ABSTRACT Recent technological development in spatial transcriptomics allows researchers to measure gene expression of cells and their spatial locations at the almost single-cell level, which generates detailed biological insight into biological processes. However, specialized spatial transcriptomics databases are rare. Here, we present the Spatial TranscriptOmics DataBase (STOmicsDB), a user-friendly database with multifunctions including search of relevant publications and tools, public dataset visualization, customized specialized databases, new data archive, and online analysis. The current version of STOmicsDB consists of 141 curated spatial transcript datasets covering 12 species, and includes 5,618 spatial multi-omics publications and 674 tools. STOmicsDB is freely accessible at https://db.cngb.org/stomics/ .
Abstract Senescence and change of differentiation direction in bone marrow stromal cells (BMSCs) are two of the most important causes of age-related bone loss. As an important post-transcriptional regulatory pathway, alternative splicing (AS) regulates diversity of gene expression. However, the role of AS in BMSCs during aging remains poorly defined. Here we identify AS in specific genes disrupt gene expression pattern and result in age-related debility of BMSCs. We demonstrate the deficiency of splicing factor Y-box protein 1 (YBX1) result in mis-splicing in genes such as Fn1, Taz, Sirt2 and Sp7 , further contributing to senescence and shift in differentiation direction of BMSCs during aging. Deletion or over-expression of YBX1 in BMSCs accelerate bone loss or stimulate bone formation in mice. Notably, we identify a small compound sciadopitysin which attenuate the degradation of YBX1 and attenuate bone loss in old mice. Our study demonstrates elaborately controlled RNA splicing governs cell fate of BMSCs and provides a potential therapeutic target for age-related osteoporosis. Summary This study demonstrates that YBX1 deficiency induces pre-mRNA mis-splicing and causes senescence and shift in differentiation direction of BMSCs and further accelerates aging-related bone loss. This study identifies Sciadopitysin could reverse this process by targeting YBX1.
Abstract Adipogenesis is the process of cell differentiation through which preadipocytes become adipocytes. Lots of research is currently ongoing to identify genes, including their gene products and microRNAs, that correlate with fat cell development. However, information fragmentation hampers the identification of key regulatory genes and pathways. Here, we present a database of literature-curated adipogenesis-related regulatory interactions, designated the Adipogenesis Regulation Network (ARN, http://210.27.80.93/arn/ ), which currently contains 3101 nodes (genes and microRNAs), 1863 regulatory interactions, and 33,969 expression records associated with adipogenesis, based on 1619 papers. A sentence-based text-mining approach was employed for efficient manual curation of regulatory interactions from approximately 37,000 PubMed abstracts. Additionally, we further determined 13,103 possible node relationships by searching miRGate, BioGRID, PAZAR and TRRUST. ARN also has several useful features: i) regulatory map information; ii) tests to examine the impact of a query node on adipogenesis; iii) tests for the interactions and modes of a query node; iv) prediction of interactions of a query node; and v) analysis of experimental data or the construction of hypotheses related to adipogenesis. In summary, ARN can store, retrieve and analyze adipogenesis-related information as well as support ongoing adipogenesis research and contribute to the discovery of key regulatory genes and pathways.
Adipogenesis is the process of cell differentiation by which mesenchymal stem cells become adipocytes. Extensive research is ongoing to identify genes, their protein products, and microRNAs that correlate with fat cell development. The existing databases have focused on certain types of regulatory factors and interactions. However, there is no relationship between the results of the experimental studies on adipogenesis and these databases because of the lack of an information center. This information fragmentation hampers the identification of key regulatory genes and pathways. Thus, it is necessary to provide an information center that is quickly and easily accessible to researchers in this field. We selected and integrated data from eight external databases based on the results of text-mining, and constructed a publicly available database and web interface (URL: http://210.27.80.93/arn/ ), which contained 30873 records related to adipogenic differentiation. Then, we designed an online analysis tool to analyze the experimental data or form a scientific hypothesis about adipogenesis through Swanson’s literature-based discovery process. Furthermore, we calculated the “Impact Factor” (“IF”) value that reflects the importance of each node by counting the numbers of relation records, expression records, and prediction records for each node. This platform can support ongoing adipogenesis research and contribute to the discovery of key regulatory genes and pathways.
Abstract Background: Blood-based detection of circulating tumor DNA (ctDNA) is a non-invasive and clinical accessible source of biomarkers that enables selection of non-small-cell lung cancer (NSCLC) patients for treatment with anti-PD-(L)1 therapies. However, new approaches are necessary to improve enrichment of responders. Patients and Methods: Pretreatment plasma ctDNA from 97 advanced-stage NSCLC patients who underwent anti-PD-(L)1 therapy from December 2015 to August 2017, with matched tissue samples from 66 patients, were profiled using a targeted next-generation sequencing (NGS) panel (Geneseeq) encompassing 422 cancer-relevant genes. External validation was performed using two large randomized trials, POPLAR and OAK. Results: In the 72 patients with adequate ctDNA release (maximum somatic allele frequency, MSAF ≥2%), high blood tumor mutational burden (bTMB) was associated with significantly prolonged median PFS (110 vs 60 days, HR=0.54 [95%CI, 0.31-0.92]; log-rank p = 0.02) and a trend towards improved DCB (34.8% vs 22.5%, p=0.39). While a high concordance was observed between bTMB and tTMB (Spearman's ρ= 0.71), the greatest progression-free survival (PFS) improvement was achieved with concomitantly high bTMB and tTMB (mPFS, 156 vs 59 days, HR=0.47 [95%CI, 0.24-0.91], log-rank p=0.02). Remarkably, the subset of patients with low ctDNA release (MSAF<2%), and consequently non-evaluable bTMB, derived similar PFS benefit as those with high bTMB. The additive predictive value of MSAF and bTMB was externally validated by results from the two large randomized trials. Conclusions: Our findings validated panel-assessed bTMB as a promising biomarker that demonstrated added value over tissue testing alone for benefit with anti-PD-(L)-1 therapies. Our findings also provided the first clinical evidence suggesting that matched tissue and blood testing might be necessary to refine the predictive value of TMB. Moreover, we identified low ctDNA MSAF as an important and robust predictor of improved immunotherapy outcome. Citation Format: Wenfeng Fang, Yuxiang Ma, Jiani C. Yin, Huaqiang Zhou, Fufeng Wang, Hua Bao, Ao Wang, Xue Wu, Shaodong Hong, Yunpeng Yang, Yan Huang, Hongyun Zhao, Yang W. Shao, Li Zhang. Combinatorial assessment of ctDNA release and mutational burden predicts clinical outcome from anti-PD-(L)1 therapies in non-small-cell lung cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 707.
MicroRNAs (miRNAs) have emerged as fine-tune regulators of the immune system modulating both acquired and innate immune responses. The recognition of a role for miRNAs in inflammation has in turn furthered the understanding of the molecular pathogenesis of diseases. However, due to the inherent complexities of miRNA regulation on their targets, the authors are still at an early stage of exploring the functional roles of miRNAs in inflammatory diseases. The regulation of miRNAs can be cell- or tissue-specific. It is likely that multiple miRNAs, rather than a single miRNA, synergistically act together to regulate gene expression and thus biological networks in response to stress. Therefore, a better understanding about how miRNAs regulate gene networks in general may provide insights into novel regulatory mechanisms. miRNAs are changing the way we think about the development of the immune system and the regulation of immune functions and inflammatory responses.
Abstract Recent technological developments in spatial transcriptomics allow researchers to measure gene expression of cells and their spatial locations at the single-cell level, generating detailed biological insight into biological processes. A comprehensive database could facilitate the sharing of spatial transcriptomic data and streamline the data acquisition process for researchers. Here, we present the Spatial TranscriptOmics DataBase (STOmicsDB), a database that serves as a one-stop hub for spatial transcriptomics. STOmicsDB integrates 218 manually curated datasets representing 17 species. We annotated cell types, identified spatial regions and genes, and performed cell-cell interaction analysis for these datasets. STOmicsDB features a user-friendly interface for the rapid visualization of millions of cells. To further facilitate the reusability and interoperability of spatial transcriptomic data, we developed standards for spatial transcriptomic data archiving and constructed a spatial transcriptomic data archiving system. Additionally, we offer a distinctive capability of customizing dedicated sub-databases in STOmicsDB for researchers, assisting them in visualizing their spatial transcriptomic analyses. We believe that STOmicsDB could contribute to research insights in the spatial transcriptomics field, including data archiving, sharing, visualization and analysis. STOmicsDB is freely accessible at https://db.cngb.org/stomics/.
Obesity is a process of fat accumulation due to the imbalance between energy intake and consumption. Long noncoding RNA (lncRNA) Hnscr is crucial for metabolic regulation, but its roles in lipid metabolism during obesity are still unknown. In this article, we found that the expression of Hnscr gradually decreased in adipose tissues of diet-induced obese mice. Furthermore, the deletion of Hnscr promoted an increase in body weight and adipose tissue weight by upregulating the expression of lipogenesis genes and downregulating lipolysis genes in inguinal white adipose tissue (iWAT) and brown adipose tissue. In vitro knockdown of Hnscr in adipocytes resulted in reduced lipolysis of adipocytes. Overexpression of Hnscr by adenovirus or drug mimics showed the opposite. Mechanistically, Hnscr regulated adipose lipid metabolism by mediating the cyclic adenosine monophosphate/protein kinase A signaling pathway. This study identifies the initial characterization of Hnscr as a critical modifier that regulates lipid metabolism, suggesting that lncRNA Hnscr is a potential target for treating obesity.
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