Cancer Drugs Show Surprising Power To Reverse Alzheimer’s in Mice

A study that compared the gene expression profile of Alzheimer’s disease with those triggered by 1,300 approved drugs identified a combination of two cancer medications as a potential treatment for the most common form of dementia.

Researchers from UC San Francisco and the Gladstone Institutes have discovered that certain cancer medications may help counteract the brain changes caused by Alzheimer’s disease. This breakthrough could lead to treatments that slow or potentially reverse the condition’s symptoms.

To begin, the scientists examined how Alzheimer’s alters gene activity in individual brain cells. They then searched for FDA-approved drugs that produced the opposite effect on gene expression.

Their focus was on medications that could correct changes in neurons and glial cells, both of which are disrupted during the progression of Alzheimer’s.

The team also reviewed millions of anonymized medical records and found that people who had taken some of these drugs for unrelated health issues were less likely to develop Alzheimer’s.

Finally, when the researchers tested the two most promising drugs (both originally developed to treat cancer) in mice with Alzheimer’s-like symptoms, the results were striking: the treatment reduced brain damage and helped restore memory function in the animals.

“Alzheimer’s disease comes with complex changes to the brain, which has made it tough to study and treat, but our computational tools opened up the possibility of tackling the complexity directly,” said Marina Sirota, PhD, the interim director of the UCSF Bakar Computational Health Sciences Institute, professor of pediatrics, and co-senior author of the paper. “We’re excited that our computational approach led us to a potential combination therapy for Alzheimer’s based on existing FDA-approved medications.”

The findings appeared in Cell on July 21. The research was funded in part by the National Institutes of Health and the National Science Foundation.

Big data from patients and cells points to a new Alzheimer’s therapy

Alzheimer’s disease affects 7 million people in the U.S. and causes a relentless decline in cognition, learning, and memory. Yet decades of research have only produced two FDA-approved drugs, neither of which can meaningfully slow this decline.

“Alzheimer’s is likely the result of numerous alterations in many genes and proteins that, together, disrupt brain health,” said Yadong Huang, MD, PhD, senior investigator and director of the Center for Translational Advancement at Gladstone, professor of neurology and pathology at UCSF, and co-senior author of the paper. “This makes it very challenging for drug development — which traditionally produces one drug for a single gene or protein that drives disease.”

The team took publicly available data from three studies of the Alzheimer’s brain that measured single-cell gene expression in brain cells from deceased donors with or without Alzheimer’s disease. They used this data to produce gene expression signatures for Alzheimer’s disease in neurons and glia.

The researchers compared these signatures with those found in the Connectivity Map, a database of results from testing the effects of thousands of drugs on gene expression in human cells.

Out of 1,300 drugs, 86 reversed the Alzheimer’s disease gene expression signature in one cell type, and 25 reversed the signature in several cell types in the brain. But just 10 had already been approved by the FDA for use in humans.

Poring through records housed in the UC Health Data Warehouse, which includes anonymized health information on 1.4 million people over the age of 65, the group found that several of these drugs seemed to have reduced the risk of developing Alzheimer’s disease over time.

“Thanks to all these existing data sources, we went from 1,300 drugs, to 86, to 10, to just 5,” said Yaqiao Li, PhD, a former UCSF graduate student in Sirota’s lab who is now a postdoctoral scholar in Huang’s lab at Gladstone and the lead author of the paper. “In particular, the rich data collected by all the UC health centers pointed us straight to the most promising drugs. It’s kind of like a mock clinical trial.”

A combination therapy poised for primetime

Li, Huang, and Sirota chose 2 cancer drugs out of the top 5 drug candidates for laboratory testing. They predicted one drug, letrozole, would remedy Alzheimer’s in neurons; and another, irinotecan, would help glia. Letrozole is usually used to treat breast cancer; irinotecan is usually used to treat colon and lung cancer.

The team used a mouse model of aggressive Alzheimer’s disease with multiple disease-related mutations. As the mice aged, symptoms resembling Alzheimer’s emerged, and they were treated with one or both drugs.

The combination of the two cancer drugs reversed multiple aspects of Alzheimer’s in the animal model. It undid the gene expression signatures in neurons and glia that had emerged as the disease progressed. It reduced both the formation of toxic clumps of proteins and brain degeneration. And, importantly, it restored memory.

“It’s so exciting to see the validation of the computational data in a widely used Alzheimer’s mouse model,” Huang said. He expects the research to advance soon to a clinical trial so the team can directly test the combination therapy in Alzheimer’s patients.

“nbs, guide us to the same pathways and the same drugs, and then resolve Alzheimer’s in a genetic model, then maybe we’re onto something,” Sirota said. “We’re hopeful this can be swiftly translated into a real solution for millions of patients with Alzheimer’s.”

Reference: “Cell-type-directed network-correcting combination therapy for Alzheimer’s disease” by Yaqiao Li, Carlota Pereda Serras, Jessica Blumenfeld, Min Xie, Yanxia Hao, Elise Deng, You Young Chun, Julia Holtzman, Alice An, Seo Yeon Yoon, Xinyu Tang, Antara Rao, Sarah Woldemariam, Alice Tang, Alex Zhang, Jeffrey Simms, Iris Lo, Tomiko Oskotsky, Michael J. Keiser, Yadong Huang and Marina Sirota, 21 July 2025, Cell.
DOI: 10.1016/j.cell.2025.06.035

This study was supported by the National Institute on Aging (R01AG060393, R01AG057683, RF1AG076647, R01AG078164, and P01AG073082), the National Science Foundation (2034836), and the Dolby Family Fund.

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