Transcript and protein signatures derived from shared molecular interactions across cancers are associated with mortality.

BACKGROUND: Characterization of shared cancer mechanisms have been proposed to improve therapy strategies and prognosis. Here, we aimed to identify shared cell-cell interactions (CCIs) within the tumor microenvironment across multiple solid cancers and assess their association with cancer mortality. METHODS: CCIs of each cancer were identified by NicheNet analysis of single-cell RNA sequencing data from breast, colon, liver, lung, and ovarian cancers. These CCIs were used to construct a shared multi-cellular tumor model (shared-MCTM) representing common CCIs across cancers. A gene signature was identified from the shared-MCTM and tested on the mRNA and protein level in two large independent cohorts: The Cancer Genome Atlas (TCGA, 9185 tumor samples and 727 controls across 22 cancers) and UK biobank (UKBB, 10,384 cancer patients and 5063 controls with proteomics data across 17 cancers). Cox proportional hazards models were used to evaluate the association of the signature with 10-year all-cause mortality, including sex-specific analysis. RESULTS: A shared-MCTM was derived from five individual cancers. A shared gene signature was extracted from this shared-MCTM and the most prominent regulatory cell type, matrix cancer-associated fibroblast (mCAF). The signature exhibited significant expression changes in multiple cancers compared to controls at both mRNA and protein levels in two independent cohorts. Importantly, it was significantly associated with mortality in cancer patients in both cohorts. The highest hazard ratios were observed for brain cancer in TCGA (HR [95%CI] = 6.90[4.64-10.25]) and ovarian cancer in UKBB (5.53[2.08-8.80]). Sex-specific analysis revealed distinct risks, with a higher mortality risk associated with the protein signature score in males (2.41[1.97-2.96]) compared to females (1.84[1.44-2.37]). CONCLUSION: We identified a gene signature from a comprehensive shared-MCTM representing common CCIs across different cancers and revealed the regulatory role of mCAF in the tumor microenvironment. The pathogenic relevance of the gene signature was supported by differential expression and association with mortality on both mRNA and protein levels in two independent cohorts.

Targeting LEF1-mediated epithelial-mesenchymal transition reverses lenvatinib resistance in hepatocellular carcinoma.

Acquired resistance is a significant hindrance to clinical application of lenvatinib in unresectable hepatocellular carcinoma (HCC). Further in-depth investigation of resistance mechanisms can help to develop additional therapeutic strategies to overcome or delay resistance. In our study, two lenvatinib-resistant (LR) HCC cell lines were established by treatment with gradient increasing concentration of lenvatinib, named Hep3B-LR and HepG2-LR. Interestingly, continuous lenvatinib treatment reinforced epithelial-mesenchymal transition (EMT), cell migration, and cell invasion. Gene set enrichment analysis (GSEA) enrichment analysis of RNA-sequencing from Hep3B-LR and corresponding parental cells revealed that activation of Wnt signaling pathway was involved in this adaptive process. Active ß-catenin and its downstream target lymphoid enhancer binding factor 1 (LEF1) were significantly elevated in LR HCC cells, which promoted lenvatinib resistance through mediating EMT-related genes. Data analysis based on Gene Expression Omnibus (GEO) and the Cancer Genome Atlas Program (TCGA) databases suggests that LEF1, as a key regulator of EMT, was a novel molecular target linked to lenvatinib resistance and poor prognosis in HCC. Using a small-molecule specific inhibitor ICG001 and knocking down LEF1 showed that targeting LEF1 restored the sensitivity of LR HCC cells to lenvatinib. Our results uncover upregulation of LEF1 confers lenvatinib resistance by facilitating EMT, cell migration, and invasion of LR HCC cells, indicating that LEF1 is a novel therapeutic target for overcoming acquired lenvatinib resistance.

DNA G-Quadruplex in NRP1 Promoter Facilitates SARS-CoV-2 Infection.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection continues to raise concerns worldwide. Numerous host factors involved in SARS-CoV-2 infection have been identified, but the regulatory mechanisms of these host factor remain unclear. Here, we report the role of G-quadruplexes (G4s) located in the host factor promoter region in SARS-CoV-2 infection. Using bioinformatics, biochemical, and biological assays, we provide evidence for the presence of G4 structures in the promoter regions of SARS-CoV-2 host factors NRP1. Specifically, we focus on two representative G4s in the NRP1 promoter and highlight its importance in SARS-CoV-2 pathogenesis. The presence of the G4 structure greatly increases NRP1 expression, facilitating SARS-CoV-2 entry into cells. Utilizing published single-cell RNA sequencing data obtained from simulated SARS-CoV-2 infection in human bronchial epithelial cells (HBECs), we found that ciliated cells with high levels of NRP1 are prominently targeted by the virus during infection. Furthermore, our study identifies E2F1 act as a transcription factor that binds to G4s. These findings uncover a previously unknown mechanism underlying SARS-CoV-2 infection and suggest that targeting G4 structures could be a potential strategy for COVID-19 prevention and treatment.

TRERNA1 upregulation mediated by HBx promotes sorafenib resistance and cell proliferation in HCC via targeting NRAS by sponging miR-22-3p.

Hepatocellular carcinoma (HCC) is among the most common malignancies and has an unfavorable prognosis. The hepatitis B virus-encoded X (HBx) protein is closely associated with hepatocarcinogenesis. Sorafenib is a unique targeted oral kinase inhibitor for advanced HCC. Long noncoding RNAs (lncRNAs) mediate HCC progression and therapeutic resistance by acting as competing endogenous RNAs (ceRNAs). However, the ceRNA regulatory mechanisms underlying sorafenib resistance in HBx-associated HCC remain largely unknown. In this study, we found that translation regulatory lncRNA 1 (TRERNA1) upregulation by HBx not only promoted HCC cell proliferation by regulating the cell cycle in vitro and in vivo but also correlated positively with poor prognosis in HCC. Importantly, TRERNA1 enhanced sorafenib resistance in HCC cells. RNA sequencing (RNA-seq) analysis indicated that NRAS proto-oncogene (NRAS) is a potential target of TRERNA1 that mediates aspects of hepatocellular carcinogenesis. TRERNA1 acts as a ceRNA to regulate NRAS expression by sponging microRNA (miR)-22-3p. In summary, we show that increased TRERNA1 expression induced by HBx reduces HCC cell sensitivity to sorafenib by activating the RAS/Raf/MEK/ERK signaling pathway. We reveal a novel regulatory mode by which the TRERNA1/miR-22-3p/NRAS axis mediates HCC progression and indicates that TRERNA1 might constitute a powerful tumor biomarker and therapeutic target in HCC.

Bulk and single cell transcriptomic data indicate that a dichotomy between inflammatory pathways in peripheral blood and arthritic joints complicates biomarker discovery.

BACKGROUND: Unbiased studies using different genome-wide methods have identified several novel biomarkers for diagnosis and treatment response in Rheumatoid Arthritis (RA). However, clinical translation has proven difficult. Here, we hypothesized that one reason could be that inflammatory responses in peripheral blood are different from those in the arthritic joint. METHODS: We performed meta-analysis of gene expression microarray data from synovium, whole blood cells (WBC), peripheral blood mononuclear cells (PBMC), and CD4+ T cells from patients with RA and healthy controls in order to identify overlapping pathways, upstream regulators and potential biomarkers. We also analyzed single cell RNA-sequencing (scRNA-seq) data from peripheral blood and whole joints from a mouse model of antigen-induced arthritis. RESULTS: Analyses of two profiling data sets from synovium from RA patients and healthy controls all showed significant activation of pathways with known pathogenic relevance, such as the Th1 pathway, the role of NFAT in regulation of the immune response, dendritic cell maturation, iCOS-iCOSL signaling in T helper cells, Fcγ receptor-mediated phagocytosis, interferon signaling, Cdc42 signaling, and cytotoxic T lymphocyte-mediated apoptosis. The most activated upstream regulators included TNF, an important drug target, as well as IFN-gamma and CD40LG, all of which are known to play important pathogenic roles in RA. The differentially expressed genes from synovium included several potential biomarkers, such as CCL5, CCL13, CCL18, CX3CL1, CXCL6, CXCL9, CXCL10, CXCL13, IL15, IL32, IL1RN, SPP1, and TNFSF11. By contrast, microarray studies of WBC, PBMC and CD4+ T cells showed variable pathways and limited pathway overlap with synovium. Similarly, scRNA-seq data from a mouse model of arthritis did not support that inflammatory responses in peripheral blood reflect those in the arthritic joints. These data showed pathway overlap between mouse joint cells and synovium from patients with RA, but not with cells in peripheral blood. CONCLUSIONS: Our findings indicate a dichotomy between gene expression changes, pathways, upstream regulators and biomarkers in synovium and cell types in peripheral blood, which complicates identification of biomarkers in blood.

Generation of Cas9 transgenic zebrafish and their application in establishing an ERV-deficient animal model.

OBJECTIVES: To investigate the effect of endogenous Cas9 on genome editing efficiency in transgenic zebrafish. RESULTS: Here we have constructed a transgenic zebrafish strain that can be screened by pigment deficiency. Compared with the traditional CRISPR injection method, the transgenic zebrafish can improve the efficiency of genome editing significantly. At the same time, we first observed that the phenotype of vertebral malformation in early embryonic development of zebrafish after ZFERV knockout. CONCLUSIONS: The transgenic zebrafish with expressed Cas9, is more efficient in genome editing. And the results of ZFERV knockout indicated that ERV may affect the vertebral development by Notch1/Delta D signal pathway.

Effects of chronic exposure to microcystin-LR on hepatocyte mitochondrial DNA replication in mice.

Microcystins (MCs) are produced by cyanobacterial blooms, and microcystin-LR (MC-LR) is the most toxic among the 80 MC variants. Data have shown that the liver is one of the specific target organs for MC-LR, which can cause mitochondrial DNA (mtDNA) damage, resulting in mitochondrial dysfunction. However, the underlying mechanism is still unclear. In the present study, we evaluated the genetic toxicity of MC-LR in mice drinking water at different concentrations (1, 5, 10, 20, and 40 µg/L) for 12 months. Our results showed that long-term and persistent exposure to MC-LR increased the 8-hydroxy-2'-deoxyguanosine (8-OHdG) levels of DNA in liver cells, damaged the integrity of mtDNA and nuclear DNA (nDNA), and altered the mtDNA content. Notably, MC-LR exposure can change the expression of mitochondrial genes and nuclear genes that are critical for regulating mtDNA replication and repairing oxidized DNA. They also further impaired the function of mitochondria and liver cells.

Rapid determination of oligopeptides and amino acids in soybean protein hydrolysates using high-resolution mass spectrometry.

INTRODUCTION: Soybean protein hydrolysates (SPHs), especially oligopeptides, have shown a variety of functional properties, including immunomodulatory and anti-oxidant effects. Soybean protein hydrolysate products have been used as functional ingredients in food, sports nutrition or clinical nutrition. However, the mixture is mostly undefined due to its complex nature, containing peptides and minor amino acids as well as small proteins. OBJECTIVES: To develop a specific and efficient method for the identification and structural characterisation of oligopeptides in SPHs, and to determine free amino acids in SPHs in the same analytical run, for evaluation of the chemical profile of SPH products. METHODS: Accurate mass spectrometry (MS) datasets of SPH samples were recorded on a high-performance liquid chromatography (HPLC) tandem high-resolution (HR) MS system. Potential oligopeptides were tentatively characterised based on their elemental compositions and ring double bond equivalent (RDBE) values, as well as HRMS/MS data. The analytical method to determine amino acids was evaluated in terms of linearity, precision, apparent recovery and limits of detection and quantitation. RESULTS: In total, 186 oligopeptides spanning the mass range of m/z 200-1500 and three major free amino acids could be determined in SPH samples in a single sample injection. Ninety-nine oligopeptides were tentatively characterised. The sensitive and specific instrumental performances also permitted the determination of 19 amino acids with a limit of quantitation of ≤ 0.1 µg/mL. CONCLUSION: The HPLC-HRMS technique has proven to be an advantageous tool for the rapid characterisation of oligopeptides and determination of amino acids in soybean protein hydrolysates.

Auto-induction of phase I and phase II metabolism of artemisinin in healthy Chinese subjects after oral administration of a new artemisinin-piperaquine fixed combination.

BACKGROUND: Artequick is a relatively inexpensive artemisinin (Qing-hao-su; QHS)-based combination therapy (ACT) that contains QHS and piperaquine (PQ), which has not been widely used because of the decreased concentration level of QHS after repeated oral administrations for five to seven days as a monotherapy. This study was designed to evaluate the potential auto-induction metabolism of QHS in healthy Chinese adults after a two-day oral administration of QHS-PQ. The effect of QHS-PQ on the activity of the CYP2B6 and CYP3A4 was also investigated. METHODS: Fourteen healthy Chinese subjects received two-day oral doses of QHS-PQ (Artequick). A two-drug cocktail consisting of bupropion and midazolam was used to assess the activities of CYP2B6 and CYP3A, respectively. Plasma samples were analysed for QHS and its phase I/II metabolites, probe drugs and their metabolites, using a validated liquid chromatography tandem mass spectrometric (LC-MS) method. RESULTS: Four major phase I metabolites of QHS (M1-M3 and deoxy-QHS) and two subsequent phase II metabolites (M4-M5) were detected in human plasma after oral administrations of QHS-PQ. The AUC0-t of the QHS and its phase I metabolites decreased significantly (P < 0.05) with increased oral clearance (CL/F) after two-day oral doses of QHS-PQ, whereas its phase II metabolites exhibited higher AUC (P < 0.01). The phase I metabolic capability, calculated by the AUC0-t ratio of all phase I metabolites to QHS, increased 1.5-fold after the repeated dose (P < 0.01), and the phase II metabolic capability increased 1.5-fold for M4 and 3.0-fold for M5. The enzyme activity of CYP2B6 and CYP3A4 increased 2.1-fold and 3.2-fold, respectively, after two-day oral doses of QHS-PQ. CONCLUSIONS: The auto-induction of both phase I and phase II metabolism of QHS was present in healthy Chinese subjects after a recommended two-day oral dose of QHS-PQ. The auto-induction metabolism also existed for phase I metabolites of QHS. The enzyme activity of CYP2B6 and CYP3A4 was induced after the two-day oral doses of QHS-PQ. Based on these results, the alternative common three-day regimen for QHS-PQ could probably lead to lower bioavailability of QHS and higher potential of drug-drug interaction caused by the induction of drug-metabolizing enzymes.

The effect of UGTs polymorphism on the auto-induction phase II metabolism-mediated pharmacokinetics of dihydroartemisinin in healthy Chinese subjects after oral administration of a fixed combination of dihydroartemisinin-piperaquine.

BACKGROUND: Dihydroartemisinin (DHA) is a component of artemisinin-based combination therapy (ACT), which is widely recommended for treatment of uncomplicated falciparum malaria. DHA is also the main metabolite of artemether and artesunate, both of which are used in ACT. Due to auto-induction metabolism, declining plasma concentrations after the repeated dosing have been reported for artemisinin (Qing-hao-su) and artemether. This study was designed to evaluate the potential auto-induction metabolism of DHA in healthy Chinese adults after multiple oral doses of DHA. The polymorphic effects of UGT1A9 (I399C>T) and UGT2B7*2 (802C>T), the major enzymes involved in the metabolism of DHA, on the pharmacokinetic profiles of DHA and its metabolite was also studied. METHODS: Sixteen healthy Chinese subjects (four I399TT/802CC, four I399CC/802TT, four I399TT/802TT and four I399CT/802CT) received four recommended oral doses of Artekin, an ACT containing DHA (80 mg/dose) and piperaquine (PQ; 640 mg/dose), at 0, 6, 24 and 32 h. Plasma samples were analysed for DHA and its metabolite using a validated liquid chromatography tandem mass spectrometric (LC-MS) method. RESULTS: DHA and its glucuronidated metabolite DHA-Glu were detected in human plasma after oral administration of DHA-PQ. Compared with the first dose, the AUC0-t of the parent drug DHA decreased significantly (P<0.01) with increased oral clearance (CL/F) after each repeated dose of DHA-PQ, whereas its metabolite DHA-Glu did not change (P>0.05) in AUC(0-t) or C(max). The phase II metabolic capability, calculated by the AUC(0-t) ratio of DHA-Glu to the parent drug DHA, increased 1.5-fold (90% CI, 1.3-1.7), 1.2-fold (90% CI, 1.1-1.3) and 1.7-fold (90% CI, 1.5-1.8) after the second, third and fourth dose, respectively. No polymorphic effect was found for UGT1A9 (I399C>T) and UGT2B7*2 (802C>T) on the pharmacokinetic profiles of DHA and its metabolite DHA-Glu. CONCLUSIONS: The auto-induction phase II metabolism of DHA was present in healthy Chinese subjects after the recommended two-day oral doses of DHA-PQ (Artekin). The metabolic capability could recover after a 12-h dosing interval, which suggested that the alternative common three-day regimen (once daily) for DHA-PQ could probably lead to higher bioavailability of DHA. The polymorphism of UGT1A9 (I399C>T) and UGT2B7*2 (802C>T) may not be a concern during the treatment with DHA.

Metabolic pathways leading to detoxification of triptolide, a major active component of the herbal medicine Tripterygium wilfordii.

Triptolide (TP) shows promising anti-inflammatory and antitumor activity but with severe toxicity. TP is a natural reactive electrophile containing three epoxide groups, which are usually linked to hepatotoxicity via their ability to covalently bind to cellular macromolecules. In this study, metabolic pathways leading to detoxification of TP were evaluated in glutathione (GSH)-depleted (treated with L-buthionine-S,R-sulfoxinine, BSO) and aminobenzotriazole (ABT; a non-specific inhibitor for P450s)-treated mice. The toxicity of TP in mice was evaluated in terms of mortality and levels of serum alanine transaminase (ALT). In incubates with NADPH- and GSH-supplemented liver microsomes, seven GSH conjugates derived from TP were detected. In mice, these hydrolytically unstable GSH conjugates underwent γ-glutamyltranspeptidase/dipeptidases-mediated hydrolysis leading to two major cysteinylglycine conjugates, which underwent further hydrolysis by dipeptidases to form two cysteine conjugates of TP. In ABT-treated mice, the hydroxylated metabolites of TP were found at a lower level than normal mice, and their subsequent conjugated metabolites were not found. The level of cysteinylglycine and cysteine conjugates derived from NADPH-independent metabolism increased in mice treated with both TP and BSO (or ABT), which could be the stress response to toxicity of TP. Compared with normal mice, mortality and ALT levels were significantly higher in TP-treated mice, indicating the toxicity of TP. Pretreatment of ABT increased the toxicity caused by TP, whereas the mortality decreased in GSH-depleted mice. Metabolism by cytochrome P450 enzymes to less reactive metabolites implied a high potential for detoxification of TP. The GSH conjugation pathway also contributed to TP's detoxification in mice.

Co-overexpression of BRD4 and CDK7 promotes cell proliferation and predicts poor prognosis in HCC.

Aberrant expression of critical components of the trans-acting super-enhancers (SE) complex contributes to the continuous and robust transcription of oncogenes in human cancers. Small-molecule inhibitors targeting core-transcriptional components such as transcriptional bromodomain protein 4 (BRD4) and cyclin-dependent kinase 7 (CDK7) have been developed and are currently undergoing preclinical and clinical testing in several malignant cancers. By analysis of TCGA data and clinical specimens, we demonstrated that BRD4 and CDK7 were frequently overexpressed in human HCCs and were associated with the poor prognosis. Shorter survival and poorly differentiated histology were linked to high BRD4 or CDK7 expression levels. Interestingly, co-overexpression of BRD4 and CDK7 was a more unfavorable prognostic factor in HCC. Treatment with JQ1 or THZ1 alone exhibited an inhibitory impact on the proliferation of HCC cells, while JQ1 synergized with THZ1 showed a more pronounced suppression. Concurrently, a combined JQ1 and THZ1 treatment abolished the transcription of oncogenes ETV4, MYC, NFE2L2. Our study suggested that BRD4 and CDK7 coupled can be a valuable biomarker in HCC diagnosis and the combination of JQ1 and THZ1 can be a promising therapeutic treatment against HCC.

An interactive atlas of genomic, proteomic, and metabolomic biomarkers promotes the potential of proteins to predict complex diseases.

Multiomics analyses have identified multiple potential biomarkers of the incidence and prevalence of complex diseases. However, it is not known which type of biomarker is optimal for clinical purposes. Here, we make a systematic comparison of 90 million genetic variants, 1453 proteins, and 325 metabolites from 500,000 individuals with complex diseases from the UK Biobank. A machine learning pipeline consisting of data cleaning, data imputation, feature selection, and model training using cross-validation and comparison of the results on holdout test sets showed that proteins were most predictive, followed by metabolites, and genetic variants. Only five proteins per disease resulted in median (min-max) areas under the receiver operating characteristic curves for incidence of 0.79 (0.65-0.86) and 0.84 (0.70-0.91) for prevalence. In summary, our work suggests the potential of predicting complex diseases based on a limited number of proteins. We provide an interactive atlas (macd.shinyapps.io/ShinyApp/) to find genomic, proteomic, or metabolomic biomarkers for different complex diseases.

An interactive atlas of genomic, proteomic, and metabolomic biomarkers promotes the potential of proteins to predict complex diseases.

Multiomics analyses have identified multiple potential biomarkers of the incidence and prevalence of complex diseases. However, it is not known which type of biomarker is optimal for clinical purposes. Here, we make a systematic comparison of 90 million genetic variants, 1,453 proteins, and 325 metabolites from 500,000 individuals with complex diseases from the UK Biobank. A machine learning pipeline consisting of data cleaning, data imputation, feature selection, and model training using cross-validation and comparison of the results on holdout test sets showed that proteins were most predictive, followed by metabolites, and genetic variants. Only five proteins per disease resulted in median (min-max) areas under the receiver operating characteristic curves for incidence of 0.79 (0.65-0.86) and 0.84 (0.70-0.91) for prevalence. In summary, our work suggests the potential of predicting complex diseases based on a limited number of proteins. We provide an interactive atlas (macd.shinyapps.io/ShinyApp/) to find genomic, proteomic, or metabolomic biomarkers for different complex diseases.

Construction of Mn doped Cu7S4 nanozymes for synergistic tumor therapy in NIR-I/II bio-windows.

In photothermal therapy (PTT) and chemodynamic therapy (CDT) of cancer, poor performance of nanoagents severely impaired the therapeutic effect of cancer. To solve the problem, we proposed and constructed a novel Mn doped Cu7S4 phothermal nanoagent both in the first near-infrared (NIR-I) and the second near- infrared (NIR-II) windows in this work, which exhibited high photothermal conversion efficiency of 40.3% at 808 nm (NIR-I window) and 33.4% at 1064 nm (NIR-II window), as well as outstanding pH-sensitive catalytic performance (peroxidase-like catalytic activity and Fenton-like catalytic activities). The as-prepared Mn doped Cu7S4 could be used to load chemotherapy drug doxorubicin (DOX) after modified by folic acid. Both in vitro and in vivo studies indicated that it could be used as nanoagent for chemodynamic therapy (CDT)/photothermal therapy (PTT)/ chemotherapy of cervical carcinoma. This study thus provided an NIR-I/NIR-II/pH responsive nanoagent for potential synergistic therapy of deep-seated tumors.

scDrugPrio: a framework for the analysis of single-cell transcriptomics to address multiple problems in precision medicine in immune-mediated inflammatory diseases.

BACKGROUND: Ineffective drug treatment is a major problem for many patients with immune-mediated inflammatory diseases (IMIDs). Important reasons are the lack of systematic solutions for drug prioritisation and repurposing based on characterisation of the complex and heterogeneous cellular and molecular changes in IMIDs. METHODS: Here, we propose a computational framework, scDrugPrio, which constructs network models of inflammatory disease based on single-cell RNA sequencing (scRNA-seq) data. scDrugPrio constructs detailed network models of inflammatory diseases that integrate information on cell type-specific expression changes, altered cellular crosstalk and pharmacological properties for the selection and ranking of thousands of drugs. RESULTS: scDrugPrio was developed using a mouse model of antigen-induced arthritis and validated by improved precision/recall for approved drugs, as well as extensive in vitro, in vivo, and in silico studies of drugs that were predicted, but not approved, for the studied diseases. Next, scDrugPrio was applied to multiple sclerosis, Crohn's disease, and psoriatic arthritis, further supporting scDrugPrio through prioritisation of relevant and approved drugs. However, in contrast to the mouse model of arthritis, great interindividual cellular and gene expression differences were found in patients with the same diagnosis. Such differences could explain why some patients did or did not respond to treatment. This explanation was supported by the application of scDrugPrio to scRNA-seq data from eleven individual Crohn's disease patients. The analysis showed great variations in drug predictions between patients, for example, assigning a high rank to anti-TNF treatment in a responder and a low rank in a nonresponder to that treatment. CONCLUSIONS: We propose a computational framework, scDrugPrio, for drug prioritisation based on scRNA-seq of IMID disease. Application to individual patients indicates scDrugPrio's potential for personalised network-based drug screening on cellulome-, genome-, and drugome-wide scales. For this purpose, we made scDrugPrio into an easy-to-use R package ( https://github.com/SDTC-CPMed/scDrugPrio ).

Detection of mosaicism for the polymorphic variants in the 5'-UTR of hOGG1 by cloning and sequence analysis and pyrosequencing.

Mosaicism refers to the presence of genetically distinct cell lines within an organism or a tissue. Somatic mosaicism exists in distinct populations of somatic cells and commonly arises as a result of somatic mutations, mainly in early embryonic development. SNPs are important markers that distinguish between different individuals in heterogeneous biological samples and contribute greatly to disease risk association studies. In this work, we investigated the relationship between the functional variants in the 5'-UTR of the hOGG1 gene and the risk of type 2 diabetes. Upon detection of the polymorphisms c.-53G>C, c.-23A>G, and c.-18G>T in the hOGG1 gene, we found that mosaicism was present in 3/28 (10.71%), 7/51 (13.73%), and 1/44 (2.27%) patients respectively, who were carriers of these single nucleotide variations, by cloning and sequence analysis and pyrosequencing. Statistical analysis showed that the frequency of the variation c.-23A>G in the hOGG1 5'-UTR in type 2 diabetic patients was significantly higher than that in healthy controls. However, sequencing of the mutant alleles in mosaic individuals showed weak peaks that may affect detection of the SNPs and impair association-based investigations.

Multi-organ single-cell analysis reveals an on/off switch system with potential for personalized treatment of immunological diseases.

Prioritization of disease mechanisms, biomarkers, and drug targets in immune-mediated inflammatory diseases (IMIDs) is complicated by altered interactions between thousands of genes. Our multi-organ single-cell RNA sequencing of a mouse IMID model, namely collagen-induced arthritis, shows highly complex and heterogeneous expression changes in all analyzed organs, even though only joints showed signs of inflammation. We organized those into a multi-organ multicellular disease model, which shows predicted molecular interactions within and between organs. That model supports that inflammation is switched on or off by altered balance between pro- and anti-inflammatory upstream regulators (URs) and downstream pathways. Meta-analyses of human IMIDs show a similar, but graded, on/off switch system. This system has the potential to prioritize, diagnose, and treat optimal combinations of URs on the levels of IMIDs, subgroups, and individual patients. That potential is supported by UR analyses in more than 600 sera from patients with systemic lupus erythematosus.

scDrugPrio: A framework for the analysis of single-cell transcriptomics to address multiple problems in precision medicine in immune-mediated inflammatory diseases.

Background: Ineffective drug treatment is a major problem for many patients with immune-mediated inflammatory diseases (IMIDs). Important reasons are the lack of systematic solutions for drug prioritisation and repurposing based on characterisation of the complex and heterogeneous cellular and molecular changes in IMIDs. Methods: Here, we propose a computational framework, scDrugPrio, which constructs network models of inflammatory disease based on single-cell RNA sequencing (scRNA-seq) data. scDrugPrio constructs detailed network models of inflammatory diseases that integrate information on cell type-specific expression changes, altered cellular crosstalk and pharmacological properties for the selection and ranking of thousands of drugs. Results: scDrugPrio was developed using a mouse model of antigen-induced arthritis and validated by improved precision/recall for approved drugs, as well as extensive in vitro, in vivo, and in silico studies of drugs that were predicted, but not approved, for the studied diseases. Next, scDrugPrio was applied to multiple sclerosis, Crohn's disease, and psoriatic arthritis, further supporting scDrugPrio through prioritisation of relevant and approved drugs. However, in contrast to the mouse model of arthritis, great interindividual cellular and gene expression differences were found in patients with the same diagnosis. Such differences could explain why some patients did or did not respond to treatment. This explanation was supported by the application of scDrugPrio to scRNA-seq data from eleven individual Crohn's disease patients. The analysis showed great variations in drug predictions between patients, for example, assigning a high rank to anti-TNF treatment in a responder and a low rank in a nonresponder to that treatment. Conclusion: We propose a computational framework, scDrugPrio, for drug prioritisation based on scRNA-seq of IMID disease. Application to individual patients indicates scDrugPrio's potential for personalised network-based drug screening on cellulome-, genome-, and drugome-wide scales. For this purpose, we made scDrugPrio into an easy-to-use R package (https://github.com/SDTC-CPMed/scDrugPrio).