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RNA-seq profiling of ADAM10 inhibition in DLD-1 and SW620 colorectal cancer cell lines

GSE311253 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2026/01/19 Platform GPL34281
At a glance

RNA-seq (gene expression) · human · 12 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
12 samples: 3 × DLD-1, CNT vs 3 × DLD-1, 1H5 vs 3 × SW620, CNT vs 3 × SW620, 1H5Groups 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
Inhibition of colorectal cancer progression through conformation-specific targeting of ADAM10 metalloproteaseFrontiers in oncology · 2025
Summary (written by the submitters)
This study examines the transcriptomic effects of ADAM10 inhibition in two human colorectal cancer cell lines, DLD-1 and SW620. Cells were treated with vehicle control or the conformation-specific ADAM10 monoclonal antibody 1H5 for 48 hours, followed by extraction of total RNA and paired-end RNA sequencing. The dataset enables comparative analysis of ADAM10-regulated pathways across different CRC genetic backgrounds, including alterations in Notch and EGFR signaling, metabolic gene programs, and other pathways associated with tumor progression.
Published in
Inhibition of colorectal cancer progression through conformation-specific targeting of ADAM10 metalloprotease
Mashati P, Sun D, Reino EG et al. · Frontiers in oncology 2025 · PMID 41675514 · doi:10.3389/fonc.2025.1704436
This dataset
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.

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 GSE311253_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1368855 and SRA study SRP648579. Searching any of these in the dataset finder brings you back here.

Study design
3 × DLD-1, CNT vs 3 × DLD-1, 1H5 vs 3 × SW620, CNT vs 3 × SW620, 1H5

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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
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