DepMap Adds 147 CRISPR Screens in 3D Cancer Models, Uncovering New Vulnerabilities
Updated
Updated · Nature.com · Aug 5
DepMap Adds 147 CRISPR Screens in 3D Cancer Models, Uncovering New Vulnerabilities
3 articles · Updated · Nature.com · Aug 5
Summary
DepMap integrated 147 genome-scale CRISPR screens from next-generation 3D cancer models with existing data, expanding the cancer dependency resource beyond more than 1,300 traditional cell lines.
314 organoid and spheroid models across 10 cancer types broadened subtype coverage and better matched tumor biology: Celligner lineage accuracy reached 69% for NextGen models versus 35% for traditional cell lines.
The added models exposed biomarker-linked weaknesses missed in 2D cultures, including SCD sensitivity in KRAS-amplified oesophagus-stomach organoids and CDK6 vulnerability in glial GBM with CDKN2A loss.
Organoids also preserved a mucinous differentiation program that revealed selective WNT-pathway dependencies, while comparisons with 2D models showed growth format mainly altered integrin and actin dependencies and media shifted lipid-metabolism dependencies.
The integrated WGS, RNA-seq and CRISPR dataset is now available through the DepMap portal, aiming to improve target discovery by capturing both tumor genotype and transcriptional state.
If 3D models reveal hidden cancer weaknesses, are decades of flat 2D cell research leading us down the wrong path?
Could the secret to curing aggressive brain cancers have been hiding in the 3D shape of our lab models all along?
Mapping Cancer’s Weaknesses: The 2026 DepMap Update Adds 150 3D Organoid Models for Precision Oncology
Overview
In August 2026, the Cancer Dependency Map (DepMap) was expanded by integrating nearly 150 three-dimensional (3D) cancer models, allowing scientists to uncover genetic vulnerabilities that traditional two-dimensional (2D) models could not reveal. Unlike 2D cell lines, which often lose key tumor features, 3D models let cells grow in environments that closely mimic real tumors, preserving important genetic programs. This led to discoveries such as glioblastoma cells with CDKN2A loss becoming highly sensitive to CDK6 inhibition, and aggressive pancreatic cancers showing deep dependency on the WNT pathway. To ensure reliable results, advanced computational pipelines were developed to separate true biological signals from technical noise. The DepMap Consortium, including academic and industry partners, now uses these insights to identify new drug targets, while also addressing ancestry bias in CRISPR screening to make cancer research more equitable and accurate.