Scientists have generated 600 new tissue models of human cancer, covering 25 distinct tumor types—a development that may speed up drug discovery for cancers that have resisted treatment for decades. The models, created from patient tumors and now available worldwide, stem from a decade-long collaboration involving MIT’s Koch Institute, the Broad Institute, Dana-Farber Cancer Institute, and the National Cancer Institute, alongside over two dozen other institutions. Their findings appear in a new study published in Nature.
The initiative tackles a long-standing shortfall in cancer research: most existing models derive from European and Southeast Asian patients, leaving rare cancers and genetic variations poorly represented. The new collection includes 150 rare tumor types, such as gallbladder and small intestine cancers, alongside more common forms like lung, liver, and pancreatic. From 2,700 tumor samples donated by patients in the U.S., U.K., and Netherlands, researchers successfully cultivated organoids—three-dimensional cell cultures that preserve the genetic and molecular features of original tumors—from about one-third of the samples.
Unlike traditional cancer cell lines, which grow in flat layers since the 1950s, organoids form complex 3D structures embedded in a gelatin-like matrix, closely replicating natural tissue. This structural fidelity allows researchers to test drug responses in ways that better mirror patient outcomes. Each model was validated to confirm its genomic sequences, RNA expression patterns, and epigenomic changes matched those of the original tumors.
All models and accompanying patient data—including inherited mutations and prior treatments, have been deposited at the American Type Culture Collection (ATCC), a nonprofit repository for cell lines. This documentation enables studies on how genetic backgrounds shape cancer progression and treatment resistance.
Filling gaps in cancer research models
The effort builds on the Cancer Genome Atlas, a 2010s project that sequenced thousands of tumors and exposed their genetic diversity. At that time, fewer than 1,000 patient-derived models existed, insufficient to represent the full spectrum of cancers. “We realized that a thousand wasn’t enough, that the international community needed to invest in many more thousands to represent all cancers, all genotypes, all ethnicities,” Boehm says. “Most existing models come from European and Southeast Asian patients, and many rare cancers are missing.”
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The models are already producing results. In a parallel Nature paper, Broad Institute researchers analyzed 300 of the new models using high-throughput sequencing and CRISPR loss-of-function screens, uncovering potential drug targets. These insights were added to the Cancer Dependency Map (DepMap), now encompassing data on over 2,000 cancer types. A third Nature study, led by the Sanger Institute, characterized an additional 256 organoids from the project.
While the Human Cancer Models Initiative (HCMI) is concluding, researchers intend to expand the collection, particularly for pediatric cancers and rare tumors. “We now have about 2,000, but if we really want to represent all humans with cancer in our preclinical research, more work is needed. We have to invite patients to donate tissue to make research tools that the whole world can use,” Boehm says.
Behind-the-scenes effort transforms global cancer research
The project’s scale shows the difficulties in cancer research. Converting a tumor sample into a functional model can take up to a year, demanding specialized techniques and rigorous validation. “A resource of this scale depends on the kind of systematic effort that often happens behind the scenes,” says Mushriq Al-Jazrawe, scientific director of the Koch Institute’s High Throughput Sciences platform. “I’m especially grateful to the technical and scientific teams across the participating institutes whose careful, expert work turns patient tumor samples into well-characterized models and data that researchers everywhere can use with confidence.”
The models are now accessible to scientists worldwide, potentially accelerating the development of targeted therapies for previously untreatable cancers.
