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Abrogation of Oncogenic RAS Signaling by a RAS(ON) Inhibitor Doublet Primes Immune-refractory KRASG12C-mutant NSCLC for Immune Checkpoint Blockade

GSE315010 Homo sapiens (human) RNA-seq (gene expression) 44 samples Submitted 2025/12/29 Platform GPL24247Platform GPL34281
At a glance

RNA-seq (gene expression) · human · 44 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
44 samples: 12 conditions, mostly in triplicateGroups 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)
To address RAS pathway hyperactivation and targeted therapy resistance in KRASG12C-mutant NSCLC, we evaluated the potential of the RAS(ON) G12C-selective covalent inhibitor elironrasib and the RAS(ON) multi-selective inhibitor daraxonrasib combination to maximize RAS pathway suppression and forestall pathway reactivation in a series of preclinical models.
Read the full summary ↓
We demonstrate that the RAS(ON) inhibitor doublet induces profound and sustained tumor regressions and overcomes the increased RAS pathway oncogenic flux that underlies resistance to inactive state–selective KRASG12C inhibitors in NSCLC. Additionally, in immune-competent preclinical models, the RAS(ON) inhibitor doublet enhances tumor immune recognition by boosting antigen presentation and remodeling the suppressive tumor microenvironment, thus promoting immune-dependent complete regressions and sensitization of an immuno-refractory model to checkpoint blockade. Collectively these findings provide a preclinical rationale for the evaluation of a targeted RAS(ON) inhibitor doublet therapy regimen in combination with immune checkpoint blockade in patients with KRASG12C-mutant NSCLC.
This dataset
Open GSE315010 in finder → Find more 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 GSE315010_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 PRJNA1394784 and SRA study SRP658362. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
12 conditions, mostly in triplicate
e3LL_vehicle_8day ×5 e3LL_RMC-6291_8day ×5 e3LL_RMC-6236_8day ×5 e3LL_RMC-6291+RMC-6236_8day ×5 NCI-H2122_vehicle_24hour ×3 NCI-H2122_vehicle_8hour ×3 NCI-H2122_RMC-6291_24hour ×3 NCI-H2122_RMC-6291_8hour ×3 +4 more

Supports a between-group comparison across 44 samples.

How we read this: 12 replicated groups read from 44 sample titles; they account for 44 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

+ 4 more — browse all 44 samples with per-sample file links →

More Lung cancer datasets

Search all 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.