Detection of γ-OHPdG in Circulating Tumor Cells of Patients With Hepatocellular Carcinoma as a Potential Prognostic Biomarker of Recurrence.

Background and Aims: Blood-based biomarkers for hepatocellular carcinoma (HCC) and its recurrence are lacking. We previously showed that hepatic γ-hydroxy-1,N 2 -propano-2'-deoxyguanosine (γ-OHPdG), an endogenous DNA adduct derived from acrolein by lipid peroxidation, increased during hepatocarcinogenesis. Additionally, higher hepatic γ-OHPdG from HCC patients after surgery were strongly associated with poor survival (P < .0001) and recurrence-free survival (P = .007) (Fu et al, Hepatology, 2018). These findings suggest that γ-OHPdG is a potential prognostic biomarker for HCC and its recurrence. To attain the goal of using γ-OHPdG as a biomarker in future preventive and therapeutic trials, we developed a blood-based method to detect γ-OHPdG in circulating liver tumor cells from HCC patient blood. Methods: We first established the specificity of anti-γ-OHPdG antibody by determining its dose-response in HepG2 cells treated with acrolein. Then, HepG2 cells in spiked blood of healthy volunteers and circulating tumor cells (CTCs) from 32 HCC patients were isolated using a RosetteSep CD45 Depletion Cocktail and Ficoll Paque. The HCC CTCs identified with anti-asialoglycoprotein receptor 1, a surface protein expressed solely in hepatocytes, were stained with an anti-γ-OHPdG antibody. The number of total HCC CTCs and γ-OHPdG-positive CTCs, as well as the staining intensity, were quantified using MetaMorph software. As an initial effort toward its clinical application, we also evaluated γ-OHPdG in CTCs from these patients along with certain clinical features. Results: The γ-OHPdG antibody specificity was demonstrated by an acrolein concentration-dependent increase of γ-OHPdG-positive HepG2 cells and the intensity of γ-OHPdG staining. The recovery of HepG2 cells from spiked blood was ∼50-60%, and the positivity rate of CTCs in blood from 32 patients with advanced HCC was 97%. The MetaMorph analysis showed a wide variation among patients in total number of CTCs, γ-OHPdG positivity, and staining intensity. Statistical analysis revealed that γ-OHPdG in CTCs of these patients appears to be associated with multifocality and poor differentiation. Conclusion: A blood-based method was developed and applied to HCC patients to evaluate the potential of γ-OHPdG in CTCs as a prognostic biomarker.

Implicating the cholecystokinin B receptor in liver stem cell oncogenesis.

Hepatocellular carcinoma (HCC) is the fastest-growing cause of cancer-related deaths worldwide. Chronic inflammation and fibrosis are the greatest risk factors for the development of HCC. Although the cell of origin for HCC is uncertain, many theories believe this cancer may arise from liver progenitor cells or stem cells. Here, we describe the activation of hepatic stem cells that overexpress the cholecystokinin-B receptor (CCK-BR) after liver injury with either a DDC diet (0.1% 3, 5-diethoxy-carbonyl 1,4-dihydrocollidine) or a NASH-inducing CDE diet (choline-deficient ethionine) in murine models. Pharmacologic blockade of the CCK-BR with a receptor antagonist proglumide or knockout of the CCK-BR in genetically engineered mice during the injury diet reduces the expression of hepatic stem cells and prevents the formation of three-dimensional tumorspheres in culture. RNA sequencing of livers from DDC-fed mice treated with proglumide or DDC-fed CCK-BR knockout mice showed downregulation of differentially expressed genes involved in cell proliferation and oncogenesis and upregulation of tumor suppressor genes compared with controls. Inhibition of the CCK-BR decreases hepatic transaminases, fibrosis, cytokine expression, and alters the hepatic immune cell signature rendering the liver microenvironment less oncogenic. Furthermore, proglumide hastened recovery after liver injury by reversing fibrosis and improving markers of synthetic function. Proglumide is an older drug that is orally bioavailable and being repurposed for liver conditions. These findings support a promising therapeutic intervention applicable to patients to prevent the development of HCC and decrease hepatic fibrosis.NEW & NOTEWORTHY This investigation identified a novel pathway involving the activation of hepatic stem cells and liver oncogenesis. Receptor blockade or genetic disruption of the cholecystokinin-B receptor (CCK-BR) signaling pathway decreased the activation and proliferation of hepatic stem cells after liver injury without eliminating the regenerative capacity of healthy hepatocytes.

Correction: Non-peptide compounds from Kronopolites svenhedini (Verhoeff) and their antitumor and iNOS inhibitory activities.

[This corrects the article DOI: 10.3762/bjoc.19.59.].

Five new sesquiterpenoids from agarwood of Aquilaria sinensis.

Five new eudesmane-type sesquiterpenoids (aquisinenoids F-J (1-5)) and five known compounds (6-10) were isolated from the agarwood of Aquilaria sinensis. Their structures, including absolute configurations, were identified by comprehensive spectroscopic analyses and computational methods. Inspired by our previous study on the same kinds of skeletons, we speculated that the new compounds have anticancer and anti-inflammatory activities. The results did not show any activity, but they revealed the structure-activity relationships (SAR).

Loss of ANCO1 Expression Regulates Chromatin Accessibility and Drives Progression of Early-Stage Triple-Negative Breast Cancer.

Mutations in the gene ankyrin repeat domain containing 11 (ANKRD11/ANCO1) play a role in neurodegenerative disorders, and its loss of heterozygosity and low expression are seen in some cancers. Here, we show that low ANCO1 mRNA and protein expression levels are prognostic markers for poor clinical outcomes in breast cancer and that loss of nuclear ANCO1 protein expression predicts lower overall survival of patients with triple-negative breast cancer (TNBC). Knockdown of ANCO1 in early-stage TNBC cells led to aneuploidy, cellular senescence, and enhanced invasion in a 3D matrix. The presence of a subpopulation of ANCO1-depleted cells enabled invasion of the overall cell population in vitro and they converted more rapidly to invasive lesions in a xenograft mouse model. In ANCO1-depleted cells, ChIP-seq analysis showed a global increase in H3K27Ac signals that were enriched for AP-1, TEAD, STAT3, and NFκB motifs. ANCO1-regulated H3K27Ac peaks had a significantly higher overlap with known breast cancer enhancers compared to ANCO1-independent ones. H3K27Ac engagement was associated with transcriptional activation of genes in the PI3K-AKT, epithelial-mesenchymal transition (EMT), and senescence pathways. In conclusion, ANCO1 has hallmarks of a tumor suppressor whose loss of expression activates breast-cancer-specific enhancers and oncogenic pathways that can accelerate the early-stage progression of breast cancer.

Non-peptide compounds from Kronopolites svenhedini (Verhoeff) and their antitumor and iNOS inhibitory activities.

Six new compounds, including a tetralone 1, two xanthones 2 and 3, a flavan derivative 4, and two nor-diterpenoids 7 and 8, accompanied by two known flavan derivatives 5 and 6 and a known olefine acid (9) were isolated from whole bodies of Kronopolites svenhedini (Verhoeff). The structures of the new compounds were determined by 1D and 2D nuclear magnetic resonance (NMR) and other spectroscopic methods, as well as computational methods. Selected compounds were evaluated for their biological properties against a mouse pancreatic cancer cell line and inhibitory effects on iNOS and COX-2 in RAW264.7 cells.

A Comprehensive Investigation of Hydrazide and Its Derived Structures in the Agricultural Fungicidal Field.

Hydrazides are present in many bioactive molecules and exhibit a variety of biological activities, such as insecticidal, herbicidal, antifungal, antitumor, and antiviral effects. In this Review, we review the application of hydrazide and its derived structures in the agricultural fungicidal field, including monohydrazides, diacylhydrazines, hydrazide-hydrazones, and sulfonyl hydrazides. In addition, the antifungal mechanism of action of the hydrazide derivatives was analyzed and summarized, mainly involving succinate dehydrogenase inhibitors, laccase inhibitors, and targeting plasma membranes. Finally, based on the structural analysis of the novel fungicidal lead compounds, the structure-activity relationship of the hydrazide derivatives was constructed and the development trend of hydrazide structures in fungicidal applications was prospected. It is hoped that this Review can provide some significant guidance for the development of new hydrazide fungicides in the future.

A CPG-Based Versatile Control Framework for Metameric Earthworm-Like Robotic Locomotion.

Annelids such as earthworms are considered to have central pattern generators (CPGs) that generate rhythms in neural circuits to coordinate the deformation of body segments for effective locomotion. At present, the states of earthworm-like robot segments are often assigned holistically and artificially by mimicking the earthworms' retrograde peristalsis wave, which is unable to adapt their gaits for variable environments and tasks. This motivates the authors to extend the bioinspired research from morphology to neurobiology by mimicking the CPG to build a versatile framework for spontaneous motion control. Here, the spatiotemporal dynamics is exploited from the coupled Hopf oscillators to not only unify the two existing gait generators for restoring temporal-symmetric phase-coordinated gaits and discrete gaits but also generate novel temporal-asymmetric phase-coordinated gaits. Theoretical and experimental tests consistently confirm that the introduction of temporal asymmetry improves the robot's locomotion performance. The CPG-based controller also enables seamless online switching of locomotion gaits to avoid abrupt changes, sharp stops, and starts, thus improving the robot's adaptability in variable working scenarios.

Design and modeling for drug combination experiments with order effects.

Combinations of drugs are now ubiquitous in treating complex diseases such as cancer and HIV due to their potential for enhanced efficacy and reduced side effects. The traditional combination experiments of drugs focus primarily on the dose effects of the constituent drugs. However, with the doses of drugs remaining unchanged, different sequences of drug administration may also affect the efficacy endpoint. Such drug effects shall be called as order effects. The common order-effect linear models are usually inadequate for analyzing combination experiments due to the nonlinear relationships and complex interactions among drugs. In this article, we propose a random field model for order-effect modeling. This model is flexible, allowing nonlinearities, and interaction effects to be incorporated with a small number of model parameters. Moreover, we propose a subtle experimental design that will collect good quality data for modeling the order effects of drugs with a reasonable run size. A real-data analysis and simulation studies are given to demonstrate that the proposed design and model are effective in predicting the optimal drug sequences in administration.

Granulocyte Colony-Stimulating Factor Accelerates the Recovery of Hepatitis B Virus-Related Acute-on-Chronic Liver Failure by Promoting M2-Like Transition of Monocytes.

Background and Aim: Acute-on-chronic liver failure (ACLF) has a high mortality rate. The role of granulocyte colony-stimulating factor (G-CSF) in ACLF remains controversial. Monocytes/macrophages are core immune cells, which are involved in the initiation and progression of liver failure; however, the effect of G-CSF on monocytes/macrophages is unclear. The study aimed to verify the clinical efficacy of G-CSF and explore the effect of it on monocytes in hepatitis B virus (HBV)-related ACLF (HBV-ACLF) paitents. Methods: We performed a large randomized controlled clinical trial for the treatment of HBV-ACLF using G-CSF. A total of 111 patients with HBV-ACLF were prospectively randomized into the G-CSF group (5 µg/kg G-CSF every day for 6 days, then every other day until day 18) or the control group (standard therapy). All participants were followed up for at least 180 days. The relationship between monocyte count and mortality risk was analyzed. The effect of G-CSF on the phenotype and function of monocytes from patients with HBV-ACLF was evaluated using flow cytometry in vivo and in vitro experiments. Results: The survival probability of the G-CSF group at 180 days was higher than that of the control group (72.2% vs. 53.8%, P = 0.0142). In the G-CSF-treated group, the monocyte counts on days 0 and 7 were independently associated with an evaluated mortality risk in the fully adjusted model (Model 3) [at day 0: hazard ratio (HR) 95% confidence interval (CI): 15.48 (3.60, 66.66), P = 0.0002; at day 7: HR (95% CI): 1.10 (0.50, 2.43), P=0.8080]. Further analysis showed that after treatment with G-CSF in HBV-ACLF patients, the expression of M1-like markers (HLA-DR and CD86) in monocytes decreased (HLA-DR: P = 0.0148; CD86: P = 0.0764). The expression of MerTK (M2-like marker) increased (P = 0.0002). The secretion of TNF-α, IL-6, and IL-10 from monocytes decreased without lipopolysaccharide (LPS) stimulation (TNF-α: P < 0.0001; IL-6: P= 0.0025; IL-10: P = 0.0004) or with LPS stimulation (TNF-α: P = 0.0439; P = 0.0611; IL-10: P = 0.0099). Similar effects were observed in vitro experiments. Conclusion: G-CSF therapy confers a survival benefit to patients with HBV-ACLF. G-CSF can promote the anti-inflammatory/pro-restorative phenotype (M2-like) transition of monocytes, which may contribute to the recovery of ACLF.Clinical Trial Registration Number: ClinicalTrials.gov, identifier (NCT02331745).

Does Chronic Use of High Dose Proton Pump Inhibitors Increase Risk for Pancreatic Cancer?

OBJECTIVES: To analyze whether use of proton pump inhibitors increase the risk for pancreatic cancer in a mouse model and human clinical cohorts. METHODS: p48-Cre/LSL-KrasG12D mice that develop precancerous pancreatic intraepithelial neoplasia (PanINs) were treated with low- or high-dose proton pump inhibitors (PPIs) orally for 1 and 4 months. The mechanism for the cholecystokinin receptor 2 (CCK-2R) activation was investigated in vitro. Two resources were employed to analyze the risk of pancreatic cancer in human subjects with PPI use. RESULTS: Serum gastrin levels were increased 8-fold (P < 0.0001) in mice treated with chronic high-dose PPIs, and this change correlated with an increase (P = 0.02) in PanIN grade and the development of microinvasive cancer. The CCK-2R expression was regulated by microRNA-148a in the p48-Cre/LSL-KrasG12D mice pancreas and in human pancreatic cancer cells in vitro. Proton pump inhibitor consumption in human subjects was correlated with pancreatic cancer risk (odds ratio, 1.54). A validation analysis conducted using the large-scale United Kingdom Biobank database confirmed the correlation (odds ratio, 1.9; P = 0.00761) of pancreatic cancer risk with PPI exposure. CONCLUSIONS: This investigation revealed in both murine models and human subjects, PPI use is correlated with a risk for development of pancreatic cancer.

Integrative analysis with a system of semiparametric projection non-linear regression models.

In integrative analysis parametric or nonparametric methods are often used. The former is easier for interpretation but not robust, while the latter is robust but not easy to interpret the relationships among the different types of variables. To combine the advantages of both methods and for flexibility, here a system of semiparametric projection non-linear regression models is proposed for the integrative analysis, to model the innate coordinate structure of these different types of data, and a diagnostic tool is constructed to classify new subjects to the case or control group. Simulation studies are conducted to evaluate the performance of the proposed method, and shows promising results. Then the method is applied to analyze a real omics data from The Cancer Genome Atlas study, compared the results with those from the similarity network fusion, another integrative analysis method, and results from our method are more reasonable.

External validation of a panel of plasma microRNA biomarkers for lung cancer.

Aim: We externally validate plasma miRNAs biomarkers for lung cancer in a large and retrospective sample set collected from a geographically distant population. Methods: Plasma samples are tested blindly to the clinical annotations by using PCR for quantitation of the four miRNAs in cohort 1 consisting of 232 lung cancer cases and 243 controls and cohort 2 comprising 239 cases and 246 controls. Results: Combined use of the four plasma miRNAs has 91% sensitivity and 95% specificity for diagnosis of lung cancer, and 85% sensitivity for early-stage lung cancer, while maintaining a specificity of 95%. Conclusion: The diagnostic values of the biomarkers are reproducibly confirmed in the independent and large sample sets, providing an assay for lung cancer detection.

Prevention of Lipid Peroxidation-derived Cyclic DNA Adduct and Mutation in High-Fat Diet-induced Hepatocarcinogenesis by Theaphenon E.

Obesity is associated with cancer risk and its link with liver cancer is particularly strong. Obesity causes non-alcoholic fatty liver disease (NAFLD) that could progress to hepatocellular carcinoma (HCC). Chronic inflammation likely plays a key role. We carried out a bioassay in the high-fat diet (HFD)-fed C57BL/6J mice to provide insight into the mechanisms of obesity-related HCC by studying γ-OHPdG, a mutagenic DNA adduct derived from lipid peroxidation. In an 80-week bioassay, mice received a low-fat diet (LFD), high-fat diet (HFD), and HFD with 2% Theaphenon E (TE) (HFD+TE). HFD mice developed a 42% incidence of HCC and LFD mice a 16%. Remarkably, TE, a standardized green tea extract formulation, completely blocked HCC in HFD mice with a 0% incidence. γ-OHPdG measured in the hepatic DNA of mice fed HFD and HFD+TE showed its levels increased during the early stages of NAFLD in HFD mice and the increases were significantly suppressed by TE, correlating with the tumor data. Whole-exome sequencing showed an increased mutation load in the liver tumors of HFD mice with G>A and G>T as the predominant mutations, consistent with the report that γ-OHPdG induces G>A and G>T. Furthermore, the mutation loads were significantly reduced in HFD+TE mice, particularly G>T, the most common mutation in human HCC. These results demonstrate in a relevant model of obesity-induced HCC that γ-OHPdG formation during fatty liver disease may be an initiating event for accumulated mutations that leads to HCC and this process can be effectively inhibited by TE. Cancer Prev Res; 11(10); 665-76. ©2018 AACR.

Integrating Circulating Immunological and Sputum Biomarkers for the Early Detection of Lung Cancer.

We have demonstrated that assessments of microRNA (miRNA) expressions in circulating peripheral blood mononucleated cell (PBMC) and sputum specimens, respectively, may help diagnose lung cancer. To assess the individual and combined analysis of the miRNAs across the different body fluids for lung cancer early detection, we analyse a panel of 3 sputum miRNAs (miRs-21, 31, and 210) and a panel of 2 PBMC miRNAs (miRs-19b-3p and 29b-3p) in a discovery cohort of 68 patients with lung cancer and 66 cancer-free smokers. We find that integrating 2 sputum miRNAs (miRs-31 and 210) and 1 PBMC miRNA (miR-19b-3p) has higher sensitivity (86.8%) and specificity (92.4%) compared with the individual panels. The synergistic value of the integrated panel of 3 biomarkers is confirmed in a validation cohort, independent of stage and histological type of lung cancer, and patients' age, sex, and ethnicity. Integrating circulating immunological and sputum biomarkers could improve the early detection of lung cancer.

Experimental design for multi-drug combination studies using signaling networks.

Combinations of multiple drugs are an important approach to maximize the chance for therapeutic success by inhibiting multiple pathways/targets. Analytic methods for studying drug combinations have received increasing attention because major advances in biomedical research have made available large number of potential agents for testing. The preclinical experiment on multi-drug combinations plays a key role in (especially cancer) drug development because of the complex nature of the disease, the need to reduce development time and costs. Despite recent progresses in statistical methods for assessing drug interaction, there is an acute lack of methods for designing experiments on multi-drug combinations. The number of combinations grows exponentially with the number of drugs and dose-levels and it quickly precludes laboratory testing. Utilizing experimental dose-response data of single drugs and a few combinations along with pathway/network information to obtain an estimate of the functional structure of the dose-response relationship in silico, we propose an optimal design that allows exploration of the dose-effect surface with the smallest possible sample size in this article. The simulation studies show our proposed methods perform well.

A prediction model for distinguishing lung squamous cell carcinoma from adenocarcinoma.

Accurate classification of squamous cell carcinoma (SCC) from adenocarcinoma (AC) of non-small cell lung cancer (NSCLC) can lead to personalized treatments of lung cancer. We aimed to develop a miRNA-based prediction model for differentiating SCC from AC in surgical resected tissues and bronchoalveolar lavage (BAL) samples. Expression levels of seven histological subtype-associated miRNAs were determined in 128 snap-frozen surgical lung tumor specimens by using reverse transcription-polymerase chain reaction (RT-PCR) to develop an optimal panel of miRNAs for acutely distinguishing SCC from AC. The biomarkers were validated in an independent cohort of 112 FFPE lung tumor tissues, and a cohort of 127 BAL specimens by using droplet digital PCR for differentiating SCC from AC. A prediction model with two miRNAs (miRs-205-5p and 944) was developed that had 0.988 area under the curve (AUC) with 96.55% sensitivity and 96.43% specificity for differentiating SCC from AC in frozen tissues, and 0.997 AUC with 96.43% sensitivity and 96.43% specificity in FFPE specimens. The diagnostic performance of the prediction model was reproducibly validated in BAL specimens for distinguishing SCC from AC with a higher accuracy compared with cytology (95.69 vs. 68.10%; P < 0.05). The prediction model might have a clinical value for accurately discriminating SCC from AC in both surgical lung tumor tissues and liquid cytological specimens.

A classifier integrating plasma biomarkers and radiological characteristics for distinguishing malignant from benign pulmonary nodules.

Lung cancer is primarily caused by cigarette smoking and the leading cancer killer in the USA and across the world. Early detection of lung cancer by low-dose CT (LDCT) can reduce the mortality. However, LDCT dramatically increases the number of indeterminate pulmonary nodules (PNs), leading to overdiagnosis. Having a definitive preoperative diagnosis of malignant PNs is clinically important. Using microarray and droplet digital PCR to directly profile plasma miRNA expressions of 135 patients with PNs, we identified 11 plasma miRNAs that displayed a significant difference between patients with malignant versus benign PNs. Using multivariate logistic regression analysis of the molecular results and clinical/radiological characteristics, we developed an integrated classifier comprising two miRNA biomarkers and one radiological characteristic for distinguishing malignant from benign PNs. The classifier had 89.9% sensitivity and 90.9% specificity, being significantly higher compared with the biomarkers or clinical/radiological characteristics alone (all p < 0.05). The classifier was validated in two independent sets of patients. We have for the first time shown that the integration of plasma biomarkers and radiological characteristics could more accurately identify lung cancer among indeterminate PNs. Future use of the classifier could spare individuals with benign growths from the harmful diagnostic procedures, while allowing effective treatments to be immediately initiated for lung cancer, thereby reduces the mortality and cost. Nevertheless, further prospective validation of this classifier is warranted.

The repurposed anthelmintic mebendazole in combination with trametinib suppresses refractory NRASQ61K melanoma.

Structure-based drug repositioning in addition to random chemical screening is now a viable route to rapid drug development. Proteochemometric computational methods coupled with kinase assays showed that mebendazole (MBZ) binds and inhibits kinases important in cancer, especially both BRAFWT and BRAFV600E. We find that MBZ synergizes with the MEK inhibitor trametinib to inhibit growth of BRAFWT-NRASQ61K melanoma cells in culture and in xenografts, and markedly decreased MEK and ERK phosphorylation. Reverse Phase Protein Array (RPPA) and immunoblot analyses show that both trametinib and MBZ inhibit the MAPK pathway, and cluster analysis revealed a protein cluster showing strong MBZ+trametinib - inhibited phosphorylation of MEK and ERK within 10 minutes, and its direct and indirect downstream targets related to stress response and translation, including ElK1 and RSKs within 30 minutes. Downstream ERK targets for cell cycle, including cMYC, were down-regulated, consistent with S- phase suppression by MBZ+trametinib, while apoptosis markers, including cleaved caspase-3, cleaved PARP and a sub-G1 population, were all increased with time. These data suggest that MBZ, a well-tolerated off-patent approved drug, should be considered as a therapeutic option in combination with trametinib, for patients with NRASQ61mut or other non-V600E BRAF mutant melanomas.

A plasma miRNA signature for lung cancer early detection.

The early detection of lung cancer continues to be a major clinical challenge. Using whole-transcriptome next-generation sequencing to analyze lung tumor and the matched noncancerous tissues, we previously identified 54 lung cancer-associated microRNAs (miRNAs). The objective of this study was to investigate whether the miRNAs could be used as plasma biomarkers for lung cancer. We determined expressions of the lung tumor-miRNAs in plasma of a development cohort of 180 subjects by using reverse transcription PCR to develop biomarkers. The development cohort included 92 lung cancer patients and 88 cancer-free smokers. We validated the biomarkers in a validation cohort of 64 individuals comprising 34 lung cancer patients and 30 cancer-free smokers. Of the 54 miRNAs, 30 displayed a significant different expression level in plasma of the lung cancer patients vs. cancer-free controls (all P < 0.05). A plasma miRNA signature (miRs-126, 145, 210, and 205-5p) with the best prediction was developed, producing 91.5% sensitivity and 96.2% specificity for lung cancer detection. Diagnostic performance of the plasma miRNA signature had no association with stage and histological type of lung tumor, and patients' age, sex, and ethnicity (all p > 0.05). The plasma miRNA signature was reproducibly confirmed in the validation cohort. The plasma miRNA signature may provide a blood-based assay for diagnosing lung cancer at the early stage, and thereby reduce the associated mortality and cost.