GEO series

Lineage identity governs oncogene dependence in murine NSCLC models of KRAS inhibitor resistance [RNA-Seq]

GSE319597 Mus musculus (mouse) RNA-seq (gene expression) 16 samples Submitted 2026/05/09 Platform GPL34328

At a glance

RNA-seq (gene expression) · mouse · 16 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: Mus musculus (mouse)
Samples: 16 samples: 16 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.

Summary (written by the submitters)

Primary and acquired resistance to targeted therapy represent significant challenges to durable treatment responses in cancer. In lung cancer and other cancer types, allele- specific and pan-KRAS inhibitors offer new promise, but these are hampered by incomplete responses as well as genetic and non-genetic mechanisms of acquired resistance.

Read the full summary ↓

To model these mechanisms, we treat genetically engineered mouse models of KrasG12C-driven lung cancer with sotorasib, a KRASG12C inhibitor, until the emergence of drug resistance. The initial response to sotorasib was rapid, but incomplete. Residual tumor burden transcriptionally resembled the alveolar type II cell, phenocopying residual disease signatures identified in patients treated with EGFR inhibitors. After continued sotorasib treatment, we observed diverse mechanisms of drug resistance in vivo, including genetic MAPK reactivation and lineage transformation from adenocarcinoma to squamous histology. Focusing mechanistic studies on squamous transformation, we showed that expression of the basal transcription factor ∆Np63 is sufficient to rewire transformed alveolar organoids to a squamous state in vitro, conferring insensitivity to KRAS inhibition. In vivo, either ectopic expression of Sox2 or loss of Nkx2-1, which are tolerated during Kras-driven tumorigenesis, poised tumors for squamous lineage commitment upon KRAS inhibition. Squamous- transformed tumors did not exhibit evidence of KRAS/MAPK reactivation, underscoring the role for lineage transcription factors and histologic transformation in mediating oncogene independence.

This dataset

Open GSE319597 in finder → Find more mouse 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 GSE319597_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 PRJNA1417768 and SRA study SRP674210. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

16 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 16 sample titles: 16 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

GSM9520993 RNA-Seq, KP VPR organoids, transduced USEC-sg∆Np63-sgSox2, biological line replicate 1, tagmented for ATAC seq
GSM9520994 RNA-Seq, KP VPR organoids, transduced USEC-sgOlfr, biological line replicate 1, tagmented for ATAC
GSM9520995 RNA-Seq, KP VPR organoids, transduced USEC-sgSox2, biological line replicate 1, tagmented for ATAC
GSM9520996 RNA-Seq, KP VPR organoids, transduced USEC-sg∆Np63, biological line replicate 1, tagmented for ATAC
GSM9520997 RNA-Seq, KP VPR organoids, transduced USEC-sg∆Np63-sgSox2, biological line replicate 2, tagmented for ATAC seq
GSM9520998 RNA-Seq, KP VPR organoids, transduced USEC-sgOlfr, biological line replicate 2, tagmented for ATAC
GSM9520999 RNA-Seq, KP VPR organoids, transduced USEC-sgSox2, biological line replicate 2, tagmented for ATAC
GSM9521000 RNA-Seq, KP VPR organoids, transduced USEC-sg∆Np63, biological line replicate 2, tagmented for ATAC
GSM9521001 RNA-Seq, KP VPR organoids, transduced USEC-sg∆Np63-sgSox2, biological line replicate 3, tagmented for ATAC seq
GSM9521002 RNA-Seq, KP VPR organoids, transduced USEC-sgOlfr, biological line replicate 3, tagmented for ATAC
GSM9521003 RNA-Seq, KP VPR organoids, transduced USEC-sgSox2, biological line replicate 3, tagmented for ATAC
GSM9521004 RNA-Seq, KP VPR organoids, transduced USEC-sg∆Np63, biological line replicate 3, tagmented for ATAC
GSM9521005 RNA-Seq, KP VPR organoids, transduced USEC-sg∆Np63-sgSox2, biological line replicate 4, tagmented for ATAC seq
GSM9521006 RNA-Seq, KP VPR organoids, transduced USEC-sgOlfr, biological line replicate 4, tagmented for ATAC
GSM9521007 RNA-Seq, KP VPR organoids, transduced USEC-sgSox2, biological line replicate 4, tagmented for ATAC
GSM9521008 RNA-Seq, KP VPR organoids, transduced USEC-sg∆Np63, biological line replicate 4, tagmented for ATAC

Datasets on a similar topic

GSE319598 Lineage identity governs oncogene dependence in murine NSCLC models of KRAS inhibitor resistance [scRNA-Seq] 9 samples shares nsclc, kras, dependence, resistance, inhibitor, identity, oncogene, lineage
GSE319747 Lineage identity governs oncogene dependence in murine NSCLC models of KRAS inhibitor resistance 41 samples shares nsclc, kras, dependence, resistance, inhibitor, identity, oncogene, lineage
GSE319596 Lineage identity governs oncogene dependence in murine NSCLC models of KRAS inhibitor resistance [ATAC-Seq] 16 samples shares nsclc, kras, dependence, resistance, inhibitor, identity, oncogene, lineage
GSE270541 Mechanisms of response and tolerance to active RAS inhibition in KRAS-mutant NSCLC 35 samples shares nsclc, kras
GSE337208 scRNA seq. of PDAC models treated with Kras inhibitors in combination with checkpoint immunotherapy 9 samples shares kras, inhibitor
GSE252839 Nuclear Factor NFAT5 Governs Cellular Plasticity-Induced KRAS-Targeted Therapy Resistance in Pancreatic Cancer 24 samples shares kras, resistance
GSE250238 JAK inhibitor overcomes resistance to immune checkpoint inhibitor treatment in gastric cancer peritoneal dissemination in mouse 29 samples shares resistance, inhibitor
GSE290828 Harnessing STING Signaling and Natural Killer Cells to overcome PARP Inhibitor Resistance in Homologous Recombination Repair altered Breast Cancer [RNA-seq] 20 samples shares resistance, inhibitor

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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.