Dual-channel hypergraph convolutional network for predicting herb-disease associations.

Herbs applicability in disease treatment has been verified through experiences over thousands of years. The understanding of herb-disease associations (HDAs) is yet far from complete due to the complicated mechanism inherent in multi-target and multi-component (MTMC) botanical therapeutics. Most of the existing prediction models fail to incorporate the MTMC mechanism. To overcome this problem, we propose a novel dual-channel hypergraph convolutional network, namely HGHDA, for HDA prediction. Technically, HGHDA first adopts an autoencoder to project components and target protein onto a low-dimensional latent space so as to obtain their embeddings by preserving similarity characteristics in their original feature spaces. To model the high-order relations between herbs and their components, we design a channel in HGHDA to encode a hypergraph that describes the high-order patterns of herb-component relations via hypergraph convolution. The other channel in HGHDA is also established in the same way to model the high-order relations between diseases and target proteins. The embeddings of drugs and diseases are then aggregated through our dual-channel network to obtain the prediction results with a scoring function. To evaluate the performance of HGHDA, a series of extensive experiments have been conducted on two benchmark datasets, and the results demonstrate the superiority of HGHDA over the state-of-the-art algorithms proposed for HDA prediction. Besides, our case study on Chuan Xiong and Astragalus membranaceus is a strong indicator to verify the effectiveness of HGHDA, as seven and eight out of the top 10 diseases predicted by HGHDA for Chuan-Xiong and Astragalus-membranaceus, respectively, have been reported in literature.

MSI-XGNN: an explainable GNN computational framework integrating transcription- and methylation-level biomarkers for microsatellite instability detection.

Microsatellite instability (MSI) is a hypermutator phenotype caused by DNA mismatch repair deficiency. MSI has been reported in various human cancers, particularly colorectal, gastric and endometrial cancers. MSI is a promising biomarker for cancer prognosis and immune checkpoint blockade immunotherapy. Several computational methods have been developed for MSI detection using DNA- or RNA-based approaches based on next-generation sequencing. Epigenetic mechanisms, such as DNA methylation, regulate gene expression and play critical roles in the development and progression of cancer. We here developed MSI-XGNN, a new computational framework for predicting MSI status using bulk RNA-sequencing and DNA methylation data. MSI-XGNN is an explainable deep learning model that combines a graph neural network (GNN) model to extract features from the gene-methylation probe network with a CatBoost model to classify MSI status. MSI-XGNN, which requires tumor-only samples, exhibited comparable performance with two well-known methods that require tumor-normal paired sequencing data, MSIsensor and MANTIS and better performance than several other tools. MSI-XGNN also showed good generalizability on independent validation datasets. MSI-XGNN identified six MSI markers consisting of four methylation probes (EPM2AIP1|MLH1:cg14598950, EPM2AIP1|MLH1:cg27331401, LNP1:cg05428436 and TSC22D2:cg15048832) and two genes (RPL22L1 and MSH4) constituting the optimal feature subset. All six markers were significantly associated with beneficial tumor microenvironment characteristics for immunotherapy, such as tumor mutation burden, neoantigens and immune checkpoint molecules such as programmed cell death-1 and cytotoxic T-lymphocyte antigen-4. Overall, our study provides a powerful and explainable deep learning model for predicting MSI status and identifying MSI markers that can potentially be used for clinical MSI evaluation.

ADAR1 Promotes Invasion and Migration and Inhibits Ferroptosis via the FAK/AKT Pathway in Colorectal Cancer.

The role of adenosine deaminase acting on RNA1 (ADAR1) in colorectal cancer (CRC) is poorly understood. This study investigated the roles and underlying molecular mechanisms of ADAR1 and its isoforms, explored the correlations between ADAR1 expression and the immune microenvironment and anticancer drug sensitivity, and examined the potential synergy of using ADAR1 expression and clinical parameters to determine the prognosis of CRC patients. CRC samples showed significant upregulation of ADAR1, and high ADAR1 expression was correlated with poor prognosis. Silencing ADAR1 inhibited the proliferation, invasion, and migration of CRC cells and induced ferroptosis by suppressing FAK/AKT activation, and the results of rescue assays were consistent with these mechanisms. Both ADAR1-p110 and ADAR1-p150 were demonstrated to regulate the FAK/AKT pathway, with ADAR1-p110 playing a particularly substantial role. In evaluating the prognosis of CRC patients, combining ADAR1 expression with clinical parameters produced a substantial synergistic effect. The in vivo tumorigenesis of CRC was significantly inhibited by silencing ADAR1. Furthermore, ADAR1 expression was positively correlated with tumor mutational burden (TMB) and microsatellite status (p < 0.05), indicating that ADAR1 plays a complex role in CRC immunotherapy. In conclusion, ADAR1 plays oncogenic roles in CRC both in vitro and in vivo, potentially by inhibiting ferroptosis via downregulation of the FAK/AKT pathway. Thus, ADAR1 serves as a potential prognostic biomarker and a promising target for CRC therapy.

Discovery of a novel pyrido[1,2-a]thiazolo[5,4-d]pyrimidinone derivatives with excellent potency against acetylcholinesterase.

As mimetic compounds of the natural alkaloid mackinazolinone, forty pyrido[1,2-a]thiazolo[5,4-d] pyrimidinone were designed and synthesized from a bioisosterism approach. The structure of these compounds was confirmed through analysis using 1H NMR, 13C NMR, and HRMS techniques. All the compounds were evaluated for their anticholinesterase activities and cytotoxicity on normal cells (293 T) by the Ellman method and methyl thiazolyl tetrazolium (MTT) method in vitro. and the structure-activity relationships (SARs) were summarized. The results showed that most of the compounds effectively inhibited acetylcholinesterase (AChE) in the micromolar range with weak cytotoxicity. Compound 7o exhibited the best inhibitory activity against AChE, displaying an IC50 values of 1.67 ± 0.09 µM and an inhibitory constant Ki of 11.31 µM as a competitive inhibitor to AChE. Molecular docking indicated that compound 7o may bind to AChE via hydrogen bond and π-π stacking. Further molecular dynamics (MD) simulations indicated a relatively low binding free energy (- 27.91 kJ·mol-1) of compound 7o with AChE. In summary, the collective findings suggested that 7o was promising as a potential novel drug candidate worthy of further investigation for the treatment of Alzheimer's disease.

microbiomeMarker: an R/Bioconductor package for microbiome marker identification and visualization.

SUMMARY: Characterizing biomarkers based on microbiome profiles has great potential for translational medicine and precision medicine. Here, we present microbiomeMarker, an R/Bioconductor package implementing commonly used normalization and differential analysis (DA) methods, and three supervised learning models to identify microbiome markers. microbiomeMarker also allows comparison of different methods of DA and confounder analysis. It uses standardized input and output formats, which renders it highly scalable and extensible, and allows it to seamlessly interface with other microbiome packages and tools. In addition, the package provides a set of functions to visualize and interpret the identified microbiome markers. AVAILABILITY AND IMPLEMENTATION: microbiomeMarker is freely available from Bioconductor (https://www.bioconductor.org/packages/microbiomeMarker). Source code is available and maintained at GitHub (https://github.com/yiluheihei/microbiomeMarker). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

BAX as the mediator of C-MYC sensitizes acute lymphoblastic leukemia to TLR9 agonists.

BACKGROUND: The prognosis of B-cell acute lymphoblastic leukemia (B-ALL) has improved significantly with current first-line therapy, although the recurrence of B-ALL is still a problem. Toll-like receptor 9 (TLR9) agonists have shown good safety and efficiency as immune adjuvants. Apart from their immune regulatory effect, the direct effect of TLR9 agonists on cancer cells with TLR9 expression cannot be ignored. However, the direct effect of TLR9 agonists on B-ALL remains unknown. METHODS: We discussed the relationship between TLR9 expression and the clinical characteristics of B-ALL and explored whether CpG 685 exerts direct apoptotic effect on B-ALL without inhibiting normal B-cell function. By using western blot, co-immunoprecipitation, immunofluorescence co-localization, and chromatin immunoprecipitation, we explored the mechanism of the apoptosis-inducing effect of CpG 685 in treating B-ALL cells. By exploring the mechanism of CpG 685 on B-ALL, the predictive biomarkers of the efficacy of CpG 685 in treating B-ALL were explored. These efficiencies were also confirmed in mouse model as well as clinical samples. RESULTS: High expression of TLR9 in B-ALL patients showed good prognosis. C-MYC-induced BAX activation was the key to the effect of CpG oligodeoxynucleotides against B-ALL. C-MYC overexpression promoted P53 stabilization, enhanced Bcl-2 associated X-protein (BAX) activation, and mediated transcription of the BAX gene. Moreover, combination therapy using CpG 685 and imatinib, a BCR-ABL kinase inhibitor, could reverse resistance to CpG 685 or imatinib alone by promoting BAX activation and overcoming BCR-ABL1-independent PI3K/AKT activation. CONCLUSION: TLR9 is not only a prognostic biomarker but also a potential target for B-ALL therapy. CpG 685 monotherapy might be applicable to Ph- B-ALL patients with C-MYC overexpression and without BAX deletion. CpG 685 may also serve as an effective combinational therapy against Ph+ B-ALL.

Biomarker discovery and application-An opportunity to resolve the challenge of liver cancer diagnosis and treatment.

Liver cancer is one of the most common malignancies, with severe morbidity and mortality. While considerable progress has been made in liver cancer treatment, the 5-year overall survival (OS) of patients has not improved significantly. Reasons include the inadequate capability of early screening and diagnosis, a high incidence of recurrence and metastasis, a high degree of tumor heterogeneity, and an immunosuppressive tumor microenvironment. Therefore, the identification and validation of specific and robust liver cancer biomarkers are of major importance for early screening, timely diagnosis, accurate prognosis, and the prevention of tumor progression. In this review, we highlight some of the latest research progress and potential applications of liver cancer biomarkers, describing hotspots and prospective directions in biomarker discovery.

Protective Roles of Xijiao Dihuang Tang on Coronary Artery Injury in Kawasaki Disease.

PURPOSE: Xijiao Dihuang Tang (XJDHT) is a classical formula of traditional Chinese medicine constituted of Cornu Bubali, Rehmannia glutinosa (Gaertn.) DC., Paeonia lactiflora Pall., and Paeonia suffruticosa Andrews. It was first mentioned in the medical classic "Beiji Qianjin Yaofang" written by Simiao Sun in Tang Dynasty. It shows very strong antipyretic and anticoagulant effects and has been clinically applied to treat various type of blood loss, purple and black spots, heat stroke, and glossitis. Kawasaki disease (KD) is considered as a kind of acute febrile illness in children with systemic vasculitis as the main lesions. The aim of this research is to clarify whether XJDHT can play a protective role in KD. METHODS: A mouse model of Candida albicans water-soluble fraction (CAWS)-induced coronary arteritis and a KD cell model with tumor necrosis factor (TNF)-α induction were employed to investigate the potential effect and mechanism of XJDHT on coronary artery injury in KD. RESULTS: Data showed that XJDHT remarkably alleviated the coronary artery injury of KD mice, as evidenced by reduced inflammation and downregulated expression of pro-inflammatory cytokines interleukin (IL)-1ß and TNF-α. In vitro investigation showed that XJDHT could promote cell proliferation, inhibit cell apoptosis, and improve mitochondrial functions. Subsequent studies demonstrated that XJDHT rescued endothelial cell injury by PI3K/Akt-NFκB signaling pathway. Component analysis of XJDHT detected thirty-eight chemically active ingredients, including paeoniflorin, albiflorin, and paeoniflorigenone, which in in vitro experiments exhibited significant rescue effects on TNF-α-mediated endothelial cell injury. CONCLUSION: Our findings demonstrated that XJDHT mitigated coronary artery injury of KD through suppressing endothelial cell damage via PI3K/Akt-NFκB signaling.

Cellular immunotherapy combined with platinum-based chemotherapy prolongs survival for non-small cell lung cancer patients.

Platinum-based chemotherapy is the primary treatment option for advanced non-small cell lung cancer (NSCLC) patients without a driver gene mutation, but its efficacy is still modest. Through a potential synergistic effect, autologous cellular immunotherapy (CIT) composed of cytokine-induced killer (CIK), natural killer (NK), and T cells might enhance it. NK cells exhibited in vitro cytotoxicity toward lung cancer cells (A549 cells) following platinum therapy. Using flow cytometry, the expression of MICA, MICB, DR4, DR5, CD112, and CD155 on lung cancer cells was assessed. In this retrospective cohort study, there were included 102 previously untreated stage IIIB/IV NSCLC patients ineligible for tyrosine kinase inhibitor (TKI) target therapy who received either chemotherapy alone (n=75) or combination therapy (n=27). The cytotoxicity of NK cells for A549 cells was increased obviously and a time-dependent enhancement of this effect was also observed. After platinum therapy, the levels of MICA, MICB, DR4, DR5, CD112, and CD155 on the surface of A549 cells were increased. In the combination group, the median PFS was 8.3 months, compared to 5.5 months in the control group (p=0.042); the median overall survival was 18.00 months, compared to 13.67 months in the combined group (p=0.003). The combination group had no obvious immune-related adverse effects. The combination of NK cells with platinum showed synergistic anticancer effects. Combining the two strategies increased survival with minor adverse effects. Incorporating CIT into conventional chemotherapy regimens may improve NSCLC treatment. However, additional evidence will require multicenter randomized controlled trials.

Furo[2,3-d]pyrimidines as Mackinazolinone/Isaindigotone Analogs: Synthesis, Modification, Antitumor Activity, and Molecular Docking Study.

The chemical transformation of the tricyclic furo[2,3-d]pyrimidines was performed under isosteric and scaffold-hopping strategies focusing on the synthesis of its arylidene and imine-containing derivatives. Naturally-occurring alkaloids mackinazolinone and isaindigotone were as templates of target heterocycles. Synthesized compounds evaluated for their antitumor activity on human cancer cervical HeLa, breast MCF-7, and colon HT-29 cell lines. Four compounds: 8c, 8e, 10b, and 10c demonstrated potency against HeLa and HT-29 cell lines, and IC50 values were between 7.37-13.72 µM, respectively. The molecular docking results showed that compounds 8c and 10b had good binding and high matching with the target EGFR protein.