Patient-Derived Organoids: A Powerful Tool in Precision Oncology
Patient-derived organoids retain key tumor features, making them powerful tools for guiding personalized cancer treatment.
In cancer, precision medicine—also known as personalized medicine—aims to tailor treatment to a patient’s specific malignancy, based on its genetic and biochemical characteristics. This can improve drug success rates and reduce side effects.
Cancer precision medicine has traditionally focused on genetic mutations—a patient’s tumor can be sequenced, revealing driver mutations that can be targeted by therapeutics and informing clinicians which drug is likely to work.
However, this approach is not always successful. Some patients have mutations that cannot be targeted by existing therapies, while others have a targetable mutation but still do not respond to the selected medication.
Patient-derived tumor models, including organoids and mouse xenografts, offer researchers a way to directly test therapies on the tumor itself.
“The development of organoids and the rise of functional precision medicine are among the most exciting developments of the past decade,” Dr. Alice Soragni, a professor and director of the Functional Personalized Medicine Initiative at the University of Colorado Anschutz and co-president of the Society for Functional Precision Medicine, told Technology Networks.
“It’s been really exciting to see data being generated that show that these models are good and faithful models of the patient’s tumor, and that, in the right circumstances, they can predict patient outcomes and response to different therapeutics,” she said.
Organoids are central to new approach methodologies (NAMs), which provide human-relevant models for drug discovery to reduce reliance on animal testing. Because more than 90% of oncology drugs that show preclinical efficacy in animal studies fail in human trials, organoids, as a human-relevant model, have great potential to accelerate the delivery of new cancer therapies to patients.
What are patient-derived organoids?
Unlike stem cell-derived organoids, where cultured pluripotent stem cells are nudged into developing into a 3D model of specific tissue, patient-derived organoids (PDOs) use cells from a patient’s tumor. PDOs therefore retain the genetic, epigenetic, and phenotypic characteristics of the original tumor, offering a more accurate reflection of the specific cancer than cell line models, animal models, or stem cell-derived organoids, which is critical for precision medicine.
PDOs can be created in two different ways, Soragni explained: “One is probably the more conventional way, which is you take tumor tissue, you develop organoids, and then you expand these and passage them over time until you get an established model.”
“My lab focuses on the other flavor of PDOs, which are passage zero cultures, also called short-term cultures,” she said.
Long-term PDOs offer the advantage of being shareable and suitable for multiple types of experiments, but they are cultured to selectively support the growth of cancer cells. Emerging data is illustrating the importance of the tumor microenvironment for drug response, which these models cannot capture. Additionally, the longer an organoid is cultured, the more likely it is to undergo clonal selection and epigenetic changes that alter its identity, making it less similar to the patient’s tumor.
With short-term PDOs, tumor tissue is sampled and placed into an extracellular matrix, developed in gel, and then drug testing can be performed. “We can do all of this within a week, so we don’t do any passaging or outgrow,” explained Soragni. In these models, the different tumor components are retained, but researchers are limited by the number of cells that are taken during sampling.
“If a sample is taken during a surgery, perhaps you can establish thousands of organoids and test hundreds of drugs,” she said. “But if a sample is taken from a biopsy and contains fewer cells, you might only be able to test one or two things.”
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Without expansion and passaging, it’s also difficult to share these models.
Soragni highlighted that the establishment success rate of these PDO types differs—short-term models are likely to establish successfully and can be used for slow-growing as well as highly malignant tumors, whereas not all tumor types can grow in long-term culture. “They have different applications,” she said. “Where I'm seeing the field converging in terms of functional precision medicine is more and more towards rapid cultures.”
Organoid models can be built to different levels of complexity, including co-culture with immune cells and integration with organ-on-a-chip systems to mimic vasculature and multi-tissue interfaces.
“There is no right or wrong model; you just need to match the model to the question you’re trying to answer.” — Prof. Alice Soragni.
“The fact that we can accomplish incredible complexity with NAMs does not necessarily make these models better,” she said. “The incredible complexity you can achieve in the lab makes some of these assays very challenging to deploy clinically.”
Leveraging PDOs for drug target discovery and screening
PDOs are a valuable preclinical resource for screening existing drugs and uncovering new drug targets.
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“There is an opportunity to broadly screen therapeutics with PDOs,” explained Soragni. “You have the ability to screen drugs that you wouldn’t necessarily think could work for a specific tumor type, or to screen drugs that are approved for different indications.”
This could enable existing drugs to be repurposed to treat the tumor or reveal pathways that hold promise for further research.
Soragni’s lab focuses largely on rare tumors. For these rare cancers, there are many unknowns. “With a very small patient population, it's hard to do clinical studies, and sometimes it's just hard to get tissue from these tumor types, and so we don't have models. Sometimes we don't have a single cell line for the type of cancers we investigate,” she said. “We don't know what the biology is, what drives this tumor, or what we should be targeting.”
Some rare cancers, such as pheochromocytomas and paragangliomas, have a variety of known genetic drivers, but only one immortalized human cell line. This cell line models just one of the genetic drivers, leaving it unknown whether drugs that are effective in the cell line will be effective in the rest of the population with different genetic drivers.
PDOs from rare cancers open the possibility of screening therapeutics to identify potential new drugs, repurposing opportunities, and under-explored targets. “Before, you could not screen because you had no model,” explained Soragni.
Additionally, PDOs could be used to stratify patients in clinical trials. “There is a big bucket of drugs that have been in clinical trials with reasonable toxicities, but in an unstratified population,” Soragni noted. “If these drugs showed 10–20% activity, there are patients who are benefiting, but the numbers aren’t good enough to get approval.”
Leveraging PDOs to identify responsive patient populations before a clinical trial could increase the likelihood of treatment success in a patient cohort and drug approval, which could, in turn, improve patient access and outcomes.
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Tackling drug resistance and tumor recurrence with PDOs
Studying the chemical and biological landscape within a PDO offers a way to understand drug resistance, a critical challenge in cancer treatment.
“In a PDO, you may already see existing intrinsic resistance mechanisms and a lack of response to particular therapeutics,” said Soragni. “There is also a true opportunity to investigate signals of emerging resistance.”
Long-term PDOs can be cultured with small amounts of therapeutics, which can nudge the cells toward resistance. Molecular analysis over time can then track the sequence of pathways that contribute to resistance, pointing researchers towards potential combination therapies or drugs that can overcome resistance mechanisms.
In short-term PDOs, Soragni and her team have been investigating the early signals of drug resistance. By leveraging secretomics, proteomics, and other omics approaches, they can detect early signals that a tumor is “pushing back” after drug treatment.
“It’s very interesting to truly leverage these models to pick up early, or perhaps, if you have long-term models, fully established mechanisms of resistance.” — Prof. Alice Soragni.
Understanding the early signals of resistance could be used to shape a cancer patient's treatment journey by using this data to introduce a combination therapy or switch drugs sooner to improve outcomes.
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“Cancer is a disease driven by evolution.” — Prof. Alice Soragni.
The dynamic nature of cancer means that, as well as developing drug resistance, tumors can recur over time. In these cases, Soragni highlighted how important it is to capture new samples and form new organoids: “I think people tend to underestimate how much things can potentially change over time. If you have a sample from a primary tumor and that patient develops metastatic or recurrent disease later down the line, you cannot rely on the information from the original tumor to make clinical decisions.”
PDOs could support clinical decision-making
A significant limitation in cancer therapy is the absence of biomarkers that predict treatment response. With these biomarkers, medications can be tailored to a patient, improving the chances of success.
Preclinically, PDOs can be used to identify markers linked to drug responses, allowing clinicians to determine which drug works for each patient based on their responses.
It is especially difficult to predict patient responses to immunotherapies due to tumor and immune system heterogeneity. “It remains a very challenging proposition to have a solid biomarker that predicts reactivity to immunotherapies,” explained Soragni. “PDOs coupled with immune cells in a co-culture offer an opportunity to identify biomarkers of immunotherapy response.”
An emerging application of PDOs is in the clinic as a companion diagnostic or in vitro treatment test that is synchronized to the patient’s condition: if a patient comes into the clinic and an organoid assay is approved, they could get their drug responsiveness tested in the lab before starting treatment.
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Using PDOs more systematically for screening and rescreening during patient care could enable clinicians to follow up in a more adaptive way to help keep the disease in check as it evolves.
“We want to make this type of functional precision medicine a true pillar of patient care.” — Prof. Alice Soragni.
Clinical PDOs may not be needed for cancer types with an established and effective therapeutic ladder, but for cancers with no standard of care, or relapsed and recurring tumors, they could offer great benefit.
“They could help an oncologist to make a data-driven decision for their patients where there is a vacuum of information,” said Soragni.
Within the Colorado Center for Personalized Medicine, Soragni and her team have launched a functional precision medicine initiative to bring organoid-based technologies into the clinic. “In the future, a patient could come to the hospital, their doctor could request a PDO assay, and the results from the assay could flow back to the patient’s chart to inform their care,” she said.
Clinical trial data to support the use of PDOs in the clinic are accumulating, Soragni said. More evidence of patient benefit from PDO-based assays, along with regulatory approval, is likely to transform precision oncology.
“It's an exciting time because institutions are looking at onboarding organoid-based technologies as part of the offerings that they have for patients.” — Prof. Alice Soragni.
“My hope is that, five years from now, if a patient has a rare, recurrent, or relapsing cancer, they can easily access PDO technologies, and the data can be interpreted by oncologists and used for therapeutic advantage,” Soragni concluded.
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