This “Absolutely Tireless” Researcher Made an Important Breakthrough for Cancer Patients
After months of looking at dead cells under a microscope, Theo Roth finally glimpsed what he had been hoping to see—flickers of green. His method was working.
"If we can go into the cell and add in new code and instructions, now we can give it whatever new functions we want."
When Roth joined the laboratory of Alex Marson at the University of California, San Francisco in June 2016, he set to work trying to figure out a new way to engineer human T cells, a type of white blood cell that's an important part of the immune system. If he succeeded, the resulting approach could make it easier and faster for scientists to develop and test cell and gene therapies, new treatments that involve genetically reprogramming the body's own cells.
For decades, researchers have been using engineered viruses to bestow human cells with new genetic characteristics. These so-called viral vectors "infect" human cells, transferring whatever new genetic material scientists put into them. The idea is that this new DNA could give T cells a boost to better fight diseases like cancer and HIV.
Several successful clinical trials have used virally-modified human T cells, and in fact, the U.S. Food and Drug Administration last year approved two such groundbreaking cancer gene therapies, Kymriah and Yescarta. But the process of genetically manipulating cells with viruses is expensive and time-consuming. In addition, viruses tend to randomly insert DNA with little predictability.
"What Theo wanted to do was to paste in big sequences of DNA at a targeted site without viruses," says Marson, an associate professor of microbiology and immunology. "That would have the benefit of being able to rewrite a specific site in the genome and do it flexibly and quickly without having to make a new virus for every site you want to manipulate."
Scientists have for a while been interested in non-viral engineering methods, but T cells are fragile and notoriously difficult to work with.
Previously, Marson's lab had collaborated with CRISPR pioneer Jennifer Doudna and her team at the University of California, Berkeley to use an electrical pulse together with CRISPR components to knock out certain genes. They also found some success with inserting very small pieces of DNA into a targeted site.
But Roth, a 27-year-old graduate student at UCSF pursuing MD and PhD degrees, was determined to figure out how to paste in much bigger sequences of genetic information. Marson says it was an "ambitious" goal. Scientists had tried before, but found that stuffing large chunks of DNA into T cells would quickly kill them.
"If we can go into the cell and add in new code and instructions, now we can give it whatever new functions we want," Roth says. "If you can add in new DNA sequences at the site that you want, then you have a much greater capacity to generate a cell that's going to be therapeutic or curative for a disease."
"He has already made his mark on the field."
So Roth began experimenting with hundreds of different variables a week, trying to find the right conditions to allow him to engineer T cells without the need for viruses. To know if the technique was working, Roth and his colleagues used a green fluorescent protein that would be expressed in cells that had successfully been modified.
"We went from having a lot of dead cells that didn't have any green to having maybe 1 percent of them being green," Roth says. "At that stage we got really excited."
After nearly a year of testing, he and collaborators found a combination of T cell ratios and DNA quantity mixed with CRISPR and zaps of electricity that seemed to work. These electrical pulses, called electroporation, deliver a jolt to cells that makes their membranes temporarily more permeable, allowing the CRISPR system to slip through. Once inside cells, CRISPR seeks out a specific place in the genome and makes a programmed, precise edit.
Roth and his colleagues used the approach to repair a genetic defect in T cells taken from children with a rare autoimmune disease and also to supercharge T cells so that they'd seek out and selectively kill human cancer cells while leaving healthy cells intact. In mice transplanted with human melanoma tissue, the edited T cells went to straight to the cancerous cells and attacked them. The findings were published in Nature in July.
Marson and Roth think even a relatively small number of modified T cells could be effective at treating some cancers, infections, and autoimmune diseases.
Roth is now working with the Parker Institute for Cancer Immunotherapy in San Francisco to engineer cells to treat a variety of cancers and hopefully commercialize his technique. Fred Ramsdell, vice president at the Parker Institute, says he's impressed by Roth's work. "He has already made his mark on the field."
Right now, there's a huge manufacturing backlog for viruses. If researchers want to start a clinical trial to test a new gene or cell therapy, they often have to wait a year to get the viruses they need.
"I think the biggest immediate impact is that it will lower the cost of a starting an early phase clinical trial."
Ramsdell says what Roth's findings allow researchers to do is engineer T cells quickly and more efficiently, cutting the time it takes to make them from several months to just a few weeks. That will allow researchers to develop and test several potential therapies in the lab at once.
"I think the biggest immediate impact is that it will lower the cost of a starting an early phase clinical trial," Roth says.
This isn't the first time Roth's work has been in the spotlight. As an undergraduate at Stanford University, he made significant contributions to traumatic brain injury research by developing a mouse model for observing the brain's cellular response to a concussion. He started the research, which was also published in Nature, the summer before entering college while he was an intern in Dorian McGavern's lab at the National Institutes of Health.
When Roth entered UCSF as a graduate student, his scientific interests shifted.
"It's definitely a big leap" from concussion research, says McGavern, who still keeps in touch with Roth. But he says he's not surprised about Roth's path. "He's absolutely tireless when it comes to the pursuit of science."
Roth says he's optimistic about the potential for gene and cell therapies to cure patients. "I want to try to figure out what one of the next therapies we should put into patients should be."
A new type of cancer therapy is shrinking deadly brain tumors with just one treatment
Few cancers are deadlier than glioblastomas—aggressive and lethal tumors that originate in the brain or spinal cord. Five years after diagnosis, less than five percent of glioblastoma patients are still alive—and more often, glioblastoma patients live just 14 months on average after receiving a diagnosis.
But an ongoing clinical trial at Mass General Cancer Center is giving new hope to glioblastoma patients and their families. The trial, called INCIPIENT, is meant to evaluate the effects of a special type of immune cell, called CAR-T cells, on patients with recurrent glioblastoma.
How CAR-T cell therapy works
CAR-T cell therapy is a type of cancer treatment called immunotherapy, where doctors modify a patient’s own immune system specifically to find and destroy cancer cells. In CAR-T cell therapy, doctors extract the patient’s T-cells, which are immune system cells that help fight off disease—particularly cancer. These T-cells are harvested from the patient and then genetically modified in a lab to produce proteins on their surface called chimeric antigen receptors (thus becoming CAR-T cells), which makes them able to bind to a specific protein on the patient’s cancer cells. Once modified, these CAR-T cells are grown in the lab for several weeks so that they can multiply into an army of millions. When enough cells have been grown, these super-charged T-cells are infused back into the patient where they can then seek out cancer cells, bind to them, and destroy them. CAR-T cell therapies have been approved by the US Food and Drug Administration (FDA) to treat certain types of lymphomas and leukemias, as well as multiple myeloma, but haven’t been approved to treat glioblastomas—yet.
CAR-T cell therapies don’t always work against solid tumors, such as glioblastomas. Because solid tumors contain different kinds of cancer cells, some cells can evade the immune system’s detection even after CAR-T cell therapy, according to a press release from Massachusetts General Hospital. For the INCIPIENT trial, researchers modified the CAR-T cells even further in hopes of making them more effective against solid tumors. These second-generation CAR-T cells (called CARv3-TEAM-E T cells) contain special antibodies that attack EFGR, a protein expressed in the majority of glioblastoma tumors. Unlike other CAR-T cell therapies, these particular CAR-T cells were designed to be directly injected into the patient’s brain.
The INCIPIENT trial results
The INCIPIENT trial involved three patients who were enrolled in the study between March and July 2023. All three patients—a 72-year-old man, a 74-year-old man, and a 57-year-old woman—were treated with chemo and radiation and enrolled in the trial with CAR-T cells after their glioblastoma tumors came back.
The results, which were published earlier this year in the New England Journal of Medicine (NEJM), were called “rapid” and “dramatic” by doctors involved in the trial. After just a single infusion of the CAR-T cells, each patient experienced a significant reduction in their tumor sizes. Just two days after receiving the infusion, the glioblastoma tumor of the 72-year-old man decreased by nearly twenty percent. Just two months later the tumor had shrunk by an astonishing 60 percent, and the change was maintained for more than six months. The most dramatic result was in the 57-year-old female patient, whose tumor shrank nearly completely after just one infusion of the CAR-T cells.
The results of the INCIPIENT trial were unexpected and astonishing—but unfortunately, they were also temporary. For all three patients, the tumors eventually began to grow back regardless of the CAR-T cell infusions. According to the press release from MGH, the medical team is now considering treating each patient with multiple infusions or prefacing each treatment with chemotherapy to prolong the response.
While there is still “more to do,” says co-author of the study neuro-oncologist Dr. Elizabeth Gerstner, the results are still promising. If nothing else, these second-generation CAR-T cell infusions may someday be able to give patients more time than traditional treatments would allow.
“These results are exciting but they are also just the beginning,” says Dr. Marcela Maus, a doctor and professor of medicine at Mass General who was involved in the clinical trial. “They tell us that we are on the right track in pursuing a therapy that has the potential to change the outlook for this intractable disease.”
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.