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In vivo transcriptome profiling of control and GANAB-KD UMUC3 bladder carcinoma cells

GSE247578 Homo sapiens (human) RNA-seq (gene expression) 11 samples Submitted 2024/12/31 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 11 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
11 samples: 4 × UMUC3 PDX,WT,7days, vs 4 × UMUC3 PDX,GANAB-KD,14days, vs 3 × UMUC3 PDX,WT,14days,Groups 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.
Summary (written by the submitters)
Carcinoma cells achieve malignant progression and therapy resistance through de-differentiation. While differentiation therapy has proven to be highly efficient in acute promyelocytic leukemia, this therapeutic strategy has not been successfully applied in human solid tumors. Here, we identify α-Glucosidase II (GANAB) as a novel driver of bladder cancer de-differentiation using a systemic biology approach and demonstrate its potential to serve as a therapeutic target of solid tumor differentiation therapy.
Read the full summary ↓
Partial knock-out of GANAB by CRISPR Cas9 differentiates one of the most aggressive bladder carcinoma line into a non-invasive papillary form in vivo and decreases chemotherapy resistance in vitro. As differentiation and de-differentiation program are mostly activated in vivo, we labelled control and GANAB-KD cells with a lentivirus to express a H2B-EGFP localized in the nuclei. After sorting by BD FACS Aria II, cells were lyzed for RNA-sequencing.
This dataset
Download · which file do I need?

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.

1 · Just have a look

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.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE247578_RAW.tar (it can run to tens of gigabytes).

3 · Start from the raw reads

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 PRJNA1039766 and SRA study SRP471542. Searching any of these in the dataset finder brings you back here.

Study design
4 × UMUC3 PDX,WT,7days, vs 4 × UMUC3 PDX,GANAB-KD,14days, vs 3 × UMUC3 PDX,WT,14days,

Supports a between-group comparison across 11 samples.

How we read this: 3 replicated groups read from 11 sample titles; they account for 11 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.

Samples in this study
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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.