The new biobank is being built on the existing institutional infrastructure of a collection established at Hospital de Amor in 2006. That collection already contains more than 420,000 biological samples from over 55,000 donors, providing the physical and organizational foundation for a focused program in genomic cancer research. The breast, colorectal and cervical cancers selected for the first phase are important health priorities in Brazil and already have established preventive, screening or early-detection measures, including mammography, cervical screening, fecal occult blood testing and colonoscopy. A peer-reviewed paper describing the biorepository and its design was published in iScience, with support from the São Paulo Research Foundation. It documents the infrastructure rather than a completed Brazilian polygenic risk score.

A principal motivation is the limited representation of Brazil’s population in large genomic studies of cancer risk. According to study coordinator Rui Manuel Reis, scientific director of the Hospital de Amor Institute for Teaching and Research, more than 90% of people included in large-scale genomic investigations of cancer risk have European ancestry. Genetic data developed in such populations may transfer poorly to a country whose residents draw on European, African, Indigenous and Asian ancestry, and whose lifestyles and exposures vary substantially across regions. The project’s genetic composition reflects this diversity, and the researchers plan to examine how ancestry is associated with tumor risk and how ancestry affects the performance of risk scores. “We can’t develop precision medicine using a template designed for a European population, with European genetics and a European lifestyle,” Reis said.

One of the main tools the team intends to develop is a polygenic risk score, an approach distinct from testing for a single well-known hereditary mutation. Alterations in genes such as BRCA1 and BRCA2 can confer a substantial increase in the risk of breast and ovarian cancer, but most cancers do not have one genetic alteration that explains an individual’s risk. Instead, many common genetic variants make small contributions, with some slightly raising risk and others slightly lowering it. A polygenic score aggregates information across these variants to estimate a person’s relative genetic predisposition to a particular tumor. The resulting value does not predict whether someone will develop cancer or establish that the disease will occur; it identifies whether that person carries a comparatively higher or lower inherited susceptibility.

Polygenic scores have already been developed through large international genomic studies and are beginning to be used to estimate susceptibility to several diseases, including cancer. Most existing scores, however, were constructed and tested primarily in people of European ancestry. The Hospital de Amor team therefore considers local validation essential before any such score is applied within SUS. Its broader dataset is intended to determine which variants are associated with breast, colorectal and cervical cancer in the Brazilian population, and whether the relationships seen in other populations hold across different ancestry groups. The study also seeks to identify how genetic predisposition interacts with lifestyle and environmental conditions rather than treating genetic information in isolation. Researchers are currently analyzing millions of genetic variations for each participant to determine which are most informative.

That distinction is important because a high polygenic risk score is not equivalent to a diagnosis or a certain future outcome. Cancer can arise through a combination of genetic predisposition and factors such as diet, obesity, physical inactivity, smoking and environmental exposure. To capture those influences, the project pairs blood collection with a comprehensive questionnaire covering participants’ lifestyles, diets, occupations and other potential risk factors. The team also plans to study how genetic variation relates to ancestry and living conditions in Brazil. “We have a very rich biobank of genetic material combined with a very comprehensive epidemiological questionnaire,” Reis said. The researchers hope these data will eventually allow them to develop risk models that reflect Brazilian reality more closely than models based solely on European ancestry.

Potential applications within SUS would involve combining validated genetic findings with other information about risk, rather than using a score alone to determine care. In a hypothetical colorectal cancer pathway, for example, someone found to have a higher genetic predisposition might receive additional attention to modifiable risk factors or, if future studies show a benefit, follow a different screening strategy from someone classified as lower risk, such as referral for an earlier colonoscopy. Similar reasoning could apply to breast and cervical cancer. These possibilities remain contingent: the project has not demonstrated that risk-guided screening improves outcomes, and the source release explicitly notes that the current tool is not ready for implementation in the public health system.

Several stages must precede any clinical rollout. The researchers first need to define which genetic variants and scores are useful, test them in a substantially larger group and validate the results at other centers. If a future test is developed, it is expected to require only a blood sample while examining dozens or hundreds of relevant markers rather than the millions of variations now being analyzed. The investigators also emphasize the need to generate local evidence before introducing tools that were developed abroad. Although genetic risk tests for different conditions are already marketed in Brazil, many were based on overseas research and have not been validated for the Brazilian population. The stated long-term objective is a tool capable of being deployed across SUS, but Reis stressed that validation must come first.

The most advanced results so far concern colorectal cancer and are expected to appear in a separate forthcoming paper; the present publication does not present a ready-to-use Brazilian risk score. The team also plans to expand the biobank to other tumors, including lung cancer, pancreatic cancer and melanoma, and to recruit patients from remote regions who are underrepresented in genomic research. Hospital de Amor’s network will assist with that geographic extension. By consolidating genomic, epidemiological and lifestyle data, the project seeks to ensure that Brazilian populations participate in precision medicine and to build prevention strategies tailored to the country. For now, the biobank’s achievement is the creation of a research platform and an initial cohort, while its proposed value for individualized cancer prevention depends on further model development, validation and evaluation in the public health system.

Subject of Research: Development and validation of a Brazilian biobank for genomic cancer-risk prediction in breast, colorectal and cervical cancers.

Article Title: Brazilian biobank may help personalize cancer prevention in the public health system

Article References: Brazilian biobank may help personalize cancer prevention in the public health system. Original publication (Bibliographic details unavailable.)

Image Credits: AI Generated

DOI: Not provided

Keywords: cancer biobank, polygenic risk scores, precision medicine, Brazilian genomics, cancer prevention, breast cancer, colorectal cancer, cervical cancer, genetic ancestry, public health, Brazilian, biobank

The biobank contains 256 organoids representing five cancer types with significant unmet medical needs: colorectal, oesophageal, pancreatic, stomach and ovarian cancers. Organoids are miniature three-dimensional cultures grown from patient tumour cells. Unlike conventional two-dimensional cell lines, in which cancer cells spread across the flat surface of a laboratory dish, organoids can reproduce important features of the original tumour’s architecture, genetic diversity and behaviour. They are not complete tumours, but they provide a more biologically realistic environment for studying how cancer cells grow and respond to treatment.

Creating the collection required a coordinated network of hospital and research centres in Birmingham, Cambridge, Glasgow, London and Southampton. Fresh tumour tissue donated by consenting patients was rapidly transported to the Sanger Institute, where researchers isolated viable cancer cells and placed them in carefully controlled culture conditions. These conditions included specialised growth factors and three-dimensional scaffolds or matrices that encourage cells to organise into structures resembling aspects of the tissue from which they originated. Establishing such cultures is technically demanding because tumour samples contain a mixture of cancer cells, immune cells, connective tissue and other normal cells, and not every sample forms a stable organoid.

To determine how faithfully the organoids represented the patients’ cancers, the researchers compared DNA sequences from the organoids with sequences from the original tumours and, where available, blood samples from the same patients. This approach allowed the team to distinguish inherited genetic variants from mutations acquired by the tumour and to monitor whether the models changed as they were maintained in the laboratory. The analysis showed that the organoids generally retained key genetic characteristics of the tumours from which they were derived, supporting their use as experimental models while also providing a way to track laboratory adaptation over time.

The researchers then applied CRISPR screening to 162 organoid models. CRISPR is a genome-editing technology that can be programmed to disrupt individual genes. In a screening experiment, thousands of cells receive different gene-targeting guides, and the population is monitored to determine which genetic disruptions prevent cells from surviving or multiplying. If cells carrying a particular guide disappear from the culture, the targeted gene may be essential under those conditions. By performing these screens across many tumour models, the team could distinguish broad cancer dependencies from vulnerabilities restricted to particular cancer types or molecular subgroups.

The screens identified thousands of dependencies. Some genes were required by many cancer models, reflecting fundamental processes such as DNA replication, protein production, cell division or energy metabolism. Others were important only in tumours carrying particular mutations or genomic changes. These selective dependencies are especially interesting for drug discovery because they may offer a route to target cancer cells while limiting damage to healthy tissues. However, a gene dependency observed in an organoid is not automatically a viable drug target; it must be validated through additional experiments, tested for safety and assessed in increasingly complex biological systems.

By integrating the CRISPR results with genomic and clinical information, the researchers identified 1,733 associations between gene dependencies and tumour features. These links included specific DNA alterations and treatment histories, helping to explain why genetically different cancers may respond differently to the same therapy. The resource also provided clues about how some tumours adapt after treatment. In several cases, organoids established from the same patient before and after therapy allowed the team to compare tumour states and identify changes associated with treatment resistance, as well as weaknesses that might be exploited by alternative approaches.

The findings do not represent an immediate new treatment for patients, and the organoids are not intended to replace clinical trials or traditional cancer models. Instead, the biobank is designed as an open research platform that can help scientists prioritise hypotheses before investing in drug development. Researchers can use the models to investigate cancer biology, test combinations of therapies, study resistance mechanisms and explore why a treatment succeeds in one molecular context but fails in another. Because the models are linked to patient data and genetic information, they may also help close the gap between laboratory discoveries and the biology of cancers observed in hospitals.

The study forms part of a broader international effort to improve next-generation cancer models. Two complementary papers published in Nature describe an expanded dependency map using genome-editing screens and the Human Cancer Models Initiative’s international collection of patient-derived models. Together, the studies point toward a more systematic era of cancer research in which experimental models are selected according to the genetic and clinical features they represent. Data from the new biobank will be made freely available through the Cell Model Passports website, while organoids are expected to be distributed through Merck and the nonprofit American Type Culture Collection, allowing laboratories worldwide to investigate cancer’s vulnerabilities with shared, better-characterised tools.

Subject of Research: Cancer gene dependencies, patient-derived tumour organoids and CRISPR screening

Article Title: A tumour-derived organoid biobank maps cancer gene dependencies

News Publication Date: 5 August 2026

Web References:
Wellcome Sanger Institute: https://www.sanger.ac.uk/
Cell Model Passports: https://cellmodelpassports.sanger.ac.uk/
Wellcome: https://wellcome.org/

References:
Herranz-Ors, C. et al. (2026), “A tumour-derived organoid biobank maps cancer gene dependencies,” Nature. DOI: 10.1038/s41586-026-10830-y
“A dependency map enhanced with next-generation 3D cancer models,” Nature. DOI: 10.1038/s41586-026-10843-7
“A compendium of next-generation patient-derived models for diverse cancers,” Nature. DOI: 10.1038/s41586-026-10806-y

Keywords: Cancer, oncology, tumour organoids, cancer biobank, CRISPR screening, gene dependencies, cancer vulnerabilities, precision medicine, treatment resistance, genomics, patient-derived models, drug discovery