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A core transcriptional regulatory circuitry controls super-enhancer-driven activation of LGR5 in colorectal cancer: RNA-seq

GSE292302 Homo sapiens (human) RNA-seq (gene expression) 42 samples Submitted 2026/05/17 Platform GPL28038Platform GPL28457
At a glance

RNA-seq (gene expression) · human · 42 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
42 samples: 15 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)
The core transcriptional regulatory program governed by a small set of master transcription factors is pivotal for establishing context-specific cellular features, as has been elegantly illustrated in embryonic stem cells. Here, we reported an uncharted role of master transcription factor MYC in actively regulating cancer-type specific super-enhancer (SE) activity, and identified a core transcriptional regulatory circuitry consisting of MYC, ETS2, and FOXP1 in colorectal cancer (CRC).
Read the full summary ↓
MYC/ETS2/FOXP1 bound to their own SEs and the SEs of other circuitry factors, thereby rapidly amplifying transcriptional effects upon activation. The majority of SEs were co-occupied by all three circuitry factors, and acute perturbation of the circuitry factors severely and selectively repressed a series of SE-controlled genes. Furthermore, there was functional inter-dependency between the circuitry and BRD4 in regulating SE-driven transcription, and targeting the circuitry factors sensitized CRC cells to BET inhibition. Notably, the key stemness gene LGR5 was activated by a circuitry-controlled distal SE in CRC, which was one of the most significantly gained tumor-specific SEs and was required for establishing CRC liver metastases. Lgr5 transcription in intestinal stem cells (ISCs) was likewise sustained by a Myc-regulated SE. Depletion of Myc in murine ISCs led to shrink of Lgr5-positive cell population, and impaired the renewal capacity of ISCs and intestinal epithelium integrity. Collectively, our study unveiled a core transcriptional regulatory module in CRC, advanced current understanding of MYC in transcription regulation, and provided mechanistic explanation for LGR5 overexpression in cancer. These findings may pave the way for precisely targeting detrimental transcription events in CRC therapy.
This dataset
Open GSE292302 in finder → Find more 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 GSE292302_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 PRJNA1237849 and SRA study SRP571360. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
15 conditions, mostly in triplicate
HT29_ETS2_AID_Ctrl ×3 HT29_ETS2_AID_IAA ×3 Myc_fl_fl_Lgr5_Cre_Vehicle ×3 Myc_fl_fl_Lgr5_Cre_TAM ×3 HT29_MYC_AID_Ctrl ×3 HT29_MYC_AID_IAA ×3 LoVo_MYC_AID_Ctrl ×3 LoVo_MYC_AID_IAA ×3 +7 more

Supports a between-group comparison across 42 samples.

How we read this: 15 replicated groups read from 42 sample titles; they account for 42 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

+ 2 more — browse all 42 samples with per-sample file links →

More Colorectal cancer datasets

Search all RNA-seq datasets in GEO →

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