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

Abstract

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.

Identification of an immune-related eRNA prognostic signature for clear cell renal cell carcinoma

“…Fan et al constructed an eRNA-related prognostic model in prostate cancer that effectively predicted patient outcomes and explored the immune characteristics of this model [ 32 ]. The similarity between our study and other model-based research lies in the fact that both involve clustering key genes, building models, and subsequently analyzing the model’s immune, mutation, and prognostic features [ 33 – 38 ]. Notably, our study extended beyond the prognosis and immune characteristics of the IREs signature; we also identified the most relevant eRNA for survival and conducted in-depth analyses of its immune and clinicopathological characteristics.…”

A systematic review on the culture methods and applications of 3D tumoroids for cancer research and personalized medicine

“…Recently, the Organoid Cell Atlas, which in addition to tumor samples and tumoroids also includes healthy organoids, was launched as a comprehensive database [291,292]. Similarly, OrganoidDB has already collected bulk and single cell transcriptomic data of more than 16.000 organoid and tumoroid models for both human and mouse samples, in addition to data generated from primary tissue and cell lines for comparison [293].…”

Industry Adoption of Organoids and Organs‐on‐Chip Technology: Toward a Paradox of Choice

“…To increase the pace of NAM adoption in industry, resources must be allocated toward model-omics data and COU assay establishment. Developers can help by publishing high dimensional datasets such as multiomic data and posting them in publicly available databases [21][22][23][24][25][26][27][28][29][30] which characterize their model ideally down to the single cell level across multiple donor cell lines. Startups and pharma can help by collaborating to run large reference compound lists through established COU assays and publishing the results.…”