Stem cells offer unique opportunities for researchers to study the reaction of drugs applied to human tissues. Moreover, stem cells can model healthy or diseased states, as well as provide the ability to genetically modify cells before drug treatment. To make the most of these cells, however, researchers need a variety of tools and techniques. This article explores several new tools and reveals ongoing aspirations.
Many applications of stem cells already exist in drug research, and even more lie ahead. For example, Amr Abid, PhD, general manager for cell technologies at GE Healthcare Life Sciences (Amersham, U.K.), says, “Stem cells offer great hope for the future in improving the attrition rate in drug development.”
Stem cells also offer new opportunities in screening drugs, especially in smaller-scale screens, according to Mahendra Rao, MD, PhD, chief of the Laboratory of Stem Cell Biology at the National Institute of Arthritis and Musculoskeletal and Skin Diseases of the National Institutes of Health (Bethesda, Md.). “Really massive screens with one million compounds are too expensive to do with stem cells right now.” Rao says. “So that’s off the table.” However, Rao points out that stem cells can be used in repurposing screens. “With existing drugs, researchers can use panels of stem cells with specific properties, like a person who has an adverse reaction,” he says. In addition, Rao points out that stem cells create an opportunity to use human cells in early-stage toxicology testing. “Before you could only do that in animals, but now you can substitute human cells,” he says. “There’s a huge advantage to using human cells versus animal cells.” For example, the affinities of receptors can differ in human and animals. Rao adds, “The signaling pathway depends on cell differences, types, and context, and [induced pluripotent stem (iPS) cells] allow you to get the right cell to study the pathway of choice.”
Industrial-scale stem cells
At Cellular Dynamics International (Madison, Wis.), researchers start with iPS cells to create terminally differentiated cells. “We manufacture these in industrial quantities for drug discovery and development, as well as safety testing,” says Chris Parker, the company’s vice president and chief commercial officer. “These cells can be used in early- and late-stage development.” He adds, “This provides access to human biology in ways that we’ve never had access to before.”
By starting with iPS cells, Cellular Dynamics can make virtually any cell. “In essence,” says Parker, “we can represent every tissue in the body in a separate dish and even explore genetic differences to better represent clinical applications in the future.” Using, say, heart cells from a population of people, researchers can employ these cells to run virtual clinical trials. “Every well in a 96-well plate could be from a different person,” says Parker. “So we can test these cells at an individual level. We can even go in and edit a gene that is affected and see what the biological response is.”
Cellular Dynamics offers a catalog of iPS cell-derived tissue cells, including cardiomyocytes, neurons, endothelial cells, and hepatocytes. The company will also make custom iPS cell lines, a process that takes about six months. “These are mostly normal, healthy cells or disease states that depend on one genetic mutation,” says Parker. “We have made about 250 iPS cell lines and then scaled those up.”
Various cells can also be used in concert. As an example, Parker envisions researchers building a brain model in a dish. “If you make a pure population of every cell in the brain and then put them together,” he says, “you could make regions, like the hippocampus.” Likewise, the company’s MyCell Services bring scientists the opportunity to purchase genetically engineered iPS cells that can be induced into various cells lines and even tissues.
Power of populations
Other companies also make stem cell-derived cell products in large quantities. “GE Healthcare is mass-producing cells derived from human embryonic stem cell lines,” says Abid. Consequently, he sees researchers taking on more complex questions. “Existing models address one point or answer one question,” Abid says. “They often even represent only one individual, but [people] behave in different ways.” So if a study starts with one cell from one person, the results apply to that person, and maybe no one else. Human embryonic stem cells (hESC), on the other hand, “can be used to represent populations,” Abid says. “We are now working with BGI [in Beijing]—the world’s largest genomics organization—to compare stem-cell lines from Caucasian versus Asian populations so that, ultimately, you can take ethnic diversity into account in a study.”
GE Healthcare has already developed an hESC-based model of cardiotoxicity called Cytiva cardiomyocytes. Abid and his colleagues use a 28-day process to differentiate the cells. “It gives us billions of cells,” Abid says. GE Healthcare’s cells can help drug companies generate “consistent data on cardiotoxicity,” Abid adds. “We understand where the toxicity comes from, and pharma and biotech and researchers can access this model.”
Abid sees GE Healthcare working toward even more models. “The next big challenge is hepatotoxicity,” he says. “Cardiotoxicity and hepatotoxicity cover about 60% of why drugs are withdrawn from the market.”
To use these models widely in drug research, scientists need consistency. “In all of these models, the key is a robust, reproducible, and scalable process,” Abid says. “That allows researchers to compare results from experiments today with what they do next year.”
Finding more in flow
Other experts also see the need for consistent stem cells. “We need cell types that are very reproducible from batch to batch to study toxicology,” says Robert Balderas, vice president, BD Biosciences – Biological Science (San Jose, Calif.). “This has always been extremely important for the evaluation of a drug.” In addition to getting such consistency from stem cells, the differentiation process could also be controlled to produce cells from various stages of differentiation. “These could be used to look at the effects of drugs on earlier stages of differentiating cells,” says Balderas.
To evaluate stem cells and the impact of drugs on them, researchers often use flow cytometry. “It can be used to evaluate the cells phenotypically or to enhance functional assays to see how cells are responding,” Balderas explains. “We’ve developed reagents to profile stem cells. We also run internal programs to find new phenotypic markers that can be used to study how cells differentiate.”
Furthermore, BD Lyoplate screening panels provide researchers with collections of cell-surface markers for mouse and human cells. “These are arrayed onto plates that can be used to screen all of the different steps through differentiation,” says Balderas. Combining flow cytometry and screening tools provides researchers with new stem cell-related approaches to various fields, especially regenerative biology where new cell types can be used and analyzed before and after a drug treatment.
Stem cells also open new approaches to gene therapy. For example, M. Ian Phillips, PhD, Norris Professor of Applied Life Sciences and director of the Center for Rare Disease Therapies at the Keck Graduate Institute (Claremont, Calif.), describes nucleases— transcription activator-like effector nucleases (TALENs) and zinc fingers—as tools to potentially genetically modify cells.
Starting by making a human iPS cell from a patient with a disease caused by a single-point mutation, researchers would use a nuclease, to open the mutation site. “Then, a new piece of DNA is inserted that fits the spot and repairs the mutation,” Phillips says. “That cell reproduces as a normal cell.”
Consider Niemann-Pick disease, for example, which arises from a malfunctioning enzyme. “The lack of the enzyme lets waste products build up inside of cells to toxic levels,” Phillips explains. So if the TALEN-based approach were used, Phillips sees repaired cells, lots of them, being injected back into the patient, who could then make the needed enzyme.
This process would get considerably more complex in conditions involving multiple genes. Nonetheless, Phillips says, “Many diseases are due to one mutation, and if you can repair it, you could cure someone of the disease.”
Cancer stem cells might also turn into a powerful opportunity for medical research. “We often see cancer treatment with chemotherapy and radiation that eliminates the measurable cancer, but it comes back in one or two years,” says Phillips. The problem might arise from cancer stem cells, which resist the treatment. “More needs to be done to identify these stem cells,” says Phillips. If researchers could identify and isolate cancer stem cells, then treatments could be tested to specifically target them and prevent a new tumor. “If you can get pure cancer stem cells,” says Phillips, “you can study them and see what it takes to kill them.”
To find those cancer stem cells, researchers need new tools. One might come from flow cytometry coupled with supercomputing. As Yuan Qi, PhD, assistant professor of computer science at Purdue University (Lafayette, Ind.), says, “We are trying to find a tiny number of cells in massive flow cytometry data, and that requires lots of number crunching.” For example, Qi says that the cancer stem cells make up about 0.01% of the data set. “Each data point represents a cell,” Qi says, “and we utilize a supercomputer to do the analysis fast.”
More specifically, Qi and his team are building a Bayesian model that can compare data from healthy mice from those with cancer. “We want to compare normal to disease and see what’s different,” he says. To do that, his computational technique analyzes a flow-cytometry dataset and builds clusters. “These groups of data correspond to cell populations, like B cells,” Qi says. “And we compare the groups from healthy and cancerous subjects to see if maybe a cluster is in cancerous mice but not in healthy ones. That way, we can identify the troublemakers.”
Beyond using this approach to find cancer stem cells, it can also be used in discovering new drugs. “You can model the response to a drug,” Qi says. “If one person takes the drug, which cell types change?” Then Qi asks: “Does the drug kill good cells or bad ones?”
So far, Qi says that it is relatively easy to tell cancerous cells from healthy ones. “It’s harder to pinpoint where the cancer cells are,” he says. The problem arises from the answer depending on the distribution of data, not just a simple yes-or-no answer. He hopes that his approach can use those cancer-driven changes in the distributions of single-cell data to unveil the cancer stem cells.
Despite the great advances that could come from using stem cells in drug research, Rao does not expect stem cells to completely replace animal cells. Nonetheless, he says, “Stem cells will bridge our potential gaps in knowledge.”
About the author
Mike May is a publishing consultant for science and technology based in Austin, Texas.