Urinary extracellular vesicles for high-precision bladder cancer subtyping and prognosis
RNA-seq (gene expression) · human · 23 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
- Homo sapiens (human)
- Topic
- Bladder cancerThis series is part of our curated briefing on it.
- Samples
- 23 samples: 8 × A vs 7 × B vs 7 × P1DGroups are read from the sample names, not from the paper. Check the list below.
- 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.
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 GSE308996_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 PRJNA1333571 and SRA study SRP625767. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 22 samples.
How we read this: 3 replicated groups read from 23 sample titles; they account for 22 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.
- GSM9257883 A00L
- GSM9257884 A001 A
- GSM9257885 A004 A
- GSM9257886 A005 A
- GSM9257887 A006 A
- GSM9257888 A007 A
- GSM9257889 A008 A
- GSM9257890 A0015 A
- GSM9257891 A0016 A
- GSM9257892 B001 B
- GSM9257893 B002 B
- GSM9257894 B003 B
- GSM9257895 B004 B
- GSM9257896 B005 B
- GSM9257897 B007 B
- GSM9257898 B009 B
- GSM9257899 P1D1 P1D
- GSM9257900 P1D2 P1D
- GSM9257901 P1D3 P1D
- GSM9257902 P1D4 P1D
- GSM9257903 P1D5 P1D
- GSM9257904 P1D6 P1D
- GSM9257905 P1D8 P1D
- GSE181389 Transcriptome profiling of HOXA13 and HOXB13 expression knockdown in bladder cancer cell lines. 59 samples same disease briefing · shares bladder
- GSE193755 Human bladder cancer cell line high throughput sequencing - genes regulated by hMSH2 12 samples same disease briefing · shares bladder
- GSE214886 Downregulation of CBX7 induced by EZH2 upregulates FGFR3 expression to reduce sensitivity to cisplatin in bladder cancer 12 samples same disease briefing · shares bladder
- GSE211924 UCHL5 promotes Tumorigenesis of Bladder Cancer by Activating AKT/mTOR signaling pathway and targeting c-myc, SLC25A19, and ICAM5. 9 samples same disease briefing · shares bladder
- GSE172359 Combination of urine exosomal mRNAs and lncRNAs as novel diagnostic biomarkers for bladder cancer 6 samples same disease briefing · shares bladder
- GSE182310 Transcriptome sequence of Human bladder cancer cell line 6 samples same disease briefing · shares bladder
- GSE193753 Human bladder cancer cell line high throughput sequencing - genes regulated by hMSH2 - CDDP therapy 6 samples same disease briefing · shares bladder
- GSE193754 Human bladder cancer cell line high throughput sequencing - genes regulated by hMSH2 - untreated 6 samples same disease briefing · shares bladder
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.