HSP90ß prevents aging-related cataract formation through regulation of the charged multivesicular body protein (CHMP4B) and p53.

Cataract is a leading ocular disease causing global blindness. The mechanism of cataractogenesis has not been well defined. Here, we demonstrate that the heat shock protein 90ß (HSP90ß) plays a fundamental role in suppressing cataractogenesis. HSP90ß is the most dominant HSP in normal lens, and its constitutive high level of expression is largely derived from regulation by Sp1 family transcription factors. More importantly, HSP90ß is significantly down-regulated in human cataract patients and in aging mouse lenses, whereas HSP90ß silencing in zebrafish causes cataractogenesis, which can only be rescued by itself but not other HSP90 genes. Mechanistically, HSP90ß can directly interact with CHMP4B, a newly-found client protein involved in control of cytokinesis. HSP90ß silencing causes upregulation of CHMP4B and another client protein, the tumor suppressor p53. CHMP4B upregulation or overexpression induces excessive division of lens epithelial cells without proper differentiation. As a result, these cells were triggered to undergo apoptosis due to activation of the p53/Bak-Bim pathway, leading to cataractogenesis and microphthalmia. Silence of both HSP90ß and CHMP4B restored normal phenotype of zebrafish eye. Together, our results reveal that HSP90ß is a critical inhibitor of cataractogenesis through negative regulation of CHMP4B and the p53-Bak/Bim pathway.

Opening the Black Box: Spatial Transcriptomics and the Relevance of Artificial Intelligence-Detected Prognostic Regions in High-Grade Serous Carcinoma.

Image-based deep learning models are used to extract new information from standard hematoxylin and eosin pathology slides; however, biological interpretation of the features detected by artificial intelligence (AI) remains a challenge. High-grade serous carcinoma of the ovary (HGSC) is characterized by aggressive behavior and chemotherapy resistance, but also exhibits striking variability in outcome. Our understanding of this disease is limited, partly due to considerable tumor heterogeneity. We previously trained an AI model to identify HGSC tumor regions that are highly associated with outcome status but are indistinguishable by conventional morphologic methods. Here, we applied spatially resolved transcriptomics to further profile the AI-identified tumor regions in 16 patients (8 per outcome group) and identify molecular features related to disease outcome in patients who underwent primary debulking surgery and platinum-based chemotherapy. We examined formalin-fixed paraffin-embedded tissue from (1) regions identified by the AI model as highly associated with short or extended chemotherapy response, and (2) background tumor regions (not identified by the AI model as highly associated with outcome status) from the same tumors. We show that the transcriptomic profiles of AI-identified regions are more distinct than background regions from the same tumors, are superior in predicting outcome, and differ in several pathways including those associated with chemoresistance in HGSC. Further, we find that poor outcome and good outcome regions are enriched by different tumor subpopulations, suggesting distinctive interaction patterns. In summary, our work presents proof of concept that AI-guided spatial transcriptomic analysis improves recognition of biologic features relevant to patient outcomes.

Endothelial TIE1 Restricts Angiogenic Sprouting to Coordinate Vein Assembly in Synergy With Its Homologue TIE2.

BACKGROUND: Vascular growth followed by vessel specification is crucial for the establishment of a hierarchical blood vascular network. We have shown that TIE2 is required for vein development while little is known about its homologue TIE1 (tyrosine kinase with immunoglobulin-like and EGF [epithelial growth factor]-like domains 1) in this process. METHODS: We analyzed functions of TIE1 as well as its synergy with TIE2 in the regulation of vein formation by employing genetic mouse models targeting Tie1, Tek, and Nr2f2, together with in vitro cultured endothelial cells to decipher the underlying mechanism. RESULTS: Cardinal vein growth appeared normal in TIE1-deficient mice, whereas TIE2 deficiency altered the identity of cardinal vein endothelial cells with the aberrant expression of DLL4 (delta-like canonical Notch ligand 4). Interestingly, the growth of cutaneous veins, which was initiated at approximately embryonic day 13.5, was retarded in mice lack of TIE1. TIE1 deficiency disrupted the venous integrity, displaying increased sprouting angiogenesis and vascular bleeding. Abnormal venous sprouts with defective arteriovenous alignment were also observed in the mesenteries of Tie1-deleted mice. Mechanistically, TIE1 deficiency resulted in the decreased expression of venous regulators including TIE2 and COUP-TFII (chicken ovalbumin upstream promoter transcription factor, encoded by Nr2f2, nuclear receptor subfamily 2 group F member 2) while angiogenic regulators were upregulated. The alteration of TIE2 level by TIE1 insufficiency was further confirmed by the siRNA-mediated knockdown of Tie1 in cultured endothelial cells. Interestingly, TIE2 insufficiency also reduced the expression of TIE1. Combining the endothelial deletion of Tie1 with 1 null allele of Tek resulted in a progressive increase of vein-associated angiogenesis leading to the formation of vascular tufts in retinas, whereas the loss of Tie1 alone produced a relatively mild venous defect. Furthermore, the induced deletion of endothelial Nr2f2 decreased both TIE1 and TIE2. CONCLUSIONS: Findings from this study imply that TIE1 and TIE2, together with COUP-TFII, act in a synergistic manner to restrict sprouting angiogenesis during the development of venous system.

Network-guided identification of cancer-selective combinatorial therapies in ovarian cancer.

Each patient's cancer consists of multiple cell subpopulations that are inherently heterogeneous and may develop differing phenotypes such as drug sensitivity or resistance. A personalized treatment regimen should therefore target multiple oncoproteins in the cancer cell populations that are driving the treatment resistance or disease progression in a given patient to provide maximal therapeutic effect, while avoiding severe co-inhibition of non-malignant cells that would lead to toxic side effects. To address the intra- and inter-tumoral heterogeneity when designing combinatorial treatment regimens for cancer patients, we have implemented a machine learning-based platform to guide identification of safe and effective combinatorial treatments that selectively inhibit cancer-related dysfunctions or resistance mechanisms in individual patients. In this case study, we show how the platform enables prediction of cancer-selective drug combinations for patients with high-grade serous ovarian cancer using single-cell imaging cytometry drug response assay, combined with genome-wide transcriptomic and genetic profiles. The platform makes use of drug-target interaction networks to prioritize those combinations that warrant further preclinical testing in scarce patient-derived primary cells. During the case study in ovarian cancer patients, we investigated (i) the relative performance of various ensemble learning algorithms for drug response prediction, (ii) the use of matched single-cell RNA-sequencing data to deconvolute cell population-specific transcriptome profiles from bulk RNA-seq data, (iii) and whether multi-patient or patient-specific predictive models lead to better predictive accuracy. The general platform and the comparison results are expected to become useful for future studies that use similar predictive approaches also in other cancer types.

DrugComb update: a more comprehensive drug sensitivity data repository and analysis portal.

Combinatorial therapies that target multiple pathways have shown great promises for treating complex diseases. DrugComb (https://drugcomb.org/) is a web-based portal for the deposition and analysis of drug combination screening datasets. Since its first release, DrugComb has received continuous updates on the coverage of data resources, as well as on the functionality of the web server to improve the analysis, visualization and interpretation of drug combination screens. Here, we report significant updates of DrugComb, including: (i) manual curation and harmonization of more comprehensive drug combination and monotherapy screening data, not only for cancers but also for other diseases such as malaria and COVID-19; (ii) enhanced algorithms for assessing the sensitivity and synergy of drug combinations; (iii) network modelling tools to visualize the mechanisms of action of drugs or drug combinations for a given cancer sample and (iv) state-of-the-art machine learning models to predict drug combination sensitivity and synergy. These improvements have been provided with more user-friendly graphical interface and faster database infrastructure, which make DrugComb the most comprehensive web-based resources for the study of drug sensitivities for multiple diseases.

Vascular adhesion protein-1 defines a unique subpopulation of human hematopoietic stem cells and regulates their proliferation.

Although the development of hematopoietic stem cells (HSC) has been studied in great detail, their heterogeneity and relationships to different cell lineages remain incompletely understood. Moreover, the role of Vascular Adhesion Protein-1 in bone marrow hematopoiesis has remained unknown. Here we show that VAP-1, an adhesin and a primary amine oxidase producing hydrogen peroxide, is expressed on a subset of human HSC and bone marrow vasculature forming a hematogenic niche. Bulk and single-cell RNAseq analyses reveal that VAP-1+ HSC represent a transcriptionally unique small subset of differentiated and proliferating HSC, while VAP-1- HSC are the most primitive HSC. VAP-1 generated hydrogen peroxide acts via the p53 signaling pathway to regulate HSC proliferation. HSC expansion and differentiation into colony-forming units are enhanced by inhibition of VAP-1. Contribution of VAP-1 to HSC proliferation was confirmed with mice deficient of VAP-1, mice expressing mutated VAP-1 and using an enzyme inhibitor. In conclusion, VAP-1 expression allows the characterization and prospective isolation of a new subset of human HSC. Since VAP-1 serves as a check point-like inhibitor in HSC differentiation, the use of VAP-1 inhibitors enables the expansion of HSC.

DrugComb: an integrative cancer drug combination data portal.

Drug combination therapy has the potential to enhance efficacy, reduce dose-dependent toxicity and prevent the emergence of drug resistance. However, discovery of synergistic and effective drug combinations has been a laborious and often serendipitous process. In recent years, identification of combination therapies has been accelerated due to the advances in high-throughput drug screening, but informatics approaches for systems-level data management and analysis are needed. To contribute toward this goal, we created an open-access data portal called DrugComb (https://drugcomb.fimm.fi) where the results of drug combination screening studies are accumulated, standardized and harmonized. Through the data portal, we provided a web server to analyze and visualize users' own drug combination screening data. The users can also effectively participate a crowdsourcing data curation effect by depositing their data at DrugComb. To initiate the data repository, we collected 437 932 drug combinations tested on a variety of cancer cell lines. We showed that linear regression approaches, when considering chemical fingerprints as predictors, have the potential to achieve high accuracy of predicting the sensitivity of drug combinations. All the data and informatics tools are freely available in DrugComb to enable a more efficient utilization of data resources for future drug combination discovery.

Tissue-specific pathway association analysis using genome-wide association study summaries.

MOTIVATION: Pathway association analysis has made great achievements in elucidating the genetic basis of human complex diseases. However, current pathway association analysis approaches fail to consider tissue-specificity. RESULTS: We developed a tissue-specific pathway interaction enrichment analysis algorithm (TPIEA). TPIEA was applied to two large Caucasian and Chinese genome-wide association study summary datasets of bone mineral density (BMD). TPIEA identified several significant pathways for BMD [false discovery rate (FDR) < 0.05], such as KEGG FOCAL ADHESION and KEGG AXON GUIDANCE, which had been demonstrated to be involved in the development of osteoporosis. We also compared the performance of TPIEA and classical pathway enrichment analysis, and TPIEA presented improved performance in recognizing disease relevant pathways. TPIEA may help to fill the gap of classic pathway association analysis approaches by considering tissue specificity. AVAILABILITY AND IMPLEMENTATION: The online web tool of TPIEA is available at https://sourceforge.net/projects/tpieav1/files CONTACT: fzhxjtu@mail.xjtu.edu.cnSupplementary information: Supplementary data are available at Bioinformatics online.

PTENP1 inhibits the growth of esophageal squamous cell carcinoma by regulating SOCS6 expression and correlates with disease prognosis.

PTEN pseudogene (PTENP1) has a tumor suppressive role in multiple cancers. However, its involvement in esophageal squamous cell carcinoma (ESCC) remains largely unknown. In this study, we set out to identify the role of PTENP1 in the development of ESCC. Gene Expression Omnibus database was employed to investigate the expression of PTENP1 in ESCC. sRNA target Database (StarBase v2.0) was used to query the downstream of PTENP1. Next, both in vitro and in vivo experiments were employed to explore the function. Cell proliferation was evaluated by CCK-8, soft agar, and colony formation assays. Expression of relative genes was assessed by quantitative real-time PCR (qRT-PCR) and Western blotting. 3'UTR luciferase assay was used to confirm the miRNA binding. The clinical significance of PTENP1 was further validated by immunohistochemistry (IHC) and correlation with clinicopathological indicators in additional samples (n = 93). We found expression of PTENP1 in ESCC was lower than that in the corresponding adjacent normal tissues (n = 17). Overexpression of PTENP1 in Eca109 and TE-1 cells resulted in inhibited proliferation and altered expression of SOCS6-p-STAT3-HIF-1α pathway both in vitro and in vivo. Subsequent IHC reported a similar trend in human ESCC samples. 3'UTR luciferase assay demonstrated that PTENP1 3'UTR decoyed miR-17-5p from binding to SOCS6. Moreover, PTENP1 expression was correlated with clinicopathological indicators to varying degrees, including histological grade, TNM stage, infiltration depth, lymph node metastasis, and overall survival. Taken together, these results suggested an anti-oncogenic role of PTENP1. Meanwhile, PTENP1 may also serve as a candidate of prognostic indicator for ESCC patients.

Toxoplasma gondii infection positively associated with schizophrenia: Evidences from UK Biobank cohort and case-controlled studies.

Toxoplasma gondii (T. gondii) is an opportunistic pathogen affecting about 1/3 of world population. While often asymptomatic in immunocompetent individuals, it can lead to severe toxoplasmosis in immunocompromised patients. Recent research has unveiled a potential link between T. gondii infection and neuropsychiatric diseases. We implemented both a cohort study and a case control study to further identify this association. In the cohort study, we analyzed data from the UK Biobank database, which included 8814 individuals tested for T. gondii SAG1 antibodies and free of neuropsychiatric disorders at baseline. Among them, 22.52% (n = 1985) tested positive for SAG1 antibody. Over an average follow-up period of 12.26 years, Cox proportional hazards models and logistic regression analysis revealed a significant association between the SAG1 seropositivity at baseline and the incidence of schizophrenia (HR: 5.89; 95% CI: 1.69-20.53). In our case-control study, 239 patients diagnosed with schizophrenia and 455 healthy individuals were involved. Using the modified agglutination test (MAT) to detect T. gondii antibodies, logistic regression analysis showed a higher prevalence of T. gondii infection among schizophrenia patients (10.04%) compared to healthy controls (3.74%). T. gondii infection emerged as a significant risk factor for schizophrenia (OR: 3.33; 95% CI: 1.68-6.61). However, our investigations did not reveal a robust association between T. gondii infection and other neuropsychiatric conditions, including Alzheimer's disease, dementia, anxiety, depression, neurodegenerative disorders, and peripheral neurological disorders such as neurological and plexus disorders.

Efficacy and safety of traditional Chinese medicine decoction as an adjuvant treatment for diabetic nephropathy: a systematic review and meta-analysis of randomized controlled trials.

Objective: This study aimed to assess the efficacy and safety of traditional Chinese medicine decoction as an adjunctive treatment for diabetic nephropathy in systematic evaluations. Methods: A comprehensive search was conducted in PubMed, Web of Science, Cochrane Library, Embase, China National Knowledge Infrastructure (CNKI), and Wanfang databases, covering the period from January 2013 to July 2023. The search was restricted to randomized controlled trials (RCTs) conducted within the past decade that investigated the use of TCM decoction as an adjunctive treatment for diabetic nephropathy. The control group received western medicine treatment, while the intervention group received TCM decoction in addition to the conventional treatment. Endnote and Excel were employed for literature management and data organization, and Revman 5.3 and Stata 16 software were used for the analyses. Results: 66 RCTs involving 6,951 participants were included in this study. The clinical efficacy of TCM decoction as an adjunctive treatment for diabetic nephropathy was found to be significantly higher than that of the control group (OR = 3.12, 95% CI [2.70, 3.60], I2 = 0%, p < 0.00001). The incidence of adverse events did not differ significantly between the intervention group and the control group (OR = 0.94, 95% CI [0.60, 1.48], I2 = 0%, p = 0.94). According to the secondary outcomes of renal function and blood glucose indicators, the intervention group showed better therapeutic efficacy compared to the control group. The most frequently used TCM categories were tonifying medicine, blood-activating medicine, astringent medicine, diuretic medicine, heat-clearing medicine, and laxative medicine. Among them, the top five frequently used Chinese medicine were Astragalus mongholicus Bunge [Fabaceae; Astragali mongholici radix](58 times), Salvia miltiorrhiza Bunge [Lamiaceae; Radix et rhizoma salviae miltiorrhizae] (42 times), Dioscorea oppositifolia L. [Dioscoreaceae; Dioscoreae rhizoma] (38 times), Poria cocos (Schw.) Wolf [Polyporaceae; Poria] (38 times), and Cornus officinalis Siebold & Zucc. [Cornaceae; Corni fructus] (35 times). Conclusion: The combined use of TCM decoction with western medicine in the treatment of diabetic nephropathy can enhance clinical effectiveness and 2 This is a provisional file, not the final typeset article achieve superior therapeutic effects in comparison to western medicine alone, without significant risks. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/#recordDetails, identifier [CRD42022529144].

Population-based cohort study of Toxoplasma gondii P22 antibody positivity correlation with anxiety.

BACKGROUND: Accumulating evidence suggests that latent infection with Toxoplasma gondii (T. gondii) is associated with a variety of neuropsychiatric and behavioral conditions. This research aims to explore the potential correlation between T. gondii antibody positivity and neuropsychiatric disorders through a comprehensive prospective cohort study. METHODS: The cohort study utilized the UK Biobank database to recruit 8814 individuals with no prior diagnosis of neuropsychiatric disorders. Cox proportional hazards models were employed to investigate the associations between T. gondii P22 antibody seropositivity (P22+) and the development of various types of neuropsychiatric disorders. RESULTS: Of the population, 14.65 % tested positive for T. gondii P22 antibody. The presence of T. gondii P22 antibody showed a slight inverse association with epilepsy (HR: 0.28; 95 % CI: 0.10-0.77), while it was positively associated with an increased risk of developing anxiety disorders (HR: 1.38; 95 % CI: 1.04-1.83). LIMITATIONS: The study sample consisted mostly of white British individuals aged 40 to 69 years old. Although we adjusted for potential confounders, there may be other unmeasured and residual confounding factors that could have influenced our reported associations. CONCLUSIONS: The findings suggested an increased risk of anxiety and potential evidence of epilepsy associated with T. gondii P22+. However, our analysis did not reveal an increased risk of several other neuropsychiatric conditions including Alzheimer's disease, dementia, substance abuse disorders, depression, and neurodegenerative disorders, associated with P22 antibody seropositivity.

Intestinal microbiota imbalance resulted by anti-Toxoplasma gondii immune responses aggravate gut and brain injury.

BACKGROUND: Toxoplasma gondii infection affects a significant portion of the global population, leading to severe toxoplasmosis and, in immunocompromised patients, even death. During T. gondii infection, disruption of gut microbiota further exacerbates the damage to intestinal and brain barriers. Therefore, identifying imbalanced probiotics during infection and restoring their equilibrium can regulate the balance of gut microbiota metabolites, thereby alleviating tissue damage. METHODS: Vimentin gene knockout (vim-/-) mice were employed as an immunocompromised model to evaluate the influence of host immune responses on gut microbiota balance during T. gondii infection. Behavioral experiments were performed to assess changes in cognitive levels and depressive tendencies between chronically infected vim-/- and wild-type (WT) mice. Fecal samples were subjected to 16S ribosomal RNA (rRNA) sequencing, and serum metabolites were analyzed to identify potential gut probiotics and their metabolites for the treatment of T. gondii infection. RESULTS: Compared to the immunocompetent WT sv129 mice, the immunocompromised mice exhibited lower levels of neuronal apoptosis and fewer neurobehavioral abnormalities during chronic infection. 16S rRNA sequencing revealed a significant decrease in the abundance of probiotics, including several species of Lactobacillus, in WT mice. Restoring this balance through the administration of Lactobacillus murinus and Lactobacillus gasseri significantly suppressed the T. gondii burden in the intestine, liver, and brain. Moreover, transplantation of these two Lactobacillus spp. significantly improved intestinal barrier damage and alleviated inflammation and neuronal apoptosis in the central nervous system. Metabolite detection studies revealed that the levels of various Lactobacillus-related metabolites, including indole-3-lactic acid (ILA) in serum, decreased significantly after T. gondii infection. We confirmed that L. gasseri secreted much more ILA than L. murinus. Notably, ILA can activate the aromatic hydrocarbon receptor signaling pathway in intestinal epithelial cells, promoting the activation of CD8+ T cells and the secretion of interferon-gamma. CONCLUSION: Our study revealed that host immune responses against T. gondii infection severely disrupted the balance of gut microbiota, resulting in intestinal and brain damage. Lactobacillus spp. play a crucial role in immune regulation, and the metabolite ILA is a promising therapeutic compound for efficient and safe treatment of T. gondii infection.

Platycodin D inhibits angiogenic vascular mimicry in NSCLC by regulating the eIF4E-mediated RNA methylome.

Image 1.

Tracing back primed resistance in cancer via sister cells.

Exploring non-genetic evolution of cell states during cancer treatments has become attainable by recent advances in lineage-tracing methods. However, transcriptional changes that drive cells into resistant fates may be subtle, necessitating high resolution analysis. Here, we present ReSisTrace that uses shared transcriptomic features of sister cells to predict the states priming treatment resistance. Applying ReSisTrace in ovarian cancer cells perturbed with olaparib, carboplatin or natural killer (NK) cells reveals pre-resistant phenotypes defined by proteostatic and mRNA surveillance features, reflecting traits enriched in the upcoming subclonal selection. Furthermore, we show that DNA repair deficiency renders cells susceptible to both DNA damaging agents and NK killing in a context-dependent manner. Finally, we leverage the obtained pre-resistance profiles to predict and validate small molecules driving cells to sensitive states prior to treatment. In summary, ReSisTrace resolves pre-existing transcriptional features of treatment vulnerability, facilitating both molecular patient stratification and discovery of synergistic pre-sensitizing therapies.

SUMO1-regulated DBC1 promotes p53-dependent stress-induced apoptosis of lens epithelial cells.

Deleted in breast cancer 1 (DBC1) was initially identified from a homozygously deleted region in human chromosome 8p21. It has been well established that DBC1 plays a dual role during cancer development. Depending on the physiological context, it can promote or inhibit tumorigenesis. Whether it plays a role in lens pathogenesis remains elusive. In the present study, we demonstrated that DBC1 is highly expressed in lens epithelial cells from different vertebrates and in retina pigment epithelial cells as well. Moreover, DBC1 is SUMOylated through SUMO1 conjugation at K591 residue in human and mouse lens epithelial cells. The SUMOylated DBC1 is localized in the nucleus and plays an essential role in promoting stress-induced apoptosis. Silence of DBC1 attenuates oxidative stress-induced apoptosis. In contrast, overexpression of DBC1 enhances oxidative stress-induced apoptosis, and this process depends on p53. Mechanistically, DBC1 interacts with p53 to regulate its phosphorylation status at multiple sites and the SUMOylation of DBC1 enhances its interaction with p53. Together, our results identify that DBC1 is an important regulator mediating stress-induced apoptosis in lens, and thus participates in control of lens cataractogenesis.

The effect of Chinese herbal formulas combined with metformin on modulating the gut microbiota in the amelioration of type 2 diabetes mellitus: A systematic review and meta-analysis.

To assess and analyse the effectiveness and safety of combined Chinese herbal formula (CHF) and metformin treatment in the modulation of the gut microbiota in the amelioration of type 2 diabetes mellitus(T2DM), all publications addressing the effect of this combination treatment on the quantitative alterations in the gut microbiota and glucose parameters were collected. Rob tool in the Cochrane handbook was performed to evaluate the methodological quality of all included studies. Relevant information and statistics were abstracted and synthesized in Review Manager 5.4 to evaluate the efficacy of combination treatment. Sensitivity analyses and subgroup analyses were used to analyse the sources of heterogeneity. Publication bias analyses were performed by Stata software to assess the robustness and quality of the outcomes. As a result, a total of 12 eligible RCTs with 1307 T2DM participants from 7 electronic databases were included. Combined CHF with metformin treatment showed better efficacies than metformin monotherapy in regulating the structure of the gut microbiota, characterized by increased Bifidobacterium, Lactobacillus and Bacteroidetes and decreased Enterobacteriaceae, Enterococcus, and Saccharomyces along with better decreases in glycated haemoglobin, fasting plasma glucose, 2-hour postprandial blood glucose, fasting insulin and homeostasis model assessment of insulin resistance. Subgroup analyses further analysed the effect of metformin doses and CHF classifications on controlling hyperglycaemia and altering the gut microbiota. In conclusion, our meta-analysis suggested that combined CHF with metformin treatment is promising for the modulation of the gut microbiota along with ameliorating hyperglycemia in T2DM patients. Importantly, more well-designed RCTs are needed to validate the outcomes and verify the treatment value for clinical purposes. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021291524, identifier CRD42021291524.

SynergyFinder Plus: Toward Better Interpretation and Annotation of Drug Combination Screening Datasets.

Combinatorial therapies have been recently proposed to improve the efficacy of anticancer treatment. The SynergyFinder R package is a software used to analyze pre-clinical drug combination datasets. Here, we report the major updates to the SynergyFinder R package for improved interpretation and annotation of drug combination screening results. Unlike the existing implementations, the updated SynergyFinder R package includes five main innovations. 1) We extend the mathematical models to higher-order drug combination data analysis and implement dimension reduction techniques for visualizing the synergy landscape. 2) We provide a statistical analysis of drug combination synergy and sensitivity with confidence intervals and P values. 3) We incorporate a synergy barometer to harmonize multiple synergy scoring methods to provide a consensus metric for synergy. 4) We evaluate drug combination synergy and sensitivity to provide an unbiased interpretation of the clinical potential. 5) We enable fast annotation of drugs and cell lines, including their chemical and target information. These annotations will improve the interpretation of the mechanisms of action of drug combinations. To facilitate the use of the R package within the drug discovery community, we also provide a web server at www.synergyfinderplus.org as a user-friendly interface to enable a more flexible and versatile analysis of drug combination data.

Plexin-A1 expression in the inhibitory neurons of infralimbic cortex regulates the specificity of fear memory in male mice.

Maintaining appropriate levels of fear memory specificity is crucial for individual's survival and mental health, whereas overgeneralized fear commonly occurs in neuropsychiatric disorders, including posttraumatic stress disorder and generalized anxiety disorder. However, the molecular mechanisms regulating fear memory specificity remain poorly understood. The medial prefrontal cortex (mPFC) is considered as a key brain region in fear memory regulation. Previous transcriptomic studies have identified that plexin-A1, a transmembrane receptor critical for axon development, was downregulated in the mPFC after fear memory training. In this study, we identified that learning-induced downregulation of the mRNA and protein levels of plexin-A1 specifically occurred in the inhibitory but not excitatory neurons in the infralimbic cortex (IL) of mPFC. Further studies of plexin-A1 by virus-mediated over-expression of functional mutants selectively in the IL inhibitory neurons revealed the critical roles of plexin-A1 for regulating memory specificity and anxiety. Moreover, our findings revealed that plexin-A1 regulated the distribution of glutamic acid decarboxylase 67, a GABA synthetase, which in turn modulated the activity of IL and its downstream brain regions. Collectively, our findings elucidate the molecular modifier of IL inhibitory neurons in regulating memory specificity and anxiety, and provide candidates for developing therapeutic strategies for the prevention or treatment of a series of fear generalization-related neuropsychiatric disorders.

Bipartite network models to design combination therapies in acute myeloid leukaemia.

Combination therapy is preferred over single-targeted monotherapies for cancer treatment due to its efficiency and safety. However, identifying effective drug combinations costs time and resources. We propose a method for identifying potential drug combinations by bipartite network modelling of patient-related drug response data, specifically the Beat AML dataset. The median of cell viability is used as a drug potency measurement to reconstruct a weighted bipartite network, model drug-biological sample interactions, and find the clusters of nodes inside two projected networks. Then, the clustering results are leveraged to discover effective multi-targeted drug combinations, which are also supported by more evidence using GDSC and ALMANAC databases. The potency and synergy levels of selective drug combinations are corroborated against monotherapy in three cell lines for acute myeloid leukaemia in vitro. In this study, we introduce a nominal data mining approach to improving acute myeloid leukaemia treatment through combinatorial therapy.