RNA-seq of PAPRi-resistant BRCA2-deficient cancer cells
RNA-seq (gene expression) · human · 9 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)
- Samples
- 9 samples: 6 × PEO_1 vs 3 × PEO_4Groups 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
- STN1 upregulation promotes PARPi resistance in BRCA2-deficient cancer cells via replication fork protection and suppression of ssDNA gap formationbioRxiv : the preprint server for biology · 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 GSE315090_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 PRJNA1394986 and SRA study SRP658555. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 9 samples.
How we read this: 2 replicated groups read from 9 sample titles; they account for 9 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.
- GSM9421064 PEO_1_1 PEO_1
- GSM9421065 PEO_1_2 PEO_1
- GSM9421066 PEO_1_3 PEO_1
- GSM9421067 PEO_1_R_1 PEO_1
- GSM9421068 PEO_1_R_2 PEO_1
- GSM9421069 PEO_1_R_3 PEO_1
- GSM9421070 PEO_4_1 PEO_4
- GSM9421071 PEO_4_2 PEO_4
- GSM9421072 PEO_4_3 PEO_4
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- GSE294300 Single-cell gene expression profiles of cells from primary colorectal cancer and adjacent normal tissue [scRNA-Seq] 36 samples shares rna-seq
- GSE297041 Chemoradiation Reprograms Tumor Cells and Immune Microenvironment In Cervical Cancer [scRNA-seq] 18 samples shares rna-seq
- GSE270680 A spatially resolved atlas of gastric cancer characterises a lymphocyte aggregated region [scRNA-seq] 77 samples shares rna-seq
- GSE292858 RNA-Seq analysis of tumor and matched normal samples from colorectal cancer patients. 73 samples shares rna-seq
- GSE269877 Single-cell RNA-sequencing of BCG naïve and recurrent non-muscle invasive bladder cancer reveals a CD6/ALCAM-mediated immune-suppressive pathway 38 samples shares rna-seq
- GSE337246 Integrated single-cell profiling of RNA and DNA interactomes reveals targetable chromatin architectures in cancer [scRNA-Seq organoids] 35 samples shares rna-seq
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.