← BioTransfer GEO Dataset Finder
GEO series

ZFP36L2 orchestrates stress-adaptive plasticity in intestinal regeneration and colorectal cancer metastasis

GSE336781 Homo sapiens (human) RNA-seq (gene expression) 93 samples Submitted 2026/07/20 Platform GPL34284Platform GPL34281Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 93 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
93 samples: 32 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.
Summary (written by the submitters)
Phenotypic plasticity is a hallmark of cancer, yet the molecular switches required for cell fate reprogramming are poorly understood. During intestinal wound healing and colorectal cancer (CRC) metastasis, differentiated cells can dynamically dedifferentiate into an intestinal stem cell (ISC) state to drive epithelial regeneration and metastatic outgrowth.
Read the full summary ↓
Here we show that the RNA-binding protein ZFP36L2, which is mutated in 5-10% of CRC, is a critical stress-responsive orchestrator of dynamic dedifferentiation into an LGR5+ ISC state. In mouse colon regeneration models, ZFP36L2 ablation inhibits dedifferentiation, ISC gene expression and function, and impairs intestinal regeneration. In human CRC, loss of ZFP36L2 function abrogates metastatic seeding and the outgrowth of LGR5+ canonical metastases, while promoting lineage plasticity and non-canonical differentiation into heterogeneous cell states. Mechanistically, we find that ZFP36L2 binds to stress-associated mRNAs containing AU-rich 3' UTRs, inducing the formation of dynamic biomolecular condensates associated with mRNA degradation and termination of the stress response. Together, this work defines ZFP36L2 acts as a critical molecular switch coupling stress sensing with phenotypic plasticity, driving cellular dedifferentiation essential for re-establishing the ISC state during wound healing and metastasis. In ZFP36L2 deficient CRC, inability to re-enter the LGR5+ state during metastatic outgrowth drives non-canonical lineage plasticity, associated with poor clinical outcomes. This SuperSeries is composed of the SubSeries listed below.
This dataset
Open GSE336781 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 GSE336781_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 PRJNA1482592 and SRA study SRP711985. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
32 conditions, mostly in triplicate
MSK107Li PDO cells, shCtrl, no ActD, ×3 MSK107Li PDO cells, shCtrl, 5h ActD, ×3 MSK107Li PDO cells, shZFP36L2, no ActD, ×3 MSK107Li PDO cells, shZFP36L2, 5h ActD, ×3 OKG146Li PDO cells, shCtrl, no ActD, ×3 OKG146Li PDO cells, shCtrl, 5h ActD, ×3 OKG146Li PDO cells, shZFP36L2, no ActD, ×3 OKG146Li PDO cells, shZFP36L2, 5h ActD, ×3 +30 more

Supports a between-group comparison across 87 samples.

How we read this: 32 replicated groups read from 93 sample titles; they account for 87 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

+ 53 more — browse all 93 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.