High-frequency recurrence index for predicting multiple recurrences in non-muscle-invasive bladder cancer (Validation cohort)
RNA-seq (gene expression) · human · 94 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
- 94 samples: 50 × NMIBC_888_URO_RNA vs 44 × NMIBC_807_URO_RNAGroups 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.
- Paper
- Transcriptome-based high-frequency recurrence index predicts frequent recurrence in non-muscle-invasive bladder cancer after Bacillus Calmette-Guérin therapyBMC 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 GSE294705_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 PRJNA1251344 and SRA study SRP578970. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 94 samples.
How we read this: 2 replicated groups read from 94 sample titles; they account for 94 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.
- GSM8917255 NMIBC_807_URO_RNA_1 NMIBC_807_URO_RNA
- GSM8917256 NMIBC_807_URO_RNA_10 NMIBC_807_URO_RNA
- GSM8917257 NMIBC_807_URO_RNA_11 NMIBC_807_URO_RNA
- GSM8917258 NMIBC_807_URO_RNA_12 NMIBC_807_URO_RNA
- GSM8917259 NMIBC_807_URO_RNA_13 NMIBC_807_URO_RNA
- GSM8917260 NMIBC_807_URO_RNA_14 NMIBC_807_URO_RNA
- GSM8917261 NMIBC_807_URO_RNA_15 NMIBC_807_URO_RNA
- GSM8917262 NMIBC_807_URO_RNA_16 NMIBC_807_URO_RNA
- GSM8917263 NMIBC_807_URO_RNA_17 NMIBC_807_URO_RNA
- GSM8917264 NMIBC_807_URO_RNA_2 NMIBC_807_URO_RNA
- GSM8917265 NMIBC_807_URO_RNA_20 NMIBC_807_URO_RNA
- GSM8917266 NMIBC_807_URO_RNA_21 NMIBC_807_URO_RNA
- GSM8917267 NMIBC_807_URO_RNA_22 NMIBC_807_URO_RNA
- GSM8917268 NMIBC_807_URO_RNA_23 NMIBC_807_URO_RNA
- GSM8917269 NMIBC_807_URO_RNA_24 NMIBC_807_URO_RNA
- GSM8917270 NMIBC_807_URO_RNA_26 NMIBC_807_URO_RNA
- GSM8917271 NMIBC_807_URO_RNA_27 NMIBC_807_URO_RNA
- GSM8917272 NMIBC_807_URO_RNA_29 NMIBC_807_URO_RNA
- GSM8917273 NMIBC_807_URO_RNA_3 NMIBC_807_URO_RNA
- GSM8917274 NMIBC_807_URO_RNA_30 NMIBC_807_URO_RNA
- GSM8917275 NMIBC_807_URO_RNA_31 NMIBC_807_URO_RNA
- GSM8917276 NMIBC_807_URO_RNA_34 NMIBC_807_URO_RNA
- GSM8917277 NMIBC_807_URO_RNA_35 NMIBC_807_URO_RNA
- GSM8917278 NMIBC_807_URO_RNA_37 NMIBC_807_URO_RNA
- GSM8917279 NMIBC_807_URO_RNA_4 NMIBC_807_URO_RNA
- GSM8917280 NMIBC_807_URO_RNA_43 NMIBC_807_URO_RNA
- GSM8917281 NMIBC_807_URO_RNA_5 NMIBC_807_URO_RNA
- GSM8917282 NMIBC_807_URO_RNA_52 NMIBC_807_URO_RNA
- GSM8917283 NMIBC_807_URO_RNA_55 NMIBC_807_URO_RNA
- GSM8917284 NMIBC_807_URO_RNA_57 NMIBC_807_URO_RNA
- GSM8917285 NMIBC_807_URO_RNA_58 NMIBC_807_URO_RNA
- GSM8917286 NMIBC_807_URO_RNA_62 NMIBC_807_URO_RNA
- GSM8917287 NMIBC_807_URO_RNA_63 NMIBC_807_URO_RNA
- GSM8917288 NMIBC_807_URO_RNA_64 NMIBC_807_URO_RNA
- GSM8917289 NMIBC_807_URO_RNA_66 NMIBC_807_URO_RNA
- GSM8917290 NMIBC_807_URO_RNA_69 NMIBC_807_URO_RNA
- GSM8917291 NMIBC_807_URO_RNA_7 NMIBC_807_URO_RNA
- GSM8917292 NMIBC_807_URO_RNA_70 NMIBC_807_URO_RNA
- GSM8917293 NMIBC_807_URO_RNA_72 NMIBC_807_URO_RNA
- GSM8917294 NMIBC_807_URO_RNA_75 NMIBC_807_URO_RNA
+ 54 more — browse all 94 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.