screen, and analyze the Tox21 10K library. The different programmatic objectives of the partners led to three distinct, overlapping compound libraries that, when combined, not only covered a diversity of chemical structures, use-categories, and properties but also incorporated many types of compound replicates. The history of development of the Tox21 "10K" chemical library and data workflows implemented to ensure quality chemical annotations and allow for various reproducibility assessments are described. Cheminformatics profiling demonstrates how the three partner libraries complement one another to expand the reach of each individual library, as reflected in coverage of regulatory lists, predicted toxicity end points, and physicochemical properties. ToxPrint chemotypes (CTs) and enrichment approaches further demonstrate how the combined partner libraries amplify structure-activity patterns that would otherwise not be detected. Finally, CT enrichments are used to probe global patterns of activity in combined ToxCast and Tox21 activity data sets relative to test-set size and chemical versus biological end point diversity, illustrating the power of CT approaches to discern patterns in chemical-activity data sets. These results support a central premise of the Tox21 program: A collaborative merging of programmatically distinct compound libraries would yield greater rewards than could be achieved separately.

Deep Graph Learning with Property Augmentation for Predicting Drug-Induced Liver Injury

Drug-induced liver injury (DILI) is a crucial factor in determining the qualification of potential drugs. However, the DILI property is excessively difficult to obtain due to the complex testing process. Consequently, an in silico screening in the early stage of drug discovery would help to reduce the total development cost by filtering those drug candidates with a high risk to cause DILI. To serve the screening goal, we apply several computational techniques to predict the DILI property, including traditional machine learning methods and graph-based deep learning techniques. While deep learning models require large training data to tune huge model parameters, the DILI data set only contains a few hundred annotated molecules. To alleviate the data scarcity problem, we propose a property augmentation strategy to include massive training data with other property information. Extensive experiments demonstrate that our proposed method significantly outperforms all existing baselines on the DILI data set by obtaining a 81.4% accuracy using cross-validation with random splitting, 78.7% using leave-one-out cross-validation, and 76.5% using cross-validation with scaffold splitting.

An Integrated Systems Biology Approach Identifies the Proteasome as A Critical Host Machinery for ZIKV and DENV Replication

The Zika virus (ZIKV) and dengue virus (DENV) flaviviruses exhibit similar replicative processes but have distinct clinical outcomes. A systematic understanding of virus-host protein-protein interaction networks can reveal cellular pathways critical to viral replication and disease pathogenesis. Here we employed three independent systems biology approaches toward this goal. First, protein array analysis of direct interactions between individual ZIKV/DENV viral proteins and 20,240 human proteins revealed multiple conserved cellular pathways and protein complexes, including proteasome complexes. Second, an RNAi screen of 10,415 druggable genes identified the host proteins required for ZIKV infection and uncovered that proteasome proteins were crucial in this process. Third, high-throughput screening of 6016 bioactive compounds for ZIKV inhibition yielded 134 effective compounds, including six proteasome inhibitors that suppress both ZIKV and DENV replication. Integrative analyses of these orthogonal datasets pinpoint proteasomes as critical host machinery for ZIKV/DENV replication. Our study provides multi-omics datasets for further studies of flavivirus-host interactions, disease pathogenesis, and new drug targets.

Trade-off Predictivity and Explainability for Machine-Learning Powered Predictive Toxicology: An in-Depth Investigation with Tox21 Data Sets

Selecting a model in predictive toxicology often involves a trade-off between prediction performance and explainability: should we sacrifice the model performance to gain explainability or vice versa. Here we present a comprehensive study to assess algorithm and feature influences on model performance in chemical toxicity research. We conducted over 5000 models for a Tox21 bioassay data set of 65 assays and ∼7600 compounds. Seven molecular representations as features and 12 modeling approaches varying in complexity and explainability were employed to systematically investigate the impact of various factors on model performance and explainability. We demonstrated that end points dictated a model's performance, regardless of the chosen modeling approach including deep learning and chemical features. Overall, more complex models such as (LS-)SVM and Random Forest performed marginally better than simpler models such as linear regression and KNN in the presented Tox21 data analysis. Since a simpler model with acceptable performance often also is easy to interpret for the Tox21 data set, it clearly was the preferred choice due to its better explainability. Given that each data set had its own error structure both for dependent and independent variables, we strongly recommend that it is important to conduct a systematic study with a broad range of model complexity and feature explainability to identify model balancing its predictivity and explainability.

Evaluation of chemical compounds that inhibit neurite outgrowth using GFP-labeled iPSC-derived human neurons

Due to the increasing number of drugs and untested environmental compounds introduced into commercial use, there is recognition for a need to develop reliable and efficient screening methods to identify compounds that may adversely impact the nervous system. One process that has been implicated in neurodevelopment is neurite outgrowth; the disruption of which can result in adverse outcomes that persist later in life. Here, we developed a green fluorescent protein (GFP) labeled neurite outgrowth assay in a high-content, high-throughput format using induced pluripotent stem cell (iPSC) derived human spinal motor neurons and cortical glutamatergic neurons. The assay was optimized for use in a 1536-well plate format. Then, we used this assay to screen a set of 84 unique compounds that have previously been screened in other neurite outgrowth assays. This library consists of known developmental neurotoxicants, environmental compounds with unknown toxicity, and negative controls. Neurons were cultured for 40 h and then treated with compounds at 11 concentrations ranging from 1.56 nM to 92 μM for 24 and 48 h. Effects of compounds on neurite outgrowth were evaluated by quantifying total neurite length, number of segments, and maximum neurite length per cell. Among the 84 tested compounds, neurite outgrowth in cortical neurons and motor neurons were selectively inhibited by 36 and 31 compounds, respectively. Colchicine, rotenone, and methyl mercuric (II) chloride inhibited neurite outgrowth in both cortical and motor neurons. It is interesting to note that some compounds like parathion and bisphenol AF had inhibitory effects on neurite outgrowth specifically in the cortical neurons, while other compounds, such as 2,2',4,4'-tetrabromodiphenyl ether and caffeine, inhibited neurite outgrowth in motor neurons. The data gathered from these studies show that GFP-labeled iPSC-derived human neurons are a promising tool for identifying and prioritizing compounds with developmental neurotoxicity potential for further hazard characterization.

Drug Repurposing Screen for Compounds Inhibiting the Cytopathic Effect of SARS-CoV-2

Drug repurposing is a rapid approach to identify therapeutics for the treatment of emerging infectious diseases such as COVID-19. To address the urgent need for treatment options, we carried out a quantitative high-throughput screen using a SARS-CoV-2 cytopathic assay with a compound collection of 8,810 approved and investigational drugs, mechanism-based bioactive compounds, and natural products. Three hundred and nineteen compounds with anti-SARS-CoV-2 activities were identified and confirmed, including 91 approved drugs and 49 investigational drugs. The anti-SARS-CoV-2 activities of 230 of these confirmed compounds, of which 38 are approved drugs, have not been previously reported. Chlorprothixene, methotrimeprazine, and piperacetazine were the three most potent FDA-approved drugs with anti-SARS-CoV-2 activities. These three compounds have not been previously reported to have anti-SARS-CoV-2 activities, although their antiviral activities against SARS-CoV and Ebola virus have been reported. These results demonstrate that this comprehensive data set is a useful resource for drug repurposing efforts, including design of new drug combinations for clinical trials for SARS-CoV-2.

Spinal schwannoma causes acute subarachnoid haemorrhage: A case report and literature review

BACKGROUND

Spinal schwannomas that arise from spinal nerve root sheaths are the most common intradural extramedullary spinal tumours and are often accompanied by nerve roots or spinal cord irritation symptoms. The phenomenon of spinal schwannoma causing subarachnoid haemorrhage (SAH) is rare, with ependymoma of the conus medullaris accounting for most cases.

CASE REPORT

A 45-year-old man was admitted to our hospital due to progressive lower limb weakness and sudden back pain after hard physical work. The patient had not been able to walk for 2hours upon admission. An emergency magnetic resonance imaging (MRI) scan showed that the spinal cord at the C6-T4 level was severely compressed by a subdural mass. During the emergency operation, exploration of the dura and arachnoid mater revealed a fresh blood clot covering a tumour located on the ventral side of the spinal cord. The size of the tumour was approximately 3×2×1cm without adhesion to the surrounding tissue, but the drainage vein was ruptured. Postoperative pathology showed that the tumour was a schwannoma with areas of fresh haemorrhage and focal necrosis.

CONCLUSIONS

Spinal schwannomas presenting with SAH are rare events. In our opinion, spinal pathology with rapid progression of neurological symptoms requires early diagnosis and emergency management. Complete excision of haemorrhagic tumours is the goal of treatment to prevent recurrence, which can effectively avoid irreversible damage to the spinal cord resulting from spinal cord compression.

Systematic Identification of Molecular Targets and Pathways Related to Human Organ Level Toxicity

The mechanisms leading to organ level toxicities are poorly understood. In this study, we applied an integrated approach to deduce the molecular targets and biological pathways involved in chemically induced toxicity for eight common human organ level toxicity end points (carcinogenicity, cardiotoxicity, developmental toxicity, hepatotoxicity, nephrotoxicity, neurotoxicity, reproductive toxicity, and skin toxicity). Integrated analysis of in vitro assay data, molecular targets and pathway annotations from the literature, and toxicity-molecular target associations derived from text mining, combined with machine learning techniques, were used to generate molecular targets for each of the organ level toxicity end points. A total of 1516 toxicity-related genes were identified and subsequently analyzed for biological pathway coverage, resulting in 206 significant pathways (p-value <0.05), ranging from 3 (e.g., developmental toxicity) to 101 (e.g., skin toxicity) for each toxicity end point. This study presents a systematic and comprehensive analysis of molecular targets and pathways related to various in vivo toxicity end points. These molecular targets and pathways could aid in understanding the biological mechanisms of toxicity and serve as a guide for the design of suitable in vitro assays for more efficient toxicity testing. In addition, these results are complementary to the existing adverse outcome pathway (AOP) framework and can be used to aid in the development of novel AOPs. Our results provide abundant testable hypotheses for further experimental validation.

[Research frontiers in precision therapy for liver cancer]

Hepatocellular carcinoma (HCC), a fatal malignancy, is highly prevalent in China. Recently, tremendous achievements have been made in HCC, both in the clinical management and the understanding of cancer biology. The discovery and application of novel serum biomarkers, such as proteins, miRNAs, and cfDNA (cell-free circulating DNA) methylation will facilitate the early management of HCC. Improvements in radiological and computational technology have made the practice of precision liver surgery a true reality. The emergence of novel molecular targeted therapies, immunotherapy and their combinations has significantly prolonged patient survival rate, but the therapeutic breakthroughs are still needed. Integrated multi-omics analysis has broadened our understanding of HCC pathogenesis, providing an unprecedented molecular characterization of HCC and revealing new therapeutic opportunities. Technological innovations and revolutions such as single-cell sequencing, genome editing, and innovative drug research and development will greatly accelerate our understanding of HCC biology and bring new therapeutic opportunities. Nevertheless, HCC is a highly heterogeneous and treatment-refractory malignancy, therefore deep insights into the biology of the disease and novel therapies for HCC remain an unmet medical need.

Conversion and outcome of dual antiplatelet therapy after bleeding in patients with acute coronary syndrome

Objective

To explore the conversion and outcome of antiplatelet therapy in patients with acute coronary syndrome (ACS) who have suffered bleeding after receiving aspirin combined with ticagrelor.

Methods

Patients who diagnosed with ACS and given aspirin 100 mg once daily combined with ticagrelor 90 mg twice daily for dual antiplatelet therapy (DAPT) were selected. The patients were divided into bleeding group and non-bleeding group according to whether bleeding events occurred within one year after DAPT. The bleeding group was divided into the next four groups according to the converted antiplatelet treatment strategy decided by the doctor and the patient. Patients in group A to D were treated with ticagrelor 90mg twice a day plus aspirin 0–50mgonce a day, ticagrelor 60mg twice a day plus aspirin 100mgonce a day, clopidogrel 75mgonce a day plus aspirin 100mg once a day and ticagrelor 90mg twice a day plus aspirin 100mg once a day, respectively. All patients were followed up for 1 year after DAPT. The primary outcome is change of bleeding degree by BARC. The secondary outcomes includes BARC bleeding, all-cause mortality and MACE.

Results

A total of 752 cases were enrolled, including 250 in the bleeding group and 502 in the non-bleeding group. The bleeding group was divided into four treatment groups, which were 63, 43, 38 and 95 cases among A, B, C and D group. There was a significant difference in the improvement of bleeding among the four groups. To be noted, patients in group A has the highest improvement rate of hemorrhage (65.1% vs 62.8% vs 47.4% vs 24.2%, P&lt;0.01). There were no significant differences in the incidence of MACE and all-cause mortality (P&gt;0.05). The incidence of major MACE in patients in the bleeding group was 14.4%, which was higher than that in the non-bleeding group (9.2%, P=0.03).The result of multivariate logistic regression analysis showed that female (OR=5.18, 95% CI: 1.61–16.65, P=0.006), low body weight (OR=7.73, 95% CI: 2.46–24.49, P&lt;0.001) and low AA-induced maximum platelet aggregation rate (OR=2.72, 95% CI:1.09–6.84, P=0.033) were independent risk factors for hemorrhage.

Conclusion

Patients with acute coronary syndrome who have suffered bleeding after receiving aspirin combined with ticagrelor were at a higher risk of MACE than those who did not. Low-dose aspirin (0–50mg/d) combined with ticagrelor or even ticagrelor alone has the best effect on reducing bleeding without increasing the risk of ischemia. Female, low body mass and low AA-induced maximum platelet aggregation rate are independent risk factors for bleeding.

Funding Acknowledgement

Type of funding source: None

[Perceived organizational support and emotional stability modify the effect of depression tendency on burnout in doctors]

Objective: To explore and analyze the relationship between burnout, depression, perceived organizational support and emotional stability, as well as their interaction on burnout, so as to provide reference for improving the situation of burnout on doctors. Methods: By cluster random sampling, a cross-sectional survey of doctors in a municipal hospitals of Zhengzhou in June to August, 2015, Henan Province was conducted. The questionnaires of Maslach Burnout Inventory-General Survey (MBI-GS) , Perceived organizational support, Eysenck Personality Questionnair-Revission Short Scale of China (EPQ-RSC) and Center for Epidemiological Studies Depression Scale (CES-D) were used for questionnaire survey and analysis. Multiple regression analysis was used to explore the interaction of organizational support and emotional stability on depressive tendency and occupational burnout. Results: Among the 389 doctors, 147 were males and 242 were females. Age M (P(25), P(75)) was 33.0 (29.0, 40.0) years, and length of work M (P(25), P(75)) was 7.0 (4.0, 16.0) years. Burnout was positively correlated with depression tendency and emotional stability (r=0.571, 0.453, P<0.01) , while burnout was negatively correlated with perceived organizational support (r=-0.260, P<0.01) . The interaction among depression tendency, perceived organizational support and emotional stability was statistically significant (β=-0.002, P<0.05) , the independent effect on burnout is 1.0% (ΔR(2)=0.010) , the positive effect of emotional stability was the largest (β=0.550) , followed by the positive effect of depression tendency (β=0.494) . When the tendency of depression increased, the burnout of doctors with high perceived organizational support and emotional stability was higher than those with high perceived organizational support and emotional instability and those with low perceived organizational support (P<0.01) . Conclusion: Emotional stability is the main factor affecting the effect of depression tendency on doctors' burnout. Doctors with stable emotion and high perceived organizational support showed obvious changes in burnout when depression tendency increased, and showed stronger burnout.

Methylene blue is a potent and broad-spectrum inhibitor against Zika virus in vitro and in vivo

Many flaviviruses including the Dengue virus (DENV), Zika virus (ZIKV), West Nile virus, Yellow Fever virus, and Japanese encephalitis virus are significant human pathogens, unfortunately without any specific therapy. Here, we demonstrate that methylene blue, an FDA-approved drug, is a broad-spectrum and potent antiviral against Zika virus and Dengue virus both in vitro and in vivo. We found that methylene blue can considerably inhibit the interactions between viral protease NS3 and its NS2B co-factor, inhibit viral protease activity, inhibit viral growth, protect 3D mini-brain organoids from ZIKV infection, and reduce viremia in a mouse model. Mechanistic studies confirmed that methylene blue works in both entry and post entry steps, reduces virus production in replicon cells and inhibited production of processed NS3 protein. Overall, we have shown that methylene blue is a potent antiviral for management of flavivirus infections, particularly for Zika virus. As an FDA-approved drug, methylene blue is well-tolerated for human use. Therefore, methylene blue represents a promising and easily developed therapy for management of infections by ZIKV and other flaviviruses.

XIST lost induces ovarian cancer stem cells to acquire taxol resistance via a KMT2C-dependent way

BACKGROUND/AIMS

The expression levels of long non-coding RNA XIST are significantly associated with paclitaxel (Pac) sensitivity in ovarian cancer, but the mechanism of action remains unclear. Therefore, this experimental design was based on lncRNA XIST analysis to regulate the effect of XIST on the tumor stem cell and paclitaxel sensitivity in ovarian cancer.

METHODS

Sphere assay and fluorescence activated cell sorting (FACS) were used to determine the expression levels of XIST and sensitivity to paclitaxel treatment. The effect of the proliferation was detected by MTT assay. Target gene prediction and screening, luciferase reporter assays were used to validate downstream target genes for lncRNA XIS and KMT2C. The expression of KMT2C was detected by RT-qPCR and Western blotting. RT-qPCR was used to detect the expression of cancer stem cell-associated genes SOX2, OCT4 and Nanog. The tumor changes in mice were detected by in vivo experiments in nude mice.

RESULTS

There was an inverse correlation between the expression of XIST and cancer stem cell (CD44 + /CD24-) population. XIST promoted methylation of histone H3 methylation at lysine 4 by enhancing the stability of lysine (K)-specific methyltransferase 2C (KMT2C) mRNA. XIST acted on the stability of KMT2C mRNA by directly targeting miR-93-5p. Overexpression of miR-93-5p can reverse the XIST overexpression-induced KMT2C decrease and sphere number increase. Overexpression of KMT2C inhibited XIST silencing-induced proliferation of cancer stem cells, and KMT2C was able to mediate paclitaxel resistance induced by XIST in ovarian cancer. The study found that XIST can affect the expression of KMT2C in the ovarian cancer via targeting miR-93-5p.

CONCLUSION

XIST promoted the sensitivity of ovarian cancer stem cells to paclitaxel in a KMT2C-dependent manner.

Drug Repurposing Screen for Compounds Inhibiting the Cytopathic Effect of SARS-CoV-2

Drug repurposing is a rapid approach to identifying therapeutics for the treatment of emerging infectious diseases such as COVID-19. To address the urgent need for treatment options, we carried out a quantitative high-throughput screen using a SARS-CoV-2 cytopathic assay with a compound collection of 8,810 approved and investigational drugs, mechanism-based bioactive compounds, and natural products. Three hundred and nineteen compounds with anti-SARS-CoV-2 activities were identified and confirmed, including 91 approved drug and 49 investigational drugs. Among these confirmed compounds, the anti-SARS-CoV-2 activities of 230 compounds, including 38 approved drugs, have not been previously reported. Chlorprothixene, methotrimeprazine, and piperacetazine were the three most potent FDA approved drugs with anti-SARS-CoV-2 activities. These three compounds have not been previously reported to have anti-SARS-CoV-2 activities, although their antiviral activities against SARS-CoV and Ebola virus have been reported. These results demonstrate that this comprehensive data set of drug repurposing screen for SARS-CoV-2 is useful for drug repurposing efforts including design of new drug combinations for clinical trials.

[Covered airway stent loaded with (125)I seeds for tracheal adenoid cystic carcinoma: a clinical observation of 8 cases]

Objective: To explore the efficacy and safety of the covered airway stent loaded with (125)I seeds for the treatment of tracheal adenoid cystic carcinoma (TACC). Methods: We retrospectively reviewed the clinical data from 8 patients with TACC who had received placement of the covered stent loaded with (125)I seeds between December 2014 and July 2017 in the endoscopic center of the Second Affiliated Hospital of Xiamen Medical College. We compared the difference in the dyspnea index, the diameter of the airway lumen, and the lesion surrounding the airway wall before and after treatment. The complications were also recorded during follow-up. Results: Eight patients underwent successful placement of a total of 11 radioactive stents (2 straight-type stents, 2 L-shape stents, and 7 Y-shape stents, all loaded a total of 243 radioactive particles). Displacement of stents took place within 2 weeks in 2 patients, who were managed with re-stenting and fixation. No further displacement occurred during follow-up. The median time to stent removal was 2.9(interquartile range: 2.3,3.0) months. After stent placement, the dyspnea index was significantly decreased compared with pre-treatment level (mean: 0.1 vs. 3.4, t=8.881, P<0.001). Bronchoscopic re-assessment showed that the residual tumor within the airway was detected in only one patient and that the tumor completely disappeared in the remaining 7 patients. Treatment with stents loaded with radioactive particles yielded smooth and pale airway mucosa with formation of partial scar formation. Chest computed tomography re-assessment demonstrated significantly larger luminal diameter than that before treatment (mean: 13.1 mm vs. 3.3 mm, t=-7.839, P<0.001). The airway wall thickness was notably reduced after treatment (mean: 4.3 mm vs. 14.4 mm, t=7.620, P<0.001). The lesions surrounding the airway wall completely disappeared in 7 patients and decreased for more than 50% in a single patient. The median duration of follow-up was 28.0(interquartile range: 24.8,31.5) months. Recurrence of tumor was documented in a single case within 2 years. Six patients did not experience recurrence within the 2-year follow-up period. No death or severe complications were recorded during follow-up. Conclusion: The (125)I radioactive stent is effective for dilating the stenotic airway and ameliorating the symptoms, and thus might be an effective and safe method for the treatment of TACC. Further studies that explore the efficacy of stents loaded with (125)I particles are needed.

Massive-scale biological activity-based modeling identifies novel antiviral leads against SARS-CoV-2

The recent global pandemic caused by the new coronavirus SARS-CoV-2 presents an urgent need for new therapeutic candidates. While the importance of traditional in silico approaches such as QSAR in such efforts in unquestionable, these models fundamentally rely on structural similarity to infer biological activity and are thus prone to becoming trapped in the very nearby chemical spaces of already known ligands. For novel and unprecedented threats such as COVID-19 much faster and efficient paradigms must be devised to accelerate the identification of new chemical classes for rapid drug development. Here we report the development of a new biological activity-based modeling (BABM) approach that builds on the hypothesis that compounds with similar activity patterns tend to share similar targets or mechanisms of action. In BABM, compound activity profiles established on massive scale across multiple assays are used as signatures to predict compound activity in a new assay or against a new target. We first trained and validated this approach by identifying new antiviral lead candidates for Zika and Ebola based on data from ~0.5 million compounds screened against ~2,000 assays. BABM models were then applied to predict ~300 compounds not previously reported to have activity for SARS-CoV-2, which were then tested in a live virus assay with high (>30%) hit rates. The most potent compounds showed antiviral activities in the nanomolar range. These potent confirmed compounds have the potential to be further developed in novel chemical space into new anti-SARS-CoV-2 therapies. These results demonstrate unprecedented ability using BABM to predict novel structures as chemical leads significantly beyond traditional methods, and its application in rapid drug discovery response in a global public health crisis.

Drug Repositioning for Noonan and LEOPARD Syndromes by Integrating Transcriptomics With a Structure-Based Approach

Noonan and LEOPARD syndromes (NS and LS) belong to a group of related disorders called RASopathies characterized by abnormalities of multiple organs and systems including hypertrophic cardiomyopathy and dysmorphic facial features. There are no approved drugs for these two rare diseases, but it is known that a missense mutation in PTPN11 genes is associated with approximately 50% and 70% of NS and LS cases, respectively. In this study, we implemented a hybrid computational drug repositioning framework by integrating transcriptomic and structure-based approaches to explore potential treatment options for NS and LS. Specifically, disease signatures were derived from the transcriptomic profiles of human induced pluripotent stem cells (iPSCs) from NS and LS patients and reverse correlated to drug transcriptomic signatures from CMap and L1000 projects on the basis that if disease and drug transcriptomic signatures are reversely correlated, the drug has the potential to treat that disease. The compounds that were ranked top based on their transcriptomic profiles were docked to mutated and wild-type 3D structures of PTPN11 by an adjusted Induced Fit Docking (IFD) protocol. In addition, we prioritized repositioned candidates for NS and LS by a consensus ranking strategy. Network analysis and phenotypic anchoring of the transcriptomic data could discriminate the two diseases at the molecular level. Furthermore, the adjusted IFD protocol was able to recapitulate the binding specificity of potential drug candidates to mutated 3D structures, revealing the relevant amino acids. Importantly, a list of potential drug candidates for repositioning was identified including 61 for NS and 43 for LS and was further verified from literature reports and on-going clinical trials. Altogether, this hybrid computational drug repositioning approach has highlighted a number of drug candidates for NS and LS and could be applied to identifying drug candidates for other diseases as well.

[A multicenter randomized prospective study of concurrent chemoradiation with 60 Gy versus 50 Gy for inoperable esophageal squamous cell carcinoma]

Objective: To determine whether 60 Gy is superior to standard 50 Gy for definitive concurrent chemoradiation(CCRT) in esophageal squamous cell carcinoma (ESCC) using modern radiation technology in a phase Ⅲ prospective randomized trial. Methods: From April 2013 to May 2017, 331 patients from 22 hospitals who were pathologically confirmed with stage ⅢA-ⅣA ESCC were randomized to 60 Gy or 50 Gy with random number table. Total of 305 patients were analyzed, including 152 in 60 Gy group and 153 in 50 Gy group. The median age was 63 years, 242(79.3%) males and 63(20.7%) females. The median length of primary tumor was 5.6 cm. The clinical characteristics between two groups were comparable. All patients were delivered 2 Gy per fraction, 5 fractions per week. Concurrent weekly chemotherapy with docetaxel (25 mg/m(2)) and cisplatin (25 mg/m(2)) and 2 cycles consolidation chemotherapy with docetaxel (70 mg/m(2)) and cisplatin (25 mg/m(2), d1-3) were administrated. The primary endpoint was local/regional progression-free survival (LRPFS). The data were compared with Pearson chi-square test or Fisher's exact test. Results: At a median follow-up of 27.3 months, the disease progression rate was 37.5% (57/152), 43.8% (67/153) in the high and standard-dose group, respectively (χ(2)=1.251, P=0.263). The 1, 2, 3-year LRPFS rate was 75.4%, 56.8%, 52.1% and 74.2%, 58.4%, 50.1%, respectively (HR: 0.95, 95%CI: 0.69-1.31, P=0.761). The 1, 2, 3-year overall survival rate was 84.1%, 64.8%, 54.1% and 85.4%, 62.9%, 54.0%, respectively (HR: 0.98, 95%CI: 0.71-1.38, P=0.927). The 1, 2, 3-year progression-free survival rate was 70.8%, 54.2%, 48.5% and 65.5%, 51.9%, 45.1%, respectively (HR: 0.93, 95%CI: 0.68-1.26, P=0.621). The incidence rates in toxicities between the two groups were similar except for higher rate of severe pneumonitis in high dose group (χ(2)=11.596, P=0.021). Conclusions: The efficacy in disease control is similar between 60 Gy and 50 Gy using modern radiation technology concurrent with chemotherapy for ESCC. The 50 Gy should be recommended as the regular radiation dose with CCRT for ESCC.

[Differences in efficacy between drug-eluting beads transbronchial arterial chemoembolization combined with systemic chemotherapy and systemic chemotherapy alone for unresectable lung squamous cell carcinoma]

Objective: To investigate the differences in efficacy between drug-eluting beads transbronchial arterial chemoembolization (DEB-BACE) combined with systemic chemotherapy and systemic chemotherapy alone for unresectable lung squamous cell carcinoma. Methods: Totally 60 cases of unresectable lung squamous cell carcinoma undergoing systemic chemotherapy in Yancheng Third People Hospital were retrospectively selected as the research object. According to patients' wishes, they were divided into chemotherapy-only group (group A) and combined treatment group (group B). Group A received gemcitabine combined with cisplatin chemotherapy. DEB-BACE was applied in the first half, and systemic chemotherapy was administered in the second half (starting 3 d after BACE). The first half and the second half of the chemotherapy dose were 1/2 of the drug dose in the chemotherapy alone group. The short-term efficacy, incidence of toxic side effects, peripheral blood T lymphocyte subsets, serum vascular endothelial growth factor (VEGF) levels, and survival time were compared between the two groups. Results: After 2 cycles of treatment, the total effective rates of group A and group B were 50.0% (15/30) and 76.7% (23/30) (P<0.05), the incidence of nausea and vomiting (63.3% vs 20.0%), decreased appetite (76.7% vs 43.3%), hair loss (86.7% vs 40.0%), and bone marrow suppression (40.0% vs 10.0%) in group A were higher than in group B (all P<0.05). After 2 cycles of treatment, the levels of CD3(+), CD4(+)and CD4(+)/CD8(+)in the two groups were higher than before treatment (group A: 47.7%±6.6% vs 52.3%±7.7%, 31.5%±4.9% vs 34.7%±5.8%, 1.05±0.24 vs 1.18±0.32; group B: 49.2%±7.0% vs 62.0%±14.0%,29.2%±5.5% vs 42.2%±7.3%, 1.07±0.26 vs 1.39±0.42; all P<0.05), while the level of CD8(+)was lower than before treatment (group A: 30.4%±5.4% vs 24.5%±4.8%; group B: 29.5%±4.1% vs 21.1%±4.5%; all P<0.05). The CD3(+), CD4(+), and CD4(+)/CD8(+) levels in group A were lower than those in group B (P<0.05), while CD8(+)level was higher than in group B (P<0.05). After 2 cycles of treatment, the VEGF levels in the two groups were lower than before treatment (group A: (423±85) vs (352±64) ng/L; group B: (404±114) vs (296±66) ng/L; P<0.05), and the VEGF level in group A was higher than that in group B (P<0.05). The 1-year survival rates of groups A and B were 54.9% and 77.9%, and the 2-year survival rates were 17.2% and 41.7% (Log rank χ(2)=4.750, P=0.029). Conclusion: DEB-BACE combined with systemic chemotherapy is superior to systemic chemotherapy in the treatment of unresectable lung squamous cell carcinoma. It can reduce toxic and side effects, improve immune function and prolong survival time, which is worthy of clinical application.

Predictive Models for Human Organ Toxicity Based on In Vitro Bioactivity Data and Chemical Structure

Traditional toxicity testing reliant on animal models is costly and low throughput, posing a significant challenge with the increasing numbers of chemicals that humans are exposed to in the environment. The purpose of this investigation was to build optimal prediction models for various human in vivo/organ-level toxicity end points (extracted from ChemIDPlus) using chemical structure and Tox21 in vitro quantitative high-throughput screening (qHTS) bioactivity assay data. Several supervised machine learning algorithms were applied to model 14 human toxicity end points pertaining to vascular, kidney, ureter and bladder, and liver organ systems. Three metrics were used to evaluate model performance: area under the receiver operating characteristic curve (AUC-ROC), balanced accuracy (BA), and Matthews correlation coefficient (MCC). The top four models, with AUC-ROC values >0.8, were derived for endocrine (0.90 ± 0.00), musculoskeletal (0.88 ± 0.02), peripheral nerve and sensation (0.85 ± 0.01), and brain and coverings (0.83 ± 0.02) toxicities, whereas the best model AUC-ROC values were >0.7 for the remaining 10 toxicities. Model performance was found to be dependent on the specific data set, model type, and feature selection method used. In addition, chemical structure and assay data showed different levels of contribution to the prediction of different toxicity end points. Although in vitro assay data, when combined with chemical structure, slightly improved the predictive accuracy for most end points (11 out of 14), a noteworthy finding was the near equal success of the structure-only models, which do not require Tox21 qHTS screening data, and the relatively poor performance of assay-only models. Thus, the top-performing structure-only models from this study could be applied for hazard screening of large sets of chemicals for potential human toxicity, whereas the largest assay contributions to models (i.e., cellular targets) could be used, along with the top-contributing structural features, to provide insight into toxicity mechanisms.

Stem Cell-Derived Endothelial Cell Model that Responds to Tobacco Smoke Like Primary Endothelial Cells

To clarify how smoking leads to heart attack and stroke, we developed an endothelial cell model (iECs) generated from human induced Pluripotent Stem Cells (iPSC) and evaluated its responses to tobacco smoke. These iECs exhibited a uniform endothelial morphology, and expressed markers PECAM1/CD31, VWF/ von Willebrand Factor, and CDH5/VE-Cadherin. The iECs also exhibited tube formation and acetyl-LDL uptake comparable to primary endothelial cells (EC). RNA sequencing (RNA-Seq) revealed a robust correlation coefficient between iECs and EC (R = 0.76), whereas gene responses to smoke were qualitatively nearly identical between iECs and primary ECs (R = 0.86). Further analysis of transcriptional responses implicated 18 transcription factors in regulating responses to smoke treatment, and identified gene sets regulated by each transcription factor, including pathways for oxidative stress, DNA damage/repair, ER stress, apoptosis, and cell cycle arrest. Assays for 42 cytokines in HUVEC cells and iECs identified 23 cytokines that responded dynamically to cigarette smoke. These cytokines and cellular stress response pathways describe endothelial responses for lymphocyte attachment, activation of coagulation and complement, lymphocyte growth factors, and inflammation and fibrosis; EC-initiated events that collectively lead to atherosclerosis. Thus, these studies validate the iEC model and identify transcriptional response networks by which ECs respond to tobacco smoke. Our results systematically trace how ECs use these response networks to regulate genes and pathways, and finally cytokine signals to other cells, to initiate the diverse processes that lead to atherosclerosis and cardiovascular disease.

Two-Dimensional Cellular and Three-Dimensional Bio-Printed Skin Models to Screen Topical-Use Compounds for Irritation Potential

Assessing skin irritation potential is critical for the safety evaluation of topical drugs and other consumer products such as cosmetics. The use of advanced cellular models, as an alternative to replace animal testing in the safety evaluation for both consumer products and ingredients, is already mandated by law in the European Union (EU) and other countries. However, there has not yet been a large-scale comparison of the effects of topical-use compounds in different cellular skin models. This study assesses the irritation potential of topical-use compounds in different cellular models of the skin that are compatible with high throughput screening (HTS) platforms. A set of 451 topical-use compounds were first tested for cytotoxic effects using two-dimensional (2D) monolayer models of primary neonatal keratinocytes and immortalized human keratinocytes. Forty-six toxic compounds identified from the initial screen with the monolayer culture systems were further tested for skin irritation potential on reconstructed human epidermis (RhE) and full thickness skin (FTS) three-dimensional (3D) tissue model constructs. Skin irritation potential of the compounds was assessed by measuring tissue viability, trans-epithelial electrical resistance (TEER), and secretion of cytokines interleukin 1 alpha (IL-1α) and interleukin 18 (IL-18). Among known irritants, high concentrations of methyl violet and methylrosaniline decreased viability, lowered TEER, and increased IL-1α secretion in both RhE and FTS models, consistent with irritant properties. However, at low concentrations, these two compounds increased IL-18 secretion without affecting levels of secreted IL-1α, and did not reduce tissue viability and TEER, in either RhE or FTS models. This result suggests that at low concentrations, methyl violet and methylrosaniline have an allergic potential without causing irritation. Using both HTS-compatible 2D cellular and 3D tissue skin models, together with irritation relevant activity endpoints, we obtained data to help assess the irritation effects of topical-use compounds and identify potential dermal hazards.

CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity

BACKGROUND

Endocrine disrupting chemicals (EDCs) are xenobiotics that mimic the interaction of natural hormones and alter synthesis, transport, or metabolic pathways. The prospect of EDCs causing adverse health effects in humans and wildlife has led to the development of scientific and regulatory approaches for evaluating bioactivity. This need is being addressed using high-throughput screening (HTS) in vitro approaches and computational modeling.

OBJECTIVES

In support of the Endocrine Disruptor Screening Program, the U.S. Environmental Protection Agency (EPA) led two worldwide consortiums to virtually screen chemicals for their potential estrogenic and androgenic activities. Here, we describe the Collaborative Modeling Project for Androgen Receptor Activity (CoMPARA) efforts, which follows the steps of the Collaborative Estrogen Receptor Activity Prediction Project (CERAPP).

METHODS

The CoMPARA list of screened chemicals built on CERAPP's list of 32,464 chemicals to include additional chemicals of interest, as well as simulated ToxCast™ metabolites, totaling 55,450 chemical structures. Computational toxicology scientists from 25 international groups contributed 91 predictive models for binding, agonist, and antagonist activity predictions. Models were underpinned by a common training set of 1,746 chemicals compiled from a combined data set of 11 ToxCast™/Tox21 HTS in vitro assays.

RESULTS

The resulting models were evaluated using curated literature data extracted from different sources. To overcome the limitations of single-model approaches, CoMPARA predictions were combined into consensus models that provided averaged predictive accuracy of approximately 80% for the evaluation set.

DISCUSSION

The strengths and limitations of the consensus predictions were discussed with example chemicals; then, the models were implemented into the free and open-source OPERA application to enable screening of new chemicals with a defined applicability domain and accuracy assessment. This implementation was used to screen the entire EPA DSSTox database of ∼875,000 chemicals, and their predicted AR activities have been made available on the EPA CompTox Chemicals dashboard and National Toxicology Program's Integrated Chemical Environment. https://doi.org/10.1289/EHP5580.

CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity

BACKGROUND

Endocrine disrupting chemicals (EDCs) are xenobiotics that mimic the interaction of natural hormones and alter synthesis, transport, or metabolic pathways. The prospect of EDCs causing adverse health effects in humans and wildlife has led to the development of scientific and regulatory approaches for evaluating bioactivity. This need is being addressed using high-throughput screening (HTS) in vitro approaches and computational modeling.

OBJECTIVES

In support of the Endocrine Disruptor Screening Program, the U.S. Environmental Protection Agency (EPA) led two worldwide consortiums to virtually screen chemicals for their potential estrogenic and androgenic activities. Here, we describe the Collaborative Modeling Project for Androgen Receptor Activity (CoMPARA) efforts, which follows the steps of the Collaborative Estrogen Receptor Activity Prediction Project (CERAPP).

METHODS

The CoMPARA list of screened chemicals built on CERAPP's list of 32,464 chemicals to include additional chemicals of interest, as well as simulated ToxCast™ metabolites, totaling 55,450 chemical structures. Computational toxicology scientists from 25 international groups contributed 91 predictive models for binding, agonist, and antagonist activity predictions. Models were underpinned by a common training set of 1,746 chemicals compiled from a combined data set of 11 ToxCast™/Tox21 HTS in vitro assays.

RESULTS

The resulting models were evaluated using curated literature data extracted from different sources. To overcome the limitations of single-model approaches, CoMPARA predictions were combined into consensus models that provided averaged predictive accuracy of approximately 80% for the evaluation set.

DISCUSSION

The strengths and limitations of the consensus predictions were discussed with example chemicals; then, the models were implemented into the free and open-source OPERA application to enable screening of new chemicals with a defined applicability domain and accuracy assessment. This implementation was used to screen the entire EPA DSSTox database of ∼ 875,000 chemicals, and their predicted AR activities have been made available on the EPA CompTox Chemicals dashboard and National Toxicology Program's Integrated Chemical Environment. https://doi.org/10.1289/EHP5580.

Mitochondrial dysfunction is involved in aristolochic acid I-induced apoptosis in renal proximal tubular epithelial cells

Aristolochic acid (AA) is a compound extracted from the Aristolochia species of herbs. AA exposure is associated with kidney injury known as aristolochic acid nephropathy (AAN). Proximal tubular epithelial cell (PTEC) is the primary target of AA and rich in mitochondria. Recently, increasing evidence suggests that mitochondrial dysfunction plays a critical role in the pathogenesis of kidney disease. However, the status of mitochondrial function in PTEC after exposure to AA remains largely unknown. The aim of this study was to explore the effect of aristolochic acid I (AAI) on cell apoptosis and mitochondrial function in PTEC. Normal rat kidney-52E (NRK-52E) cells were exposed to different concentrations of AAI for different time periods. Cell viability was detected by 3-(4,5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide, cell apoptosis was analyzed by flow cytometry, and the expression of cleaved caspase-3 by Western blotting. Mitochondrial function was evaluated by reactive oxygen species (ROS), mitochondrial membrane potential (MMP), mitochondrial DNA (mtDNA) copy number, and adenosine triphosphate (ATP). It was found that AAI reduced cell viability and increased cell apoptosis in a dose- and time-dependent manner. In parallel to increased apoptosis, NRK-52E cell manifested signs of mitochondrial dysfunction in response to AAI treatment. The data indicated that AAI could increase ROS level, lower MMP, decrease mtDNA copy number, and reduce ATP production. In addition, Szeto-Schiller 31, a mitochondria-targeted antioxidant peptide, attenuated AAI-induced mitochondrial dysfunction and apoptosis. Our study depicted significant aberrant of mitochondrial function in AAI-treated NRK-52E cell, which suggested that mitochondrial dysfunction may be involved in AAI-induced apoptosis in PTEC.

Identification and Profiling of Environmental Chemicals That Inhibit the TGFβ/SMAD Signaling Pathway

The transforming growth factor beta (TGFβ) superfamily of secreted signaling molecules and their cognate receptors regulate cell fate and behaviors relevant to many developmental and disease processes. Disruption of TGFβ signaling during embryonic development can, for example, affect morphogenesis and differentiation through complex pathways that may be SMAD (Small Mothers Against Decapentaplegic) dependent or SMAD independent. In the present study, the SMAD Binding Element (SBE)-beta lactamase (bla) HEK 293T cell line, which responds to the activation of the SMAD2/3/4 complex, was used in a quantitative high-throughput screening (qHTS) assay to identify potential TGFβ disruptors in the Tox21 10K compound library. From the primary screening we identified several kinase inhibitors, organometallic compounds, and dithiocarbamates (DTCs) that inhibited TGFβ1-induced SMAD signaling of reporter gene activation independent of cytotoxicity. Counterscreen of SBE antagonists on human embryonic neural stem cells demonstrated cytotoxicity, providing additional evidence to support evaluation of these compounds for developmental toxicity. We profiled the inhibitory patterns of putative SBE antagonists toward other developmental signaling pathways, including wingless-related integration site (WNT), retinoic acid α receptor (RAR), and sonic hedgehog (SHH). The profiling results from SBE-bla assay identify chemicals that disrupt TGFβ/SMAD signaling as part of an integrated qHTS approach for prioritizing putative developmental toxicants.

Bioactivity Signatures of Drugs vs. Environmental Chemicals Revealed by Tox21 High-Throughput Screening Assays

Humans are exposed to tens of thousands of chemicals over the course of a lifetime, yet there remains inadequate data on the potential harmful effects of these substances on human health. Using quantitative high-throughput screening (qHTS), we can test these compounds for potential toxicity in a more efficient and cost-effective way compared to traditional animal studies. Tox21 has developed a library of ~10,000 chemicals (Tox21 10K) comprising one-third approved and investigational drugs and two-thirds environmental chemicals. In this study, the Tox21 10K was screened in a qHTS format against a panel of 70 cell-based assays with 213 readouts covering a broad range of biological pathways. Activity profiles were compared with chemical structure to assess their ability to differentiate drugs from environmental chemicals, and structure was found to be a better predictor of which chemicals are likely to be drugs. Drugs and environmental chemicals were further analyzed for diversity in structure and biological response space and showed distinguishable, but not distinct, responses in the Tox21 assays. Inclusion of other targets and pathways to further diversify the biological response space covered by these assays is likely required to better evaluate the safety profile of drugs and environmental chemicals to prioritize for in-depth toxicological studies.

MiR-519d reduces the 5-fluorouracil resistance in colorectal cancer cells by down-regulating the expression of CCND1

OBJECTIVE

To investigate the effects of miR-519d on the 5-fluorouracil resistance in colorectal cancer cells and to explore the mechanism.

MATERIALS AND METHODS

Colorectal cancer cells HCT116 and SW480 were transfected with miR519d-mimic or siCCND1 by transient transfection. The sensitivity of cells to 5-Fu was assayed by MTT assay. Dual luciferase assay was used to examine the effect of CCND1 on the sensitivity of cells to 5-Fu mediated by miR-519d.

RESULTS

MiR-519d was overexpressed in colorectal cancer cells after transient transfection with miR-519d mimics. Overexpression of miR-519d increased the sensitivity of colorectal cancer cells to 5-Fu. MiR-519d negatively regulated the expression of CCND1 via directly bound to CCND1 3`UTR. si-CCND1 could downregulate the CCND1 expression in colorectal cancer HCT116 and SW480 cells. si-CCND1 increased the sensitivity of colorectal cancer cells to 5-Fu.

CONCLUSIONS

miR-519d inhibits the expression of CCND1 and then plays a role in alleviating 5-Fu resistance in colorectal cancer cells.

Novel Consensus Architecture To Improve Performance of Large-Scale Multitask Deep Learning QSAR Models

Advances in the development of high-throughput screening and automated chemistry have rapidly accelerated the production of chemical and biological data, much of them freely accessible through literature aggregator services such as ChEMBL and PubChem. Here, we explore how to use this comprehensive mapping of chemical biology space to support the development of large-scale quantitative structure-activity relationship (QSAR) models. We propose a new deep learning consensus architecture (DLCA) that combines consensus and multitask deep learning approaches together to generate large-scale QSAR models. This method improves knowledge transfer across different target/assays while also integrating contributions from models based on different descriptors. The proposed approach was validated and compared with proteochemometrics, multitask deep learning, and Random Forest methods paired with various descriptors types. DLCA models demonstrated improved prediction accuracy for both regression and classification tasks. The best models together with their modeling sets are provided through publicly available web services at https://predictor.ncats.io .

The NCATS Pharmaceutical Collection: a 10-year update

The National Center for Advancing Translational Sciences (NCATS) Pharmaceutical Collection (NPC), a comprehensive collection of clinically approved drugs, was made a public resource in 2011. Over the past decade, the NPC has been systematically profiled for activity across an array of pathways and disease models, generating an unparalleled amount of data. These data have not only enabled the identification of new repurposing candidates with several in clinical trials, but also uncovered new biological insights into drug targets and disease mechanisms. This retrospective provides an update on the NPC in terms of both successes and lessons learned. We also report our efforts in bringing the NPC up-to-date with drugs approved in recent years.

MiR-223 regulates CDDP resistance in pancreatic cancer via targeting FoxO3a

OBJECTIVE

FoxO3a is a well-defined tumor suppressor gene in the forkhead transcription factor O subfamily (FoxO), and its reduction is related to the occurrence of various tumors. It was found that miR-223 expression is abnormally elevated in pancreatic cancer tissues. Bioinformatics analysis revealed a targeted complementary binding relationship between miR-223 and FoxO3a. This study explored whether miR-155 regulates the expression of FoxO3a and affects the proliferation, apoptosis, and cisplatin (CDDP) resistance of oral cancer cells.

MATERIALS AND METHODS

Dual-Luciferase reporter gene assay validated the targeted relationship between miR-223 and FoxO3a. The CDDP-resistant pancreatic cancer cell line BXPC3/CDDP was established, and the expressions of miR-223 and FoxO3a were compared. BXPC3/CDDP cells were divided into miR-NC group and miR-223 inhibitor group. QRT-PCR was adopted to test miR-223 and FoxO3a mRNA expressions. Western blot was performed to determine FoxO3a protein expression. Cell apoptosis was detected by flow cytometry and cell proliferation was detected by EdU staining.

RESULTS

There was a targeted regulatory relationship between miR-223 and FoxO3a mRNA. The expression of miR-223 was significantly higher, while the expression of FoxO3a mRNA and protein was significantly lower in BXPC3/CDDP cells than that in BXPC3 cells. Cell Counting Kit-8 (CCK-8) experiments showed that the same concentration of CDDP exhibited significantly lower proliferation inhibition in BXPC3/CDDP cells than BXPC3 cells. Compared with miR-NC group, transfection of miR-223 inhibitor significantly increased the expression of FoxO3a in BXPC3/CDDP cells, which significantly attenuated cell proliferation and enhanced apoptosis in CDDP-treated cells.

CONCLUSIONS

Increased expression of miR-233 was associated with CDDP resistance in pancreatic cancer cells. Inhibition of miR-223 expression upregulated FoxO3a expression, restrained pancreatic cancer cell proliferation, promoted cell apoptosis, and enhanced CDDP sensitivity in pancreatic cancer cells.

Limited Chemical Structural Diversity Found to Modulate Thyroid Hormone Receptor in the Tox21 Chemical Library

BACKGROUND

Thyroid hormone receptors (TRs) are critical endocrine receptors that regulate a multitude of processes in adult and developing organisms, and thyroid hormone disruption is of high concern for neurodevelopmental and reproductive toxicities in particular. To date, only a small number of chemical classes have been identified as possible TR modulators, and the receptors appear highly selective with respect to the ligand structural diversity. Thus, the question of whether TRs are an important screening target for protection of human and wildlife health remains.

OBJECTIVE

Our goal was to evaluate the hypothesis that there is limited structural diversity among environmentally relevant chemicals capable of modulating TR activity via the collaborative interagency Tox21 project.

METHODS

We screened the Tox21 chemical library (8,305 unique structures) in a quantitative high-throughput, cell-based reporter gene assay for TR agonist or antagonist activity. Active compounds were further characterized using additional orthogonal assays, including mammalian one-hybrid assays, coactivator recruitment assays, and a high-throughput, fluorescent imaging, nuclear receptor translocation assay.

RESULTS

Known agonist reference chemicals were readily identified in the TR transactivation assay, but only a single novel, direct agonist was found, the pharmaceutical betamipron. Indirect activation of TR through activation of its heterodimer partner, the retinoid-X-receptor (RXR), was also readily detected by confirmation in an RXR agonist assay. Identifying antagonists with high confidence was a challenge with the presence of significant confounding cytotoxicity and other, non-TR-specific mechanisms common to the transactivation assays. Only three pharmaceuticals-mefenamic acid, diclazuril, and risarestat-were confirmed as antagonists.

DISCUSSION

The results support limited structural diversity for direct ligand effects on TR and imply that other potential target sites in the thyroid hormone axis should be a greater priority for bioactivity screening for thyroid axis disruptors. https://doi.org/10.1289/EHP5314.

[Clinical observation of five pediatric-type follicular lymphoma in adult]

目的

探讨成人儿童型滤泡淋巴瘤（PTFL）患者的病理诊断、临床特征、治疗及转归特点。

方法

回顾性分析在江苏省人民医院就诊的5例成人PTFL患者的临床病理特点、实验室检查、诊治经过及随访结果，并结合文献进行综述。

结果

5例PTFL患者均为成年发病，中位年龄22（15~33）岁。起病时表现为局部无痛性淋巴结肿大，无发热、盗汗、消瘦等全身B症状。组织病理表现为典型的大滤泡结构，增殖指数高，存在免疫球蛋白重链基因克隆性重排，组化提示无BCL-2蛋白表达，荧光原位杂交未见BCL-2基因异常。所有患者均为Ⅰ~Ⅱ期，治疗仅通过局部肿块切除，未追加局部放疗或全身系统性免疫化疗。中位随访27个月，5例患者均处于持续缓解状态。

结论

成人PTFL病理增殖指数较高，无BCL-2表达和基因异常，临床多为局限病变，通过局部手术治疗预后较好，与经典成人滤泡淋巴瘤有显著差异。

Abstract 985: Development and validation of cell-based TFEB translocation assay in a high-content and high-throughput screening format

Transcription factor EB (TFEB) is a master regulator of lysosomal gene expression and mitochondrial biogenesis. Autophagy is known to act as a double edged sword in cancer. Autophagy acts as a tumor suppressor during the tumorigenesis process but it also helps to sustain the survival of already transformed cancer cells. Lysosomes sit at the end of the autophagy pathway, which is critical to meet the needs of autophagy. Therefore, small molecules that inhibit TFEB-mediated lysosomal biogenesis and autophagic degradation may be helpful for inhibiting cancer cell growth and limiting cancer progression. On the other hand, small molecules that enhance TFEB-mediated lysosomal degradation may be used to prevent tumorigenesis. In order to identify compounds that modulate TFEB translocation, an image-based TFEB translocation assay was developed in a 1536-well plate format with a GFP-TFEB stable AML12 cell line, which is an immortalized mouse hepatocyte cell line. Torin 1, a known TFEB translocation inducer, was used as positive control in the study. Torin 1 increased TFEB nuclear translocation in a concentration dependent manner with an EC50 of 150nM. To optimize the assay condition, various cell densities per well and time courses were tested. To validate this assay, a group of 384 known anticancer compounds were screened at 11 concentrations ranging from 0.8 nM to 46 μM. From this screening, we identified 25 compounds that enhanced TFEB nuclear translocation with EC50s ranging from 2 nM to 12 μM. Several known and novel TFEB inducers were among these compounds. These results demonstrate that this high-content and high-throughput assay can be used to screen large numbers of chemicals and provide a robust in vitro system to identify TFEB agonists and antagonists, which may be used to either prevent (agonists) or treat (antagonist) cancer.

Citation Format: Li Zhang, Ruili Huang, Wen Xing Ding, Menghang Xia. Development and validation of cell-based TFEB translocation assay in a high-content and high-throughput screening format [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 985.

Identifying Compounds with Genotoxicity Potential Using Tox21 High-Throughput Screening Assays

Genotoxicity is a critical component of a comprehensive toxicological profile. The Tox21 Program used five quantitative high-throughput screening (qHTS) assays measuring some aspect of DNA damage/repair to provide information on the genotoxic potential of over 10 000 compounds. Included were assays detecting activation of p53, increases in the DNA repair protein ATAD5, phosphorylation of H2AX, and enhanced cytotoxicity in DT40 cells deficient in DNA-repair proteins REV3 or KU70/RAD54. Each assay measures a distinct component of the DNA damage response signaling network; >70% of active compounds were detected in only one of the five assays. When qHTS results were compared with results from three standard genotoxicity assays (bacterial mutation, in vitro chromosomal aberration, and in vivo micronucleus), a maximum of 40% of known, direct-acting genotoxicants were active in one or more of the qHTS genotoxicity assays, indicating low sensitivity. This suggests that these qHTS assays cannot in their current form be used to replace traditional genotoxicity assays. However, despite the low sensitivity, ranking chemicals by potency of response in the qHTS assays revealed an enrichment for genotoxicants up to 12-fold compared with random selection, when allowing a 1% false positive rate. This finding indicates these qHTS assays can be used to prioritize chemicals for further investigation, allowing resources to focus on compounds most likely to induce genotoxic effects. To refine this prioritization process, models for predicting the genotoxicity potential of chemicals that were active in Tox21 genotoxicity assays were constructed using all Tox21 assay data, yielding a prediction accuracy up to 0.83. Data from qHTS assays related to stress-response pathway signaling (including genotoxicity) were the most informative for model construction. By using the results from qHTS genotoxicity assays, predictions from models based on qHTS data, and predictions from commercial bacterial mutagenicity QSAR models, we prioritized Tox21 chemicals for genotoxicity characterization.