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Loss of Spindly sensitizes EML4-ALK v3 lung cancer cells to HSP90 inhibitors

GSE197655 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2025/02/01 Platform GPL23227
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
Lung 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.
Summary (written by the submitters)
Heat Shock Protein 90 inhibitors (HSP90i) have shown encouraging activity in EML4-ALK+ non-small cell lung cancer (NSCLC) patients but clinical responses have been heterogeneous. It has been suggested that distinct EML4-ALK variants may have a differential impact on the response to HSP90 inhibition. Here, we show that NSCLC cells harboring the most common EML4-ALK variant 1 (v1) or variant 3 (v3) are similarly sensitive to HSP90i.
Read the full summary ↓
To discover new genetic alterations that could be involved in stratifying sensitivity, we performed a genome-wide CRISPR/Cas9 knockout screen and found that loss of Spindly increases the sensitivity of EML4-ALK v3, but not v1, NSCLC cells to low concentrations of HSP90i from three distinct chemical families. Upon loss of Spindly, prolonged exposure to low concentrations of HSP90i impairs chromosome congression and cellular fitness. Collectively, our data suggest that mutations leading to loss of Spindly in EML4-ALK v3 NSCLC patients may increase sensitivity to low doses of HSP90i.
This dataset
Open GSE197655 in finder → Find more human RNA-seq datasets → Lung 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 GSE197655_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 PRJNA811500 and SRA study SRP361997. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly with about 4 replicates each
DMSO/NTC-sgRNA # ×4 DMSO/SPDL1-sgRNA1 # ×4 DMSO/SPDL1-sgRNA2 # ×4 17-AAG/NTC-sgRNA # ×4 17-AAG/SPDL1-sgRNA1 # ×4 17-AAG/SPDL1-sgRNA2 # ×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 Lung 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.