Transcriptome profiling of HOXA13 and HOXB13 expression knockdown in bladder cancer cell lines.
RNA-seq (gene expression) · human · 59 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
- 59 samples: 59 samples, each with a distinct title — no replicated groupsGroups 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 GSE181389_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 PRJNA751872 and SRA study SRP331023. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 59 sample titles: 59 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.
- GSM5501483 HOXA13_UMUC5_24h_T1_a
- GSM5501484 HOXA13_UMUC5_24h_T1_b
- GSM5501485 HOXA13_UMUC5_24h_T2_a
- GSM5501486 HOXA13_UMUC5_24h_T2_b
- GSM5501487 HOXA13_UMUC5_24h_T2_c
- GSM5501488 HOXA13_UMUC5_24h_T3_a
- GSM5501489 HOXA13_UMUC5_24h_T3_b
- GSM5501490 HOXA13_UMUC5_24h_NC1_a
- GSM5501491 HOXA13_UMUC5_24h_NC2_a
- GSM5501492 HOXA13_UMUC5_24h_NC2_b
- GSM5501493 HOXA13_UMUC5_24h_NC3_a
- GSM5501494 HOXA13_UMUC5_48h_T1_a
- GSM5501495 HOXA13_UMUC5_48h_T2_a
- GSM5501496 HOXA13_UMUC5_48h_T2_b
- GSM5501497 HOXA13_UMUC5_48h_T3_a
- GSM5501498 HOXA13_UMUC5_48h_T3_b
- GSM5501499 HOXA13_UMUC5_48h_NC2_a
- GSM5501500 HOXA13_UMUC5_48h_NC2_b
- GSM5501501 HOXA13_UMUC5_48h_NC3_a
- GSM5501502 HOXA13_UMUC5_48h_NC3_b
- GSM5501503 HOXA13_UMUC5_48h_NC3_c
- GSM5501504 HOXB13_5637_24h_T1_a
- GSM5501505 HOXB13_5637_24h_T1_b
- GSM5501506 HOXB13_5637_24h_T2_a
- GSM5501507 HOXB13_5637_24h_T2_b
- GSM5501508 HOXB13_5637_24h_T3_a
- GSM5501509 HOXB13_5637_24h_T3_b
- GSM5501510 HOXB13_5637_24h_NC2_a
- GSM5501511 HOXB13_5637_24h_NC3_a
- GSM5501512 HOXB13_5637_72h_T1_a
- GSM5501513 HOXB13_5637_72h_T2_a
- GSM5501514 HOXB13_5637_72h_T2_b
- GSM5501515 HOXB13_5637_72h_T3_a
- GSM5501516 HOXB13_5637_72h_T3_b
- GSM5501517 HOXB13_5637_72h_NC1_a
- GSM5501518 HOXB13_5637_72h_NC1_b
- GSM5501519 HOXB13_5637_72h_NC3_a
- GSM5501520 HOXB13_5637_72h_NC3_b
- GSM5501521 HOXB13_TCCSUP_48h_T1_a
- GSM5501522 HOXB13_TCCSUP_48h_T1_b
+ 19 more — browse all 59 samples with per-sample file links →
- 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
- GSE182310 Transcriptome sequence of Human bladder cancer cell line 6 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
- 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
- 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
- GSE222567 Benchmarking pathway analysis methods offer novel prognostic cancer biomarkers and therapeutics: application in bladder cancer 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.