The evolution and heterogeneity of lethal metastatic bladder cancer subtypes
RNA-seq (gene expression) · human · 89 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
- 89 samples: 87 distinct titles, 2 of them repeatedGroups 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.
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 GSE302273_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 PRJNA1289766 and SRA study SRP593000. Searching any of these in the dataset finder brings you back here.
How we read this: Read from 89 sample titles: 87 distinct titles with little repetition. 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.
- GSM9055505 Primary 16-079
- GSM9055507 Primary 17-020
- GSM9055508 Primary 17-026
- GSM9055510 Primary 18-016
- GSM9055511 Metastatic 18-101
- GSM9055514 Primary 19-004
- GSM9055515 Primary 19-007
- GSM9084429 15-108H1_Liver1
- GSM9084430 15-108J1_Liver2
- GSM9084431 15-108K6_Lung-1
- GSM9084432 15-108L5_Lung2
- GSM9084433 15-109DD_Bone
- GSM9084434 15-109G5_Liver1
- GSM9084435 15-109H8_Liver2
- GSM9084436 15-109I9_Liver3
- GSM9084437 16-070H7_Liver1
- GSM9084438 16-070I4_Liver-2
- GSM9084439 16-070M6_LN1
- GSM9084440 16-070P2_LN2
- GSM9084441 16-079FF_Bone
- GSM9084442 16-079G2_Liver1
- GSM9084443 16-079H1_Liver2
- GSM9084444 16-079M3_LN1
- GSM9084445 16-079N3_LN2
- GSM9084446 16-097AA_Bone
- GSM9084447 16-097G2_Lung1
- GSM9084448 16-097H2_Lung2
- GSM9084449 16-097J4_Liver1
- GSM9084450 16-097K2_Liver2
- GSM9084451 17-020H4_Lung
- GSM9084452 17-020K1_Pleura
- GSM9084453 17-026H2_Omentum1
- GSM9084454 17-026I1_Liver
- GSM9084455 17-026J3_Omentum2
- GSM9084456 17-026N2_Small-bowel
- GSM9084457 17-030G1_Liver
- GSM9084458 17-030H1_Adrenal
- GSM9084459 17-030I1_L-ab-wall-met
- GSM9084460 17-030L1_Pericolonic-met
- GSM9084461 17-047G5_Lung-LN
+ 49 more — browse all 89 samples with per-sample file links →
- 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.