Worried About Eating GMOs? That’s Not the Real Problem
The 21st century food system is awash in ethical issues. To name just a handful: There's the environmental impacts of farming, the human health effects of diets based on animal products and processed foods, the growing clamor around food waste, and the longstanding concerns about agricultural labor. The last decade has seen the emergence of "ethical consumption," as people have been encouraged to avoid products that are associated with animal cruelty or unfair to farmers.
Misguided concerns about GMOs are missing the point altogether and distracting from a far more substantive ethical problem.
But consumers have never been so ignorant about where food comes from, and they are vulnerable to oversimplifications and faulty messaging. Many would include the first generation of crops from agricultural applications of recombinant DNA methods for genetic improvement—so called GMOs—among the foods they should avoid for ethical reasons. Unfortunately, these misguided concerns are missing the point altogether and distracting from a far more substantive ethical problem.
As we stand on the precipice of a new era in food and biotechnology – crops and animals with genomes altered through gene editing – it is more important than ever to let go of unnecessary fears and to pay attention to the real hazards of agricultural innovation.
But first, as a bioethicist with almost 40 years of experience working on issues in the food system, let me stress the overall context and rationale for trying to make changes in plant and animal genetics. Doing so, whether through conventional breeding or biotechnology, allows producers to meet the challenges of seasonal climate differences and increase yields.
And just because a food was created through ordinary plant breeding vs. genetic modification does not automatically make it safe. Things can and do go wrong in ordinary plant breeding, such as with potatoes and tomatoes. These both produce toxins in the green parts of the plant, and breeders exercise caution to ensure that toxins aren't transferred to edible parts.
Despite real risks, there is no regulatory oversight that protects us from these known hazards. We rely on the professional ethics of agricultural scientists. And GMOs are, in comparison, much more carefully tested and regulated. The claim that they are "unregulated" is just false.
We should not ignore the role that all gene technologies have played in displacing small farmers, depleting rural communities, and shifting economic control.
I do want to shift the public's attention away from the anti-GMO debate to more substantive questions about contemporary agriculture that really have little to do with where the genes in their food came from, or how they got there.
No matter how important genetic improvements might be in terms of total global food production, we should not ignore the role that all gene technologies—including breeding—have played in displacing small farmers, depleting rural communities and shifting economic control of agriculture into a small circle of powerful actors. Globally, these changes have had disproportionately harmful effects on women and people of color.
Combined with mechanization and chemicals, gene technologies have freed planters from their dependence on impoverished and poorly educated field hands, but they did nothing to help the fieldworkers transition to a new line of work. These are the real problems that deserve the public's and the science community's attention, not the overly narrow worries about eating GMOs.
But these problems are viewed as "not ours" by agricultural insiders, and they continue to be ignored by scientists whose focus is solely on biology. Many of the concerns that are today viewed as "urban problems" or "social issues" have origins in agriculture. For example, in California tomatoes, the development of mechanical harvesting led to a rapid concentration of ownership and the displacement of thousands of field hands. In the South, similar technologies displaced black farmers working land owned by whites, causing migration to urban centers and unskilled jobs. I must fault the science community for a lack of willingness to even take the thrust of these more socially oriented critiques seriously.
The new suite of tools for genetic modification that go under the name "gene editing" promise greater precision. They should allow scientists to target the locus for new genes in a plant or animal genome, and minimize the chance for causing unwanted impacts on gene functioning. This added precision is reducing some of the uncertainties in the mind of technology developers, and they have been expressing hope that their own confidence will be shared by regulators and by the public at large. In fact, the U.S. government recently issued a statement that gene-edited crops do not require additional regulation because they're just as safe as crops produced through conventional breeding.
It is indeed possible that the public doubts about genetically modified food will be assuaged by this argument. We can only wait and see. Whether or not gene editing will lead to more reflection about agriculture's complicity in problems of economic inequality or structural racism depends much more on the culture of the science community than it does on the technology itself.
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.