New therapy may improve stem cell transplants for blood cancers
In 2018, Robyn was diagnosed with myelofibrosis, a blood cancer causing chronic inflammation and scarring. As a research scientist by training, she knew she had limited options. A stem cell transplant is a terminally ill patient's best chance for survival against blood cancers, including leukaemia. It works by destroying a patient's cancer cells and replacing them with healthy cells from a donor.
However, there is a huge risk of Graft vs Host disease (GVHD), which affects around 30-40% of recipients. Patients receive billions of cells in a stem cell transplant but only a fraction are beneficial. The rest can attack healthy tissue leading to GVHD. It affects the skin, gut and lungs and can be truly debilitating.
Currently, steroids are used to try and prevent GVHD, but they have many side effects and are effective in only 50% of cases. “I spoke with my doctors and reached out to patients managing GVHD,” says Robyn, who prefers not to use her last name for privacy reasons. “My concerns really escalated for what I might face post-transplant.”
Then she heard about a new highly precise cell therapy developed by a company called Orca Bio, which gives patients more beneficial cells and fewer cells that cause GVHD. She decided to take part in their phase 2 trial.
How It Works
In stem cell transplants, patients receive immune cells and stem cells. The donor immune cells or T cells attack and kill malignant cells. This is the graft vs leukaemia effect (GVL). The stem cells generate new healthy cells.
Unfortunately, T cells can also cause GVHD, but a rare subset of T cells, called T regulatory cells, can actually prevent GVHD.
Orca’s cell sorting technology distinguishes T regulatory cells from stem cells and conventional T cells on a large scale. It’s this cell sorting technology which has enabled them to create their new cell therapy, called Orca T. It contains a precise combination of stem cells and immune cells with more T regulatory cells and fewer conventional T cells than in a typical stem cell transplant.
“Ivan Dimov’s idea was to spread out the cells, keep them stationary and then use laser scanning to sort the cells,” explains Nate Fernhoff, co-founder of Orca Bio. “The beauty here is that lasers don't care how quickly you move them.”
Over the past 40 years, scientists have been trying to create stem cell grafts that contain the beneficial cells whilst removing the cells that cause GVHD. What makes it even harder is that most transplant centers aren’t able to manipulate grafts to create a precise combination of cells.
Innovative Cell Sorting
Ivan Dimov, Jeroen Bekaert and Nate Fernhoff came up with the idea behind Orca as postdocs at Stanford, working with cell pioneer Irving Weissman. They recognised the need for a more effective cell sorting technology. In a small study at Stanford, Professor Robert Negrin had discovered a combination of T cells, T regulatory cells and stem cells which prevented GVHD but retained the beneficial graft vs leukaemia effect (GVL). However, manufacturing was problematic. Conventional cell sorting is extremely slow and specific. Negrin was only able to make seven highly precise products, for seven patients, in a year. Annual worldwide cases of blood cancer number over 1.2 million.
“We started Orca with this idea: how do we use manufacturing solutions to impact cell therapies,” co-founder Fernhoff reveals. In conventional cell sorting, cells move past a stationary laser which analyses each cell. But cells can only be moved so quickly. At a certain point they start to experience stress and break down. This makes it very difficult to sort the 100 billion cells from a donor in a stem cell transplant.
“Ivan Dimov’s idea was to spread out the cells, keep them stationary and then use laser scanning to sort the cells,” Fernhoff explains. “The beauty here is that lasers don't care how quickly you move them.” They developed this technology and called it Orca Sort. It enabled Orca to make up to six products per week in the first year of manufacturing.
Every product Orca makes is for one patient. The donor is uniquely matched to the patient. They have to carry out the cell sorting procedure each time. Everything also has to be done extremely quickly. They infuse fresh living cells from the donor's vein to the patient's within 72 hours.
“We’ve treated almost 200 patients in all the Orca trials, and you can't do that if you don't fix the manufacturing process,” Fernhoff says. “We're working on what we think is an incredibly promising drug, but it's all been enabled by figuring out how to make a high precision cell therapy at scale.”
Clinical Trials
Orca revealed the results of their phase 1b and phase 2 trials at the end of last year. In their phase 2 trial only 3% of the 29 patients treated with Orca T cell therapy developed chronic GVHD in the first year after treatment. Comparatively, 43% of the 95 patients given a conventional stem cell transplant in a contemporary Stanford trial developed chronic GVHD. Of the 109 patients tested in phase 1b and phase 2 trials, 74% using Orca T didn't relapse or develop any form of GVHD compared to 34% in the control trial.
“Until a randomised study is done, we can make no assumption about the relative efficacy of this approach," says Jeff Szer, professor of haematology at the Royal Melbourne Hospital. "But the holy grail of separating GVHD and GVL is still there and this is a step towards realising that dream.”
Stan Riddell, an immunology professor, at Fred Hutchinson Cancer Centre, believes Orca T is highly promising. “Orca has advanced cell selection processes with innovative methodology and can engineer grafts with greater precision to add cell subsets that may further contribute to beneficial outcomes,” he says. “Their results in phase 1 and phase 2 studies are very exciting and offer the potential of providing a new standard of care for stem cell transplant.”
However, though it is an “intriguing step,” there’s a need for further testing, according to Jeff Szer, a professor of haematology at the Peter MacCallum Cancer Centre at the Royal Melbourne Hospital.
“The numbers tested were tiny and comparing the outcomes to anything from a phase 1/2 setting is risky,” says Szer. “Until a randomised study is done, we can make no assumption about the relative efficacy of this approach. But the holy grail of separating GVHD and GVL is still there and this is a step towards realising that dream.”
The Future
The team is soon starting Phase 3 trials for Orca T. Its previous success has led them to develop Orca Q, a cell therapy for patients who can't find an exact donor match. Transplants for patients who are only a half-match or mismatched are not widely used because there is a greater risk of GVHD. Orca Q has the potential to control GVHD even more and improve access to transplants for many patients.
Fernhoff hopes they’ll be able to help people not just with blood cancers but also with other blood and immune disorders. If a patient has a debilitating disease which isn't life threatening, the risk of GVHD outweighs the potential benefits of a stem cell transplant. The Orca products could take away that risk.
Meanwhile, Robyn has no regrets about participating in the Phase 2 trial. “It was a serious decision to make but I'm forever grateful that I did,” she says. “I have resumed a quality of life aligned with how I felt pre-transplant. I have not had a single issue with GVHD.”
“I want to be able to get one of these products to every patient who could benefit from it,” Fernhoff says. “It's really exciting to think about how Orca's products could be applied to all sorts of autoimmune disorders.”
Since the early 2000s, AI systems have eliminated more than 1.7 million jobs, and that number will only increase as AI improves. Some research estimates that by 2025, AI will eliminate more than 85 million jobs.
But for all the talk about job security, AI is also proving to be a powerful tool in healthcare—specifically, cancer detection. One recently published study has shown that, remarkably, artificial intelligence was able to detect 20 percent more cancers in imaging scans than radiologists alone.
Published in The Lancet Oncology, the study analyzed the scans of 80,000 Swedish women with a moderate hereditary risk of breast cancer who had undergone a mammogram between April 2021 and July 2022. Half of these scans were read by AI and then a radiologist to double-check the findings. The second group of scans was read by two researchers without the help of AI. (Currently, the standard of care across Europe is to have two radiologists analyze a scan before diagnosing a patient with breast cancer.)
The study showed that the AI group detected cancer in 6 out of every 1,000 scans, while the radiologists detected cancer in 5 per 1,000 scans. In other words, AI found 20 percent more cancers than the highly-trained radiologists.
Scientists have been using MRI images (like the ones pictured here) to train artificial intelligence to detect cancers earlier and with more accuracy. Here, MIT's AI system, MIRAI, looks for patterns in a patient's mammograms to detect breast cancer earlier than ever before. news.mit.edu
But even though the AI was better able to pinpoint cancer on an image, it doesn’t mean radiologists will soon be out of a job. Dr. Laura Heacock, a breast radiologist at NYU, said in an interview with CNN that radiologists do much more than simply screening mammograms, and that even well-trained technology can make errors. “These tools work best when paired with highly-trained radiologists who make the final call on your mammogram. Think of it as a tool like a stethoscope for a cardiologist.”
AI is still an emerging technology, but more and more doctors are using them to detect different cancers. For example, researchers at MIT have developed a program called MIRAI, which looks at patterns in patient mammograms across a series of scans and uses an algorithm to model a patient's risk of developing breast cancer over time. The program was "trained" with more than 200,000 breast imaging scans from Massachusetts General Hospital and has been tested on over 100,000 women in different hospitals across the world. According to MIT, MIRAI "has been shown to be more accurate in predicting the risk for developing breast cancer in the short term (over a 3-year period) compared to traditional tools." It has also been able to detect breast cancer up to five years before a patient receives a diagnosis.
The challenges for cancer-detecting AI tools now is not just accuracy. AI tools are also being challenged to perform consistently well across different ages, races, and breast density profiles, particularly given the increased risks that different women face. For example, Black women are 42 percent more likely than white women to die from breast cancer, despite having nearly the same rates of breast cancer as white women. Recently, an FDA-approved AI device for screening breast cancer has come under fire for wrongly detecting cancer in Black patients significantly more often than white patients.
As AI technology improves, radiologists will be able to accurately scan a more diverse set of patients at a larger volume than ever before, potentially saving more lives than ever.
Here's how one doctor overcame extraordinary odds to help create the birth control pill
Dr. Percy Julian had so many personal and professional obstacles throughout his life, it’s amazing he was able to accomplish anything at all. But this hidden figure not only overcame these incredible obstacles, he also laid the foundation for the creation of the birth control pill.
Julian’s first obstacle was growing up in the Jim Crow-era south in the early part of the twentieth century, where racial segregation kept many African-Americans out of schools, libraries, parks, restaurants, and more. Despite limited opportunities and education, Julian was accepted to DePauw University in Indiana, where he majored in chemistry. But in college, Julian encountered another obstacle: he wasn’t allowed to stay in DePauw’s student housing because of segregation. Julian found lodging in an off-campus boarding house that refused to serve him meals. To pay for his room, board, and food, Julian waited tables and fired furnaces while he studied chemistry full-time. Incredibly, he graduated in 1920 as valedictorian of his class.
After graduation, Julian landed a fellowship at Harvard University to study chemistry—but here, Julian ran into yet another obstacle. Harvard thought that white students would resent being taught by Julian, an African-American man, so they withdrew his teaching assistantship. Julian instead decided to complete his PhD at the University of Vienna in Austria. When he did, he became one of the first African Americans to ever receive a PhD in chemistry.
Julian received offers for professorships, fellowships, and jobs throughout the 1930s, due to his impressive qualifications—but these offers were almost always revoked when schools or potential employers found out Julian was black. In one instance, Julian was offered a job at the Institute of Paper Chemistory in Appleton, Wisconsin—but Appleton, like many cities in the United States at the time, was known as a “sundown town,” which meant that black people weren’t allowed to be there after dark. As a result, Julian lost the job.
During this time, Julian became an expert at synthesis, which is the process of turning one substance into another through a series of planned chemical reactions. Julian synthesized a plant compound called physostigmine, which would later become a treatment for an eye disease called glaucoma.
In 1936, Julian was finally able to land—and keep—a job at Glidden, and there he found a way to extract soybean protein. This was used to produce a fire-retardant foam used in fire extinguishers to smother oil and gasoline fires aboard ships and aircraft carriers, and it ended up saving the lives of thousands of soldiers during World War II.
At Glidden, Julian found a way to synthesize human sex hormones such as progesterone, estrogen, and testosterone, from plants. This was a hugely profitable discovery for his company—but it also meant that clinicians now had huge quantities of these hormones, making hormone therapy cheaper and easier to come by. His work also laid the foundation for the creation of hormonal birth control: Without the ability to synthesize these hormones, hormonal birth control would not exist.
Julian left Glidden in the 1950s and formed his own company, called Julian Laboratories, outside of Chicago, where he manufactured steroids and conducted his own research. The company turned profitable within a year, but even so Julian’s obstacles weren’t over. In 1950 and 1951, Julian’s home was firebombed and attacked with dynamite, with his family inside. Julian often had to sit out on the front porch of his home with a shotgun to protect his family from violence.
But despite years of racism and violence, Julian’s story has a happy ending. Julian’s family was eventually welcomed into the neighborhood and protected from future attacks (Julian’s daughter lives there to this day). Julian then became one of the country’s first black millionaires when he sold his company in the 1960s.
When Julian passed away at the age of 76, he had more than 130 chemical patents to his name and left behind a body of work that benefits people to this day.