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Divergent clinical and immunologic outcomes based on STK11 co-mutation status in resectable KRAS-mutant lung cancers following neoadjuvant immune checkpoint blockade

GSE280232 Homo sapiens (human) Single-cell RNA-seq 42 samples Submitted 2024/10/24 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 42 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Topic
Lung cancerThis series is part of our curated briefing on it.
Samples
42 samples: 42 samples, each with a distinct title — no replicated groupsGroups 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
Divergent Clinical and Immunologic Outcomes Based on STK11 Co-mutation Status in Resectable KRAS-Mutant Lung Cancers Following Neoadjuvant Immune Checkpoint BlockadeClinical cancer research : an official journal of the American Association for Cancer Research · 2025
Summary (written by the submitters)
Co-mutations of the KRAS and STK11 genes in advanced non-small cell lung cancer (NSCLC) are associated with immune checkpoint blockade (ICB) resistance. While neoadjuvant chemoimmunotherapy is now a standard of care treatment for early-stage NSCLC, the clinical and immunologic impact of KRAS and STK11 co-mutations in this setting are unknown.
Read the full summary ↓
We evaluated the clinical outcomes and intratumoral T cell profiles of resected KRAS-mutant tumors treated with neoadjuvant ICB. Relative to KRASmut/STK11wt tumors, KRASmut/STK11mut exhibited significantly higher recurrence risk. Single-cell transcriptomics showed enhanced oxidative phosphorylation with evidence of decreased PGE-2 signaling and increased IL-2 signaling in CD8+ tumor-infiltrating lymphocytes (TIL) from KRASmut/STK11mut tumors, a finding that was mirrored in KRASwt tumors that relapsed. TIL from KRASmut/STK11mut tumors expressed high levels of molecules associated with tumor residence, including CD39 and ZNF683 (HOBIT). These divergent T cell transcriptional fates suggest T cell maintenance and residence may be detrimental to anti-tumor immunity in the context of neoadjuvant ICB for resectable NSCLC, regardless of KRAS mutation status. Our work provides a basis for future investigations into the mechanisms underpinning PGE-2 and IL-2 signaling as they relate to T cell immunity to cancer and to divergent clinical outcomes in KRASmut/STK11mut NSCLC treated with neoadjuvant ICB.
Published in
Divergent Clinical and Immunologic Outcomes Based on STK11 Co-mutation Status in Resectable KRAS-Mutant Lung Cancers Following Neoadjuvant Immune Checkpoint Blockade
Rosner S, Connor S, Sanber K et al. · Clinical cancer research : an official journal of the American Association for Cancer Research 2025 · PMID 39545922 · doi:10.1158/1078-0432.CCR-24-2983
This dataset
Open GSE280232 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 GSE280232_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1177414 and SRA study SRP540640. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39545922) ↗
Study design
42 samples, each with a distinct title — no replicated groups

Supports a case/control comparison: 26 samples read as cases, 16 as controls.

How we read this: Read from 42 sample titles: 42 distinct titles with little repetition. 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

+ 2 more — browse all 42 samples with per-sample file links →

More Lung cancer datasets

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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.