Jamie Rettinger with his now fiance Amie Purnel-Davis, who helped him through the clinical trial.
Melanoma is the deadliest form of skin cancer. About 85,000 people are diagnosed with it each year in the U.S. and more than 8,000 die of the cancer when it spreads to other parts of the body, according to the Centers for Disease Control and Prevention (CDC).
There are two peaks in diagnosis of melanoma; one is in younger women ages 30-40 and often is tied to past use of tanning beds; the second is older men 60+ and is related to outdoor activity from farming to sports. Light-skinned people have a twenty-times greater risk of melanoma than do people with dark skin.
"When I graduated from medical school, in 2005, melanoma was a death sentence" --Diwakar Davar.
Jamie had a follow up PET scan about six months after his surgery. A suspicious spot on his lung led to a biopsy that came back positive for melanoma. The cancer had spread. Treatment with a monoclonal antibody (nivolumab/Opdivo®) didn't prove effective and he was referred to the UPMC Hillman Cancer Center in Pittsburgh, a four-hour drive from his home in western Ohio.
An alternative monoclonal antibody treatment brought on such bad side effects, diarrhea as often as 15 times a day, that it took more than a week of hospitalization to stabilize his condition. The only options left were experimental approaches in clinical trials.
Early research
"When I graduated from medical school, in 2005, melanoma was a death sentence" with a cure rate in the single digits, says Diwakar Davar, 39, an oncologist at UPMC Hillman Cancer Center who specializes in skin cancer. That began to change in 2010 with introduction of the first immunotherapies, monoclonal antibodies, to treat cancer. The antibodies attach to PD-1, a receptor on the surface of T cells of the immune system and on cancer cells. Antibody treatment boosted the melanoma cure rate to about 30 percent. The search was on to understand why some people responded to these drugs and others did not.
At the same time, there was a growing understanding of the role that bacteria in the gut, the gut microbiome, plays in helping to train and maintain the function of the body's various immune cells. Perhaps the bacteria also plays a role in shaping the immune response to cancer therapy.
One clue came from genetically identical mice. Animals ordered from different suppliers sometimes responded differently to the experiments being performed. That difference was traced to different compositions of their gut microbiome; transferring the microbiome from one animal to another in a process known as fecal transplant (FMT) could change their responses to disease or treatment.
When researchers looked at humans, they found that the patients who responded well to immunotherapies had a gut microbiome that looked like healthy normal folks, but patients who didn't respond had missing or reduced strains of bacteria.
Davar and his team knew that FMT had a very successful cure rate in treating the gut dysbiosis of Clostridioides difficile, a persistant intestinal infection, and they wondered if a fecal transplant from a patient who had responded well to cancer immunotherapy treatment might improve the cure rate of patients who did not originally respond to immunotherapies for melanoma.
The ABCDE of melanoma detection
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Clinical trial
"It was pretty weird, I was totally blasted away. Who had thought of this?" Jamie first thought when the hypothesis was explained to him. But Davar's explanation that the procedure might restore some of the beneficial bacterial his gut was lacking, convinced him to try. He quickly signed on in October 2018 to be the first person in the clinical trial.
Fecal donations go through the same safety procedures of screening for and inactivating diseases that are used in processing blood donations to make them safe for transfusion. The procedure itself uses a standard hollow colonoscope designed to screen for colon cancer and remove polyps. The transplant is inserted through the center of the flexible tube.
Most patients are sedated for procedures that use a colonoscope but Jamie doesn't respond to those drugs: "You can't knock me out. I was watching them on the TV going up my own butt. It was kind of unreal at that point," he says. "There were about twelve people in there watching because no one had seen this done before."
A test two weeks after the procedure showed that the FMT had engrafted and the once-missing bacteria were thriving in his gut. More importantly, his body was responding to another monoclonal antibody (pembrolizumab/Keytruda®) and signs of melanoma began to shrink. Every three months he made the four-hour drive from home to Pittsburgh for six rounds of treatment with the antibody drug.
"We were very, very lucky that the first patient had a great response," says Davar. "It allowed us to believe that even though we failed with the next six, we were on the right track. We just needed to tweak the [fecal] cocktail a little better" and enroll patients in the study who had less aggressive tumor growth and were likely to live long enough to complete the extensive rounds of therapy. Six of 15 patients responded positively in the pilot clinical trial that was published in the journal Science.
Davar believes they are beginning to understand the biological mechanisms of why some patients initially do not respond to immunotherapy but later can with a FMT. It is tied to the background level of inflammation produced by the interaction between the microbiome and the immune system. That paper is not yet published.
Surviving cancer
It has been almost a year since the last in his series of cancer treatments and Jamie has no measurable disease. He is cautiously optimistic that his cancer is not simply in remission but is gone for good. "I'm still scared every time I get my scans, because you don't know whether it is going to come back or not. And to realize that it is something that is totally out of my control."
"It was hard for me to regain trust" after being misdiagnosed and mistreated by several doctors he says. But his experience at Hillman helped to restore that trust "because they were interested in me, not just fixing the problem."
He is grateful for the support provided by family and friends over the last eight years. After a pause and a sigh, the ruggedly built 47-year-old says, "If everyone else was dead in my family, I probably wouldn't have been able to do it."
"I never hesitated to ask a question and I never hesitated to get a second opinion." But Jamie acknowledges the experience has made him more aware of the need for regular preventive medical care and a primary care physician. That person might have caught his melanoma at an earlier stage when it was easier to treat.
Davar continues to work on clinical studies to optimize this treatment approach. Perhaps down the road, screening the microbiome will be standard for melanoma and other cancers prior to using immunotherapies, and the FMT will be as simple as swallowing a handful of freeze-dried capsules off the shelf rather than through a colonoscopy. Earlier this year, the Food and Drug Administration approved the first oral fecal microbiota product for C. difficile, hopefully paving the way for more.
An older version of this hit article was first published on May 18, 2021
Artificial Intelligence is already helping to grow some of the food we eat.
The chef-farmers choose from among 45 types of herb and leafy-greens seeds, plop them into grow trays, and a few weeks later they pick and serve. While success is predicated on at least a small amount of these humans’ care, the systems are autonomously surveilled round-the-clock from Babylon’s base of operations. And artificial intelligence is helping to run the show.
Babylon piloted the use of specialized cameras that take pictures in different spectrums to gather some less-obvious visual data about plants’ wellbeing and alert people if something seems off.
Imagine consistently perfect greens and tomatoes and strawberries, grown hyper-locally, using less water, without chemicals or environmental contaminants. This is the hefty promise of controlled environment agriculture (CEA) — basically, indoor farms that can be hydroponic, aeroponic (plant roots are suspended and fed through misting), or aquaponic (where fish play a role in fertilizing vegetables). But whether they grow 4,160 leafy-green servings per year, like one Babylon farm, or millions of servings, like some of the large, centralized facilities starting to supply supermarkets across the U.S., they seek to minimize failure as much as possible.
Babylon’s soilless hydroponic growing system
Courtesy Babylon Micro-Farms
Here, AI is starting to play a pivotal role. CEA growers use it to help “make sense of what’s happening” to the plants in their care, says Scott Lowman, vice president of applied research at the Institute for Advanced Learning and Research (IALR) in Virginia, a state that’s investing heavily in CEA companies. And although these companies say they’re not aiming for a future with zero human employees, AI is certainly poised to take a lot of human farming intervention out of the equation — for better and worse.
Most of these companies are compiling their own data sets to identify anything that might block the success of their systems. Babylon had already integrated sensor data into its farms to measure heat and humidity, the nutrient content of water, and the amount of light plants receive. Last year, they got a National Science Foundation grant that allowed them to pilot the use of specialized cameras that take pictures in different spectrums to gather some less-obvious visual data about plants’ wellbeing and alert people if something seems off. “Will this plant be healthy tomorrow? Are there things…that the human eye can't see that the plant starts expressing?” says Amandeep Ratte, the company’s head of data science. “If our system can say, Hey, this plant is unhealthy, we can reach out to [users] preemptively about what they’re doing wrong, or is there a disease at the farm?” Ratte says. The earlier the better, to avoid crop failures.
Natural light accounts for 70 percent of Greenswell Growers’ energy use on a sunny day.
Courtesy Greenswell Growers
IALR’s Lowman says that other CEA companies are developing their AI systems to account for the different crops they grow — lettuces come in all shapes and sizes, after all, and each has different growing needs than, for example, tomatoes. The ways they run their operations differs also. Babylon is unusual in its decentralized structure. But centralized growing systems with one main location have variabilities, too. AeroFarms, which recently declared bankruptcy but will continue to run its 140,000-square foot vertical operation in Danville, Virginia, is entirely enclosed and reliant on the intense violet glow of grow lights to produce microgreens.
Different companies have different data needs. What data is essential to AeroFarms isn’t quite the same as for Greenswell Growers located in Goochland County, Virginia. Raising four kinds of lettuce in a 77,000-square-foot automated hydroponic greenhouse, the vagaries of naturally available light, which accounts for 70 percent of Greenswell’s energy use on a sunny day, affect operations. Their tech needs to account for “outside weather impacts,” says president Carl Gupton. “What adjustments do we have to make inside of the greenhouse to offset what's going on outside environmentally, to give that plant optimal conditions? When it's 85 percent humidity outside, the system needs to do X, Y and Z to get the conditions that we want inside.”
AI will help identify diseases, as well as when a plant is thirsty or overly hydrated, when it needs more or less calcium, phosphorous, nitrogen.
Nevertheless, every CEA system has the same core needs — consistent yield of high quality crops to keep up year-round supply to customers. Additionally, “Everybody’s got the same set of problems,” Gupton says. Pests may come into a facility with seeds. A disease called pythium, one of the most common in CEA, can damage plant roots. “Then you have root disease pressures that can also come internally — a change in [growing] substrate can change the way the plant performs,” Gupton says.
AI will help identify diseases, as well as when a plant is thirsty or overly hydrated, when it needs more or less calcium, phosphorous, nitrogen. So, while companies amass their own hyper-specific data sets, Lowman foresees a time within the next decade “when there will be some type of [open-source] database that has the most common types of plant stress identified” that growers will be able to tap into. Such databases will “create a community and move the science forward,” says Lowman.
In fact, IALR is working on assembling images for just such a database now. On so-called “smart tables” inside an Institute lab, a team is growing greens and subjects them to various stressors. Then, they’re administering treatments while taking images of every plant every 15 minutes, says Lowman. Some experiments generate 80,000 images; the challenge lies in analyzing and annotating the vast trove of them, marking each one to reflect outcome—for example increasing the phosphate delivery and the plant’s response to it. Eventually, they’ll be fed into AI systems to help them learn.
For all the enthusiasm surrounding this technology, it’s not without downsides. Training just one AI system can emit over 250,000 pounds of carbon dioxide, according to MIT Technology Review. AI could also be used “to enhance environmental benefit for CEA and optimize [its] energy consumption,” says Rozita Dara, a computer science professor at the University of Guelph in Canada, specializing in AI and data governance, “but we first need to collect data to measure [it].”
The chef-farmers can choose from 45 types of herb and leafy-greens seeds.
Courtesy Babylon Micro-Farms
Any system connected to the Internet of Things is also vulnerable to hacking; if CEA grows to the point where “there are many of these similar farms, and you're depending on feeding a population based on those, it would be quite scary,” Dara says. And there are privacy concerns, too, in systems where imaging is happening constantly. It’s partly for this reason, says Babylon’s Ratte, that the company’s in-farm cameras all “face down into the trays, so the only thing [visible] is pictures of plants.”
Tweaks to improve AI for CEA are happening all the time. Greenswell made its first harvest in 2022 and now has annual data points they can use to start making more intelligent choices about how to feed, water, and supply light to plants, says Gupton. Ratte says he’s confident Babylon’s system can already “get our customers reliable harvests. But in terms of how far we have to go, it's a different problem,” he says. For example, if AI could detect whether the farm is mostly empty—meaning the farm’s user hasn’t planted a new crop of greens—it can alert Babylon to check “what's going on with engagement with this user?” Ratte says. “Do they need more training? Did the main person responsible for the farm quit?”
Lowman says more automation is coming, offering greater ability for systems to identify problems and mitigate them on the spot. “We still have to develop datasets that are specific, so you can have a very clear control plan, [because] artificial intelligence is only as smart as what we tell it, and in plant science, there's so much variation,” he says. He believes AI’s next level will be “looking at those first early days of plant growth: when the seed germinates, how fast it germinates, what it looks like when it germinates.” Imaging all that and pairing it with AI, “can be a really powerful tool, for sure.”
Researchers from the University of Cambridge have laid the foundations for growing synthetic embryos that could develop a beating heart, gut and brain.
The organoid revolution
In 1981, scientists discovered how to keep stem cells alive. This was a significant breakthrough, as stem cells have notoriously rigorous demands. Nevertheless, stem cells remained a relatively niche research area, mainly because scientists didn’t know how to convince the cells to turn into other cells.
Then, in 1987, scientists embedded isolated stem cells in a gelatinous protein mixture called Matrigel, which simulated the three-dimensional environment of animal tissue. The cells thrived, but they also did something remarkable: they created breast tissue capable of producing milk proteins. This was the first organoid — a clump of cells that behave and function like a real organ. The organoid revolution had begun, and it all started with a boob in Jello.
For the next 20 years, it was rare to find a scientist who identified as an “organoid researcher,” but there were many “stem cell researchers” who wanted to figure out how to turn stem cells into other cells. Eventually, they discovered the signals (called growth factors) that stem cells require to differentiate into other types of cells.
For a human embryo (and its organs) to develop successfully, there needs to be a “dialogue” between these three types of stem cells.
By the end of the 2000s, researchers began combining stem cells, Matrigel, and the newly characterized growth factors to create dozens of organoids, from liver organoids capable of producing the bile salts necessary for digesting fat to brain organoids with components that resemble eyes, the spinal cord, and arguably, the beginnings of sentience.
Synthetic embryos
Organoids possess an intrinsic flaw: they are organ-like. They share some characteristics with real organs, making them powerful tools for research. However, no one has found a way to create an organoid with all the characteristics and functions of a real organ. But Magdalena Żernicka-Goetz, a developmental biologist, might have set the foundation for that discovery.
Żernicka-Goetz hypothesized that organoids fail to develop into fully functional organs because organs develop as a collective. Organoid research often uses embryonic stem cells, which are the cells from which the developing organism is created. However, there are two other types of stem cells in an early embryo: stem cells that become the placenta and those that become the yolk sac (where the embryo grows and gets its nutrients in early development). For a human embryo (and its organs) to develop successfully, there needs to be a “dialogue” between these three types of stem cells. In other words, Żernicka-Goetz suspected the best way to grow a functional organoid was to produce a synthetic embryoid.
As described in the aforementioned Nature paper, Żernicka-Goetz and her team mimicked the embryonic environment by mixing these three types of stem cells from mice. Amazingly, the stem cells self-organized into structures and progressed through the successive developmental stages until they had beating hearts and the foundations of the brain.
“Our mouse embryo model not only develops a brain, but also a beating heart [and] all the components that go on to make up the body,” said Żernicka-Goetz. “It’s just unbelievable that we’ve got this far. This has been the dream of our community for years and major focus of our work for a decade and finally we’ve done it.”
If the methods developed by Żernicka-Goetz’s team are successful with human stem cells, scientists someday could use them to guide the development of synthetic organs for patients awaiting transplants. It also opens the door to studying how embryos develop during pregnancy.
This article originally appeared on Big Think, home of the brightest minds and biggest ideas of all time.
