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A study conducted by researchers at King’s College London has found that a class of drugs known as cyclophilin inhibitors can reverse key features of alcohol-related liver disease by altering the structural composition of liver tissue. The research used laboratory-grown three-dimensional (3D) models derived from human liver tissue to explore how the drugs act on fibrosis—a process that causes liver tissue to become stiff and functionally impaired.

Fibrosis is a hallmark of progressive liver damage, including damage caused by long-term alcohol use. It develops when repeated liver injury leads to the replacement of normal tissue with scar tissue. The accumulation of scar tissue impairs the liver’s flexibility and function and can result in irreversible organ damage if left untreated.

Despite its prevalence, there are no approved medical therapies for treating fibrosis caused by alcohol-related liver disease. In this study, the team focused on the role of a family of proteins known as cyclophilins, which have previously been implicated in driving fibrosis in various types of liver injury. Early-stage clinical studies have explored the use of cyclophilin inhibitors in other forms of liver disease, but their mechanisms of action in alcohol-related contexts were not well understood.

Human-derived models used to mimic disease progression

To investigate this, the researchers developed two experimental models using human liver tissue obtained from patients undergoing surgical procedures at King’s College Hospital NHS Foundation Trust. All samples were taken from non-tumor regions of the liver.

The first model involved precision-cut liver slices exposed to alcohol in the laboratory, simulating the type of cellular stress and tissue remodeling seen in alcohol-related liver damage. When treated with a cyclophilin inhibitor, the tissue exhibited reduced accumulation of fibrotic proteins. These proteins normally contribute to the structural stiffness that characterizes fibrotic tissue. Molecular analyses of these samples showed that the drug reduced the expression of genes involved in fibrosis pathways.

In a second model, the team isolated hepatic stellate cells from the same liver samples. Stellate cells are the primary fibrogenic cell type in the liver, becoming activated in response to injury. These cells were chemically stimulated in the laboratory to mimic their activated state, and then treated with the cyclophilin inhibitor. The treatment altered the type and organization of structural proteins these cells produced, effectively reducing their fibrogenic activity.

Together, the two models demonstrated that cyclophilin inhibitors can both prevent the accumulation of fibrotic proteins and modify the architecture of liver tissue damaged by alcohol exposure. These findings provide new insight into how these drugs function at a cellular and molecular level in human tissues.

Research highlights translational potential of human tissue models

The use of human-derived models gives the study a high level of clinical relevance, which is often lacking in preclinical studies based on animal models or immortalized cell lines. Access to surgically resected tissue enabled the team to study disease mechanisms in a setting that closely mirrors real-world disease progression in humans.

The study was led by researchers from the Roger Williams Institute of Liver Studies at King’s College London and funded by the Foundation for Liver Research and Hepion Pharmaceuticals. The experimental work was carried out by Una Rastovic, a doctoral researcher, and Dr Sara Campinoti, a postdoctoral scientist.

The results have been published in the British Journal of Pharmacology.

Reference: Rastovic U, Campinoti S, Wei L, et al. Comprehensive analysis of extracellular matrix remodelling via cyclophilin inhibition in human models of alcohol-related liver fibrosis. Br J Pharmacol. 2025. doi: 10.1111/bph.70139

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From virtual counselors that can hear depression creeping into a person’s voice to smart watches that can detect stress, artificial intelligence is poised to revolutionize mental health care for patients with breast cancer.

In a new paper, UVA Cancer Center’s J. Kim Penberthy, PhD, and colleagues detail the many ways artificial intelligence could help ensure patients receive the support they need. AI, they say, can identify patients at risk for mental-health struggles, get them treatment earlier, provide continuous psychological monitoring and even perform personalized interventions tailored to the individual.

But that’s just the tip of the iceberg. AI, the researchers say, can overcome some of the biggest barriers patients face to getting mental-health support by expanding options beyond clinic walls and delivering care exactly where and when it’s needed – even to rural areas where patients lack local mental-health treatment options.

Soon, doctors may combine multiple AI technologies to provide patients a “holistic, interactive treatment experience” that ensures the mental-health support is every bit as good as the care for the cancer itself, the UVA researchers write.

“AI can help us notice when a patient is struggling and get them the right support faster,” said Penberthy, a clinical psychologist at UVA Health and UVA Cancer Center. “This technology is moving quickly, and it’s exciting to see how soon it could make a real difference in people’s lives.“

Breast cancer and mental health

Breast cancer is the most common cancer in women, with 2.3 million new diagnoses each year. Up to half of those patients will go on to experience anxiety, depression or post-traumatic stress disorder (PTSD). While there have been great advances in how we treat breast cancer, mental-health support for these patients has lagged behind, the UVA researchers note.

“Mental health care is a lifeline for women with breast cancer,” Penberthy said. “Up to half experience anxiety or depression, and without support, treatment and quality of life can suffer. AI can help spot distress early and connect women to the care they need.“

The co-authors envision a future – a near future – where AI plays a vast and crucial role in supporting patients’ mental health. The technology, they say, should not replace clinicians and care providers, but instead can extend providers’ reach and presence. By monitoring patients in real time, for example, AI could alert doctors that a patient may be struggling or slipping into depression.

Similarly, AI-powered chatbots and telepsychiatry platforms offer “scalable, cost-effective solutions” to increase access to psychological care, the researchers write. These advanced AI chatbots go far beyond the simple conversations often associated with their ilk. Instead of just responding to straightforward questions, the electronic entities can provide on-demand emotional support, suggest coping mechanisms, detail relaxation techniques and offer continuous psychological support even when therapists are unavailable.

AI, the researchers write, has tremendous potential to improve “accessibility, personalization, efficiency and cost-effectiveness“ of mental health care for patients with breast cancer. But they caution that the technology also brings challenges and ethical considerations. For example, AI can be a powerful tool to analyze mental health data, but this requires strict safeguards to protect patient privacy. Similarly, studies have shown that AI can “underperform” for patients from minority or underrepresented backgrounds, potentially contributing to care disparities, the authors write. 

Those are the type of things that doctors and researchers will have to keep in mind as they explore the potential of AI, Penberthy and her collaborators say. But they are excited for what the future holds, noting that AI has “immense” potential for improving mental health support for patients with breast cancer.

We’re just beginning to scratch the surface of AI’s potential in health care and the positive impact AI will have in our lives. I’m incredibly optimistic about what the future will bring!” 

David Penberthy, MD, MBA, co-author

UVA’s cutting-edge cancer research

Finding new ways to improve patient care is a core mission of both UVA Cancer Center and UVA’s Paul and Diane Manning Institute of Biotechnology. UVA Cancer Center is one of only 57 cancer centers in the country designated “comprehensive” by the National Cancer Institute in recognition of their exceptional patient care and cutting-edge cancer research.

The Manning Institute, meanwhile, has been launched to accelerate the development of new treatment and cures for the most challenging diseases. This will be complemented by a statewide clinical trials network that expands access to potential new treatments as they are developed and tested.

AI paper published

The Penberthys and their co-author – Jennifer Bires, MSW, LCSW, OSW-C – have published their paper in the scientific journal AI in Precision Oncology.

Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) have been found to reduce overall cancer risk, specifically in endometrial, ovarian, and meningioma cancers, among patients with obesity, a new study published in JAMA Oncology found.

GLP-1s, originally prescribed for glycemic control in type 2 diabetes, have become popular for weight management; however, their long-term impact on cancer risk remains unclear. As of 2021, there were more than 100 million US adults living with obesity, which is associated with at least 13 types of cancer in addition to type 2 diabetes.¹ Previous studies have only focused on GLP-1s or other glucose-lowering drugs in patients with type 2 diabetes, with little evidence on how they might impact cancer risk in people with obesity regardless of their diabetes status. This retrospective cohort study aimed to evaluate any increased risk of cancer that may be associated with GLP-1 use in people with obesity.

“As obesity rates continue to rise, identifying effective interventions to mitigate cancer risk among individuals with obesity is a critical public health priority,” the study authors noted.

The study compared the incidence of 14 cancers among adults with obesity who were prescribed GLP-1s compared with nonusers. Using real-world data from the OneFlorida+ Clinical Research Network, the study population consisted of 86,632 adults—43,317 of whom were taking GLP-1s and 43,315 nonusers. The study included patients eligible for antiobesity medications between January 1, 2014, and January 31, 2024. The 2013 American Heart Association/American College of Cardiology/The Obesity Society guidelines defined eligibility for antiobesity medication as an individual having either a recorded diagnosis of obesity (body mass index [BMI]) or a BMI of 27 to 29.9 with at least 1 weight-related comorbidity.

The 14 cancer outcomes assessed consisted of liver, thyroid, pancreatic, bladder, colorectal, kidney, breast, endometrial, meningioma, upper gastrointestinal, ovarian, multiple myeloma, prostate, and lung cancer. Lung cancer was included because previous studies suggested GLP-1s may suppress cell proliferation in lung cancer in addition to lowering the associated risk. Of the 86,632 adults in the cohort, the mean age was 52.4 years, 68.2% were female, 44.2% were non-Hispanic White, 50.7% had type 2 diabetes, and 48.3% had obesity (BMI ≥ 30).

Prevalence of Cancer Among GLP-1 Users

The incidence rate of the total 14 cancers for GLP-1 users was 13.6 per 1000 persons and 16.2 per 1000 persons for GLP-1 nonusers. The HR for overall cancer risk among GLP-1 RA users vs nonusers was 0.83 (95% CI, 0.76-0.91; P = .002). GLP-1s were found to have a statistically significant decreased risk of endometrial cancer (HR, 0.75; 95% CI, 0.57-0.99; P = .05), ovarian cancer (HR, 0.53; 95% CI, 0.29-0.96; P = .04), and meningioma (HR, 0.69; 95% CI, 0.48-0.97; P = .05). On the other hand, GLP-1s did show an increased risk of kidney cancer; however, the difference between GLP-1 users and nonusers was not statistically significant (HR, 1.38; 95% CI, 0.99-1.93; P = .04).

Researchers used a Fine-Gray model to account for the fact that death could prevent the outcome from occurring, ensuring risk estimates were more accurate. They also ran a sensitivity analysis combining endometrial and ovarian cancers into 1 outcome, which gave more statistical power and showed stronger evidence (HR 0.68; 95% CI 0.52–0.87). These results further strengthened the initial findings that GLP-1s did help to reduce the developmental risk of certain cancers in people with obesity.

“Given that more than 137 million individuals in the US are currently eligible for GLP-1RA therapies, even modest changes in cancer risk could have substantial public health implications,” the study authors added.

Prior research continues to support these findings. A preclinical trial found that GLP-1s, like exenatide, can inhibit proliferation and invasion of ovarian cancer cells. The findings from this preclinical trial suggest that GLP-1s support the antitumor effect in ovarian tissue.² Additionally, a survey of human tumors found that approximately 355 of meningiomas expressed measurable amounts of GLP-1 receptors, thus leading scientists to suggest meningioma cells may directly respond to GLP-1, allowing it to significantly improve metabolic profiles.³

While this study aligns with prior evidence, its observational design cannot establish causality between GLP-1 use and cancer risk, as unmeasured confounding factors may have influenced the results. Important variables such as comorbidities and lifestyle factors were not captured, raising the possibility that cancer risk among GLP-1 users differs systematically from nonusers. In addition, the follow-up period may have been too short to fully assess long-term cancer outcomes. For less common cancers such as ovarian and pancreatic, the low incidence within the study population led to wider confidence intervals and limited statistical power.¹

“These findings should be interpreted with caution. Future studies with larger sample sizes are warranted to validate these associations,” the study authors concluded. “These findings highlight the importance of tailored risk assessments and underscore the need for further long-term studies to clarify the impact of GLP-1RAs on cancer risk in high-risk populations.”

References

1. Dai H, Li Y, Lee Y, et al. GLP-1 receptor agonists and cancer risk in adults with obesity. JAMA Oncol. Published online August 21, 2025. doi:10.1001/jamaoncol.2025.2681

2. Zhang AMY, Wellberg EA, Kopp JL, Johnson JD. Hyperinsulinemia in obesity, inflammation, and cancer. Diabetes Metab J. 2021;45(3):285-311. doi:10.4093/dmj.2020.0250

3. Körner M, Christ E, Wild D, Reubi JC. Glucagon-like peptide-1 receptor overexpression in cancer and its impact on clinical applications. Front Endocrinol (Lausanne). 2012;3:158. doi:10.3389/fendo.2012.00158