Tumor Biobank Reveals Cancers’ Weak Spots
A biobank of patient-derived tumor organoids is helping scientists identify the genes cancers need to grow and survive.
Using a biobank of patient-derived cancer models, researchers have created the first large-scale map of the genes that cancers rely on to survive.
The biobank, which includes 256 clinically annotated tumor organoids, enabled researchers to identify the genes that specific cancers depend on for growth, revealing targetable weak points that could inform the development of future cancer therapies.
Details of the new biobank were published in the journal Nature.
A more human-relevant picture of cancer
Traditionally, 2D cell lines, in which cells are grown in a flat layer on a laboratory plate, have been used to study cancer. These workhorse models have provided important insights into cancer biology, but fail to capture the diversity and complexity of tumors seen in patients. In addition, most cell lines adapt to in vitro culture in ways that aren’t well understood.
Tumor organoids, which are 3D cultures derived from patient tissue and grown with niche factors in an extracellular matrix, better reflect patient tumors and can therefore help address some of the limitations of existing models.
“Organoids give scientists the ability to study cancer in richer detail, giving them new insights into its weak spots.”— Dr. Catherine Elliott, director of research at Cancer Research UK.
To build an open resource of tumor organoids, researchers from the Wellcome Sanger Institute worked with collaborators across five clinical sites in the United Kingdom.
Fresh tumor samples obtained through surgical resections or biopsies from consenting patients were sent to the Wellcome Sanger Institute for organoid derivation. From 878 unique donors, 256 organoid cultures were successfully established. The organoids were derived from five cancer types: colorectal, esophageal, pancreatic, stomach, and ovarian.
To further improve the usefulness of the biobank, the researchers performed a comprehensive genomic characterization of organoids and their patient-matched tumor samples using whole-genome sequencing. They also conducted RNA sequencing, only of the organoids. This allowed scientists to benchmark the models against the original tumor and track any changes that may arise as organoids are grown over time.
Identifying cancer's weak spots
In a first-of-its-kind study performed in organoids, the researchers used CRISPR gene editing to systematically switch off genes in 162 unique organoid cultures to investigate whether the cells survived. They identified thousands of genetic dependencies, including both common genes required by many cancers to survive, and more specific vulnerabilities linked to particular tumor types.
By combining this data with rich genomic and clinical information, the team found links between genetic dependencies and specific features such as DNA changes or treatment history. This uncovered new insights into the specific biological pathways that different cancers rely on for survival.
Organoid cultures were compared with their patient-matched tumor samples across multiple genomic features. This confirmed that the organoids faithfully recapitulated features from the tumor from which they were derived, supporting their use as a model for studying cancer.
Comparing organoids grown from the same patient before and after treatment helped reveal how certain tumors evolve and develop resistance to therapy. This also uncovered potential new weaknesses that could be explored with different treatment approaches.
“This study brings together patient-derived cancer models, genomics, and functional screening at a scale that has not previously been possible in organoids. It provides a new way to uncover cancer vulnerabilities in models that capture more of the diversity of real tumors, and creates a resource that the wider research community can build on,” explained Dr. Mathew Garnett, senior author at the Wellcome Sanger Institute.
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Refining organoid models and accessibility
Rather than replacing traditional 2D cell lines, the organoid biobank complements them, helping researchers address areas where existing models are less informative. The study reflects a wider effort to refine organoid models and make them more accessible to the research community.
A complementary paper, also published in Nature, presents results from the Human Cancer Models Initiative (HCMI), a decade-long effort to create an accessible resource of models and data. The collection includes 665 next-generation laboratory models representing 25 cancer types from 2,780 donors.
A second related paper in Nature incorporated many of the 3D models generated as part of the biobank and HCMI into DepMap, an existing dataset of more than a thousand 2D cancer models. The expanded resource now includes nearly 150 cancer models that grow as 3D cultures and is designed to help scientists uncover new cancer dependencies.
By linking patient-derived models with clinical and genomic data, these resources provide powerful platforms that could help bridge the gap between laboratory discoveries and patients, ultimately bringing the promise of personalized cancer medicine closer to reality.
Reference: Herranz-Ors C, Bhosle SG, Beck AE, et al. A tumour-derived organoid biobank maps cancer gene dependencies. Nature. 2026. doi: 10.1038/s41586-026-10830-y
This article is a rework of a press release issued by the Wellcome Sanger Institute. Material has been edited for length and content.
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