Cancer researchers have unveiled one of the most extensive collections of patient-derived tumor models ever assembled, creating a living laboratory for studying how human cancers evolve, resist treatment, and respond to new therapies. Developed through the National Institutes of Health’s Human Cancer Models Initiative (HCMI), the international resource contains 665 next-generation models representing 25 cancer types and derived from tumors donated by 2,780 patients. The collection is designed to capture the biological diversity of cancer more faithfully than conventional laboratory systems, offering researchers a detailed experimental window into the diseases they aim to treat.
The models include organoids and other laboratory-grown systems engineered to preserve important characteristics of the tumors from which they originated. Organoids are three-dimensional cellular structures that can reproduce aspects of the architecture and cellular composition of an organ. In brain cancer research, for example, HCMI models include neurosphere-like clusters with properties associated with neural stem cells. Unlike many traditional cancer cell lines, which can acquire extensive genetic changes after years of laboratory growth, these models are intended to remain closely connected to the biology of individual patients’ tumors.
That connection is supported by a large body of molecular and clinical information. HCMI has developed models spanning common cancer subtypes and including many of the major genetic alterations that define those diseases. Researchers can associate each model with genomic, transcriptomic, epigenomic, and clinical data, allowing them to examine cancer at several biological levels at once. Genomic data reveal mutations and chromosomal changes, transcriptomic data show which genes are active, and epigenomic data describe chemical and structural mechanisms that regulate gene activity without changing the underlying DNA sequence.
A central question in cancer modeling is whether a tumor retains its defining features after being removed from the body and cultured for extended periods. To address this issue, HCMI scientists compared 421 original tumors with their paired laboratory models. The results showed a striking degree of similarity. The models agreed with their parent tumors on 97.8% of assessed genetic alterations, showed 95% concordance in epigenetic features, and retained 92% similarity in RNA expression patterns. These findings indicate that the culture conditions used to grow the models did not substantially erase the molecular identity of the cancers.
The preservation of these features is particularly important for investigating treatment resistance, one of the most persistent challenges in oncology. A tumor may fail to respond to an initial therapy, or it may adapt during treatment and return in a more aggressive form. HCMI models can help scientists trace the genetic and molecular events behind that process. In glioblastoma models, researchers identified inherited abnormalities, acquired amplification of cancer-promoting genes, and mutational signatures associated with previous exposure to temozolomide, a chemotherapy drug commonly used against the disease. Such signatures are molecular records of DNA damage and repair processes that can reveal how a tumor has responded to therapy in the past.
Because the models retain characteristics of individual tumors, they may also support more precise studies of drug sensitivity. Researchers can expose different models to the same treatment and compare the results with the genetic alterations present in each cancer. This approach may help identify vulnerabilities that are shared across patients, as well as weaknesses restricted to a smaller molecular subgroup. In the longer term, these experiments could improve the design of targeted therapies and help explain why a drug benefits some patients but not others.
The collection also broadens the range of cancers available for laboratory investigation. Of the models, 153 represent rare cancers, which are often difficult to study because patient numbers are low and biological samples are scarce. The resource includes 71 models from people of non-European ancestry, an important step toward addressing the underrepresentation of diverse populations in biomedical research. Although the collection does not capture every aspect of tumor biology—particularly the full influence of a patient’s immune system, blood supply, and surrounding tissues—it provides a more diverse foundation for research than many existing model repositories.
More than 500 models, specifically 522, are accompanied by detailed clinical information. Scientists can search the HCMI catalog according to cancer type, treatment history, demographic characteristics, and other features. The models are being distributed to the broader research community through a partnership with the American Type Culture Collection, allowing laboratories around the world to work with standardized biological material rather than relying on isolated, difficult-to-reproduce samples. The associated data are intended to make experiments more comparable and to accelerate the movement of discoveries from basic research toward preclinical testing.
The HCMI compendium represents the culmination of a decade-long effort involving the National Cancer Institute and collaborators in the United States and internationally, including research groups at the Wellcome Sanger Institute, the Broad Institute of MIT and Harvard, and Cold Spring Harbor Laboratory. Published in Nature, the work establishes a large-scale framework for connecting patient tumors to experimentally tractable models. By combining preserved tumor biology with detailed molecular and clinical records, the initiative gives cancer researchers a powerful way to investigate tumor evolution, uncover mechanisms of resistance, and search for therapeutic vulnerabilities that could ultimately improve precision oncology.
Subject of Research: Patient-derived cancer models, tumor biology, cancer evolution, treatment resistance, organoids, and precision oncology
News Publication Date: 5-Aug-2026
Web References:
https://www.cancer.gov/ccg/research/functional-genomics/hcmi
https://www.atcc.org/hcmi
https://hcmi-searchable-catalog.nci.nih.gov/
https://www.cancer.gov/
References:
Nature article, DOI: 10.1038/s41586-026-10806-y
Keywords: Human Cancer Models Initiative, HCMI, cancer research, patient-derived tumor models, organoids, tumor biology, cancer genomics, epigenomics, transcriptomics, glioblastoma, temozolomide resistance, precision oncology, drug sensitivity, rare cancers, National Cancer Institute, NIH
