Blood Test Can Detect Lymphoma Cells Before a Tumor Grows Back
Lina Zeldovich has written about science, medicine and technology for Popular Science, Smithsonian, National Geographic, Scientific American, Reader’s Digest, the New York Times and other major national and international publications. A Columbia J-School alumna, she has won several awards for her stories, including the ASJA Crisis Coverage Award for Covid reporting, and has been a contributing editor at Nautilus Magazine. In 2021, Zeldovich released her first book, The Other Dark Matter, published by the University of Chicago Press, about the science and business of turning waste into wealth and health. You can find her on http://linazeldovich.com/ and @linazeldovich.
When David M. Kurtz was doing his clinical fellowship at Stanford University Medical Center in 2009, specializing in lymphoma treatments, he found himself grappling with a question no one could answer. A typical regimen for these blood cancers prescribed six cycles of chemotherapy, but no one knew why. "The number seemed to be drawn out of a hat," Kurtz says. Some patients felt much better after just two doses, but had to endure the toxic effects of the entire course. For some elderly patients, the side effects of chemo are so harsh, they alone can kill. Others appeared to be cancer-free on the CT scans after the requisite six but then succumbed to it months later.
"Anecdotally, one patient decided to stop therapy after one dose because he felt it was so toxic that he opted for hospice instead," says Kurtz, now an oncologist at the center. "Five years down the road, he was alive and well. For him, just one dose was enough." Others would return for their one-year check up and find that their tumors grew back. Kurtz felt that while CT scans and MRIs were powerful tools, they weren't perfect ones. They couldn't tell him if there were any cancer cells left, stealthily waiting to germinate again. The scans only showed the tumor once it was back.
Blood cancers claim about 68,000 people a year, with a new diagnosis made about every three minutes, according to the Leukemia Research Foundation. For patients with B-cell lymphoma, which Kurtz focuses on, the survival chances are better than for some others. About 60 percent are cured, but the remaining 40 percent will relapse—possibly because they will have a negative CT scan, but still harbor malignant cells. "You can't see this on imaging," says Michael Green, who also treats blood cancers at University of Texas MD Anderson Medical Center.
The new blood test is sensitive enough to spot one cancerous perpetrator amongst one million other DNA molecules.
Kurtz wanted a better diagnostic tool, so he started working on a blood test that could capture the circulating tumor DNA or ctDNA. For that, he needed to identify the specific mutations typical for B-cell lymphomas. Working together with another fellow PhD student Jake Chabon, Kurtz finally zeroed-in on the tumor's genetic "appearance" in 2017—a pair of specific mutations sitting in close proximity to each other—a rare and telling sign. The human genome contains about 3 billion base pairs of nucleotides—molecules that compose genes—and in case of the B-cell lymphoma cells these two mutations were only a few base pairs apart. "That was the moment when the light bulb went on," Kurtz says.
The duo formed a company named Foresight Diagnostics, focusing on taking the blood test to the clinic. But knowing the tumor's mutational signature was only half the process. The other was fishing the tumor's DNA out of patients' bloodstream that contains millions of other DNA molecules, explains Chabon, now Foresight's CEO. It would be like looking for an escaped criminal in a large crowd. Kurtz and Chabon solved the problem by taking the tumor's "mug shot" first. Doctors would take the biopsy pre-treatment and sequence the tumor, as if taking the criminal's photo. After treatments, they would match the "mug shot" to all DNA molecules derived from the patient's blood sample to see if any molecular criminals managed to escape the chemo.
Foresight isn't the only company working on blood-based tumor detection tests, which are dubbed liquid biopsies—other companies such as Natera or ArcherDx developed their own. But in a recent study, the Foresight team showed that their method is significantly more sensitive in "fishing out" the cancer molecules than existing tests. Chabon says that this test can detect circulating tumor DNA in concentrations that are nearly 100 times lower than other methods. Put another way, it's sensitive enough to spot one cancerous perpetrator amongst one million other DNA molecules.
They also aim to extend their test to detect other malignancies such as lung, breast or colorectal cancers.
"It increases the sensitivity of detection and really catches most patients who are going to progress," says Green, the University of Texas oncologist who wasn't involved in the study, but is familiar with the method. It would also allow monitoring patients during treatment and making better-informed decisions about which therapy regimens would be most effective. "It's a minimally invasive test," Green says, and "it gives you a very high confidence about what's going on."
Having shown that the test works well, Kurtz and Chabon are planning a new trial in which oncologists would rely on their method to decide when to stop or continue chemo. They also aim to extend their test to detect other malignancies such as lung, breast or colorectal cancers. The latest genome sequencing technologies have sequenced and catalogued over 2,500 different tumor specimens and the Foresight team is analyzing this data, says Chabon, which gives the team the opportunity to create more molecular "mug shots."
The team hopes that that their blood cancer test will become available to patients within about five years, making doctors' job easier, and not only at the biological level. "When I tell patients, "good news, your cancer is in remission', they ask me, 'does it mean I'm cured?'" Kurtz says. "Right now I can't answer this question because I don't know—but I would like to." His company's test, he hopes, will enable him to reply with certainty. He'd very much like to have the power of that foresight.
This article is republished from our archives to coincide with Blood Cancer Awareness Month, which highlights progress in cancer diagnostics and treatment.
Lina Zeldovich has written about science, medicine and technology for Popular Science, Smithsonian, National Geographic, Scientific American, Reader’s Digest, the New York Times and other major national and international publications. A Columbia J-School alumna, she has won several awards for her stories, including the ASJA Crisis Coverage Award for Covid reporting, and has been a contributing editor at Nautilus Magazine. In 2021, Zeldovich released her first book, The Other Dark Matter, published by the University of Chicago Press, about the science and business of turning waste into wealth and health. You can find her on http://linazeldovich.com/ and @linazeldovich.
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.