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April 24, 2026

New Low-Toxicity Transplant Method Reverses Type 1 Diabetes in Mice

Researchers at Stanford Medicine say they have developed a combination treatment method that cured or prevented type 1 diabetes in mouse models by pairing blood stem cell transplantation with pancreatic islet cell transplantation under a substantially reduced preconditioning regimen. The approach creates a mixed immune system from both donor and recipient cells, which stopped autoimmune destruction of insulin-producing cells while also producing long-term tolerance to the transplanted tissue. The findings, published in the Journal of Clinical Investigation Insight, show that reversing type 1 diabetes can be accomplished without chronic immunosuppression or the toxic conditioning via radiation or chemotherapy currently used for hematopoietic stem cell (HCT) transplantation.

“The possibility of translating these findings into humans is very exciting,” said senior author Seung K. Kim, MD, PhD, a professor of developmental biology at Stanford. “The key steps in our study—which result in animals with a hybrid immune system containing cells from both the donor and the recipient—are already being used in the clinic for other conditions. We believe this approach will be transformative for people with type 1 diabetes or other autoimmune diseases, as well as for those who need solid organ transplants.”

Type 1 diabetes is an autoimmune disease that attacks pancreatic islet cells. While islet transplantation can restore insulin production, it typically requires immunosuppressive drugs that carry risks including infection, malignancy, and organ damage. The Stanford team’s approach reduced these negative effects by inducing immune tolerance through mixed hematopoietic chimerism, a state in which donor and recipient immune cells coexist.

“Mixed hematopoietic chimerism after hematopoietic cell transplantation (HCT) can modulate the immune system and induce tolerance to allogeneic tissues,” the researchers wrote. “However, bone marrow conditioning-related toxicities preclude wider adoption of HCT for transplant allotolerance.”

The current findings by the Stanford team builds on a series of research initiatives beginning with work published in 2022, in which the researchers showed they could cure toxin-induced diabetes in mouse models using antibody-based immune conditioning combined with moderate radiation (200–300 cGy), followed by transplantation of donor-matched blood stem cells and islets. This study served as a proof of concept but used radiation at levels that are potentially toxic.

A November study published in JCI, along with the new research addressed two significant challenges for developing an effective transplantation protocol: autoimmune diabetes, in which the immune system targets islet cells, and the need to reduce conditioning toxicity. In the November study, the researchers added an immune-modulating drug used in autoimmune disease to their regimen. This change enabled the formation of a hybrid immune system that both accepted donor islets and prevented autoimmune attack. All treated mice were protected from developing diabetes, and those with already possessing the disease were cured.

To further reduce toxicity, the April study added additional agents, baricitinib, venetoclax, and an αCD47 antibody, to go with αCD117 antibody and transient T cell depletion. These agents were selected because they target distinct biological pathways involved in immune regulation and bone marrow niche clearance. Baricitinib, a JAK1/2 inhibitor, reduces inflammatory signaling and supports donor cell engraftment. Venetoclax promotes apoptosis of specific immune cells, and αCD47 disrupts a signaling pathway that normally protects cells from clearance, which helped in the removal of host stem cells to make space for donor cells.

“We systematically tested baricitinib (JAK1/2 inhibitor), venetoclax (Bcl2 inhibitor), and αCD47 antibody, agents in current clinical use, and quantified hematopoietic chimerism after HCT,” the researchers wrote. “Combined with αCD117 antibody, transient T cell depletion, and just 10 centigray (cGy) total body irradiation (TBI), these agents enabled durable mixed chimerism and matching allo-islet tolerance, to cure diabetes without evidence of [graft-versus-host disease].”

This new combination allowed researchers to reduce radiation exposure to 10 cGy, a fraction of the levels used in conventional bone marrow transplantation. Mice treated using this regimen showed stable engraftment of donor cells, maintained fertility, and experienced no graft-versus-host disease. They also remained insulin-independent for the duration of the study.

The findings provide a potential pathway toward clinical adoption, which could be speedier than usual since many of the agents used for this approach are already approved or under evaluation in humans.

Work at Stanford will continue in this area and will focus on testing the reduced-intensity regimen in autoimmune diabetes models, refining conditioning strategies, and exploring alternative sources of islet cells, including those derived from stem cells.

If successfully, translated to the clinic, this treatment regimen could reduce or eliminate the need for lifelong insulin therapy, while expanding the use of transplantation-based therapies across a wider set of patients.

The post New Low-Toxicity Transplant Method Reverses Type 1 Diabetes in Mice appeared first on Inside Precision Medicine.

April 24, 2026

Effect of a WeChat Intervention Based on the Common-Sense Model on Breast Cancer–Related Lymphedema Preventive Behaviors: Quasi-Experimental Study

Background: Breast cancer–related lymphedema is the most prevalent postoperative complication among breast cancer survivors. Although mobile health tools are increasingly used for patient education, evidence supporting their efficacy in lymphedema prevention remains limited. Objective: This study aimed to evaluate the effectiveness of a WeChat-based intervention grounded in the common-sense model (CSM) in improving preventive behaviors, modifying illness perceptions, and reducing lymphedema incidence among breast cancer survivors and to validate the targets of the intervention. Methods: This study used a quasi-experimental design. Participants (N=192) were recruited from the breast cancer department of a cancer hospital in Guangzhou, China. The control group (n=98) received routine care. The intervention group (n=94) participated in a 3-month CSM-guided WeChat mini-program (“Nantian e-Care”) delivering tailored educational articles, exercise tutorials, arm circumference monitoring, and real-time nurse consultations. Outcomes, including preventive behaviors, illness perceptions, and lymphedema incidence, were assessed 1, 3, and 6 months post surgery. Generalized estimating equations were used for the analysis. Results: The intervention group exhibited significant improvements in lifestyle adjustments (Wald =6.9, =.03) and physical exercise adherence (Wald =6.9, =.03) compared with the control group. Illness perception, including identity (Wald =8.1, =.04), timeline cyclical (Wald =8.5, =.04), personal control (Wald =9.3, =.03), illness coherence (Wald =29.8, <.001), and behavioral (Wald =19.5, <.001) and physical factors (Wald =24.1, <.001) were markedly enhanced. Mechanistically, skin care improvements were driven by intervention effects, personal control, illness coherence, and behavioral attribution. Lifestyle changes were correlated with intervention and illness coherence. Adherence to physical exercise was not statistically significantly affected by the intervention, although a trend was observed. Critically, the intervention group demonstrated a lower incidence of lymphedema at 6 months (7.50% vs 16.48%, =3.9, =.048). Conclusions: The CSM-guided WeChat intervention effectively promoted preventive behaviors, optimized illness perceptions, and reduced lymphedema risk. These findings underscore the value of integrating theory-driven mobile health tools into postoperative care and highlight scalable strategies for chronic disease management in resource-limited settings. Trial Registration: Chinese Clinical Trial Registry ChiCTR2100048798; https://www.chictr.org.cn/showprojEN.html?proj=130038 International Registered Report Identifier (IRRID): RR2-10.1007/s00520-024-09078-x

April 24, 2026

Optimizing Navigation and Text Messaging Interventions to Promote Participation in a Food Is Medicine Program Among People Participating in Cardiac Rehabilitation: Human-Centered Design Study

Background: Food Is Medicine (FIM) programs integrate interventions such as medically tailored meals or produce prescriptions into clinical care. However, there is limited evidence on how to design these programs to be responsive to the lived experiences of participants to optimize initiation, engagement, and long-term retention. Objective: The objective of the study was to develop interventions to promote initiation, engagement, and retention in FIM programs that are responsive to the lived experiences of participants. Methods: We used a human-centered design approach to engage current and former cardiac rehabilitation participants in the development of interventions to promote participation and engagement in a FIM program. We recruited participants through invitations sent via electronic health record messages. We interviewed participants about their experiences, preferences, and unmet needs related to healthy eating and program design. Additionally, we elicited participant feedback on draft versions of patient navigator scripts and text messages promoting healthy eating habits. Results: A total of six participants identified themes across Theory of Planned Behavior constructs and emergent themes, including the cost of healthy food, cultural appropriateness, clear and timely communication, transportation, local food access, scheduling flexibility, the ability to provide feedback to the program, and personalized support for navigating food resources. Participants described financial strain as a key barrier to healthy eating and noted that social influence often shaped eating behaviors. Feedback on navigator scripts led to revisions clarifying program logistics, addressing barriers such as language and cultural dietary restrictions, and tailoring positive endorsements to individual health goals. Based on participant feedback, text messages were made more concise, reframed positively (eg, humor and gratitude), and encouraged to be warmer, with respectful language that is easy to understand, while avoiding stigmatizing or overly clinical phrasing. Participants also suggested that messages should reflect empathy and offer actionable information to increase trust and engagement with the program. Trust in the health care system and a sense of dignity in receiving food support emerged as critical themes influencing overall satisfaction and retention. Participants emphasized that endorsement from their health care team and cardiologist was important for building trust in the program. Communication between health care navigators and FIM navigators could help reduce the burden placed on patients to navigate food resources. Conclusions: Using a human-centered design approach, we gained insights about participant-identified needs for navigation scripts and text messages that are culturally sensitive and personalized to promote optimal participation in a FIM program.
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April 24, 2026

AI Learns to Predict Breast Cancer Risk from How Single Cells Respond to Pressure

A study headed by researchers at City of Hope and the University of California, Berkeley has found that physical and mechanical properties of normal human mammary epithelial cells can offer a “functional readout” of biological age and breast cancer susceptibility.

The team created a novel, high-throughput microfluidic platform that can assess women’s breast cancer risk at the cellular level. The mechano-node-pore sensing (mechano-NPS) platform, which the researchers claim is the first of its kind, squeezes individual breast epithelial cells, creating a taxing environment to measure how they deform, recover, and behave under stress.

Using the platform the researchers uncovered an unexpected insight, which is that breast cells appear to have a “mechanical age” separate from a person’s chronological age, demonstrated by how the cells physically respond to stress. For their study the team developed a machine learning classifier, MechanoAge, to estimate chronological age based on the mechanical phenotypes, and a biological age-based risk index, Mechano-RISQ.

“We learned that the older the mechanical age, as determined by how cells respond to being squeezed through our microfluidic device, the higher the risk for breast cancer,” explained Lydia Sohn, PhD, the Almy C. Maynard and Agnes Offield Maynard Chair in Mechanical Engineering at UC Berkeley. The researchers suggest that, as more than 90% of women lack a known genetic predisposition to or a family history of breast cancer, their innovative approach could fill a critical gap in risk assessment and save countless lives.

Sohn is co-senior author of the team’s published paper in eBioMedicine, titled “MechanoAge, a machine learning platform to identify individuals susceptible to breast cancer based on mechanical properties of single cells,” in which they concluded, “Age-related biomechanical changes may represent a fundamental hallmark of cellular function, with distinct mechanical phenotypes underlying critical processes in aging, cancer, and potentially other diseases. Recognizing and utilizing these biomechanical markers could greatly enhance early detection, refine risk stratification, and improve targeted intervention strategies.”

Breast cancer is one of the most frequently diagnosed cancers worldwide and a leading cause of cancer-related mortality among women, the authors noted, and “… has long been the subject of efforts to improve risk stratification and early-detection strategies.”

About 6% of women who develop breast cancer carry known genetic mutations. But for women outside this group, risk is estimated indirectly based on population models or measurements like breast density. These approaches can both overestimate and underestimate women’s individual breast cancer risk, leading to over-screening, under-screening, unnecessary worry or missed warning signs. And despite significant progress in screening technologies and therapeutic interventions, accurately determining which individuals—particularly among those considered average risk—are most likely to develop breast cancer remains what the team calls “one of the most persistent challenges in oncology and public health.”

For these “ostensibly average-risk individuals,” the team added, “it remains difficult to identify those with latent risk that stems from cellular, molecular, and biophysical alterations that current models are not designed to capture.”

Researchers Mark LaBarge of City of Hope (right) and Lydia Sohn (left) UC Berkeley [City of Hope and UC Berkeley]

Currently, there is no non-genetic test available that can identify women at higher risk for breast cancer. A downside to screening mammograms is that they can catch cancer only once it has begun to grow. Co-senior author, Mark LaBarge, PhD, a professor in the Department of Population Sciences at City of Hope, said “For women with a known genetic risk factor for breast cancer, there are things you can do like follow a higher-risk screening protocol. For everybody else, you’re left wondering, ‘Am I at high risk?’”

Emerging evidence links cellular aging and biophysical alterations with cancer susceptibility. For their reported study the researchers used the mechano-NPS platform to profile primary human mammary epithelial cells (HMECs) from women of different ages and risk backgrounds. They also developed a machine learning algorithm that identifies and measures cells that show signs of accelerated aging, quantifying an individual breast cancer risk score.

In this type of mechano-node-pore sensing, an electrical current is measured across a liquid-filled channel, much like how current is measured across a wire. As cells pass through, they disrupt the current, generating measurements about the cells’ size and shape. By making parts of the channel very narrow, researchers squeeze cells, then measure how long it takes each cell to recover its normal shape.

Machine-learning algorithms developed by the researchers were then used to detect differences in cells from older and younger women. The researchers found that the physical properties of breast cells changed with age; cells from older women were stiffer and took longer to bounce back after being squeezed.

Then came a surprising finding: a subset of younger women had cells that behaved like they came from older women. These cells came from women with genetic mutations that put them at high risk of breast cancer. Researchers then refined the algorithm to assign a risk score based on all the mechanical and physical properties measured in the cells. This algorithm successfully identified women with known genetic risks. Next the team used it to compare cells from healthy women, women who had family history of breast cancer and cells taken from the healthy breast of women with breast cancer in the other breast. “Normal epithelial cells from women with germline mutations, strong family history of cancer, or contralateral breast cancer exhibit mechanically aged phenotypes despite normal histology,” the investigators stated. “Together with prior molecular and epigenetic studies, these findings support a model in which accelerated biological aging of mammary epithelia may underpin breast cancer susceptibility across genetic and non-genetic risk groups.”

Using the MechanoAge platform, researchers shifted the scientific lens to the cellular level, calculating risk by looking for physical changes in individual cells. “Mechanical phenotyping captures an integrative cellular state that reflects underlying molecular networks rather than single biomarkers,” the team noted. “Mechano-RISQ offers a proof of principle approach for identifying individuals at elevated risk of breast cancer, especially among average-risk populations, and may complement existing risk models by incorporating biophysical measures of mammary epithelial cell aging.”

“With accuracy, we were able to figure out which women were at high risk of breast cancer and which women didn’t seem to be,” LaBarge said. “By translating physical changes in cells into quantifiable data, this tool gives women something tangible to discuss with their doctors—not just risk estimates, but evidence drawn directly from their own cells.” In their paper the scientists further stated, “This approach could enable earlier, individualized risk stratification, particularly for women who lack identifiable high-risk mutations yet harbor susceptible tissue states.”

Importantly, the AI platform uses simple electronics that would be easy and affordable to replicate on a large scale. “Our team isn’t the first to measure the mechanical properties of cells; however, other approaches require advanced imaging technology that’s expensive, cumbersome and has limited availability,” said Sohn. “In contrast, MechanoAge uses computer chips that are simpler than an Apple Watch and ‘Radio Shack parts’ that are cheap and easy to assemble, potentially making the device highly scalable.”

While engineers study the aging of materials such as metals, concrete and polymers, this is the first time that mechanical age has been quantified in biological cells. The finding that cells have a “mechanical age” separate from the individual’s chronological age would not have been possible without MechanoAge.

This work grew out of more than 12 years of collaboration between the two labs, combining engineering innovation with cancer and aging biology. The long-term partnership enabled discoveries that neither group could have reached alone. “It’s a true collaboration. We’ve learned a lot from each other,” Sohn said. “In my view, this is what happens when you have a real collaboration that develops over a long time,” LaBarge added. “This result is not what we imagined at the beginning.”

The post AI Learns to Predict Breast Cancer Risk from How Single Cells Respond to Pressure appeared first on GEN – Genetic Engineering and Biotechnology News.

April 24, 2026

Single-Cell Atlas of the Prenatal Brain Reveals How Down Syndrome Reshapes Development

A cellular-resolution molecular map details how Down syndrome alters human brain development before birth. The study analyzed more than 100,000 nuclei from human prenatal neocortex samples collected across 26 pre-genotyped donors during gestational weeks 13 to 23—the only window during which all the cortical neurons a person will carry for their entire life are generated. The findings suggest that Down syndrome disrupts the developmental sequence of that process, creating shifts that may help explain later differences in cognition, learning, and sensory processing.

This work is published in Science in the paper, “A single-cell multiomic analysis identifies molecular and gene-regulatory mechanisms dysregulated in developing Down syndrome neocortex.“

“There’s a new level of detail here that had never existed before,” said Luis de la Torre-Ubieta, PhD, an assistant professor of psychiatry and biobehavioral sciences at UCLA and a member of the Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research. “For the first time, we can really try to understand systematically what’s going on in the developing brain of individuals with Down syndrome.”

“No one had looked at the developing human brain in Down syndrome directly using single-cell genomics,” he continued.

The Down syndrome research field has historically focused on two areas: the adult brain and the disorder’s connection to neurodegeneration. What remained largely unexamined, despite clear indicators that Down syndrome is a developmental condition, was how the condition shapes the developing brain itself.

The development of the prenatal neocortex typically follows a tightly orchestrated sequence. Progenitor cells must first divide repeatedly to expand their own pool, building up a sufficient base for all future neurons. Only then do they begin differentiating into neurons, starting with deep-layer cell types and progressing toward upper-layer cells in a carefully timed order.

The study found that progenitor cells appear to rush prematurely into neuron production, depleting their own pool and skewing the balance of neuron types generated. Specifically, the researchers observed a relative increase in upper-layer intratelencephalic neurons and a reduction in deep-layer corticothalamic neurons.

Those two cell populations play fundamentally different roles: CT neurons project outward from the cortex—connecting to brain structures and to the spinal cord to govern sensation and movement; IT neurons wire within the cortex, connecting the two hemispheres and contributing to information processing. This finding offers a new hypothesis for how early developmental changes might contribute to the cognitive profile of the condition.

The finding also offers a new answer to a longstanding question in the field: Why do people with Down syndrome tend to have smaller brains? Earlier theories centered on elevated rates of cell death. The current study found less evidence of widespread neuronal death and instead points to the depletion of the progenitor pool.

The study employed paired single-nucleus multiomics to reconstruct not just a snapshot of which cells are present, but the regulatory programs that guide cell fate—and how those programs are disrupted in Down syndrome. Systems-level approaches also led them to uncover alterations in cell metabolism and changes in how the vasculature interacts with the developing nervous system, both of which could speed up neuron production.

The study’s significance extends beyond Down syndrome. The researchers specifically tested for overlap between the molecular disruptions they identified and the genetic risk signatures associated with other neurodevelopmental and neuropsychiatric conditions, including autism, epilepsy, and developmental delay. They found substantial convergence, particularly in the gene-regulatory networks governing the specification of IT versus CT neurons.

“Down syndrome could be a model to understand intellectual disability and neuropsychiatric disorders more broadly,” de la Torre-Ubieta said. “Also to uncover the shared biology underlying these conditions—because the mechanisms are often still unknown.”

The publication coincides with a companion paper from researchers at the University of Wisconsin-Madison, appearing in the same issue of Science. While the UCLA study focuses on the prenatal period, the Wisconsin team examined the postnatal brain, studying Down syndrome between approximately one and five years of age.

Together, the two papers provide a continuous molecular view of Down syndrome brain development from mid-gestation through infancy—a resource that did not previously exist and that the researchers expect will serve as a reference for their field for years to come.

While the researchers are careful to emphasize that the findings do not point to a near-term clinical application, the study provides the clearest picture yet of the cellular and molecular events that distinguish the Down syndrome brain during development, and a framework for identifying future therapeutic targets.

The post Single-Cell Atlas of the Prenatal Brain Reveals How Down Syndrome Reshapes Development appeared first on GEN – Genetic Engineering and Biotechnology News.

April 24, 2026

Epigenetic Mapping in Pancreatic Cells Identifies New Diabetes Target

Researchers at Lund University in Sweden have conducted the first study looking at epigenetic changes associated with type 2 diabetes in alpha and beta pancreatic cells. Published today in Nature Metabolism, their findings show that the ONECUT2 gene plays a key role in the development of type 2 diabetes by altering insulin production.

“The study shows that many genes central to insulin and glucagon production are regulated by differences in DNA methylation,” says Charlotte Ling, PhD, professor of epigenetics at Lund University and lead author of the study. “It has made it possible, for the first time, to describe detailed, cell-specific epigenetic patterns.”

The number of people living with diabetes is rapidly increasing worldwide, with approximately 95% of cases attributed to type 2 diabetes. This condition develops gradually and is characterized by a reduced ability to use insulin effectively, leading to elevated blood sugar levels. Over time, high blood sugar can lead to a range of complications that significantly impact the patient’s quality of life.

Lifestyle factors like diet and physical activity are major drivers of this condition; however, genetics can also contribute to the development of type 2 diabetes, increasing the risk for some people over others. While genome- and epigenome-wide studies on diabetes have identified genetic and epigenetic mechanisms involved in type 2 diabetes, previous epigenetics studies had only looked at whole tissues and none had investigated epigenetic changes within specific cell types that are involved in blood sugar regulation.

Ling’s team focused on alpha and beta pancreatic cells, which secrete insulin and glucagon hormones, respectively, to regulate blood sugar levels. By analyzing hundreds of thousands of cells from 24 people, with and without diabetes, the researchers created the most detailed epigenetics mapping of pancreatic cells to date. This allowed them to discover over 22,000 regions in nearly 8,000 genes that were differentially methylated between alpha and beta cells.

“Here, for the first time, we show exactly which regions regulate insulin and glucagon production through DNA methylation, which gives us the opportunity to develop future treatments based on epigenetics,” says Ling.

They then used CRISPR epigenetic editing to alter DNA methylation around the genes encoding for insulin and glucagon, which revealed that levels of the ONECUT2 transcription factor were elevated in beta cells from type 2 diabetes patients. This epigenetic upregulation was found to impair the ability of beta cells to release insulin, which in turn disrupted glucose regulation and reduced energy production within the cell.

Based on their findings, the researchers developed a web tool intended as a comprehensive resource available to researchers investigating the impact of age, sex, and type 2 diabetes on DNA methylation and gene expression in alpha and beta cells.

“We now want to understand which of these changes can actually be reversed, and whether this can help beta cells regain their function in diabetes,” says Ling. “A key aspect is to see whether the effects of editing DNA methylation can be sustained in the cell over time.”

The post Epigenetic Mapping in Pancreatic Cells Identifies New Diabetes Target appeared first on Inside Precision Medicine.

April 24, 2026

STAT+: FDA to speed up review of three psychedelics as mental health treatments

The Food and Drug Administration will accelerate its review of psychedelic drugs developed by Compass Pathways, the Usona Institute, and Transcend Therapeutics for mental health disorders, as part of the Trump administration’s plan to boost access to the controversial yet promising medications.

The agency will grant priority review vouchers specifically to Compass’ psilocybin product for treatment-resistant depression, Usona’s similar medicine for major depressive disorder, and an MDMA-like treatment for post-traumatic stress disorder from Transcend.

The FDA identified the medications receiving the vouchers, but not the companies developing them. Compass, Usona, and Transcend confirmed they received vouchers.

Continue to STAT+ to read the full story…

April 24, 2026

Fibroblast Subset Directs Immune Cell Positioning in Lymph Nodes

Researchers at the University of Lausanne have identified a specialized fibroblast population that actively organizes immune cell interactions within lymph nodes, revealing a key mechanism underlying effective T cell responses to infection and cancer.

The study, published in Immunity, shows that stromal cells, long considered primarily structural, play a central role in orchestrating where and how immune cells meet, with direct consequences for immune activation and memory formation.

Spatial organization drives immune efficiency

Lymph nodes act as surveillance hubs of the immune system, filtering lymphatic fluid and coordinating responses to pathogens or tumor cells. Within these small, highly organized structures, immune cells are not randomly distributed. Instead, they occupy defined niches that facilitate efficient communication.

Cytotoxic T lymphocytes (CTLs), for example, are typically positioned in central regions of the lymph node, where they interact with type 1 dendritic cells (cDC1s) that present antigen and initiate activation. As explained by the study authors, “cytotoxic T lymphocytes are typically found in central regions of the lymph node, where they colocalize and interact with specialized cells called type 1 dendritic cells that present danger signals to them.”

While the importance of this organization has long been appreciated, the mechanisms guiding immune cells to the correct locations have remained incompletely understood.

A fibroblast niche organizes T cell positioning

To address this question, the Lausanne team focused on fibroblasts, a class of stromal cells that form the structural backbone of lymphoid tissues. Using mouse models and human lymph node samples, they identified a distinct subset of fibroblasts located in the central compartment.

These fibroblasts are characterized by expression of MAdCAM1 and by their production of high levels of the chemokine CCL19. This signaling molecule acts as an attractant that guides cytotoxic T cells into proximity with dendritic cells, enabling productive immune interactions. As the researchers note, CCL19 “acts as an ‘attractant signal’ for cytotoxic T lymphocytes, bringing them into physical contact with type 1 dendritic cells.”

By shaping this spatial organization, the fibroblast subset creates a functional niche that promotes T cell activation. When this system was disrupted, cytotoxic T cells failed to position correctly and showed impaired differentiation into memory T cells, highlighting the importance of tissue architecture for long-term immunity.

Notch signaling maintains the stromal network

The researchers also identified the molecular pathway that sustains this fibroblast population. A signaling axis involving Notch2 and its downstream mediator RBPj was found to be essential for maintaining the identity and activity of the CCL19-producing fibroblasts.

In addition, Jagged-1, a ligand produced primarily by dendritic cells, appears to initiate or reinforce this signaling loop. This suggests a feedback mechanism in which immune cells and stromal cells cooperate to maintain the lymph node architecture.

According to the scientists, this pathway must remain active throughout life. When Notch2 signaling was disrupted in fibroblasts, the structural integrity of the niche was lost, leading to defective T cell responses and reduced formation of memory cells.

A conserved mechanism across immune tissues

Although the study focused on lymph nodes, the same organizational principles appear to extend to other immune organs. The researchers observed similar regulation of CCL19 production in the spleen and Peyer’s patches, which are involved in blood filtration and intestinal immunity.

Comparable fibroblast populations were also identified in human lymph nodes, suggesting that this mechanism is conserved across species and relevant to human immune function.

Implications for immunotherapy and vaccines

The findings add to a growing body of evidence that stromal cells play active roles in shaping immune responses. Rather than acting as passive scaffolds, fibroblasts help define where immune interactions occur and how effectively they proceed.

This has important implications for disease. In cancer, for example, ineffective T cell responses may result not only from intrinsic immune dysfunction but also from disrupted tissue organization that prevents optimal cell–cell interactions.

In vaccination, enhancing the formation or function of such stromal niches could improve immune activation and the development of long-lasting memory responses.

Looking ahead

The identification of a fibroblast-driven mechanism for organizing immune cell positioning provides a new foundation for understanding how immune responses are initiated and maintained.

Future research will be needed to explore whether targeting stromal signaling pathways, such as Notch2, can be used to modulate immune responses in therapeutic settings. While such approaches remain speculative, they highlight the potential of integrating tissue architecture into the design of next-generation immunotherapies.

“Overall, these findings deepen our understanding of the organization of the immune system and how effective T cell responses against infections and cancer are initiated,” said Sanjiv Luther, PhD, senior author of the study. “In the future, this knowledge could help improve vaccine design and clarify why immune defenses sometimes fail against certain pathogens or tumors.”

The post Fibroblast Subset Directs Immune Cell Positioning in Lymph Nodes appeared first on Inside Precision Medicine.

April 24, 2026

STAT+: A biotech VC on what Eli Lilly saw in a struggling cancer startup for $3.2B

Kelonia Therapeutics became the newest biotech takeout target this week. The privately held company, which is developing cell therapies for cancer and autoimmune diseases, will be acquired by Eli Lilly.

The acquisition is a boon for the small startup, which has subsisted on $60 million over the last five years and previously struggled to stay afloat. (Check out an earlier slide deck and memo on the company here.) Kelonia came within a week of running out of cash three times. Now it’s being bought for $3.2 billion with potential milestone payments that could double that payout.

On this week’s edition of its biotech podcast, “The Readout Loud,” STAT spoke with Bryan Roberts, a partner at VC firm Venrock, which incubated the biotech, to discuss how this small company managed to land a big deal.

Continue to STAT+ to read the full story…

April 24, 2026

STAT+: Utah medical board calls for immediate suspension of state’s AI doctor experiment

Utah’s high-profile experiment with using an artificial intelligence system to renew prescriptions without physician oversight is facing its first major challenge as doctors in the state push back.

Utah’s Office of Artificial Intelligence Policy in January announced an agreement with AI doctor startup Doctronic to launch a chatbot that can conduct a clinical evaluation of a patient and autonomously renew prescriptions for nearly 200 drugs. In a letter published Friday, the Utah Medical Licensing Board said it only learned about the agreement after it had been launched and asked the state to halt the program.

“Proceeding with this agreement without consulting the Medical Board potentially places Utah citizens at risk and remains a major concern of the board,” they wrote. “It is the strong recommendation of the Utah Medical Licensing Board that this program be immediately suspended pending further discussion.”

Continue to STAT+ to read the full story…