A simple ten-minute universal cancer test that can be detected by the human eye or an electronic device - published in Nature Communications (Dec 2018) by the Trau lab at the University of Queensland. Red indicates the presence of cancerous cells and blue doesn't.
Matt Trau, a professor of chemistry at the University of Queensland, stunned the science world back in December when the prestigious journal Nature Communications published his lab's discovery about a unique property of cancer DNA that could lead to a simple, cheap, and accurate test to detect any type of cancer in under 10 minutes.
No one believed it. I didn't believe it. I thought, "Gosh, okay, maybe it's a fluke."
Trau granted very few interviews in the wake of the news, but he recently opened up to leapsmag about the significance of this promising early research. Here is his story in his own words, as told to Editor-in-Chief Kira Peikoff.
There's been an incredible explosion of knowledge over the past 20 years, particularly since the genome was sequenced. The area of diagnostics has a tremendous amount of promise and has caught our lab's interest. If you catch cancer early, you can improve survival rates to as high as 98 percent, sometimes even now surpassing that.
My lab is interested in devices to improve the trajectory of cancer patients. So, once people get diagnosed, can we get really sophisticated information about the molecular origins of the disease, and can we measure it in real time? And then can we match that with the best treatment and monitor it in real time, too?
I think those approaches, also coupled with immunotherapy, where one dreams of monitoring the immune system simultaneously with the disease progress, will be the future.
But currently, the methodologies for cancer are still pretty old. So, for example, let's talk about biopsies in general. Liquid biopsy just means using a blood test or a urine test, rather than extracting out a piece of solid tissue. Now consider breast cancer. Still, the cutting-edge screening method is mammography or the physical interrogation for lumps. This has had a big impact in terms of early detection and awareness, but it's still primitive compared to interrogating, forensically, blood samples to look at traces of DNA.
Large machines like CAT scans, PET scans, MRIs, are very expensive and very subjective in terms of the operator. They don't look at the root causes of the cancer. Cancer is caused by changes in DNA. These can be changes in the hard drive of the DNA (the genomic changes) or changes in the apps that the DNA are running (the epigenetics and the transcriptomics).
We don't look at that now, even though we have, emerging, all of these technologies to do it, and those technologies are getting so much cheaper. I saw some statistics at a conference just a few months ago that, in the United States, less than 1 percent of cancer patients have their DNA interrogated. That's the current state-of-the-art in the modern medical system.
Professor Matt Trau, a cancer researcher at the University of Queensland in Australia.
(Courtesy)
Blood, as the highway of the body, is carrying all of this information. Cancer cells, if they are present in the body, are constantly getting turned over. When they die, they release their contents into the blood. Many of these cells end up in the urine and saliva. Having technologies that can forensically scan the highways looking for evidence of cancer is little bit like looking for explosives at the airport. That's very valuable as a security tool.
The trouble is that there are thousands of different types of cancer. Going back to breast cancer, there's at least a dozen different types, probably more, and each of them change the DNA (the hard drive of the disease) and the epigenetics (or the RAM memory). So one of the problems for diagnostics in cancer is to find something that is a signature of all cancers. That's been a really, really, really difficult problem.
Ours was a completely serendipitous discovery. What we found in the lab was this one marker that just kept coming up in all of the types of breast cancers we were studying.
No one believed it. I didn't believe it. I thought, "Gosh, okay, maybe it's a fluke, maybe it works just for breast cancer." So we went on to test it in prostate cancer, which is also many different types of diseases, and it seemed to be working in all of those. We then tested it further in lymphoma. Again, many different types of lymphoma. It worked across all of those. We tested it in gastrointestinal cancer. Again, many different types, and still, it worked, but we were skeptical.
Then we looked at cell lines, which are cells that have come from previous cancer patients, that we grow in the lab, but are used as model experimental systems. We have many of those cell lines, both ones that are cancerous, and ones that are healthy. It was quite remarkable that the marker worked in all of the cancer cell lines and didn't work in the healthy cell lines.
What could possibly be going on?
Well, imagine DNA as a piece of string, that's your hard drive. Epigenetics is like the beads that you put on that string. Those beads you can take on and off as you wish and they control which apps are run, meaning which genetic programs the cell runs. We hypothesized that for cancer, those beads cluster together, rather than being randomly distributed across the string.
Ultimately, I see this as something that would be like a pregnancy test you could take at your doctor's office.
The implications of this are profound. It means that DNA from cancer folds in water into three-dimensional structures that are very different from healthy cells' DNA. It's quite literally the needle in a haystack. Because when you do a liquid biopsy for early detection of cancer, most of the DNA from blood contains a vast abundance of healthy DNA. And that's not of interest. What's of interest is to find the cancerous DNA. That's there only in trace.
Once we figured out what was going on, we could easily set up a system to detect the trace cancerous DNA. It binds to gold nanoparticles in water and changes color. The test takes 10 minutes, and you can detect it by eye. Red indicates cancer and blue doesn't.
We're very, very excited about where we go from here. We're starting to test the test on a greater number of cancers, in thousands of patient samples. We're looking to the scientific community to engage with us, and we're getting a really good response from groups around the world who are supplying more samples to us so we can test this more broadly.
We also are very interested in testing how early can we go with this test. Can we detect cancer through a simple blood test even before there are any symptoms whatsoever? If so, we might be able to convert a cancer diagnosis to something almost as good as a vaccine.
Of course, we have to watch what are called false positives. We don't want to be detecting people as positives when they don't have cancer, and so the technology needs to improve there. We see this version as the iPhone 1. We're interested in the iPhone 2, 3, 4, getting better and better.
Ultimately, I see this as something that would be like a pregnancy test you could take at your doctor's office. If it came back positive, your doctor could say, "Look, there's some news here, but actually, it's not bad news, it's good news. We've caught this so early that we will be able to manage this, and this won't be a problem for you."
If this were to be in routine use in the medical system, countless lives could be saved. Cancer is now becoming one of the biggest killers in the world. We're talking millions upon millions upon millions of people who are affected. This really motivates our work. We might make a difference there.
Doctors used new eye drops to treat a rare genetic disorder.
The gene therapy: In May 2023, the FDA approved Vyjuvek, the first gene therapy to treat DEB.
Vyjuvek uses an inactivated herpes simplex virus to deliver working copies of the gene for collagen 7 to the body’s cells. In small trials, 65 percent of DEB-caused wounds sprinkled with it healed completely, compared to just 26 percent of wounds treated with a placebo.
“It was like looking through thick fog.” -- Antonio Vento Carvajal.
The patient: Antonio Vento Carvajal, a 14 year old living in Florida, was one of the trial participants to benefit from Vyjuvek, which was developed by Pittsburgh-based pharmaceutical company Krystal Biotech.
While the topical gene therapy could help his skin, though, it couldn’t do anything to address the severe vision loss Antonio experienced due to his DEB. He’d undergone multiple surgeries to have scar tissue removed from his eyes, but due to his condition, the blisters keep coming back.
“It was like looking through thick fog,” said Antonio, noting how his impaired vision made it hard for him to play his favorite video games. “I had to stand up from my chair, walk over, and get closer to the screen to be able to see.”
The idea: Encouraged by how Antonio’s skin wounds were responding to the gene therapy, Alfonso Sabater, his doctor at the Bascom Palmer Eye Institute, reached out to Krystal Biotech to see if they thought an alternative formula could potentially help treat his patient’s eyes.
The company was eager to help, according to Sabater, and after about two years of safety and efficacy testing, he had permission, under the FDA’s compassionate use protocol, to treat Antonio’s eyes with a version of the topical gene therapy delivered as eye drops.
The results: In August 2022, Sabater once again removed scar tissue from Antonio’s right eye, but this time, he followed up the surgery by immediately applying eye drops containing the gene therapy.
“I would send this message to other families in similar situations, whether it’s DEB or another condition that can benefit from genetic therapy. Don’t be afraid.” -- Yunielkys “Yuni” Carvajal.
The vision in Antonio’s eye steadily improved. By about eight months after the treatment, it was just slightly below average (20/25) and stayed that way. In March 2023, Sabater performed the same procedure on his young patient’s other eye, and the vision in it has also steadily improved.
“I’ve seen the transformation in Antonio’s life,” said Sabater. “He’s always been a happy kid. Now he’s very happy. He can function pretty much normally. He can read, he can study, he can play video games.”
Looking ahead: The topical gene therapy isn’t a permanent fix — it doesn’t alter Antonio’s own genes, so he has to have the eye drops reapplied every month. Still, that’s far less invasive than having to undergo repeated surgeries.
Sabater is now working with Krystal Biotech to launch trials of the eye drops in other patients, and not just those with DEB. By changing the gene delivered by the therapy, he believes it could be used to treat other eye disorders that are far more common — Fuchs’ dystrophy, for example, affects the vision of an estimated 300 million people over the age of 30.
Antonio’s mother, Yunielkys “Yuni” Carvajal, meanwhile, has said that having her son be the first to receive the eye drops was “very scary,” but she’s hopeful others will take a chance on new gene therapies if given the opportunity.
“I would send this message to other families in similar situations, whether it’s DEB or another condition that can benefit from genetic therapy,” she said. “Don’t be afraid.”
This article originally appeared on Freethink, home of the brightest minds and biggest ideas of all time.
A chatbot from the nonprofit National Eating Disorders Association aimed to provide 24/7 guidance on eating disorders. Several drawbacks point to the importance of therapist-tech collaboration in multiple areas of health.
Then everything went off the rails. Tessa told Maxwell an unequivocal yes, and that “it’s important to approach weight loss with a balanced and realistic mindset,” and recommended eating whole foods and lean proteins to create a 500-1000 calorie per day deficit that would lead to a loss of 1-2 pounds per week. To most people, the advice sounds anodyne, but alarm bells sounded in Maxwell’s head.
“This is actively going to feed eating disorders,” Maxwell says. “Having a chatbot be the direct response to someone reaching out for support for an eating disorder instead of the helpline seems careless.”
“The scripts that are being fed into the chatbot are only going to be as good as the person who’s feeding them.” -- Alexis Conason.
According to several decades of research, deliberate weight loss in the form of dieting is a serious risk for people with eating disorders. Maxwell says that following medical advice like what Tessa prescribed was what triggered her eating disorder as a child. And Maxwell wasn’t the only one who got such advice from the bot. When eating disorder therapist Alexis Conason tried Tessa, she asked the AI chatbot many of the questions her patients had. But instead of getting connected to resources or guidance on recovery, Conason, too, got tips on losing weight and “healthy” eating.
“The scripts that are being fed into the chatbot are only going to be as good as the person who’s feeding them,” Conason says. “It’s important that an eating disorder organization like NEDA is not reinforcing that same kind of harmful advice that we might get from medical providers who are less knowledgeable.”
Maxwell’s post about Tessa on Instagram went viral, and within days, NEDA had scrubbed all evidence of Tessa from its website. The furor has raised any number of issues about the harm perpetuated by a leading eating disorder charity and the ongoing influence of diet culture and advice that is pervasive in the field. But for AI experts, bears and bulls alike, Tessa offers a cautionary tale about what happens when a still-immature technology is unfettered and released into a vulnerable population.
Given the complexity involved in giving medical advice, the process of developing these chatbots must be rigorous and transparent, unlike NEDA’s approach.
“We don’t have a full understanding of what’s going on in these models. They’re a black box,” says Stephen Schueller, a clinical psychologist at the University of California, Irvine.
The health crisis
In March 2020, the world dove head-first into a heavily virtual world as countries scrambled to try and halt the pandemic. Even with lockdowns, hospitals were overwhelmed by the virus. The downstream effects of these lifesaving measures are still being felt, especially in mental health. Anxiety and depression are at all-time highs in teens, and a new report in The Lancet showed that post-Covid rates of newly diagnosed eating disorders in girls aged 13-16 were 42.4 percent higher than previous years.
And the crisis isn’t just in mental health.
“People are so desperate for health care advice that they'll actually go online and post pictures of [their intimate areas] and ask what kind of STD they have on public social media,” says John Ayers, an epidemiologist at the University of California, San Diego.
For many people, the choice isn’t chatbot vs. well-trained physician, but chatbot vs. nothing at all.
I know a bit about that desperation. Like Maxwell, I have struggled with a multi-decade eating disorder. I spent my 20s and 30s bouncing from crisis to crisis. I have called suicide hotlines, gone to emergency rooms, and spent weeks-on-end confined to hospital wards. Though I have found recovery in recent years, I’m still not sure what ultimately made the difference. A relapse isn't improbably, given my history. Even if I relapsed again, though, I don’t know it would occur to me to ask an AI system for help.
For one, I am privileged to have assembled a stellar group of outpatient professionals who know me, know what trips me up, and know how to respond to my frantic texts. Ditto for my close friends. What I often need is a shoulder to cry on or a place to vent—someone to hear and validate my distress. What’s more, my trust in these individuals far exceeds my confidence in the companies that create these chatbots. The Internet is full of health advice, much of it bad. Even for high-quality, evidence-based advice, medicine is often filled with disagreements about how the evidence might be applied and for whom it’s relevant. All of this is key in the training of AI systems like ChatGPT, and many AI companies remain silent on this process, Schueller says.
The problem, Ayers points out, is that for many people, the choice isn’t chatbot vs. well-trained physician, but chatbot vs. nothing at all. Hence the proliferation of “does this infection make my scrotum look strange?” questions. Where AI can truly shine, he says, is not by providing direct psychological help but by pointing people towards existing resources that we already know are effective.
“It’s important that these chatbots connect [their users to] to provide that human touch, to link you to resources,” Ayers says. “That’s where AI can actually save a life.”
Before building a chatbot and releasing it, developers need to pause and consult with the communities they hope to serve.
Unfortunately, many systems don’t do this. In a study published last month in the Journal of the American Medical Association, Ayers and colleagues found that although the chatbots did well at providing evidence-based answers, they often didn’t provide referrals to existing resources. Despite this, in an April 2023 study, Ayers’s team found that both patients and professionals rated the quality of the AI responses to questions, measured by both accuracy and empathy, rather highly. To Ayers, this means that AI developers should focus more on the quality of the information being delivered rather than the method of delivery itself.
Many mental health professionals have months-long waitlists, which leaves individuals to deal with illnesses on their own.
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The human touch
The mental health field is facing timing constraints, too. Even before the pandemic, the U.S. suffered from a shortage of mental health providers. Since then, the rates of anxiety, depression, and eating disorders have spiked even higher, and many mental health professionals report waiting lists that are months long. Without support, individuals are left to try and cope on their own, which often means their condition deteriorates even further.
Nor do mental health crises happen during office hours. I struggled the most late at night, long after everyone else had gone to bed. I needed support during those times when I was most liable to hurt myself, not in the mornings and afternoons when I was at work.
In this sense, a 24/7 chatbot makes lots of sense. “I don't think we should stifle innovation in this space,” Schueller says. “Because if there was any system that needs to be innovated, it's mental health services, because they are sadly insufficient. They’re terrible.”
But before building a chatbot and releasing it, Tina Hernandez-Boussard, a data scientist at Stanford Medicine, says that developers need to pause and consult with the communities they hope to serve. It requires a deep understanding of what their needs are, the language they use to describe their concerns, existing resources, and what kinds of topics and suggestions aren’t helpful. Even asking a simple question at the beginning of a conversation such as “Do you want to talk to an AI or a human?” could allow those individuals to pick the type of interaction that suits their needs, Hernandez-Boussard says.
NEDA did none of these things before deploying Tessa. The researchers who developed the online body positivity self-help program upon which Tessa was initially based created a set of online question-and-answer exercises to improve body image. It didn’t involve generative AI that could write its own answers. The bot deployed by NEDA did use generative AI, something that no one in the eating disorder community was aware of before Tessa was brought online. Consulting those with lived experience would have flagged Tessa’s weight loss and “healthy eating” recommendations, Conason says.
The question for healthcare isn’t whether to use AI, but how.
NEDA did not comment on initial Tessa’s development and deployment, but a spokesperson told Leaps.org that “Tessa will be back online once we are confident that the program will be run with the rule-based approach as it was designed.”
The tech and therapist collaboration
The question for healthcare isn’t whether to use AI, but how. Already, AI can spot anomalies on medical images with greater precision than human eyes and can flag specific areas of an image for a radiologist to review in greater detail. Similarly, in mental health, AI should be an add-on for therapy, not a counselor-in-a-box, says Aniket Bera, an expert on AI and mental health at Purdue University.
“If [AIs] are going to be good helpers, then we need to understand humans better,” Bera says. That means understanding what patients and therapists alike need help with and respond to.
One of the biggest challenges of struggling with chronic illness is the dehumanization that happens. You become a patient number, a set of laboratory values and test scores. Treatment is often dictated by invisible algorithms and rules that you have no control over or access to. It’s frightening and maddening. But this doesn’t mean chatbots don’t have any place in medicine and mental health. An AI system could help provide appointment reminders and answer procedural questions about parking and whether someone should fast before a test or a procedure. They can help manage billing and even provide support between outpatient sessions by offering suggestions for what coping skills to use, the best ways to manage anxiety, and point to local resources. As the bots get better, they may eventually shoulder more and more of the burden of providing mental health care. But as Maxwell learned with Tessa, it’s still no replacement for human interaction.
“I'm not suggesting we should go in and start replacing therapists with technologies,” Schueller says. Instead, he advocates for a therapist-tech collaboration. “The technology side and the human component—these things need to come together.”