Democratize the White Coat by Honoring Black, Indigenous, and People of Color in Science
This article is part of the magazine, "The Future of Science In America: The Election Issue," co-published by LeapsMag, the Aspen Institute Science & Society Program, and GOOD.
Journalists, educators, and curators have responded to Black Lives Matter by highlighting the history and achievements of Black Americans in a variety of fields, including science. The movement has also sparked important demands to address longstanding scientific inequities such as lack of access to quality healthcare and the disproportionate impact of climate change and environmental pollution on neighborhoods of Black, Indigenous, and people of color (BIPOC). Making such improvements requires bringing BIPOC into science and into positions of leadership in laboratories, graduate schools, medical practices, and clinical trials. The moment is right to challenge scientific gatekeepers to respond to Black Lives Matter by widening the pathways that determine who becomes a scientist, a researcher, or a clinician.
The scientific workforce has long lacked diversity, which in turn discourages Black people from pursuing such careers. Causes include a dearth of mentors and role models, preconceived notions that science is exclusive to white males, and subpar STEM education. Across race, gender, class, ability, and all other dimensions that inform how an individual navigates the world, from the familial to the global level, seeing role models who resemble you impacts what you strive for and believe possible. As Marian Wright Edelman stated, "You can't be what you can't see"—a truth with ever-increasing resonance since the U.S. is projected to be minority-white by 2045.
Black Americans have paved the way for the nation to lead in science and technology, despite marginalization and exclusion from textbooks. Physicist Dr. Shirley Ann Jackson invented the technology behind Caller I.D. and Call Waiting. Otis Boykin's patents made televisions and radios what they are today. Thanks to the 2017 movie Hidden Figures, millions of Americans know about Katherine Johnson, the NASA mathematician whose calculations were essential to the successful trajectory of the Apollo 11 mission.
However, highlighting past role models who were Black achievers is not enough and paints too static a picture—especially when examples of transformative work by contemporary BIPOC scientists serving BIPOC communities abound. Cognitive neuroscientist Dr. Jonathan Jackson founded the Community Access, Recruitment, & Engagement (CARE) Research Center with the goal to break down barriers so that people of color participate in clinical trials. Geneticist Dr. Nanibaa' Garrison's research creates ethical frameworks to overcome genomic injustices so Indigenous populations can benefit from genetic research. Computer scientists Joy Buolamwini and Dr. Timnit Gebru's research drew attention to reinforced racial bias in artificial intelligence, leading Microsoft, Amazon, and IBM this summer to halt use of their facial recognition software.
"Integration does not mean equality if the space being integrated isn't exuberantly down for the cause."
In order to honor concretely the ubiquitous public statements and commitments to justice and equity that flooded everyone's inboxes in early June, we must include traditionally underrepresented voices in all phases of science and its applications. For guidance, we would benefit from listening to activists leading, for example, climate marches and protests over toxic water. Indeed, science is at the core of the issues for which young BIPOC are mobilizing. We need to sit down with these individuals to gain their input on how the narratives, practices, and opportunities in science should change. As Zeena Abdulkarim, a youth climate change organizer working with Zero Hour, explains: "Minority communities are exposed to what the privileged and people in power are not; therefore these communities know the right steps to take in the change we need for the kickstart of true social and environmental justice."
Two other Black youth, for example, used the platform of the laboratory while in high school to mobilize for change. Elle Lanair Lett, now specializing in epidemiology as an M.D.-Ph.D. student in Philadelphia, was prompted by family prevalence of diabetes to research the genetics of pancreatic cells. Dr. Otana Jakpor, now an ophthalmology resident in Michigan, was motivated by the pollution in her hometown of Riverside, California, to research the pulmonary effects of indoor air purifiers, with findings that influenced California ozone regulations. Both became finalists in a national science fair, propelling them on paths toward science careers. These young scientists demonstrate how people's communities and lived experiences can shape trajectories of science research, which, in turn, determines which visions for society are materialized and popularized.
We can also gain insight from another childhood science fair veteran, self-proclaimed "Black STEMinist" Augusta Uwamanzu-Nna, who graduated from college in May and works as a bioengineer. In her view, "we need to shift the burden away from Black people and onto individuals who have contributed to our current reality—fundamentally requiring understanding, open-mindedness, a lack of bias, cultural competency, anti-racism, anti-homophobia, and many, many other things."
Celebrating BIPOC's accomplishments in science and cultivating new leadership today are strong first steps to make science a guiding force for all. Ms. Uwamanzu-Nna keenly reminds us, "Integration does not mean equality if the space being integrated isn't exuberantly down for the cause." Indeed, educational institutions, scientific companies, and medical centers must acknowledge and embrace their role in democratizing science in order for society to realize racial and scientific justice.
[Editor's Note: To read other articles in this special magazine issue, visit the beautifully designed e-reader version.]
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.