GEO series

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

GSE319596 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 16 samples Submitted 2026/05/09 Platform GPL34328

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 16 samples

What it is: ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
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 GSE319596 in finder → Find more mouse ChIP / ATAC / CUT&Tag 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 GSE319596_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

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

GSM9520977 KP VPR organoids, transduced USEC-sg∆Np63-sgSox2, biological line replicate 1, tagmented for ATAC seq
GSM9520978 KP VPR organoids, transduced USEC-sgOlfr, biological line replicate 1, tagmented for ATAC
GSM9520979 KP VPR organoids, transduced USEC-sg∆Np63, biological line replicate 1, tagmented for ATAC
GSM9520980 KP VPR organoids, transduced USEC-sgSox2, biological line replicate 1, tagmented for ATAC
GSM9520981 KP VPR organoids, transduced USEC-sg∆Np63-sgSox2, biological line replicate 2, tagmented for ATAC seq
GSM9520982 KP VPR organoids, transduced USEC-sgOlfr, biological line replicate 2, tagmented for ATAC
GSM9520983 KP VPR organoids, transduced USEC-sg∆Np63, biological line replicate 2, tagmented for ATAC
GSM9520984 KP VPR organoids, transduced USEC-sgSox2, biological line replicate 2, tagmented for ATAC
GSM9520985 KP VPR organoids, transduced USEC-sg∆Np63-sgSox2, biological line replicate 3, tagmented for ATAC seq
GSM9520986 KP VPR organoids, transduced USEC-sgOlfr, biological line replicate 3, tagmented for ATAC
GSM9520987 KP VPR organoids, transduced USEC-sg∆Np63, biological line replicate 3, tagmented for ATAC
GSM9520988 KP VPR organoids, transduced USEC-sgSox2, biological line replicate 3, tagmented for ATAC
GSM9520989 KP VPR organoids, transduced USEC-sg∆Np63-sgSox2, biological line replicate 4, tagmented for ATAC seq
GSM9520990 KP VPR organoids, transduced USEC-sgOlfr, biological line replicate 4, tagmented for ATAC
GSM9520991 KP VPR organoids, transduced USEC-sg∆Np63, biological line replicate 4, tagmented for ATAC
GSM9520992 KP VPR organoids, transduced USEC-sgSox2, biological line replicate 4, tagmented for ATAC

Datasets on a similar topic

GSE319747 Lineage identity governs oncogene dependence in murine NSCLC models of KRAS inhibitor resistance 41 samples shares nsclc, kras, dependence, resistance, inhibitor, identity, oncogene
GSE319597 Lineage identity governs oncogene dependence in murine NSCLC models of KRAS inhibitor resistance [RNA-Seq] 16 samples shares nsclc, kras, dependence, resistance, inhibitor, identity, oncogene
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
GSE270541 Mechanisms of response and tolerance to active RAS inhibition in KRAS-mutant NSCLC 35 samples shares nsclc, kras
GSE279088 Molecular dynamics driving phenotypic divergence among KRAS mutants in pancreatic tumorigenesis [ATAC-Seq] 74 samples shares kras, atac-seq
GSE250099 KRAS-mediated upregulation of CIP2A promotes suppression of PP2A-B56a to initiate pancreatic cancer development [ATAC-seq] 18 samples shares kras, atac-seq
GSE252839 Nuclear Factor NFAT5 Governs Cellular Plasticity-Induced KRAS-Targeted Therapy Resistance in Pancreatic Cancer 24 samples shares kras, resistance
GSE337208 scRNA seq. of PDAC models treated with Kras inhibitors in combination with checkpoint immunotherapy 9 samples shares kras, 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.