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Abstract Genome-wide association studies (GWAS) identified over fifty loci associated with lung cancer risk. However, underlying mechanisms and target genes are largely unknown, as most risk-associated variants might regulate gene expression in a context-specific manner. Here, we generate a barcode-shared transcriptome and chromatin accessibility map of 117,911 human lung cells from age/sex-matched ever- and never-smokers to profile context-specific gene regulation. Identified candidate cis-regulatory elements (cCREs) are largely cell type-specific, with 37% detected in one cell type. Colocalization of lung cancer candidate causal variants (CCVs) with these cCREs combined with transcription factor footprinting prioritize the variants for 68% of the GWAS loci. CCV-colocalization and trait relevance score indicate that epithelial and immune cell categories, including rare cell types, contribute to lung cancer susceptibility the most. A multi-level cCRE-gene linking system identifies candidate susceptibility genes from 57% of the loci, where most loci display cell-category-specific target genes, suggesting context-specific susceptibility gene function.

Abstract Background Lysine demethylase 5C (KDM5C) has been implicated in the development of several human cancers. This study aims to investigate the role of KDM5C in the progression of colorectal cancer (CRC) and explore the associated molecular mechanism. Methods Bioinformatics tools were employed to predict the target genes of KDM5C in CRC. The expression levels of KDM5C and prefoldin subunit 5 (PFDN5) in CRC cells were determined by RT-qPCR and western blot assays. The interaction between KDM5C, H3K4me3, and PFDN5 was validated by chromatin immunoprecipitation. Expression and prognostic values of KDM5C and PFDN5 in CRC were analyzed in a cohort of 72 patients. The function of KDM5C/PFDN5 in c-Myc signal transduction was analyzed by luciferase assay. Silencing of KDM5C and PFDN5 was induced in CRC cell lines to analyze the cell malignant phenotype in vitro and tumorigenic activity in nude mice. Results KDM5C exhibited high expression, while PFDN5 displayed low expression in CRC cells and clinical CRC samples. High KDM5C levels correlated with poor survival and unfavorable clinical presentation, whereas elevated PFDN5 correlated with improved patient outcomes. KDM5C mediated demethylation of H3K4me3 on the PFDN5 promoter, suppressing its transcription and thereby enhancing the transcriptional activity of c-Myc. KDM5C knockdown in CRC cells suppressed cell proliferation, migration and invasion, epithelial-mesenchymal transition, and tumorigenic activity while increasing autophagy and apoptosis rates. However, the malignant behavior of cells was restored by the further silencing of PFDN5. Conclusion This study demonstrates that KDM5C inhibits PFDN5 transcription, thereby activating c-Myc signal transduction and promoting CRC progression.

Eye diseases (EDs) represent a group of disorders affecting the visual system, most of which can lead to visual impairment and blindness. Accumulating evidence reveals that non-coding RNAs (ncRNAs) are closely associated with a wide variety of EDs. However, abundant associations between ncRNAs and EDs are scattered across the published literature, obstructing a global view of ncRNA-ED associations. A public resource of high-quality manually curated ncRNAomics knowledge associated with EDs remains unavailable. To address this gap, we thus developed Nc2Eye (http://nc2eye.bio-data.cn/), which is the first knowledgebase dedicated to providing a comprehensive ncRNAomics resource for bridging basic and clinical research in EDs. Through a comprehensive review of more than 2400 published papers, Nc2Eye catalogs 7088 manually curated ncRNA-ED associations involving 4363 ncRNAs across eight species. We also provide detailed descriptions and annotation information for each ncRNA-disease association such as ncRNA categories, experimental methods, expression pattern and related clinical drugs. To further expand the pathogenic ncRNAs, we also collected more than 90 high-throughput EDs-related transcriptome datasets. Furthermore, a user-friendly interface was constructed for convenient and flexible data browsing, querying, and retrieving. We believe that Nc2Eye is a timely and valuable knowledgebase for significantly improving and useful for discovery of new diagnostic and therapeutic biomarkers.

Engineered organoids by sequential introduction of key mutations could help modeling the dynamic cancer progression. However, it remains difficult to determine gene paths which were sufficient to capture cancer behaviors and to broadly explain cancer mechanisms. Here, as a case study of colorectal cancer (CRC), functional and dynamic characterizations of five types of engineered organoids with different mutation combinations of five driver genes (APC, SMAD4, KRAS, TP53, and PIK3CA) showed that sequential introductions of all five driver mutations could induce enhanced activation of more hallmark signatures, tending to cancer. Comparative analysis of engineered organoids and corresponding CRC tissues revealed sequential introduction of key mutations could continually shorten the biological distance from engineered organoids to CRC tissues. Nevertheless, there still existed substantial biological gaps between the engineered organoid even with five key mutations and CRC samples. Thus, we proposed an integrative strategy to prioritize gene cascading paths for shrinking biological gaps between engineered organoids and CRC tissues. Our results not only recapitulated the well-known adenoma–carcinoma sequence model (e.g., AKST-organoid with driver mutations in APC, KRAS, SMAD4, and TP53), but also provided potential paths for delineating alternative pathogenesis underlying CRC populations (e.g., A-organoid with APC mutation). Our strategy also can be applied to both organoids with more mutations and other cancers, which can improve and innovate mechanism across cancer patients for drug design and cancer therapy.

Alzheimer's disease (AD), a degenerative disease of the central nervous system, is the most common form of dementia in old age. The complexity and behavior of circular RNA (circRNA)-associated competing endogenous RNA (ceRNA) network remained poorly characterized in AD. The aim of this study was to elucidate the regulatory networks of dysregulated circRNAs from ceRNA view and identify potential risk circRNAs involved in AD pathogenesis. Consistent differentially expressed genes (CDEGs) were obtained using meta-analysis for multiple microarrays, and differentially expressed miRNAs (DEmiRs) were identified using empirical Bayes method. The circRNA-associated ceRNA network (cirCeNET) was constructed based on “ceRNA hypothesis” using an integrated system biology method. A total of 1,872 CDEGs and 48 DEmiRs were screened across different datasets. By mapping CDEGs and DEmiRs into the cirCeNET, an AD-related circRNA-associated ceRNA network (ADcirCeNET) was constructed, including 3,907 edges and 1,407 nodes (276 circRNAs, 14 miRNAs and 1,117 mRNAs). By prioritizing AD risk circRNA-associated ceRNAs, we found that the circRNA KIAA1586 occurred most frequently in the AD risk circRNA-associated ceRNAs and function as a ceRNA that operates by competitively binding three known AD-risk miRNAs. In silico functional analysis suggested that circRNA KIAA1586-related ceRNA network was significantly enriched in known AD-associated biological processes. Our study provided a global view and systematic dissection of circRNA-associated ceRNA network. The identified circRNA KIAA1586 may be a key risk factor involved in AD pathogenesis.

Long noncoding RNAs (lncRNAs) are emerging as a class of important regulators participating in various biological functions and disease processes. With the widespread application of next-generation sequencing technologies, large numbers of lncRNAs have been identified, producing plenty of lncRNA annotation resources in different contexts. However, at present, we lack a comprehensive overview of these lncRNA annotation resources. In this study, we reviewed 24 currently available lncRNA annotation resources referring to>205 000 lncRNAs in over 50 tissues and cell lines. We characterized these annotation resources from different aspects, including exon structure, expression, histone modification and function. We found many distinct properties among these annotation resources. Especially, these resources showed diverse chromatin signatures, remarkable tissue and cell type dependence and functional specificity. Our results suggested the incompleteness and complementarity of current lncRNA annotations and the necessity of integration of multiple resources to comprehensively characterize lncRNAs. Finally, we developed 'LNCat' (lncRNA atlas, freely available at http://biocc.hrbmu.edu.cn/LNCat/), a user-friendly database that provides a genome browser of lncRNA structures, visualization of different resources from multiple angles and download of different combinations of lncRNA annotations, and supports rapid exploration, comparison and integration of lncRNA annotation resources. Overall, our study provides a comprehensive comparison of numerous lncRNA annotations, and can facilitate understanding of lncRNAs in human disease. [ABSTRACT FROM AUTHOR]

Background: DNA methylation is thought to be extensively involved in the pathogenesis of many diseases, including major psychosis. However, most studies focus on DNA methylation alteration at promoters of protein-coding genes, despite the poor correlation between DNA methylation and gene expression. Methods: We analyzed differentially methylated regions and differentially expressed genes in patients with schizophrenia and bipolar disorder and normal subjects. Gene expression and DNA methylation were analyzed with RNA-seq and MeDIP-seq of post-mortem brain tissue (brain region BA9) cohort in five schizophrenia, seven bipolar disorder cases and six controls, respectively. Results: Here, we performed a large-scale integrative analysis using MeDIP-seq, coupled with RNA-seq, on brain samples from major psychotic and normal subjects and observed obvious discrepancy between DNA methylation and gene expression. We found that differentially methylated regions (DMRs) were distributed across different types of genomic elements, especially introns. These intronic DMRs were significantly enriched for diverse regulatory elements, such as enhancers and binding sites of certain transcriptional factors (e.g., Pol3). Notably, we found that parts of intronic DMRs overlapped with some intragenic miRNAs, such as hsa-mir-7-3. These intronic DMR-related miRNAs were found to target many differentially expressed genes. Moreover, functional analysis demonstrated that differential target genes of intronic DMR-related miRNAs were sufficient to capture many important biological processes in major psychosis, such as neurogenesis, suggesting that miRNAs may function as important linkers mediating the relationships between DNA methylation alteration and gene expression changes. Conclusions: Collectively, our study indicated that DNA methylation alteration could induce expression changes indirectly by affecting miRNAs and the exploration of DMR-related miRNAs and their targets enhanced understanding of the molecular mechanisms underlying major psychosis. [ABSTRACT FROM AUTHOR]

Selective hydrogenation of cinnamaldehyde (CAL) to cinnamyl alcohol (COL) is of both fundamental and industrial interest. It is of great significance to evaluate the possible differences between different supports arising from metal dispersion and electronic effects, in terms of activity and selectivity. Herein, Pt catalysts on different carbon supports including carbon nanotubes (CNTs) and reduced graphene oxides (RGO) were developed by a simple wet impregnation method. The resultant catalysts were well characterized by XRD, Raman, N2 physisorption, TEM, and XPS analysis. Applied in the hydrogenation of cinnamaldehyde, 3.5 wt% Pt/CNT shows much higher selectivity towards cinnamyl alcohol (62%) than 3.5 wt% Pt/RGO@SiO2 (48%). The enhanced activity can be ascribed to the high graphitization degree of CNTs and high density of dispersed Pt electron cloud.