ROCKVILLE, Md. & LONDON—Earlier this summer, four research-focused institutions doing work in the cancer and cell modeling realms teamed up on an international project to develop a large, globally accessible bank of new cancer cell culture models for the research community.
Specifically, the effort brought together the National Cancer Institute (NCI), Cancer Research UK, the Wellcome Trust Sanger Institute and the foundation Hubrecht Organoid Technology. Together, they will work to develop the Human Cancer Models Initiative (HCMI), which will bring together expertise from around the world to make some 1,000 cancer cell models.
“As part of NCI’s Precision Medicine Initiative in Oncology, this new project is timed perfectly to take advantage of the latest cell culture and genomic sequencing techniques to create models that are representative of patient tumors and are annotated with genomic and clinical information,” said Dr. Louis Staudt, director of NCI’s Center for Cancer Genomics. “This effort is a first step towards learning how to use these tools to design individualized treatments.”
NCI and its partners in the HCMI work point out that by using new techniques to grow cells, scientists will be able to make models that more closely resemble the tissue architecture and complexity of human tumors compared to cell lines in use now.
“This exciting new project means that we can expand our resources for researchers around the world,” said Dr. Ian Walker, Cancer Research UK’s director of clinical research. “We want scientists to have the best resources to be able to easily study all types of cancer, and these new cell lines could transform how we study cancer and could help to develop better treatments for patients.”
Scientists in the global HCMI team will construct the models from tissues derived from patients with different types of cancer. This may very well include rare cancers and pediatric cancers which, the partners note, “are often under-represented or not available at all in existing cell line collections.” The tumors and the models derived from them will be genetically sequenced; researchers will have access to this information, as well as the anonymized clinical data about the patients and their tumors.
In addition to reflecting the biology of tumors more accurately and better representing patient populations, the work of these four international partners could also speed up development of additional new models and make research more efficient by avoiding unnecessary duplication of scientific efforts.
“New cancer model derivation technologies are allowing us to generate even more and improved cancer models for research,” noted Dr. Mathew Garnett, group leader at the Wellcome Trust Sanger Institute. “ A concerted and coordinated effort to make new models will accelerate this process, while also allowing for rapid learning, protocol sharing and standardized culturing methods.”
For his part, Dr. Hans Clevers of the foundation Hubrecht Organoid Technology said, simply: “We are delighted to take part in this global partnership to make new resources for researchers.”
In other recent NCI news, the institute announced July 6 that the largest study ever to investigate how genetic and biological factors contribute to breast cancer risk among black women had launched—a collaborative research project designed to identify genetic factors that may underlie breast cancer disparities and that is funded by the NCI.
The Breast Cancer Genetic Study in African-Ancestry Populations initiative does not involve new patient enrollment but builds on years of research cooperation among investigators who are part of the African-American Breast Cancer Consortium, the African-American Breast Cancer Epidemiology and Risk Consortium and the NCI Cohort Consortium. These investigators, who come from many different institutions, will share bio-specimens, data and resources from 18 previous studies, resulting in a study population of 20,000 black women with breast cancer.
Survival rates for women with breast cancer have been steadily improving over the past several decades. However, these improvements have not been shared equally; black women are more likely to die of their disease. Perhaps of most concern is that black women are more likely than white women to be diagnosed with aggressive subtypes of breast cancer. The rate of triple-negative breast cancer, an aggressive subtype, is twice as high in black women as compared to white women.
The exact reasons for these persistent disparities are unclear, although studies suggest that they are the result of a complex interplay of genetic, environmental and societal factors, including access to healthcare.
And in other Cancer Research UK news, the organization announced July 7 that a team of scientists have used imaging techniques as a new way to identify patients who could benefit from certain breast cancer treatments.
The team at King’s College London, in collaboration with scientists at the CRUK/MRC Oxford Institute for Radiation Oncology, used fluorescence lifetime imaging to confirm if key proteins have joined together.
Fluorescence lifetime imaging is a technique that can accurately measure the distance between two protein molecules. In this study, the researchers measured the distance between HER2 and HER3 proteins in breast cancer cells from patients.
The researchers think that patients whose imaging results show that these proteins have bonded together could benefit from HER2-targeted treatment, regardless of whether their tumor has high levels of HER2.
July 7 also brought news from the Wellcome Trust Sanger Institute about recent research published in Cell showing that patient-derived cancer cell lines harbor most of the same genetic changes found in patients’ tumors, and could be used to learn how tumors are likely to respond to new drugs, increasing the success rate for developing new personalized cancer treatments.
Led by scientists from the Wellcome Trust Sanger Institute, the European Bioinformatics Institute (EMBL-EBI) and the Netherlands Cancer Institute, the international study discovered a strong link between many mutations in patient cancer samples, and the sensitivity to particular drugs. Aside from the benefits inherent in advancing personalized medicine so that physicians can choose the best available oncology drugs for patients, it could also aid in designing better clinical trials for potential cancer therapeutics.
The partners in this effort say it was the first systematic, large-scale study to combine molecular data from patients, laboratory cancer cell lines and drug sensitivity—in the research, they looked at genetic mutations known to cause cancer in more than 11,000 patient samples of 29 different tumor types, building a catalog of the genetic changes that cause cancer in patients and mapping the alterations onto 1,000 cancer cell lines. Next, they tested the cell lines for sensitivity to 265 different cancer drugs to understand which of these changes effect sensitivity.
The researchers made two significant discoveries: firstly, that the majority of molecular abnormalities found in patient’s cancers are also found in cancer cells in the laboratory. This means that cell lines are indeed useful models to identify which drugs would work best for patients. Secondly, many of the molecular abnormalities detected in the thousands of patient cancer samples can, both individually but also in combination, have a strong effect on whether a particular drug affects a cancer cell’s survival.
The researchers say this suggests strongly that cancer cell lines could be better exploited than they are now in order to learn which drugs offer the most effective treatment to specific patients.
Previous studies have sequenced the DNA of cancers from patients to identify the molecular abnormalities that drive the biology of cancer cells. Researchers have also shown that large collections of cancer cell lines grown in the laboratory can be used for measuring sensitivity to many hundreds of drugs. However, this is the first study to systematically combine these two sets of information.
“If a cell line has the same genetic features as a patient’s tumor, and that cell line responded to a specific drug, we can focus new research on this finding. This could ultimately help assign cancer patients into more precise groups based on how likely they are to respond to therapy,” noted Dr. Francesco Iorio, joint first author and postdoctoral researcher at both EMBL-EBI and the Sanger Institute.
“We need better ways to figure out which groups of patients are more likely to respond to a new drug before we run complex and expensive clinical trials,” added Dr. Ultan McDermott, joint leader of the study and a clinician scientist from the Sanger Institute. “Our research shows that cancer cell lines do capture the molecular alterations found in tumors, and so can be predictive of how a tumor will respond to a drug. This means the cell lines could tell us much more about how a tumor is likely to respond to a new drug before we try to test it in patients. We hope this information will ultimately help in the design of clinical trials that target those patients with the greatest likelihood of benefiting from treatment.”
