Rapamycin, but not propranolol, can partially revert CCM phenotype in brain endothelial cells and ameliorates chronic cavernoma development in combination with lapatinib
RNA-seq (gene expression) · mouse · 16 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Mus musculus (mouse)
- Samples
- 16 samples
- Data you can get
- A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
- Paper
- Rapamycin Partially Reverts Cavernoma Endothelial Cell Phenotype and, When Combined With Lapatinib, Ameliorates Chronic LesionsJournal of cellular and molecular medicine · 2026
Read the full summary ↓
Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.
Processed table
The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE298723_RAW.tar (it can run to tens of gigabytes).
Raw sequencing reads
The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.
What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA1271011 and SRA study SRP589448. Searching any of these in the dataset finder brings you back here.
The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.
+ 16 more — browse all 16 samples with per-sample file links →
- GSE271769 Impact of severe traumatic brain injury (TBI) on cerebral blood flow and the endothelial cell phenotype 16 samples shares endothelial, phenotype
- GSE296698 Vascular Cell Senescence and Age-Related Endothelial Dysfunction: The Role of the Senescence-Associated Secretory Phenotype and CXCL12 15 samples shares endothelial, phenotype
- GSE192687 Single-cell RNAseq analysis of renal endothelial cells in murine diabetic nephropathy 5464 samples shares endothelial
- GSE274544 Single cell profiling reveals three endothelial to hematopoietic transitions with divergent isoform expression landscapes [scRNA-Seq] 1494 samples shares endothelial
- GSE229427 Tracking spatio-temporal dynamics of the endothelial niche during fetal hematopoiesis 216 samples shares endothelial
- GSE271971 Pulmonary microvascular endothelial cells support alveolar epithelial growth via bone morphogenetic protein 6 secretion 72 samples shares endothelial
- GSE298240 Inhibition of p38 MAPK after repetitive mild TBI ameliorates immune signaling and behavioral deficit 58 samples shares ameliorates
- GSE299114 Endothelial Cells retain inflammatory memory through chromatin remodeling [RNA-Seq 2] 53 samples shares endothelial
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.