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Gene expression changes associated with acquired resistance to anti-EGFR therapy (cetuximab) in colorectal cancer cells

GSE262796 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2024/07/02 Platform GPL30173
At a glance

RNA-seq (gene expression) · human · 18 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
18 samples: 18 samples, each with a distinct title — no replicated groupsGroups 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)
Despite the implementation of personalized medicine, patients with metastatic CRC (mCRC) still have a dismal overall survival due to the frequent occurrence of acquired resistance mechanisms thereby leading to clinical relapse. Understanding molecular mechanisms that support acquired resistance to anti-EGFR targeted therapy in mCRC is therefore clinically relevant and key to improving patient outcomes.
Read the full summary ↓
Here, we observe distinct metabolic changes between cetuximab-resistant CRC cell populations, with in particular an increased glycolytic activity in KRAS-mutant cetuximab-resistant LIM1215 but not in KRAS-amplified resistant DiFi cells. We show that cetuximab-resistant LIM1215 cells have the capacity to recycle glycolysis-derived lactate to sustain their growth capacity. This is associated with an upregulation of the lactate importer MCT1 at both transcript and protein levels. Pharmacological inhibition of MCT1, with AR-C155858, reduces the uptake and oxidation of lactate and impairs growth capacity in cetuximab-resistant LIM1215 cells. This study identifies MCT1-dependent lactate utilization as a clinically actionable, metabolic vulnerability to overcome KRAS-mutant-mediated acquired resistance to anti-EGFR therapy in CRC.
This dataset
Open GSE262796 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 GSE262796_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 PRJNA1093402 and SRA study SRP498671. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
18 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 18 sample titles: 18 distinct titles with little repetition. 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
More Colorectal cancer datasets

Search all human RNA-seq datasets in GEO →

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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.