Enhancing PARP inhibitor treatment efficacy for urothelial carcinoma by new biomarkers and synergistic combination treatment with bromodomain protein inhibitor PLX51107
RNA-seq (gene expression) · human · 36 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
- 36 samples: 12 conditions, mostly in triplicateGroups 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
- Improving PARP inhibitor efficacy in bladder cancer without genetic BRCAness by combination with PLX51107Molecular oncology · 2026
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 GSE285648_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 PRJNA1205370 and SRA study SRP554792. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 36 samples.
How we read this: 12 replicated groups read from 36 sample titles; they account for 36 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.
- GSM8706312 T24_DMSO_2 T24_DMSO
- GSM8706313 T24_DMSO_3 T24_DMSO
- GSM8706314 T24_DMSO_4 T24_DMSO
- GSM8706315 T24_Talazoparib_1 T24_Talazoparib
- GSM8706316 T24_Talazoparib_2 T24_Talazoparib
- GSM8706317 T24_Talazoparib_4 T24_Talazoparib
- GSM8706318 T24_Olaparib_1 T24_Olaparib
- GSM8706319 T24_Olaparib_2 T24_Olaparib
- GSM8706320 T24_Olaparib_3 T24_Olaparib
- GSM8706321 T24LTT_DMSO_2 T24LTT_DMSO
- GSM8706322 T24LTT_DMSO_3 T24LTT_DMSO
- GSM8706323 T24LTT_DMSO_4 T24LTT_DMSO
- GSM8706324 T24LTT_Tala_1 T24LTT_Tala
- GSM8706325 T24LTT_Tala_3 T24LTT_Tala
- GSM8706326 T24LTT_Tala_4 T24LTT_Tala
- GSM8706327 T24LTT_Olaparib_1 T24LTT_Olaparib
- GSM8706328 T24LTT_Olaparib_3 T24LTT_Olaparib
- GSM8706329 T24LTT_Olaparib_4 T24LTT_Olaparib
- GSM8706330 J82_DMSO_1 J82_DMSO
- GSM8706331 J82_DMSO_3 J82_DMSO
- GSM8706332 J82_DMSO_4 J82_DMSO
- GSM8706333 J82_Tala_2 J82_Tala
- GSM8706334 J82_Tala_3 J82_Tala
- GSM8706335 J82_Tala_4 J82_Tala
- GSM8706336 J82LTT_DMSO_1 J82LTT_DMSO
- GSM8706337 J82LTT_DMSO_2 J82LTT_DMSO
- GSM8706338 J82LTT_DMSO_4 J82LTT_DMSO
- GSM8706339 J82LTT_Talazoparib_2 J82LTT_Talazoparib
- GSM8706340 J82LTT_Talazoparib_3 J82LTT_Talazoparib
- GSM8706341 J82LTT_Talazoparib_4 J82LTT_Talazoparib
- GSM8706342 RT112_DMSO_1 RT112_DMSO
- GSM8706343 RT112_DMSO_2 RT112_DMSO
- GSM8706344 RT112_DMSO_4 RT112_DMSO
- GSM8706345 RT112_Talazoparib_1 RT112_Talazoparib
- GSM8706346 RT112_Talazoparib_3 RT112_Talazoparib
- GSM8706347 RT112_Talazoparib_4 RT112_Talazoparib
- GSE172359 Combination of urine exosomal mRNAs and lncRNAs as novel diagnostic biomarkers for bladder cancer 6 samples same disease briefing · shares combination, biomarkers
- GSE217413 Cisplatin resistance driver gene CLSPN product is a target for immunotherapy in urothelial carcinoma. 4 samples same disease briefing · shares urothelial
- GSE176493 Comprehensive target engagement by EZH2 inhibitor CPI-0209 allows for preferential targeting of ARID1A mutant urothelial carcinoma 252 samples same disease briefing · shares urothelial
- GSE181389 Transcriptome profiling of HOXA13 and HOXB13 expression knockdown in bladder cancer cell lines. 59 samples same disease briefing
- GSE193755 Human bladder cancer cell line high throughput sequencing - genes regulated by hMSH2 12 samples same disease briefing
- GSE214886 Downregulation of CBX7 induced by EZH2 upregulates FGFR3 expression to reduce sensitivity to cisplatin in bladder cancer 12 samples same disease briefing
- 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
- GSE182310 Transcriptome sequence of Human bladder cancer cell line 6 samples same disease briefing
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.