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CRISPR-Cas9 Screening Identifies Resistance Mechanisms to KRAS Inhibition in Pancreatic Cancer

GSE310675 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/11/27 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 12 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
Pancreatic cancerThis series is part of our curated briefing on it.
Samples
12 samples: 12 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
CRISPR-Cas9 Screening Identifies Resistance Mechanisms to KRAS Inhibition in Pancreatic CancerCancer research · 2026
Summary (written by the submitters)
KRAS inhibitors (KRASi) targeting various KRAS mutations have entered clinical trials for pancreatic cancer. Despite promising preliminary clinical responses, most patients relapse due to intrinsic and acquired resistance. Thus, combination treatments are essential to extend the efficacy of KRAS-targeted therapies.
Read the full summary ↓
To further determine genetic mechanisms of KRASi resistance, we performed KRASi-anchored CRISPR-Cas9 loss-of-function screens in KRAS G12D-, KRAS G12R-, and KRAS Q61H-mutant PDAC cell lines, using six KRASi, to identify genes, that when lost, modulate sensitivity to KRAS inhibition. We pharmacologically validated several hits from our screens, including EGFR, CK2 p110 alpha and p110 gamma, and YAP, by combining targeted inhibitors with KRASi. We determined that KRAS Q61H-mutant PDAC cell lines are intrinsically less dependent on KRAS for survival than other KRAS mutational subtypes. Further, we found that EGFR inhibitor erlotinib synergized with the RAS(ON) multi-selective inhibitor RMC-7977 in KRAS Q61H-mutant PDAC cell lines, and in cell lines with highly active EGFR, by mitigating ERK rebound activity. We also developed KRASi-resistant cell lines and observed sustained ERK MAPK dependence in the KRASi-resistant cell lines despite decreased ERK activity. Our findings enhance the understanding of KRASi intrinsic and acquired resistance and identify therapeutic vulnerabilities that can potentially be exploited for KRASi combination therapies in patients with PDAC.
Published in
CRISPR-Cas9 Screening Identifies Resistance Mechanisms to KRAS Inhibition in Pancreatic Cancer
Long SA, Todd H, Goodhart G et al. · Cancer research 2026 · PMID 41248420 · doi:10.1158/0008-5472.CAN-25-1835
This dataset
Open GSE310675 in finder → Find more human RNA-seq datasets → Pancreatic 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 GSE310675_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 PRJNA1366928 and SRA study SRP647172. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41248420) ↗
Study design
12 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 12 sample titles: 12 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
More Pancreatic cancer datasets

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