The New Prospective Parenthood: When Does More Info Become Too Much?
Peggy Clark was 12 weeks pregnant when she went in for a nuchal translucency (NT) scan to see whether her unborn son had Down syndrome. The sonographic scan measures how much fluid has accumulated at the back of the baby's neck: the more fluid, the higher the likelihood of an abnormality. The technician said the baby was in such an odd position, the test couldn't be done. Clark, whose name has been changed to protect her privacy, was told to come back in a week and a half to see if the baby had moved.
"With the growing sophistication of prenatal tests, it seems that the more questions are answered, the more new ones arise."
"It was like the baby was saying, 'I don't want you to know,'" she recently recalled.
When they went back, they found the baby had a thickened neck. It's just one factor in identifying Down's, but it's a strong indication. At that point, she was 13 weeks and four days pregnant. She went to the doctor the next day for a blood test. It took another two weeks for the results, which again came back positive, though there was still a .3% margin of error. Clark said she knew she wanted to terminate the pregnancy if the baby had Down's, but she didn't want the guilt of knowing there was a small chance the tests were wrong. At that point, she was too late to do a Chorionic villus sampling (CVS), when chorionic villi cells are removed from the placenta and sequenced. And she was too early to do an amniocentesis, which isn't done until between 14 and 20 weeks of the pregnancy. So she says she had to sit and wait, calling those few weeks "brutal."
By the time they did the amnio, she was already nearly 18 weeks pregnant and was getting really big. When that test also came back positive, she made the anguished decision to end the pregnancy.
Now, three years after Clark's painful experience, a newer form of prenatal testing routinely gives would-be parents more information much earlier on, especially for women who are over 35. As soon as nine weeks into their pregnancies, women can have a simple blood test to determine if there are abnormalities in the DNA of chromosomes 21, which indicates Down syndrome, as well as in chromosomes 13 and 18. Using next-generation sequencing technologies, the test separates out and examines circulating fetal cells in the mother's blood, which eliminates the risks of drawing fluid directly from the fetus or placenta.
"Finding out your baby has Down syndrome at 11 or 12 weeks is much easier for parents to make any decision they may want to make, as opposed to 16 or 17 weeks," said Dr. Leena Nathan, an obstetrician-gynecologist in UCLA's healthcare system. "People are much more willing or able to perhaps make a decision to terminate the pregnancy."
But with the growing sophistication of prenatal tests, it seems that the more questions are answered, the more new ones arise--questions that previous generations have never had to face. And as genomic sequencing improves in its predictive accuracy at the earliest stages of life, the challenges only stand to increase. Imagine, for example, learning your child's lifetime risk of breast cancer when you are ten weeks pregnant. Would you terminate if you knew she had a 70 percent risk? What about 40 percent? Lots of hard questions. Few easy answers. Once the cost of whole genome sequencing drops low enough, probably within the next five to ten years according to experts, such comprehensive testing may become the new standard of care. Welcome to the future of prospective parenthood.
"In one way, it's a blessing to have this information. On the other hand, it's very difficult to deal with."
How Did We Get Here?
Prenatal testing is not new. In 1979, amniocentesis was used to detect whether certain inherited diseases had been passed on to the fetus. Through the 1980s, parents could be tested to see if they carried disease like Tay-Sachs, Sickle cell anemia, Cystic fibrosis and Duchenne muscular dystrophy. By the early 1990s, doctors could test for even more genetic diseases and the CVS test was beginning to become available.
A few years later, a technique called preimplantation genetic diagnosis (PGD) emerged, in which embryos created in a lab with sperm and harvested eggs would be allowed to grow for several days and then cells would be removed and tested to see if any carried genetic diseases. Those that weren't affected could be transferred back to the mother. Once in vitro fertilization (IVF) took off, so did genetic testing. The labs test the embryonic cells and get them back to the IVF facilities within 24 hours so that embryo selection can occur. In the case of IVF, genetic tests are done so early, parents don't even have to decide whether to terminate a pregnancy. Embryos with issues often aren't even used.
"It was a very expensive endeavor but exciting to see our ability to avoid disorders, especially for families that don't want to terminate a pregnancy," said Sara Katsanis, an expert in genetic testing who teaches at Duke University. "In one way, it's a blessing to have this information (about genetic disorders). On the other hand, it's very difficult to deal with. To make that decision about whether to terminate a pregnancy is very hard."
Just Because We Can, Does It Mean We Should?
Parents in the future may not only find out whether their child has a genetic disease but will be able to potentially fix the problem through a highly controversial process called gene editing. But because we can, does it mean we should? So far, genes have been edited in other species, but to date, the procedure has not been used on an unborn child for reproductive purposes apart from research.
"There's a lot of bioethics debate and convening of groups to try to figure out where genetic manipulation is going to be useful and necessary, and where it is going to need some restrictions," said Katsanis. She notes that it's very useful in areas like cancer research, so one wouldn't want to over-regulate it.
There are already some criteria as to which genes can be manipulated and which should be left alone, said Evan Snyder, professor and director of the Center for Stem Cells and Regenerative Medicine at Sanford Children's Health Research Center in La Jolla, Calif. He noted that genes don't stand in isolation. That is, if you modify one that causes disease, will it disrupt others? There may be unintended consequences, he added.
"As the technical dilemmas get fixed, some of the ethical dilemmas get fixed. But others arise. It's kind of like ethical whack-a-mole."
But gene editing of embryos may take years to become an acceptable practice, if ever, so a more pressing issue concerns the rationale behind embryo selection during IVF. Prospective parents can end up with anywhere from zero to thirty embryos from the procedure and must choose only one (rarely two) to implant. Since embryos are routinely tested now for certain diseases, and selected or discarded based on that information, should it be ethical—and legal—to make selections based on particular traits, too? To date so far, parents can select for gender, but no other traits. Whether trait selection becomes routine is a matter of time and business opportunity, Katsanis said. So far, the old-fashioned way of making a baby combined with the luck of the draw seems to be the preferred method for the marketplace. But that could change.
"You can easily see a family deciding not to implant a lethal gene for Tay-Sachs or Duchene or Cystic fibrosis. It becomes more ethically challenging when you make a decision to implant girls and not any of the boys," said Snyder. "And then as we get better and better, we can start assigning genes to certain skills and this starts to become science fiction."
Once a pregnancy occurs, prospective parents of all stripes will face decisions about whether to keep the fetus based on the information that increasingly robust prenatal testing will provide. What influences their decision is the crux of another ethical knot, said Snyder. A clear-cut rationale would be if the baby is anencephalic, or it has no brain. A harder one might be, "It's a girl, and I wanted a boy," or "The child will only be 5' 2" tall in adulthood."
"Those are the extremes, but the ultimate question is: At what point is it a legitimate response to say, I don't want to keep this baby?'" he said. Of course, people's responses will vary, so the bigger conundrum for society is: Where should a line be drawn—if at all? Should a woman who is within the legal scope of termination (up to around 24 weeks, though it varies by state) be allowed to terminate her pregnancy for any reason whatsoever? Or must she have a so-called "legitimate" rationale?
"As the technical dilemmas get fixed, some of the ethical dilemmas get fixed. But others arise. It's kind of like ethical whack-a-mole," Snyder said.
One of the newer moles to emerge is, if one can fix a damaged gene, for how long should it be fixed? In one child? In the family's whole line, going forward? If the editing is done in the embryo right after the egg and sperm have united and before the cells begin dividing and becoming specialized, when, say, there are just two or four cells, it will likely affect that child's entire reproductive system and thus all of that child's progeny going forward.
"This notion of changing things forever is a major debate," Snyder said. "It literally gets into metaphysics. On the one hand, you could say, well, wouldn't it be great to get rid of Cystic fibrosis forever? What bad could come of getting rid of a mutant gene forever? But we're not smart enough to know what other things the gene might be doing, and how disrupting one thing could affect this network."
As with any tool, there are risks and benefits, said Michael Kalichman, Director of the Research Ethics Program at the University of California San Diego. While we can envision diverse benefits from a better understanding of human biology and medicine, it is clear that our species can also misuse those tools – from stigmatizing children with certain genetic traits as being "less than," aka dystopian sci-fi movies like Gattaca, to judging parents for making sure their child carries or doesn't carry a particular trait.
"The best chance to ensure that the benefits of this technology will outweigh the risks," Kalichman said, "is for all stakeholders to engage in thoughtful conversations, strive for understanding of diverse viewpoints, and then develop strategies and policies to protect against those uses that are considered to be problematic."
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.