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Background: Experimental verification of a drug discovery process is expensive and time-consuming. Therefore, efficiently and effectively identify drug–target interactions (DTIs) has been research focus. In present, many machine learning algorithms are used for predicting drug-target interactions. The key idea is to train the classifier using existing DTI so as to predict new or unknown DTI. However, there are various challenges such as class imbalance and parameter optimization of many classifiers that need to be solved before developing an optimal drug-target interaction model. Methods: In this paper, we propose a framework named SSELM-neg for drug-target interaction prediction, in which a screening approach was used to choose high quality negative samples and a spherical search approach is used to optimize the parameters of the extreme learning machine. Results: Results show that the performance of the proposed technique outperforms the other state-of-the-art methods in 10-fold cross-validation experiments in terms of AUC(0.986, 0.993, 0.988, 0.969 ) and AUPR(0.982, 0.991, 0.982, 0.946) for E dataset, GPCR dataset, IC dataset and NR dataset. Conclusion: Screening approach produce the high quality negative samples with the same numbers of the positive samples, which solve the class imbalance problem. Extreme learning machine was optimized by a spherical search approach in identifying DTIs. Therefore, our models achieve better performance than other state-of-the-art methods.

Background: Patients with preeclampsia display a spectrum of onset time and severity of clinical presentation, yet the underlying molecular bases for the early-onset and late-onset clinical subtypes are not known. Although several transcriptome studies have been done on placentae from PE patients, only a small number of differentially expressed genes have been identified due to very small sample sizes and no distinguishing of clinical subtypes. Methods: We carried out RNA-seq on 65 high-quality placenta samples, including 33 from 30 patients and 32 from 30 control subjects, to search for dysregulated genes and the molecular network and pathways they are involved in. Results: We identified two functionally distinct sets of dysregulated genes in the two major subtypes: 2,977 differentially expressed genes in early-onset severe preeclampsia, which are enriched with metabolism-related pathways, notably transporter functions; and 375 differentially expressed genes in late-onset severe preeclampsia, which are enriched with immune-related pathways. We also identified some key transcription factors, which may drive the widespread gene dysregulation in both early-onset and late-onset patients. Conclusion: These results suggest that early-onset and late-onset severe preeclampsia have different molecular mechanisms, whereas the late-onset mild preeclampsia may have no placenta-specific causal factors. A few regulators may be the key drivers of the dysregulated molecular pathways.

Although germline mutations in BRCA-associated protein-1 (BAP1) predispose to cutaneous melanoma (CM), BAP1 is rarely mutated in primary CM outside the familial context. The role of BAP1 in the pathogenesis of CM remains obscure. Here, we discovered an unexpected role of BAP1 in suppressing CM growth and metastasis. BAP1 deletion by CRISPR-Cas9 system severely compromises colony-forming capability of murine CM cell line B16-F10 and human CM cell lines, SK-MEL-28 and A375. Furthermore, BAP1 loss abrogates tumor growth and lung metastasis in murine syngeneic tumor models. Deletion of BAP1 in B16-F10 cells leads to preferential downregulation of genes accompanied with increased H2A ubiquitination at lysine 119. Transcriptomic characterization of BAP1 deletion reveals multiple deregulated cellular functions including extracellular matrix-receptor interaction and MAPK signaling pathway which may contribute to BAP1's effect on metastasis and proliferation. Our findings indicate that BAP1 could be a potential therapeutic target for CM.

Background Colorectal cancer (CRC) is the third most common cancer worldwide. Cancer discrimination is a typical application of gene expression analysis using a microarray technique. However, microarray data suffer from the curse of dimensionality and usual imbalanced class distribution between the majority (tumor samples) and minority (normal samples) classes. Feature gene selection is necessary and important for cancer discrimination. Objectives To select feature genes for the discrimination of CRC. Methods We improve the feature selection algorithm based on differential evolution, DEFSw by using RUSBoost classifier and weight accuracy instead of the common classifier and evaluation measure for selecting feature genes from imbalance data. We firstly extract differently expressed genes (DEGs) from the CRC dataset of the TCGA and then select the feature genes from the DEGs using the improved DEFSw algorithm. Finally, we validate the selected feature gene sets using independent datasets and retrieve the cancer related information for these genes based on text mining through the Coremine Medical online database. Results We select out 16 single-gene feature sets for colorectal cancer discrimination and 19 single-gene feature sets only for colon cancer discrimination. Conclusions In summary, we find a series of high potential candidate biomarkers or signatures, which can discriminate either or both of colon cancer and rectal cancer with high sensitivity and specificity.

Summary Immune activation has been shown to play a critical role in the development of schizophrenia; however its underlying mechanism remains unknown. Our report demonstrates a high-quality protein interaction network for schizophrenia (SCZ Network), constructed using our “neighborhood walk” approach in combination with “random walk with restart”. The spatiotemporal expression pattern of the genes in this disease network revealed two developmental stages sensitive to perturbation by immune activation: mid-to late gestation, and adolescence. Furthermore, we induced immune activation at these stages in mice, carried out transcriptome sequencing on the mouse brains, and illustrated clear potential molecular pathways and key regulators correlating maternal immune activation during gestation and an increased risk for schizophrenia after a second immune activation at puberty. This work provides not only valuable resources for the study on molecular mechanisms underlying schizophrenia, but also a systematic strategy for the discovery of molecular pathways of complex mental disorders., Graphical abstract, Highlights • A high-quality molecular network for schizophrenia (SCZ Network) • A landscape of molecular pathways linking immune activation and schizophrenia • The spatiotemporal network dynamics revealing stages susceptible to immune activation • Identification of the molecular pathways and regulators in the immune-activated brain, Clinical neuroscience; Immunology; Bioinformatics; Biocomputational method; Systems biology

Background The glioblastoma (GBM) mesenchymal (MES) phenotype, induced by NF-κB activation, is characterized by aggressive tumor progression and poor clinical outcomes. Our previous analysis indicated that MES GBM has a unique alternative splicing (AS) pattern; however, the underlying mechanism remains obscure. We aimed to reveal how splicing regulation contributes to MES phenotype promotion in GBM. Methods We screened novel candidate splicing factors that participate in NF-κB activation and MES phenotype promotion in GBM. In vitro and in vivo assays were used to explore the function of RSRP1 in MES GBM. Results Here, we identified that arginine/serine-rich protein 1 (RSRP1) promotes the MES phenotype by facilitating GBM cell invasion and apoptosis resistance. Proteomic, transcriptomic, and functional analyses confirmed that RSRP1 regulates AS in MES GBM through mediating spliceosome assembly. One RSRP1-regulated AS event resulted in skipping PARP6 exon 18 to form truncated, oncogenic PARP6-s. This isoform was unable to effectively suppress NF-κB. Cotreatment of cultured GBM cells and GBM tumor-bearing mice with spliceosome and NF-κB inhibitors exerted a synergistic effect on MES GBM growth. Conclusion We identified a novel mechanism through which RSRP1-dependent splicing promotes the GBM MES phenotype. Targeting AS via RSRP1-related spliceosomal factors might constitute a promising treatment for GBM.

As a traditional Chinese medicine, Dalbergia tsoi Merr.et Chun (JZX) has been used for the treatment of wounds since ancient times. However, the active compounds and molecular mechanisms of JZX in the acceleration of wound healing are still unknown. Herein, we explored the main active compounds and key molecular mechanisms by which JZX accelerates wound healing. The ethanol extract of JZX was subjected to UPLC-Q-Orbitrap HRMS analysis to identify the main compounds. The pharmacological effect of JZX on wound healing was evaluated using a mouse excision wound model. Network pharmacology was utilized to predict the effective compounds and related signal transduction pathways of JZX that were involved in accelerating wound healing. The predicted key signaling pathways were then validated by immunohistochemical analysis. Interactions between the active compounds and therapeutic targets were confirmed by molecular docking analysis. JZX accelerated wound healing, improved tissue quality, and inhibited inflammation and oxidative stress. Moreover, our results suggested that the active components of JZX, such as butin, eriodyctiol, and formononetin, are the key compounds that facilitate wound treatment. Our studies also indicated that JZX accelerated wound healing by regulating the PI3K/Akt signaling pathway and inducing the expression of TGF-β1, FGF2, VEGFA, ECM1, and α-SMA at different stages of skin wound healing. The JZX extract accelerates wound healing by reducing inflammation and inhibiting oxidative stress, regulating the PI3K/Akt signaling pathway, and promoting the expression of growth factors, suggesting that JZX has potential clinical applicability in wound treatment.

Increasing evidence has shown that noncoding RNAs play significant roles in the initiation, progression, and metastasis of tumours via participating in competing endogenous RNA (ceRNA) networks. However, the survival-associated ceRNA in lung adenocarcinoma (LUAD) remains poorly understood. In this study, we aimed to investigate the regulatory mechanisms underlying ceRNA in LUAD to identify novel prognostic factors. mRNA, lncRNA, and miRNA sequencing data obtained from the GDC data portal were utilized to identify differentially expressed (DE) RNAs. Survival-related RNAs were recognized using univariate Kaplan-Meier survival analysis. We performed functional enrichment analysis of survival-related mRNAs using the clusterProfiler package of R and STRING. lncRNA-miRNA and miRNA-mRNA interactions were predicted based on miRcode, Starbase, and miRanda. Subsequently, the survival-associated ceRNA network was constructed for LUAD. Multivariate Cox regression analysis was used to identify prognostic factors. Finally, we acquired 15 DE miRNAs, 49 DE lncRNAs, and 843 DE mRNAs associated with significant overall survival. Functional enrichment analysis indicated that survival-related DE mRNAs were enriched in cell cycle. The survival-associated lncRNA-miRNA-mRNA ceRNA network was constructed using five miRNAs, 49 mRNAs, and 21 lncRNAs. Furthermore, seven hub RNAs (LINC01936, miR-20a-5p, miR-31-5p, TNS1, TGFBR2, SMAD7, and NEDD4L) were identified based on the ceRNA network. LINC01936 and miR-31-5p were found to be significant using the multifactorial Cox regression model. In conclusion, we successfully constructed a survival-related lncRNA-miRNA-mRNA ceRNA regulatory network in LUAD and identified seven hub RNAs, which provide novel insights into the regulatory molecular mechanisms associated with survival of LUAD, and identified two independent prognostic predictors for LUAD.

Accumulating evidence suggests that the pathogenesis of preeclampsia involves poor placentation caused by insufficient trophoblast invasion and impaired uterine spiral artery remodeling, yet the underlying molecular mechanism remains unclear. We carried out transcriptome profiling on placentae from preeclamptic patients and normal subjects, and identified about four hundred long non-coding RNAs differentially expressed in placentae of patients with early-onset severe preeclampsia. Here, we report our identification of lncRNA SH3PXD2A-AS1 as a potential causal factor for this disease and its downstream pathways involved in placentation. We found that expression level of SH3PXD2A-AS1 in the placentae is positively correlated with clinical severity of the patients. We demonstrated that SH3PXD2A-AS1 inhibited invasion and migration through recruiting CCCTC-binding factor (CTCF) to the promoters of SH3PXD2A and CCR7 to inhibit their transcription. Therefore, we conclude that the upregulation of lncRNA SH3PXD2A-AS1 may contribute to the pathogenesis of preeclampsia through prohibiting trophoblast invasion during placentation.

Objective MicroRNAs (MiRNAs) is considered to play an important role in the occurrence and development of ovarian cancer(OC). Although miRNAs has been widely recognized in ovarian cancer, the role of hsa-miR-30a-5p (miR-30a) in OC has not been fully elucidated. Methods Through the analysis of public data sets in Gene Expression Omnibus (GEO) database and literature review, the significance of miR-30a expression in OC is evaluated. Three mRNA datasets of OC and normal ovarian tissue, GSE14407, GSE18520 and GSE36668, were downloaded from GEO to find the differentially expressed gene (DEG). Then the target genes of hsa-miR-30a-5p were predicted by miRWALK3.0 and TargetScan. Then, the gene overlap between DEG and the predicted target genes of miR-30a in OC was analyzed by Gene Ontology (GO) enrichment analysis. Protein-protein interaction (PPI) network was constructed by STRING and Cytoscape, and the effect of HUB gene on the prognosis of OC was analyzed. Results A common pattern of up-regulation of miR-30a in OC was found. A total of 225 DEG, were identified, both OC-related and miR-30a-related. Many DEG are enriched in the interactions of intracellular matrix tissue, ion binding and biological process regulation. Among the 10 major Hub genes analyzed by PPI, five Hub genes were significantly related to the overall poor survival of OC patients, in which the low expression of ESR1 ,MAPK10, Tp53 and the high expression of YKT ,NSF were related to poor prognosis of OC.

Dysregulated RNA editing is well documented in several diseases, such as cancer and neurodegenerative diseases. The extent to which RNA editing might be involved in diseases originated in the placenta remains unknown. Here, we have systematically profiled RNA editome on the placentae, 9 from patients with early-onset severe preeclampsia (EOSPE) and 32 from normal subjects, and a widespread RNA editing dysregulation in EOSPE has been identified. The mis-edited gene set is enriched with known preeclampsia-associated genes and differentially expressed genes in EOSPE. The RNA editing events at 2 microRNA binding sites in 3′-untranslated region of the LEP mRNA were generated, which could inhibit the microRNA-induced mRNA downregulation of LEP in placenta-derived cell line, consistent with the observation in the placentae of preeclampsia patients. These results demonstrate the association of dysregulated placental RNA editing with preeclampsia, and providing a resource for further study on the role of RNA editing in the pathogenesis of this disease.

Placenta‐origin pregnancy complications, including preeclampsia (PE), gestational diabetes mellitus (GDM), fetal growth restriction (FGR), and macrosomia (MA) are common occurrences in pregnancy, resulting in significant morbidity and mortality for both mother and fetus. However, despite their frequency, there are no reliable methods for the early diagnosis of these complications. Since cfDNA is mainly derived from placental trophoblasts and maternal hematopoietic cells, it might have information for gene expression which can be used for disease prediction. Here, low coverage whole‐genome sequencing on plasma DNA from 2,199 pregnancies is performed based on retrospective cohorts of 3,200 pregnant women. Read depth in the promoter regions is examined to define read‐depth distribution patterns of promoters for pregnancy complications and controls. Using machine learning methods, classifiers for predicting pregnancy complications are developed. Using these classifiers, complications are successfully predicted with an accuracy of 80.3%, 78.9%, 72.1%, and 83.0% for MA, FGR, GDM, and PE, respectively. The findings suggest that promoter profiling of cfDNA may be used as a biological biomarker for predicting pregnancy complications at early gestational age., Cell free DNA (cfDNA) comprises a nucleosome footprint that carries information of its tissue of origin. Different pregnancy complications show distinct patterns of promoter profiling. Based on promoter profiling and machine learning methods, the prediction classifiers can forecast four types of pregnancy complications, such as macrosomia, fetal growth restriction, gestational diabetes, and preeclampsia at early gestational age.

Dysregulated RNA editing is well documented in several diseases such as cancer. The extent to which RNA editing might be involved in diseases originated in the placenta remains unknown, because RNA editing has rarely been studied in the placenta. Here, we have systematically profiled RNA editome on the placentae from 9 patients with early-onset severe preeclampsia (EOSPE) and 32 normal subjects, and a widespread RNA editing dysregulation in EOSPE has been identified. The mis-edited gene set is enriched with known preeclampsia-associated genes and differentially expressed genes in EOSPE. The “RNA editing events” at two microRNA binding sites in 3’-UTR of the LEP mRNA were generated, which could lead to increased expression level of LEP in trophoblast cells. Upregulation of LEP were also observed in the placentae of PE patients. These results suggest that widespread placental RNA editing may be involved in placental development and dysregulation of RNA editing in the placenta may contribute to the pathogenesis of preeclampsia.

Patients with preeclampsia display a spectrum of onset time and severity of clinical presentation, yet the underlying molecular bases for the early-onset and late-onset clinical subtypes are not known. Since the root cause of PE is thought to be located in the placentae, we carried out RNA-seq on 65 high-quality placenta samples, including 33 from 30 patients and 32 from 30 control subjects, to search for molecular features. We identified two functionally distinct sets of dysregulated genes in two major subtypes: metabolism-related genes, notably transporter genes, in early-onset severe preeclampsia and immune-related genes in late-onset severe preeclampsia, while the late-onset mild preeclampsia could not be distinguished from normal controls. A small number of dysregulated transcription factors may drive the widespread gene dysregulation in both early-onset and late-onset patients. These results suggest that early-onset and late-onset severe preeclampsia have different molecular mechanisms, whereas the late-onset mild preeclampsia may have no placenta-specific causal factors.

Immune activation has been recently found to play a large part in the development of schizophrenia, but the underlying mechanism remains largely unknown. Here, we report the construction of a high-quality protein interaction network for schizophrenia (SCZ Network) using a “neighborhood walking” approach to searching across human interactome network for disease-related neighborhoods. The spatiotemporal expression pattern of the immune genes in the SCZ Network demonstrates that this disease network is sensitive to the perturbation of immune activation during mid- to late fetal development and adolescence. The immune genes in the network are involved in pathways regulating the formation, structure and function of synapses and neural connections. Using single-cell transcriptome sequencing on the brains of immune-activated mice, we found that immune activation disturbed the SCZ network in the major brain cell types and the dysregulated pathways were also involved in synapse regulation, demonstrating that our “neighborhood walking” approach enables biological discovery in complex disorders.

Genome engineering of human cells plays an important role in biotechnology and molecular medicine. In particular, insertions of functional multi-transgene cassettes into suitable endogenous sequences will lead to novel applications. Although several tools have been exploited in this context, safety issues such as cytotoxicity, insertional mutagenesis and off-target cleavage together with limitations in cargo size/expression often compromise utility. Phage λ integrase (Int) is a transgenesis tool that mediates conservative site-specific integration of 48 kb DNA into a safe harbor site of the bacterial genome. Here, we show that an Int variant precisely recombines large episomes into a sequence, termed attH4X, found in 1000 human Long INterspersed Elements-1 (LINE-1). We demonstrate single-copy transgenesis through attH4X-targeting in various cell lines including hESCs, with the flexibility of selecting clones according to transgene performance and downstream applications. This is exemplified with pluripotency reporter cassettes and constitutively expressed payloads that remain functional in LINE1-targeted hESCs and differentiated progenies. Furthermore, LINE-1 targeting does not induce DNA damage-response or chromosomal aberrations, and neither global nor localized endogenous gene expression is substantially affected. Hence, this simple transgene addition tool should become particularly useful for applications that require engineering of the human genome with multi-transgenes. MOE (Min. of Education, S’pore) Published version

Induced pluripotent stem cells (iPSCs) are rapidly evolving into an important research tool due to their close resemblance with pluripotent embryonic stem cells (ESCs). Of particular interest at this point are iPSC applications in disease modeling and drug discovery/testing. The high mobility group AT-hook 2 (HMGA2) protein is a nonhistone chromatin factor normally expressed in ESCs and during early developmental stages. Aberrant HMGA2 expression is associated, for example, with abnormal body stature, diabetes mellitus, heart development and uterine leiomyomas. Furthermore, the protein is re-expressed in many primary tumor cells and plays an important role in metastasis. Here we used iPSC formation in conjunction with exogenous human HMGA2 expression to gain insight into biological functions of HMGA2. Gene expression profiling and gene ontology analyses showed that anatomical development and cell adhesion/differentiation processes are strongly affected by HMGA2. This could help to uncover, at the molecular level, some of the known phenotypic consequences of aberrant HMGA2 expression. Furthermore, our data showed that expression of key diabetes susceptibility genes is influenced by HMGA2, which revealed an interesting link to the recently indentified Lin28/let-7 pathway regulating mammalian glucose metabolism. Contrary to a previous report, our results indicate that HMGA2 is not involved in the regulation of telomerase gene expression. Finally, our data support a model in which tight regulation of intracellular HMGA2 levels is important both to maintain a pluripotent ESC state and to induce differentiation into certain cell lineages during later developmental stages.