GEO series

Transcriptional profiling of 22Rv1 cells upon treatments of RBN-2397 and tapinarof

GSE269640 Homo sapiens (human) RNA-seq (gene expression) 10 samples Submitted 2025/05/22 Platform GPL29480

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)
Samples: 10 samples
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: PARP7 Inhibitors and AHR Agonists Act Synergistically across a Wide Range of Cancer ModelsMolecular cancer therapeutics · 2025

Summary (written by the submitters)

Small molecule inhibitors of the mono (ADP) ribosyl transferase PARP7 are being evaluated therapeutically as a monotherapy for tumors overexpressing PARP7 and in combination with immune checkpoint inhibitors. We previously showed that sensitivity to the PARP7 inhibitor (PARP7i) RBN-2397 could be enhanced by co-treatment with agonists of the aryl hydrocarbon receptor (AHRa) in cell lines that show strong intrinsic sensitivity to RBN-2397.

Read the full summary ↓

Here we demonstrate that a range of tumor cell lines that are relatively insensitive to PARP7i or AHRa as individual agents are profoundly sensitive to the combination. Our data show that this synergistic response is dependent on AHR/ARNT and is associated with increased levels of nuclear AHR and increased transcription of AHR target genes. In some hormone-dependent cell lines, we find that combination treatment is associated with proteasomal turnover of the steroid hormone receptors, androgen receptor (AR) and estrogen receptor (ER). Both wildtype and therapy-resistant mutant forms of these receptors are degraded upon treatment with AHRa and PARP7i in breast and prostate cancer models. These results suggest that combining PARP7i with AHRa may extend the utility of these drugs to a wider range of tumors, including those that are refractory to hormone therapy.

Published in

PARP7 Inhibitors and AHR Agonists Act Synergistically across a Wide Range of Cancer Models

Chen H, Gou X, Mao Y et al. · Molecular cancer therapeutics 2025 · PMID 39313957 · doi:10.1158/1535-7163.MCT-24-0211

This dataset

Open GSE269640 in finder → Find more human RNA-seq datasets →

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 GSE269640_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 PRJNA1122860 and SRA study SRP513295. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39313957) ↗

Samples in this study

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+ 10 more — browse all 10 samples with per-sample file links →

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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.