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Molecular Determinants of Sotorasib Clinical Efficacy in KRAS G12C–Mutated Non–Small-Cell Lung Cancer

GSE295032 Homo sapiens (human) RNA-seq (gene expression) 234 samples Submitted 2025/06/02 Platform GPL20301
At a glance

RNA-seq (gene expression) · human · 234 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
234 samples: 234 × pre-treatment tumor RNA from individual with NSCLC_SGroups 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
Molecular determinants of sotorasib clinical efficacy in KRAS(G12C)-mutated non-small-cell lung cancerNature medicine · 2025
Summary (written by the submitters)
This study describes transcriptional subtypes of non-squamous non–small cell lung cancer (NSCLC). Baseline tissue samples (fresh/archival) were analyzed using a whole-transcriptome RNA assay (Tempus RS.v2; Tempus Labs, Inc., Chicago, IL, USA). Objectives included expression characterization of the KRAS G12C subject population with respect to genetic mutation (ATM, SMARCA4, KEAP1, STK11) and transcriptional signatures: KPCL (Skoulidis, Cancer Discov (2015) 5 (8): 860–877) & NRF2 activation (Singh, Clin Cancer Res (2021) 27 (3): 877–888).
Published in
Molecular determinants of sotorasib clinical efficacy in KRAS(G12C)-mutated non-small-cell lung cancer
Skoulidis F, Li BT, de Langen AJ et al. · Nature medicine 2025 · PMID 40437272 · doi:10.1038/s41591-025-03732-5
This dataset
Open GSE295032 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 GSE295032_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 PRJNA1252675 and SRA study SRP579666. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40437272) ↗
Study design
234 × pre-treatment tumor RNA from individual with NSCLC_S

Supports a between-group comparison across 234 samples.

How we read this: 1 replicated groups read from 234 sample titles; they account for 234 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

+ 194 more — browse all 234 samples with per-sample file links →

More Lung cancer datasets

Search all human RNA-seq datasets in GEO →

Share this dataset

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.