Slow-Growing Breast Cancer Cells May Explain Why Relapse Happens Decades Later

Researchers at Garvan Institute of Medical Research have identified a previously underappreciated mechanism that may explain why some breast cancers return many years, even decades, after apparently successful treatment.

The study, published in Nature Communications, reveals that certain estrogen receptor-positive (ER+) breast cancer cells survive therapy not by entering complete dormancy, but by continuing to divide at an extraordinarily slow pace. These stealth-like cells can gradually form microscopic secondary tumors that remain undetectable for years before eventually triggering metastatic relapse.

The findings offer new insight into one of the most persistent challenges in breast cancer care: why relapse can occur long after patients are considered cancer-free.

The long shadow of ER-positive breast cancer

ER-positive breast cancer is the most common subtype of breast cancer and is typically treated with hormone therapies designed to block estrogen signaling. These treatments are often highly effective at eliminating actively dividing tumor cells.

However, ER-positive disease has a unique clinical problem: recurrence risk persists for decades.

Even after five to ten years of endocrine therapy, up to 30% of patients can eventually develop metastatic relapse. Once breast cancer spreads to distant organs such as bone, lung, or brain, the disease becomes largely incurable.

Traditionally, relapse has been attributed to dormant cancer cells—cells that enter a state of complete hibernation before later “waking up.” But the new study suggests this may not be the only pathway.

“We have become very good at treating primary breast cancer, but late relapses remain a major challenge,” said Liz Caldon, associate professor and senior author of the study.

Not dormant—just incredibly slow

The researchers discovered that some breast cancer cells never fully stop proliferating during therapy. Instead, they survive by drastically slowing their rate of division.

This subtle distinction may be clinically critical.

Rather than entering complete cellular arrest, these cells continue to grow at an almost imperceptible pace, allowing them to evade therapies that primarily target rapidly dividing cells.

“Instead, they survive by growing extremely slowly in the background, until a tiny speck becomes a pebble,” Caldon explained.

Over many years, these microscopic lesions, known as micrometastases, can gradually expand until they become clinically detectable or disrupt vital organs.

The work challenges a long-standing binary view of cancer persistence in which tumor cells are considered either actively proliferating or fully dormant. Instead, the findings support the existence of an intermediate “slow-cycling” state that may be particularly effective at evading treatment.

Isolating the slowest cancer cells

Studying these rare cells was technically difficult because of their exceptionally slow growth.

The research team spent years isolating and cultivating these populations in the laboratory. Once established, they introduced the cells into preclinical models to determine whether slow proliferation impaired metastatic potential.

It did not.

Despite dividing slowly, the cells retained the ability to migrate throughout the body and colonize distant organs such as bone and lung.

“It took years to isolate these specific cells because they were dividing so slowly, almost in defiance of how we typically expect cancer to behave,” said Kristine Fernandez, first author of the study.

“These cells were migrating to organs like the bone and lungs, proving that speed isn’t everything when it comes to metastasis.”

The findings reinforce a growing understanding in oncology that aggressive cancer behavior is not solely defined by rapid proliferation. Cellular adaptability and survival under therapeutic pressure may be equally important.

Rac1 emerges as a potential therapeutic target

After identifying the slow-growing cells, the researchers investigated what allowed them to survive.

The study pinpointed a signaling pathway centered on Rac1, a protein involved in cell movement, structural organization, and survival. Using advanced biosensor imaging, the team directly visualized Rac1 pathway activation inside live slow-growing cancer cells.

Inhibiting this pathway appeared therapeutically promising.

Experimental Rac1 inhibitors significantly reduced tumor size and tumor number in patient-derived breast cancer models.

This suggests that targeting Rac1-dependent survival programs could potentially eliminate slow-growing residual cancer cells before they evolve into clinically significant metastases.

Rethinking cancer relapse biology

The findings contribute to a broader shift in cancer biology away from viewing residual disease as uniformly dormant.

Instead, tumors may contain multiple survival states, including cells that persist through continuous but ultra-slow proliferation. These populations may be especially dangerous because they remain biologically active while escaping conventional therapeutic detection.

The work also raises important clinical questions about long-term endocrine therapy. Current treatment durations are largely standardized, yet some patients may harbor persistent slow-cycling tumor cells despite years of therapy.

“If we can understand the specific biology of these slow-growing cells, we might eventually be able to offer better ways to track whether a decade of hormone therapy is actually working and ultimately prevent recurrence,” Caldon said.

Toward preventing late relapse

The study’s implications extend beyond breast cancer alone. Slow-cycling drug-tolerant cancer cells have increasingly been identified across multiple tumor types, including melanoma, lung cancer, and leukemia.

By identifying a concrete signaling mechanism underlying this state in ER-positive breast cancer, the research provides a potential therapeutic entry point for preventing relapse before metastatic disease emerges.

The next challenge will be determining whether Rac1 inhibitors, or similar approaches targeting slow-cycling survival programs, can safely and effectively eliminate residual cancer cells in patients.

If successful, such strategies could fundamentally alter how clinicians approach long-term relapse prevention in breast cancer, shifting the focus from simply suppressing visible disease to actively eradicating the hidden cellular reservoirs that remain years after treatment ends.

The post Slow-Growing Breast Cancer Cells May Explain Why Relapse Happens Decades Later appeared first on Inside Precision Medicine.

Asthma Drug Formoterol Shows Potential to Reverse MASH

Researchers at the Medical University of South Carolina (MUSC) have found evidence that the asthma medication formoterol may reverse metabolic dysfunction-associated steatohepatitis (MASH), a progressive fatty liver disease associated with obesity and type 2 diabetes that can lead to fibrosis, cirrhosis, liver failure, and liver transplantation. The research, published in npj Metabolic Health and Disease, arose unexpectedly as a result of findings on the use of formoterol in mouse models of diabetic kidney injury, which also showed that the mice had low levels of liver fat accumulation.

“Kind of unexpectedly, we found that the liver damage also reversed,” said senior author Joshua Lipschutz, MD, division director of nephrology and Arthur Williams Endowed Chair in nephrology at MUSC.

Based on this observation, the MUSC researchers initiated a study to find out whether the beta-2 adrenergic receptor pathway targeted by formoterol could influence metabolic disease in the liver as well as the kidney. According to the researchers, the connection between the diseases lies in shared metabolic dysfunction associated with type 2 diabetes relating to mitochondrial dysfunction and impaired energy metabolism.

To test the hypothesis, the team used a high-fat diet mouse model designed to mimic MASH. Mice fed the diet for 16 weeks developed liver steatosis and were subsequently treated with formoterol for four weeks. Testing of the mice after the four weeks of treatment found that steatosis was largely resolved as a result.

The evidence showed that formoterol increased mitochondrial biogenesis, a process that increases the number and function of mitochondria within cells.

“It looked like formoterol was rescuing the injury by increasing mitochondrial biogenesis,” Lischutz said. “It kind of revs up the mitochondria so they work better.”

The researcher noted that mice treated with formoterol had increased levels of PGC1α (a protein that helps control how cells produce and use energy) and electron transport chain proteins, along with an increase in mitochondrial proteins and lower lipid accumulation in liver tissue. Human HepaRG liver cells exposed to free fatty acids also showed reduced lipid accumulation and increased after formoterol treatment.

“The coordinated induction of oxidative phosphorylation and amino acid metabolism pathways suggests that formoterol may promote metabolic competence through non-lipid sources, including amino acids,” the researchers wrote.

While there were no approved drugs to treat MASH when the MUSC researchers initiated their study, current treatments still remain limited with resmetirom and semaglutide the only current approved therapies for this condition. Both medications have shown only limited efficacy in a subset of patients and have known side effects.

“All the current drugs for diabetic nephropathy only slow progression, but they don’t reverse the damage. This drug actually reversed the damage at the histologic, ultrastructural, and functional levels,” said Lipschutz.

Further, formoterol is already an approved and established medication that has been prescribed for year to treat both asthma and chronic obstructive pulmonary disease (COPD). Because its metabolic effects in humans and its safety profile has been detailed in its approval for these conditions, it could hasten approval for these other therapeutic uses.

“If you can repurpose something that’s approved and already being used safely, that’s kind of our dream as physician-scientists,” Lipschutz added.

Lipschutz and colleagues are currently conducting a clinical trial for the use of formoterol in chronic kidney disease (NCT07022418). Future research will focus on what dosing levels would be appropriate to use as treatment for CKD and MASH, whether inhaled delivery would be effective, and how durable the response to this potential treatment could be.

The post Asthma Drug Formoterol Shows Potential to Reverse MASH appeared first on Inside Precision Medicine.

STAT+: Trump pivots on kratom derivative 7-OH, floating approval for some forms

President Trump on Monday suggested the federal government could move to approve some forms of 7-OH, an opioid derived from the naturally occurring kratom plant.  

“We’re looking very seriously at natural 7-OH and getting that approved,” Trump said. 

It was not clear what Trump meant by “natural 7-OH.” Small amounts of the compound, shorthand for 7-hydroxymitragynine, occur naturally in kratom, which is increasingly used as a recreational drug and an unapproved pain treatment. While kratom is significantly less dangerous than potent synthetic opioids like fentanyl or prescription pain pills, it can still cause addiction and overdose. 

Continue to STAT+ to read the full story…

STAT+: Medicare’s miss on Alzheimer’s drug spending

This is the online version of STAT’s weekly email newsletter Health Care Inc. Sign up here.

Did you know the U.S. Mint requires gold coins to be made with American-made gold, but instead it gets illegally mined gold that can be traced back to a Colombian drug cartel? Truly mind-blowing stuff from this New York Times investigation. Let me know what the health care angle is on that one: bob.herman@statnews.com.

It’s tough to make predictions, especially about the future

Two years ago, my old pal Rachel Cohrs Zhang and I reported how Medicare’s actuaries predicted the new Alzheimer’s drug Leqembi would cost the program $3.5 billion in 2025. It turns out that prediction was way off.

Continue to STAT+ to read the full story…

Three things in AI to watch, according to a Nobel-winning economist

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here.

A few months before he was awarded the Nobel Prize in economics in 2024, Daron Acemoglu published a paper that earned him few fans in Silicon Valley. Contrary to what Big Tech CEOs had been promising—an overhaul of all white-collar work—Acemoglu estimated that AI would give only a small boost to US productivity and would not obviate the need for human work. It’s okay at automating certain tasks, he wrote, but some jobs will be perfectly fine.

Two years later, Acemoglu’s measured take has not caught on. Chatter about an AI jobs apocalypse pops up everywhere from Senator Bernie Sanders’s rallies to conversations I overhear in line at the grocery store. Some previously skeptical economists have gotten more open to the idea that something seismic could be coming with AI. A California gubernatorial candidate said last week that he wants to tax corporate AI use and pay victims of “AI-driven layoffs.” 

On the one hand, the data is still on Acemoglu’s side; studies repeatedly find that AI is not affecting employment rates or layoffs. But the technology has advanced quite a bit since his cautious predictions. I spoke with him to understand if any of the latest developments in AI have changed his thesis, and to find out what does worry him these days if not imminent AGI.

AI agents

One of the biggest technical leaps in AI since Acemoglu’s paper has been agentic AI, or tools that can go beyond chatbots and operate on their own to complete the goal you give them. Because they can work independently rather than just answering questions, companies are increasingly pitching agents as a one-to-many replacement for human workers.

“I think that’s just a losing proposition,” Acemoglu says. He thinks agents are better thought of as tools to augment particular pieces of someone’s work than something malleable enough to handle a person’s whole job.

One reason has to do with all the various tasks that go into a job, something Acemoglu has been researching in his work on AI since 2018. For example, an x-ray technician juggles 30 different tasks, from taking down patient histories to organizing archives of mammogram images. A worker can naturally switch between formats, databases, and working styles to do this, Acemoglu says, but how many individual tools or protocols would an AI require to do the same?

Whether or not agents will supercharge AI’s impact on jobs will come down to whether they can eventually handle the orchestration between tasks that humans do naturally. AI companies are in heated competition to prove that their AI agents can work independently for ever longer periods without making mistakes, sometimes exaggerating the results—but Acemoglu says many jobs will be spared from an AI takeover if agents can’t fluidly switch between tasks.

The new hiring spree

For years Big Tech has been offering staggering salaries to recruit AI researchers. But I asked Acemoglu about a different hiring spree I’ve noticed: AI companies are all building in-house economics teams.

OpenAI hired Ronnie Chatterji from Duke University in 2024 to be its chief economist and announced last year that Chatterji will work with Jason Furman—Harvard economist and former advisor to Barack Obama—to research AI and jobs. Anthropic has convened a group of 10 leading economists to do similar work. And just last week, Google DeepMind announced it had hired Alex Imas, an economist from the University of Chicago, to be its “director of AGI economics.”

Acemoglu has noticed colleagues getting snatched up for these roles too. “It makes sense,” he says: AI companies are well aware that public skepticism about AI, in large part due to job concerns, is growing. And they have strong incentives to shape the economic narrative around their technology (consider OpenAI’s latest proposal for a new era of industrial policy).

“What I hope we won’t get,” Acemoglu says, “is that they’re interested in economists just to further their viewpoints or further the hype.” That tension hangs over the emerging field of “AI economics”; it’s concerning that some of the most influential research about AI’s impact on work may increasingly come from the companies with the most to gain from favorable conclusions.

AI apps

I don’t think of AI as hard to use; most of us interact with it via chatbots that use plain language. But Acemoglu says we should consider how it compares with the sort of software that kicked off earlier tech transformations, like PowerPoint for slide decks and Word for documents. 

“Anybody could install these on their computer and get them to do the things that they want them to do,” he says. They spread accordingly. 

“We have not seen the development of apps based on AI that have the same usability,” he says. Even if anyone can chat with an AI model, it tends to take a while for the average worker to get practical and productive use out of it. That’s part of the reason why AI has not yet shown any seismic impact on the job market or the economy. One of the key signals Acemoglu is watching, then, is the creation of apps that make AI easier to use. 

But he acknowledges that for a while, we’re going to see all sorts of conflicting evidence about AI: anecdotes that college grads are finding the job market worse and worse, but no noticeable effect of AI on productivity, for example. “There’s a huge amount of uncertainty,” he says. And that’s the most telling thing about the AI economy right now: the certainty of the rhetoric alongside the uncertainty of everything else.

No FDA permission, no problem: New flavored vape policy worries experts

The tobacco industry chalked up another win on Friday with a new policy announced by the Food and Drug Administration that gives what one expert called a “get-out-of-jail-free card” to some manufacturers illegally selling e-cigarettes and nicotine pouches.

The FDA has a significant backlog of applications from the makers of vapes and nicotine pouches seeking authorization to sell their products. Some have gone ahead and put their products on sale anyway while awaiting word from the agency. In the new guidance, first reported by the New York Times, the agency said it will not prioritize cracking down on illegal sales under two conditions.

Read the rest…

<![CDATA[Anosognosia drives untreated schizophrenia into homelessness and jail. Here’s why civil care fails and how structured treatment can decrease the number of arrests.]]>

RegVelo AI Model Predicts Cell Fate, Tackles Developmental Disorders and Cancer

In a new study published in Cell titled, “RegVelo: gene-regulatory-informed dynamics of single cells,” researchers from Stowers Institute of Medical Research have developed a new AI model that connects two areas of single-cell biology that have often remained separate: estimating how cells change over time and inferring the gene regulatory networks controlling those changes.  

“You can imagine if you had a very early set of cells, having a particular set of instructions could allow you to reproduce, in vitro, some of these cell types in a very natural way. These cells could then be used in cell therapies in regenerative medicine,” said Tatjana Sauka-Spengler, PhD, Stowers Institute Investigator and co-senior author of the study.  

While development is often described as a series of static snapshots of cell states, RegVelo models how these fate decisions are encoded in gene regulatory networks over time and space, and what drives cell state transitions. In zebrafish neural crest development, RegVelo identified an early driver of pigment cell formation (tfec) and revealed a previously unknown regulator of pigment cell fate (elf1). The neural crest is a developmental system that gives rise to many different cell types, including pigment cells, craniofacial tissues, and parts of the peripheral nervous system. 

CRISPR/Cas9-mediated knockout and single-cell Perturb-seq supported predictions, showing that the model could do more than describe developmental changes and generate biologically meaningful hypotheses that held up in living systems. 

Alejandro Sánchez Alvarado, PhD, Stowers President and chief scientific officer says RegVelo’s value “extends well beyond” neural crest cells and is applicable to any system in which cells change over time, from basic developmental biology to modeling tumor trajectories and the cellular outcomes that may inform treatment. 

“Sauka-Spengler and her collaborators have developed a meaningfully different way to process this kind of data,” said Sánchez Alvarado. “It allows us to infer the most likely path of each component through space and time, and to use deep learning to predict those dynamics and test them experimentally.” 

Single-cell biology research has made it possible to build increasingly detailed maps of development. RNA velocity methods can help researchers estimate how cells move through developmental landscapes, while gene regulatory network approaches can identify relationships among genes. However, these methods have typically been used in parallel rather than together.  

“For a long time, cellular dynamics and gene regulation have largely been modeled separately,” said Fabian Theis, PhD, the study’s co-senior author and director of the institute of computational biology at Helmholtz Munich. “RegVelo brings those pieces together, allowing us to ask not only how cells are changing, but which regulatory interactions are helping drive those changes.”  

The framework jointly models splicing kinetics and gene regulatory relationships, allowing researchers to map the hidden timeline of cell development, predict how cells shift from one state to another, and test what might happen when specific regulators are perturbed. 

The framework can incorporate additional regulatory layers, including chromatin, protein activity, and other multimodal measurements. While the study’s limitations include simplifying assumptions around latent time, regulatory interactions, and computational cost, the results demonstrate a compelling proof of principle.

“When dynamic cell-state modeling is linked directly to gene regulation, it becomes possible to move closer to mechanism and then discovery,” Sauka-Spengler said. 

The post RegVelo AI Model Predicts Cell Fate, Tackles Developmental Disorders and Cancer appeared first on GEN – Genetic Engineering and Biotechnology News.

Brain-Controlled Hearing Aid Singles Out Voices in a Crowd

Scientists at Columbia University have developed a brain-controlled hearing technology that allows users to amplify the conversation they are focusing on while reducing other voices. Published today in Nature Neuroscience, this study marks the first time this kind of technology has been tested in humans. 

“We have developed a system that acts as a neural extension of the user, leveraging the brain’s natural ability to filter through all the sounds in a complex environment to dynamically isolate the specific conversation they wish to hear,” said Nima Mesgarani, PhD, principal investigator at Columbia’s Zuckerman Institute and associate professor of electrical engineering at Columbia’s Fu Foundation School of Engineering and Applied Science. “This science empowers us to think beyond traditional hearing aids, which simply amplify sound, toward a future where technology can restore the sophisticated, selective hearing of the human brain.”

While modern hearing aids can amplify human speech while suppressing background noise, they cannot separate and enhance specific voices when multiple people are speaking. This can make it difficult for users to concentrate on a specific conversation in everyday scenarios such as restaurants, classrooms, busy workplaces, and family gatherings.

The hearing device developed by Mesgarani’s team mimics the way the human brain can naturally identify and focus on a single speaker out of many within a crowd. Previously, the researchers had found a way of identifying which brain signals are linked to a specific conversation, by matching the timing of peaks and valleys of the brain waves to the sounds and silences of that conversation. They also identified distinct patterns of brain activity that indicate which conversation a person is focusing on and which one they are filtering out. 

In the current study, the scientists developed a machine learning algorithm that could examine the user’s brainwaves and identify which conversation they are paying attention to in real time, making that voice louder and others quieter to make it easier to listen to. This system was tested on epilepsy patients who already had electrodes implanted in their brains. The electrodes were used to measure the user’s brain activity as they focused on two overlapping conversations played simultaneously, and the algorithm automatically detected which conversation they were trying to focus on. 

“The results mark an important step toward a new generation of brain-controlled hearing technologies that align with the listener’s intent, potentially transforming how people navigate noisy, multi-talker environments,” said Vishal Choudhari, PhD, who led the development and evaluation of the system.

More research will be needed before minimally invasive wearable systems can integrate this kind of brain sensing technology with advanced audio processing capabilities, especially to ensure they can accurately decode conversations in real time and in real-world scenarios where multiple voices can be heard. 

“The central unanswered question was whether brain-controlled hearing technology could move beyond incremental advances, towards a prototype that could help someone hear better in real time,” said Choudhari. “For the first time, we have shown that such a system that reads brain signals to selectively enhance conversations can provide a clear real-time benefit. This moves brain-controlled hearing from theory toward practical application.”

The post Brain-Controlled Hearing Aid Singles Out Voices in a Crowd appeared first on Inside Precision Medicine.

Anna Sitar on Mental Health Fitness 

Influencer Anna Sitar reflects on the importance of realness

In recognition of Mental Health Awareness Month, the Child Mind Institute has launched the Mental Health Fitness campaign — a national call to action highlighting the importance that caring for one’s mental health is just as important as physical health. 

Known for embodying the color yellow and sharing sunshine, influencer Anna Sitar always keeps it honest when it comes to her mental health. Rather than curating only the good moments, Anna shares how she keeps her mental well-being in check through small, consistent habits like journaling, therapy, and being vulnerable with her followers. Her message is simple — actively look for the good, even on harder days.

“Being able to share the way that I’m feeling, whether it’s my highest highs or my lowest lows, has shown me that there’s other people out there who feel the same way I do. It’s allowed me to inspire them to look for the good in their every day and hopefully improve their lives.”


About Anna Sitar

Anna Sitar is a content creator and influencer who’s amassed over 1.6 million followers on Instagram. She’s known for her refreshing honesty in conversations around mental health and normalizing vulnerability in digital spaces. Through her content, Anna encourages others to embrace authenticity and prioritize self-reflection.

About Mental Health Fitness

For decades, we’ve understood that physical fitness doesn’t just happen — it takes skills, regular practice, and a supportive environment. The same is true for mental health. Developed by experts at the Child Mind Institute for three different age groups, our Mental Health Fitness guides have been used by more than 1.8 million students, caregivers, and educators to build emotion regulation skills and resilience. Whether your child is 5 or 15, struggling or thriving, they can learn these skills. And you can practice alongside them. Learn more at Mental Health Fitness.

Related Resources

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