← BioTransfer GEO Dataset Finder
GEO series

Organ-on-a-chip reveals the synergistic effect of mregDC and Treg in non-small cell lung cancer

GSE307324 Homo sapiens Expression profiling by high throughput sequencing 6 samples Submitted 2025/09/11 Platform GPL29480
Summary
Since the introduction of the first lung alveolus organ-on-a-chip, organ-on-a-chip technology has evolved over 15 years and is now widely applied in disease modeling, drug development, toxicological assessment, and personalized precision medicine due to its high biomimicry, dynamic and mechanical microenvironment simulation, and multi-cellular co-culture capabilities. Here, we utilized and developed a tumor metastasis organ-on-a-chip (TMOC) model to systematically investigate how modulating mregDC-Treg interactions can alleviate T cell exhaustion and tumor metastasis. To precisely study how mregDCs shape T cell exhaustion in the NSCLC TME, our TMOC spontaneously generates a hypoxia gradient from the tumor periphery to the center, mimicking the real TME, while enabling real-time observation of fluorescently labeled tumor cells metastasizing to adjacent tissue niches via a pump-driven self-circulating blood flow system. This TMOC model is suitable for the study of tumor immune microenvironment and has potential application prospects in other tumor metastasis studies.
This dataset
Download

Direct links to NCBI, no account and no request form: the whole study as GSE307324_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 6 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA1315226 and SRA study SRP617648. Searching any of these in the dataset finder brings you back here.

Samples in this study

The sample list for this study is not cached yet. Press Sort into groups and it will be fetched from NCBI.

+ 6 more — browse all 6 samples with per-sample file links →

Similar datasets

Search all human RNA-seq datasets in GEO →

Share this dataset

Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.