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Ivermectin inhibits the growth of esophageal squamous cell carcinoma by activating ATF4-mediated endoplasmic reticulum stress-autophagy pathway

GSE201404 Homo sapiens (human) RNA-seq (gene expression) 10 samples Submitted 2024/12/18 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 10 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
Esophageal cancerThis series is part of our curated briefing on it.
Samples
10 samples: 10 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.
Paper
Ivermectin inhibits the growth of ESCC by activating the ATF4-mediated endoplasmic reticulum stress-autophagy pathwayActa biochimica et biophysica Sinica · 2024
Summary (written by the submitters)
Esophageal squamous cell carcinoma (ESCC) is one of the most common form of malignancies in the world. However, there is currently a lack of effective chemotherapeutic drugs for ESCC, and it is urgent to develop new and safe drugs for this disease. Ivermectin is a broad-spectrum antiparasitic drug with demonstrable antitumor activity.
Read the full summary ↓
However, the precise cellular and molecular mechanisms of ivermectin in cancers growth inhibition remain unclear. In this study, we report a role of ivermectin in ESCC suppression by activating the endoplasmic reticulum (ER) stress and autophagy. In transcriptome analysis, we found that ATF4 and DDIT3 are involved in ER stress activation by ivermectin. Moreover, ivermectin treatment suppressed the growth of ESCC xenograft tumors in nude mice. Taken together, our results identify the antitumor molecular basis of ivermectin targeting the ER stress-autophagy pathway and suggest that ivermectin is a potential drug for the treatment of ESCC.
Published in
Ivermectin inhibits the growth of ESCC by activating the ATF4-mediated endoplasmic reticulum stress-autophagy pathway
Liu H, Chai Z, Gao Y et al. · Acta biochimica et biophysica Sinica 2024 · PMID 39574166 · doi:10.3724/abbs.2024210
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 GSE201404_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 PRJNA831453 and SRA study SRP371984. Searching any of these in the dataset finder brings you back here.

Study design
10 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 10 sample titles: 10 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 Esophageal 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.