GeTeSEPdb: A comprehensive database and online tool for the identification and analysis of gene profiles with temporal-specific expression patterns.

Gene expression is dynamic and varies at different stages of processes. The identification of gene profiles with temporal-specific expression patterns can provide valuable insights into ongoing biological processes, such as the cell cycle, cell development, circadian rhythms, or responses to external stimuli such as drug treatments or viral infections. However, currently, no database defines, identifies or archives gene profiles with temporal-specific expression patterns. Here, using a high-throughput regression analysis approach, eight linear and nonlinear parametric models were fitted to gene expression profiles from time-series experiments to identify eight types of gene profiles with temporal-specific expression patterns. We curated 2684 time-series transcriptome datasets and identified 2644,370 gene profiles exhibiting temporal-specific expression patterns. The results were stored in the database GeTeSEPdb (gene profiles with temporal-specific expression patterns database, http://www.inbirg.com/GeTeSEPdb/). Moreover, we implemented an online tool to identify gene profiles with temporal-specific expression patterns from user-submitted data. In summary, GeTeSEPdb is a comprehensive web service that can be used to identify and analyse gene profiles with temporal-specific expression patterns. This approach facilitates the exploration of transcriptional changes and temporal patterns of responses. We firmly believe that GeTeSEPdb will become a valuable resource for biologists and bioinformaticians.

ABCB1-mediated docetaxel resistance reversed by erastin in prostate cancer.

Docetaxel (Doc) currently serves as the primary first-line treatment for patients with castrate-resistant prostate cancer (CRPC). Erastin, a small molecule compound, can trigger inhibition of the cystine-glutamate reverse transport system and other pathways, leading to iron-dependent cell death (ferroptosis). Beyond its role in inducing cancer cell death, erastin demonstrates potential when combined with chemotherapy drugs to heighten cancer cell drug susceptibility. However, the augmentation by erastin of the effects of Doc treatment on prostate cancer, and the underlying mechanisms involved, remain unclear. In the present study, we determined the role and the underlying molecular mechanism of erastin against CRPC. The results showed that CRPC cell lines were resistant to Doc, and the expression of ferroptosis-related factors in drug-resistant cell lines was downregulated. Erastin, in synergy with Doc, exerts a pro-apoptotic effect. Erastin significantly inhibited the activity of ATP-binding cassette subfamily B member 1 (ABCB1) but did not change its protein expression and localization. Finally, in mice, erastin treatment dramatically reduced tumor growth in vivo. Taken together, our findings demonstrate that erastin enhances Doc-induced apoptosis to a certain extent and reverses Doc resistance in prostate cancer by inhibiting the activity of multidrug-resistant protein ABCB1.

PertOrg 1.0: a comprehensive resource of multilevel alterations induced in model organisms by in vivo genetic perturbation.

Genetically modified organisms (GMOs) can be generated to model human genetic disease or plant disease resistance, and they have contributed to the exploration and understanding of gene function, physiology, disease onset and drug target discovery. Here, PertOrg (http://www.inbirg.com/pertorg/) was introduced to provide multilevel alterations in GMOs. Raw data of 58 707 transcriptome profiles and associated information, such as phenotypic alterations, were collected and curated from studies involving in vivo genetic perturbation (e.g. knockdown, knockout and overexpression) in eight model organisms, including mouse, rat and zebrafish. The transcriptome profiles from before and after perturbation were organized into 10 116 comparison datasets, including 122 single-cell RNA-seq datasets. The raw data were checked and analysed using widely accepted and standardized pipelines to identify differentially expressed genes (DEGs) in perturbed organisms. As a result, 8 644 148 DEGs were identified and deposited as signatures of gene perturbations. Downstream functional enrichment analysis, cell type analysis and phenotypic alterations were also provided when available. Multiple search methods and analytical tools were created and implemented. Furthermore, case studies were presented to demonstrate how users can utilize the database. PertOrg 1.0 will be a valuable resource aiding in the exploration of gene functions, biological processes and disease models.

OrganoidDB: a comprehensive organoid database for the multi-perspective exploration of bulk and single-cell transcriptomic profiles of organoids.

Organoids, three-dimensional in vitro tissue cultures derived from pluripotent (embryonic or induced) or adult stem cells, are promising models for the study of human processes and structures, disease onset and preclinical drug development. An increasing amount of omics data has been generated for organoid studies. Here, we introduce OrganoidDB (http://www.inbirg.com/organoid_db/), a comprehensive resource for the multi-perspective exploration of the transcriptomes of organoids. The current release of OrganoidDB includes curated bulk and single-cell transcriptome profiles of 16 218 organoid samples from both human and mouse. Other types of samples, such as primary tissue and cell line samples, are also integrated to enable comparisons with organoids. OrganoidDB enables queries of gene expression under different modes, e.g. across different organoid types, between different organoids from different sources or protocols, between organoids and other sample types, across different development stages, and via correlation analysis. Datasets and organoid samples can also be browsed for detailed information, including organoid information, differentially expressed genes, enriched pathways and single-cell clustering. OrganoidDB will facilitate a better understanding of organoids and help improve organoid culture protocols to yield organoids that are highly similar to living organs in terms of composition, architecture and function.

The genomic architectures of tumour-adjacent tissues, plasma and saliva reveal evolutionary underpinnings of relapse in head and neck squamous cell carcinoma.

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) is characterised by a dismal prognosis; nonetheless, limited studies have unveiled the mechanisms underlying HNSCC relapse. METHODS: Next-generation sequencing was performed to identify the somatic mutations in 188 matched samples, including primary tumours, tumour-adjacent tissues (TATs), pre- and post-operative plasma, saliva and peripheral blood lymphocytes (PBLs) from 27 patients. The evolutionary relationship between TATs and tumours were analysed. The dynamic changes of tumour- and TAT-specific mutations in liquid biopsies were monitored together with survival analysis. RESULTS: Alterations were detected in 27 out of 27 and 19 out of 26 tumours and TATs, respectively. TP53 was the most prevalently mutated gene in TATs. Some TATs shared mutations with primary tumours, while some other TATs were evolutionarily unrelated to tumours. Notably, TP53 mutations in TATs are stringently associated with premalignant transformation and are indicative of worse survival (hazard ratio = 14.01). TAT-specific mutations were also detected in pre- and/or post-operative liquid biopsies and were indicative of disease relapse. CONCLUSIONS: TATs might undergo the processes of premalignant transformation, tumorigenesis and eventually relapse by either inheriting tumorigenic mutations from ancestral clones where the tumour originated or gaining private mutations independent of primary tumours. Detection of tumour- and/or TAT-specific genetic alterations in post-operative biopsies shows profound potential in prognostic use.