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RNA-seq of lungs from SCID mice pre-treated with EVs from Tsc1-null or wild-type E15.5 neural progenitors prior to ELT3 cell injection

GSE307366 Mus musculus Expression profiling by high throughput sequencing 6 samples Submitted 2025/09/05 Platform GPL21103
Summary
Pulmonary lymphangioleiomyomatosis (LAM) is a rare metastatic sarcoma characterized by the abnormal proliferation and dissemination of TSC1/TSC2-null smooth muscle-like cells. While extracellular vesicles (EVs) are known to regulate cancer metastasis, their roles in LAM have not been fully elucidated. Here, we identify distinct LAM-EV subtypes derived from primary tumor or metastasizing LAM cells that promote metastasis via ITGα6/β1–c-Src–FAK signaling. These EVs enhance LAM cell migration, invasion, and stemness by either shuttling ATP synthesis to cell pseudopodia or activating integrin adhesion complexes. In vivo, CD9⁺CD63⁺CD81⁺ EVs isolated from Tsc1-null or wild-type E15.5 mouse embryonic neural progenitors were labeled and injected intravenously into SCID mice, followed 48 hours later by intravenous injection of 0.5×10⁶ ELT3 cells, a well-characterized LAM model. Lungs were harvested 72 hours post-injection for RNA-seq analyses. Lungs from Tsc1-null EV-treated mice showed increased metastatic burden (rat DNA content) and differential expression of 815 genes (522 upregulated, 293 downregulated) compared to wild-type EV-injected mice. Reactome analysis revealed enrichment in extracellular matrix remodeling, collagen biosynthesis, and the assembly of multimeric structures. These findings establish EVs as key mediators of LAM metastasis and identify them as potential therapeutic targets.
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Direct links to NCBI, no account and no request form: the whole study as GSE307366_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 PRJNA1316871 and SRA study SRP617624. Searching any of these in the dataset finder brings you back here.

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