← BioTransfer GEO Dataset Finder
GEO series

Prospective derivation of a 'Living Organoid Biobank' of colorectal cancer patients

GSE65253 Homo sapiens (human) RNA-seq (gene expression) 108 samples Submitted 2015/05/07 Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 108 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
Colorectal cancerThis series is part of our curated briefing on it.
Samples
108 samples: 12 conditions, mostly with about 7 replicates eachGroups 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)
In Rspondin-based three-dimensional cultures, Lgr5 stem cells from multiple organs form ever-expanding epithelial organoids that retain their tissue identity. Here we report the establishment of tumor organoid cultures from 20 consecutive colorectal carcinoma (CRC) patients. For most, organoids were also generated from adjacent normal tissue.
Read the full summary ↓
Organoids closely resemble the original tumor. The spectrum of genetic changes within the 'living biobank' agrees well with previous large-scale mutational analyses of CRC. Gene expression analysis indicates that the major CRC molecular subtypes are represented. Tumor organoids are amenable to high-throughput drug screens allowing detection of gene-drug associations. As an example, a single organoid culture was exquisitely sensitive to Wnt secretion (porcupine) inhibitors and carried a mutation in the negative Wnt feedback regulator RNF43, rather than in APC. Organoid technology may fill the gap between cancer genetics and patient trials, complement cell line- and xenograft-based drug studies and allow personalized therapy design.
This dataset
Open GSE65253 in finder → Find more human RNA-seq datasets → Colorectal cancer landscape →
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.

Series matrix ↓
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 GSE65253_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
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.

Raw reads on ENA ↗

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 PRJNA273501 and SRA study SRP052795. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 25957691) ↗
Study design
12 conditions, mostly with about 7 replicates each
Organoid 1 derived from patient ×7 Organoid 10 derived from patient ×7 Organoid 11 derived from patient ×7 Organoid 12 derived from patient ×7 Organoid 2 derived from patient ×7 Organoid 3 derived from patient ×7 Organoid 4 derived from patient ×7 Organoid 5 derived from patient ×7 +28 more

Supports a between-group comparison across 84 samples.

How we read this: 12 replicated groups read from 108 sample titles; they account for 84 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

+ 68 more — browse all 108 samples with per-sample file links →

More Colorectal cancer datasets

Search all human RNA-seq datasets in GEO →

Share this dataset

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.