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Inhibition of DUSP18 impairs cholesterol biosynthesis and promotes anti-tumor immunity in colorectal cancer

GSE264145 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2024/06/21 Platform GPL24676Platform GPL24247
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 × HCT116 cells, shCt vs 3 × HCT116 cells, shDusp18 vs 3 × MC38 cells, shCt vs 3 × MC38 cells, shdusp18Groups 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 DUSP18 impairs cholesterol biosynthesis and promotes anti-tumor immunity in colorectal cancerNature communications · 2024
Summary (written by the submitters)
We discovered, through mining TCGA data and conducting CRISPR screens, that DUSP18 expression within tumor cells significantly influences the immune microenvironment of colorectal cancer.To explore the role of DUSP18 in regulating the immune microenvironment of colorectal cancer (CRC), we established MC38 and HCT116 cell lines with targeted gene knockdown via shRNA and performed RNA-Seq.
Published in
Inhibition of DUSP18 impairs cholesterol biosynthesis and promotes anti-tumor immunity in colorectal cancer
Zhou X, Wang G, Tian C et al. · Nature communications 2024 · PMID 38992029 · doi:10.1038/s41467-024-50138-x
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 GSE264145_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 PRJNA1101055 and SRA study SRP502141. Searching any of these in the dataset finder brings you back here.

Study design
3 × HCT116 cells, shCt vs 3 × HCT116 cells, shDusp18 vs 3 × MC38 cells, shCt vs 3 × MC38 cells, shdusp18

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
More Colorectal cancer datasets

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