Where Are the Lab-Grown Replacement Organs?
The headline blared from newspapers all the way back in 2006: "First Lab-Grown Organs Implanted in Humans!" A team from Wake Forest University had biopsied cells from the bladders of patients with spina bifida and used them to create brand new full-size bladders, which they then implanted. Although the bladders had to be emptied via catheter, they were still functioning a few years after implantation, and the public grew confident that doctors had climbed an intermediary step on the way to the medicine of science fiction. Ten years later, though, more than 20 people a day are still dying while waiting for an organ transplant, which leads to a simple question: Where are our fake organs?
"We can make small organs and tissues but we can't make larger ones."
Not coming anytime soon, unfortunately. The company that was created to transition Wake Forest's bladders to the market failed. And while there are a few simple bioengineered skins and cartilages already on the market, they are hardly identical to the real thing. Something like a liver could take another 20 to 25 years, says Shay Soker, professor at Wake Forest's Institute for Regenerative Medicine. "The first barrier is the technology: We can make small organs and tissues but we can't make larger ones," he says. "Also there are several cell types or functions that you can reliably make from stem cells, but not all of them, so the technology of stem cells has to catch up with what the body can do." Finally, he says, you have support the new organ inside the body, providing it with a circulatory and nervous system and integrating it with the immune system.
While these are all challenging problems, circulation appears to be the most intractable. "Tissue's not able to survive if the cells don't have oxygen, and the bigger it gets, the more complex vasculature you need to keep that alive," says Chiara Ghezzi, research professor in the Tufts University Department of Biomedical Engineering. "Vasculature is highly organized in the body. It has a hierarchical structure, with different branches that have different roles depending on where they are." So far, she says, researchers have had trouble scaling up from capillaries to larger vessels that could be grafted onto blood vessels in a patient's body.
"The FDA is still getting its hands and minds around the field of tissue engineering."
Last, but hardly least, is the question of FDA approval. Lab-grown organs are neither drugs nor medical devices, and the agency is not set up to quickly or easily approve new technologies that don't fit into current categories. "The FDA is still getting its hands and minds around the field of tissue engineering," says Soker. "They were not used to that… so it requires the regulatory and financial federal agencies to really help and support these initiatives."
A pencil eraser-size model of the human brain is now being used for drug development and research.
If all of this sounds discouraging, it's worth mentioning some of the incredible progress the field has made since the first strides toward lab-grown organs began nearly 30 years ago: Though full-size replacement organs are still decades away, many labs have diverted their resources into what they consider an intermediate step, developing miniature organs and systems that can be used for drug development and research. This platform will yield more relevant results (Imagine! Testing cardiovascular drugs on an actual human heart!) and require the deaths of far fewer animals. And it's already here: Two years ago, scientists at Ohio State University developed a pencil eraser-size model of the human brain they intend to use for this exact purpose.
Perhaps the most exciting line of research these days is one that at first doesn't seem to have anything to do with bioengineered organs at all. Along with his colleagues, Chandan Sen, Director of the Center for Regenerative Medicine and Cell-based Therapies at Ohio State University, has developed a nanoscale chip that can turn any cell in the body into any other kind of cell—reverting fully differentiated adult cells into, essentially, stem cells, which can then grow into any tissue you want. Sen has used his chip to reprogram skin cells in the bodies of mice into neurons to help them recover from strokes, and blood vessels to save severe leg injuries. "There's this concept of a bioreactor, where you convince an organ to grow outside the body. They're getting more and more sophisticated over time. But to my mind it will never match the sophistication or complexity of the human body," Sen says. "I believe that in order to have an organ that behaves the way you want it to in the live body, you must use the body itself as a bioreactor, not a bunch of electronic gadgetry." There you have it, the next step in artificial organ manufacture is as crazy as it is intuitive: Grow it back where it was in the first place.
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.