<HashMap><database>GEO</database><file_versions><headers><Content-Type>application/xml</Content-Type></headers><body><files><Other>ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE297nnn/GSE297820/</Other></files><type>primary</type></body><statusCode>OK</statusCode><statusCodeValue>200</statusCodeValue></file_versions><scores/><additional><omics_type>Transcriptomics</omics_type><species>Homo sapiens</species><gds_type>Expression profiling by high throughput sequencing</gds_type><full_dataset_link>https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE297820</full_dataset_link><repository>GEO</repository><entry_type>GSE</entry_type></additional><is_claimable>false</is_claimable><name>scRNA-seq of iPSC-derived dendritic cells under distinct differentiation and maturation protocols</name><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.</description><dates><publication>2026/08/25</publication></dates><accession>GSE297820</accession><cross_references><GSM>GSM9000269</GSM><GSM>GSM9000273</GSM><GSM>GSM9000272</GSM><GSM>GSM9000271</GSM><GSM>GSM9000270</GSM><GPL>34284</GPL><GSE>297820</GSE><taxon>Homo sapiens</taxon></cross_references></HashMap>