{"database":"GEO","file_versions":[{"headers":{"Content-Type":["application/json"]},"body":{"files":{"Other":["ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE297nnn/GSE297820/"]},"type":"primary"},"statusCode":"OK","statusCodeValue":200}],"scores":null,"additional":{"omics_type":["Transcriptomics"],"species":["Homo sapiens"],"gds_type":["Expression profiling by high throughput sequencing"],"full_dataset_link":["https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE297820"],"repository":["GEO"],"entry_type":["GSE"],"additional_accession":[]},"is_claimable":false,"name":"scRNA-seq of iPSC-derived dendritic cells under distinct differentiation and maturation protocols","description":"Dendritic cells (DCs) derived from human induced pluripotent stem cells (iPSCs) offer a promising platform for immunotherapy and disease modeling. To optimize differentiation protocols for generating functionally distinct DC subsets, we performed single-cell RNA sequencing (scRNA-seq) on iPSC-derived DCs cultured under various combinations of cytokine-driven differentiation and maturation conditions. We compared the effects of GM-CSF, IL-4, FLT3L, and different maturation cocktails including TNF-α, IL-1β, PGE2, and IFN-γ (mat2) or IFN-β (mat3). The dataset captures transcriptional profiles of cells representing both monocyte-like and migratory dendritic cell populations. These data provide a valuable resource for understanding iPSC-DC heterogeneity and guiding the development of engineered DC-based therapies.","dates":{"publication":"2026/08/25"},"accession":"GSE297820","cross_references":{"GSM":["GSM9000269","GSM9000273","GSM9000272","GSM9000271","GSM9000270"],"GPL":["34284"],"GSE":["297820"],"taxon":["Homo sapiens"]}}