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RNA-seq of RET-aberrant cancer cell lines treated with RET-TKI selpercatinib

GSE261830 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2024/09/30 Platform GPL24676
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)
Samples
12 samples: 3 × LC-2/ad cells, parent cells # vs 3 × LC-2/ad cells, treated with selpercatinib for 48 h # vs 3 × TPC-1 cells, parent cells # vs 3 × TPC-1 cells, treated with selpercatinib for 48 h #Groups 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
YAP Regulates HER3 Signaling-Driven Adaptive Resistance to RET Inhibitors in RET-Aberrant CancersClinical cancer research : an official journal of the American Association for Cancer Research · 2025
Summary (written by the submitters)
RET-aberrant cancer discovered as a relevant targetable oncogene in several types of tumors, whose inhibitors have marked efficacy. However, some of patients with RET-aberrant cancer are insensitive to RET- tyrosine kinase inhibitors (TKIs) and are clinically non-responders. Recently, drug-tolerant mechanisms have been gaining attention as targets for initial therapies aimed at overcoming drug resistance.
Read the full summary ↓
However, the underlying mechanisms of drug-tolerant cells emergence treated with RET-TKIs derived from RET-aberrant cancer cells remains unknown. In this study, HER3 signal activity through YAP1 was led to maintaining cell survival and inducing the emergence of cells tolerant to RET-TKIs selpercatinib and pralsetinib in high YAP1 expressed RET- rearranged cancer cells. These results suggested that YAP1-HER3 axis plays pivotal roles for cell survival under an exposure with RET-TKIs in the intrinsic resistance to RET-TKIs and the emergence of tolerant cells by RET-TKIs in YAP1 expressed RET-aberrant cancer, suggesting that YAP1/HER3 inhibition and RET-TKIs is a highly potent combination for initial treatment.
Published in
YAP Regulates HER3 Signaling-Driven Adaptive Resistance to RET Inhibitors in RET-Aberrant Cancers
Katayama Y, Yamada T, Tanimura K et al. · Clinical cancer research : an official journal of the American Association for Cancer Research 2025 · PMID 39495173 · doi:10.1158/1078-0432.CCR-24-1762
This dataset
Open GSE261830 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 GSE261830_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 PRJNA1089177 and SRA study SRP496165. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39495173) ↗
Study design
3 × LC-2/ad cells, parent cells # vs 3 × LC-2/ad cells, treated with selpercatinib for 48 h # vs 3 × TPC-1 cells, parent cells # vs 3 × TPC-1 cells, treated with selpercatinib for 48 h #

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
Datasets on a similar topic

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