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Connectivity Mapping-based Identification and Pre-clinical Evaluation of ISOX: A Novel Therapeutic for Pancreatic Cancer

GSE240597 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2024/03/13 Platform GPL20301
At a glance

RNA-seq (gene expression) · human · 24 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
Pancreatic cancerThis series is part of our curated briefing on it.
Samples
24 samples: 6 conditions, mostly with about 4 replicates eachGroups 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
Connectivity mapping-based identification of pharmacological inhibitor targeting HDAC6 in aggressive pancreatic ductal adenocarcinomaNPJ precision oncology · 2024
Summary (written by the submitters)
Pancreatic Cancer (PC) remains highly lethal due to limited therapeutic options. Here we utilize a genomic-data-driven Connectivity Mapping (CMAP) to identify a drug closer to real-world PC targeting. ISOX emerged as a top potential drug from the CMAP pipeline across human PC tissues, cell lines, tumoroids, and patient-derived xenografts datasets.
Read the full summary ↓
Here, we use PC cells, human and mouse tumoroids, and in vivo mouse models to test the ability of ISOX alone and in combination with 5FU to inhibit tumor growth. Transcriptomic and pathway analysis of the ISOX-LINCS signature identified the various pathways as targets for ISOX, suggesting a multiple-target action. Specifically, we discovered that genetic and pharmacological targeting of HDAC6 affected non-histone protein cMYC acetylation leading to cMYC instability, thereby disrupting PC stem cells. Finally, KrasG12D harboring organoids and mice responded effectively against ISOX and 5FU treatment by enhancing survival and controlling metastasis incidence. Overall, our data validate ISOX as a novel drug to treat advanced PC patients without toxicity to normal cells
Published in
Connectivity mapping-based identification of pharmacological inhibitor targeting HDAC6 in aggressive pancreatic ductal adenocarcinoma
Atri P, Shah A, Natarajan G et al. · NPJ precision oncology 2024 · PMID 38454151 · doi:10.1038/s41698-024-00562-5
This dataset
Open GSE240597 in finder → Find more human RNA-seq datasets → Pancreatic 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 GSE240597_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 PRJNA1004288 and SRA study SRP454515. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38454151) ↗
Study design
6 conditions, mostly with about 4 replicates each
Untreated_1 ×4 Untreated_2 ×4 Untreated_3 ×4 Treated_1 ×4 Treated_2 ×4 Treated_3 ×4

Supports a between-group comparison across 24 samples.

How we read this: 6 replicated groups read from 24 sample titles; they account for 24 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 Pancreatic cancer datasets

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