ENCD (http://www.bio-server.cn/ENCD/) is a manually curated database that provides comprehensive experimentally supported associations among endocrine system diseases (ESDs) and long non-coding ribonucleic acid (lncRNAs). The incidence of ESDs has increased in recent years, often accompanying other chronic diseases, and can lead to disability. A growing body of research suggests that lncRNA plays an important role in the progression and metastasis of ESDs. However, there are no resources focused on collecting and integrating the latest and experimentally supported lncRNA–ESD associations. Hence, we developed an ENCD database that consists of 1379 associations between 35 ESDs and 501 lncRNAs in 12 human tissues curated from literature. By using ENCD, users can explore the genetic data for diseases corresponding to the body parts of interest as well as study the lncRNA regulating mechanism for ESDs. ENCD also provides a flexible tool to visualize a disease- or gene-centric regulatory network. In addition, ENCD offers a submission page for researchers to submit their newly discovered endocrine disorders-genetic data entries online. Collectively, ENCD will provide comprehensive insights for investigating the ESDs associated with lncRNAs. Database URL http://www.bio-server.cn/ENCD

During the complex process of tumour development, the unique destiny of cells is driven by the fine-tuning of multilevel features such as gene expression, network regulation and pathway activation. The dynamic formation of the tumour microenvironment influences the therapeutic response and clinical outcome. Thus, characterizing the developmental landscape and identifying driver features at multiple levels will help us understand the pathological development of disease in individual cell populations and further contribute to precision medicine. Here, we describe a database, CellTracer (http://bio-bigdata.hrbmu.edu.cn/CellTracer), which aims to dissect the causative multilevel interplay contributing to cell development trajectories. CellTracer consists of the gene expression profiles of 1 941 552 cells from 222 single-cell datasets and provides the development trajectories of different cell populations exhibiting diverse behaviours. By using CellTracer, users can explore the significant alterations in molecular events and causative multilevel crosstalk among genes, biological contexts, cell characteristics and clinical treatments along distinct cell development trajectories. CellTracer also provides 12 flexible tools to retrieve and analyse gene expression, cell cluster distribution, cell development trajectories, cell-state variations and their relationship under different conditions. Collectively, CellTracer will provide comprehensive insights for investigating the causative multilevel interplay contributing to cell development trajectories and serve as a foundational resource for biomarker discovery and therapeutic exploration within the tumour microenvironment.

Identifying underlying molecular mechanisms and biomarkers of epithelial ovarian carcinoma (EOC) proliferation and metastasis remains challenging. Patients of EOC are usually diagnosed at an advanced stage and the availability of invasion-related targets is limited. Herein, we explored the single-cell RNA sequencing (scRNA-seq) dataset of EOC and defined tumor physiological reprograming compared to bulk RNA-seq. The energy metabolism and anti-apoptotic pathway was found as critical contributors to intratumor heterogeneity. Moreover, hypoxia, oxidative phosphorylation (OXPHOS) and glycolysis were positively correlated, which have biologically activity trajectories during epithelial mesenchymal transition (EMT). The HMGH1, EGR1 and RUNX1 were found to be critical inducers of the EMT process in EOC. Experimental validation revealed that suppressed EGR1 decreased the expression of FAS and HSPG2 and associating with EMT progression in EOC. In tumor microenvironment (TME), CAFs were found have significant contribution to tumor immune infiltration and metastasis and accumulation of CAFs was associated with poorer patient survival. In conclusion, physiological features and molecular mechanisms in the TME of EOC were revealed and provided effective targets for the suppression of tumor metastasis.

Identifying underlying molecular mechanisms and biomarkers of epithelial ovarian carcinoma (EOC) proliferation and metastasis remains challenging. Patients of EOC are usually diagnosed at an advanced stage and the availability of invasion-related targets is limited. Herein, we explored the single-cell RNA sequencing (scRNA-seq) dataset of EOC and defined tumor physiological reprograming compared to bulk RNA-seq. The energy metabolism and anti-apoptotic pathway was found as critical contributors to intratumor heterogeneity. Moreover, hypoxia, oxidative phosphorylation (OXPHOS) and glycolysis were positively correlated, which have biologically activity trajectories during epithelial mesenchymal transition (EMT). The HMGH1, EGR1 and RUNX1 were found to be critical inducers of the EMT process in EOC. Experimental validation revealed that suppressed EGR1 decreased the expression of FAS and HSPG2 and associating with EMT progression in EOC. In tumor microenvironment (TME), CAFs were found have significant contribution to tumor immune infiltration and metastasis and accumulation of CAFs was associated with poorer patient survival. In conclusion, physiological features and molecular mechanisms in the TME of EOC were revealed and provided effective targets for the suppression of tumor metastasis.