GEO series

Epigenetic and oncogenic inhibitors cooperatively drive differentiation and kill KRAS-mutant colorectal cancers [CRC cell lines]

GSE265926 Homo sapiens (human) RNA-seq (gene expression) 48 samples Submitted 2024/07/22 Platform GPL18573

At a glance

RNA-seq (gene expression) · human · 48 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: 48 samples: 16 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.
Paper: Epigenetic and Oncogenic Inhibitors Cooperatively Drive Differentiation and Kill KRAS-Mutant Colorectal CancersCancer discovery · 2024

Summary (written by the submitters)

Current treatments for KRAS-mutant colorectal cancers (CRCs) are often limited by cellular plasticity and rewiring responses. Here we describe a promising therapeutic strategy that simultaneously targets epigenetic and oncogenic signals. Specifically, we show that inhibitors of the histone methyltransferase, EZH2, synergize with various RAS pathway inhibitors and promote dramatic tumor regression in vivo.

Read the full summary ↓

Together these agents cooperatively suppress WNT-driven transcription and drive CRCs into a more differentiated cell state by inducing the Groucho/TLE corepressor, TLE4, along with a network of WNT pathway inhibitors and intestinal differentiation proteins. However, these agents also induce the pro-apoptotic protein BMF, which subsequently kills these more differentiated cells. Accordingly, cell death can be prevented by activating β-catenin, blocking differentiation, or by ablating BMF expression. Collectively, these studies reveal a new therapeutic approach for treating KRAS-mutant CRCs and illustrate a critical convergence of EZH2 and RAS on oncogenic WNT signals, intestinal differentiation, and apoptosis.

Published in

Epigenetic and Oncogenic Inhibitors Cooperatively Drive Differentiation and Kill KRAS-Mutant Colorectal Cancers

Loi P, Schade AE, Rodriguez CL et al. · Cancer discovery 2024 · PMID 39121480 · doi:10.1158/2159-8290.CD-23-0866

This dataset

Open GSE265926 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 GSE265926_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 PRJNA1104829 and SRA study SRP504176. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39121480) ↗

Study design

16 conditions, mostly in triplicate

LOVO, DMSO, ×3 LOVO, MEKi, ×3 LOVO, EZH2i, ×3 LOVO, COMBO, ×3 SW620, DMSO, ×3 SW620, MEKi, ×3 SW620, EZH2i, ×3 SW620, COMBO, ×3 +8 more

Supports a between-group comparison across 48 samples.

How we read this: 16 replicated groups read from 48 sample titles; they account for 48 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

GSM8232020 LOVO, DMSO, 1 LOVO, DMSO,
GSM8232021 LOVO, DMSO, 2 LOVO, DMSO,
GSM8232022 LOVO, DMSO, 3 LOVO, DMSO,
GSM8232023 LOVO, MEKi, 1 LOVO, MEKi,
GSM8232024 LOVO, MEKi, 2 LOVO, MEKi,
GSM8232025 LOVO, MEKi, 3 LOVO, MEKi,
GSM8232026 LOVO, EZH2i, 1 LOVO, EZH2i,
GSM8232027 LOVO, EZH2i, 2 LOVO, EZH2i,
GSM8232028 LOVO, EZH2i, 3 LOVO, EZH2i,
GSM8232029 LOVO, COMBO, 1 LOVO, COMBO,
GSM8232030 LOVO, COMBO, 2 LOVO, COMBO,
GSM8232031 LOVO, COMBO, 3 LOVO, COMBO,
GSM8232032 SW620, DMSO, 1 SW620, DMSO,
GSM8232033 SW620, DMSO, 2 SW620, DMSO,
GSM8232034 SW620, DMSO, 3 SW620, DMSO,
GSM8232035 SW620, MEKi, 1 SW620, MEKi,
GSM8232036 SW620, MEKi, 2 SW620, MEKi,
GSM8232037 SW620, MEKi, 3 SW620, MEKi,
GSM8232038 SW620, EZH2i, 1 SW620, EZH2i,
GSM8232039 SW620, EZH2i, 2 SW620, EZH2i,
GSM8232040 SW620, EZH2i, 3 SW620, EZH2i,
GSM8232041 SW620, COMBO, 1 SW620, COMBO,
GSM8232042 SW620, COMBO, 2 SW620, COMBO,
GSM8232043 SW620, COMBO, 3 SW620, COMBO,
GSM8232044 SKCO1, DMSO, 1 SKCO1, DMSO,
GSM8232045 SKCO1, DMSO, 2 SKCO1, DMSO,
GSM8232046 SKCO1, DMSO, 3 SKCO1, DMSO,
GSM8232047 SKCO1, MEKi, 1 SKCO1, MEKi,
GSM8232048 SKCO1, MEKi, 2 SKCO1, MEKi,
GSM8232049 SKCO1, MEKi, 3 SKCO1, MEKi,
GSM8232050 SKCO1, EZH2i, 1 SKCO1, EZH2i,
GSM8232051 SKCO1, EZH2i, 2 SKCO1, EZH2i,
GSM8232052 SKCO1, EZH2i, 3 SKCO1, EZH2i,
GSM8232053 SKCO1, COMBO, 1 SKCO1, COMBO,
GSM8232054 SKCO1, COMBO, 2 SKCO1, COMBO,
GSM8232055 SKCO1, COMBO, 3 SKCO1, COMBO,
GSM8232056 LS513, DMSO, 1 LS513, DMSO,
GSM8232057 LS513, DMSO, 2 LS513, DMSO,
GSM8232058 LS513, DMSO, 3 LS513, DMSO,
GSM8232059 LS513, KRASi, 1 LS513, KRASi,

+ 8 more — browse all 48 samples with per-sample file links →

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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.