Background: Given the increasing prevalence of depression and anxiety disorders and enduring barriers to care, there is a critical need for alternative treatment options. Generative artificial intelligence (AI) chatbots show promise for increasing access to mental health care, though more direct research is needed to establish their efficacy. Objective: This pilot study aimed to test the efficacy of a generative mental health chatbot rooted in solution-focused therapy compared to the general-purpose ChatGPT and an assessment-only control (AOC) group on depression, anxiety, and well-being. Methods: A total of 185 English-speaking adults were recruited online and randomly assigned to one of three groups: AI therapy, ChatGPT, or AOC. Of these, 147 eligible participants filled out a pretreatment assessment. Over a 3-week period, the AI therapy group (n=44) was instructed to complete 3 structured, fully automated app-based sessions per week (9 total), while the ChatGPT group (n=60) was instructed to engage in 9 unstructured conversations with ChatGPT (GPT-4o–based models). The control group (n=43) received no intervention. In the AI therapy group, 39% (n=17) completed all sessions, as did 62% (n=38) of those in the ChatGPT group. Primary outcome measures, self-assessed online at baseline and postintervention, included the Patient Health Questionnaire-9 (PHQ-9), Overall Depression Severity and Impairment Scale (ODSIS) (depression), 7-item Generalized Anxiety Disorder Scale (anxiety), and World Health Organization Well-Being Index (5-item version) (well-being). Linear mixed effects models were used for data analysis. Results: Compared to AOC, both the AI therapy group (=−0.47; =.01) and the ChatGPT group (=−0.44; =.02) demonstrated significant reductions in depression scores measured by PHQ-9. The AI therapy group showed nonsignificant reductions in anxiety (=−0.37; =.11) and ODSIS depression scores (=−0.25; =.22) and an increase in well-being (=0.12; =.53) compared to AOC. Similarly, a nonsignificant reduction in anxiety (=−0.27; =.22) and ODSIS depression scores (=−0.12; =.53) and an increase in well-being (=0.20; =.29) were observed in the ChatGPT group compared to AOC. The AI therapy group did not significantly outperform the ChatGPT group on any outcomes (PHQ-9: =−0.19; =0.03; =.87; 7-item Generalized Anxiety Disorder Scale: =−0.57; =−0.11; =.62; ODSIS: =−0.59; =−0.13; =.50; and WHO: =−0.38; =−0.07; =.69). Conclusions: Both the structured generative AI chatbot and ChatGPT showed a significant reduction in depression scores compared to the control group. No significant effects were observed across other outcomes, although descriptive trends indicated improvements in anxiety. While the AI therapy group showed descriptively better outcomes for depression and anxiety, differences between groups were not significant. A larger sample and longer intervention may be needed for the emerging trends to yield clinically meaningful effect sizes. Trial Registration: OSF Registries osf.io/r76ef;
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Brain Astrocytes Form Far-Reaching Connections in Mice
A study in mice headed by NYU Langone Health researchers has found that cells long thought to play a secondary role in brain function build their own far-reaching connections. These pathways appear to connect distant regions in ways that had not been mapped before.
Experts usually describe the brain as a network of nerve cells (neurons) that send each other signals to pass along information. These neurons are maintained by another kind of brain cell, the star-shaped astrocyte, which ferries in nutrients and carries away waste.
The newly reported study, headed by Melissa Cooper, PhD, a postdoctoral fellow in the department of neuroscience at NYU Grossman School of Medicine, revealed that, like neurons, astrocytes form organized webs, which enable them to communicate with other specific astrocytes across the brain rather than only sending local, generalized signals. In some cases, the pathways were found to link areas that were not already joined together by neurons.
“For more than a century, neuroscientists have thought of neurons as the main actors in the brain,” said Cooper. “Yet our findings suggest that astrocytes, which are usually viewed as merely support cells, are also running their own widespread signaling pathway, adding another layer to how brain regions stay connected.” The team suggests that while their study was carried out in mice, not humans, the findings form the basis for future studies investigating how astrocyte networks might link with injury, disease, or aging and to learning and memory.”
Cooper is first and co-corresponding author of the team’s published work in Nature, titled “Astrocytes connect specific brain regions through plastic networks,” in which the researchers stated, “Astrocyte networks can directly link brain regions that are not connected by neurons, suggesting that previously unassociated brain regions communicate with one another through gap junction-coupled astrocytes.”
“Neuronal axons have traditionally been considered to be the primary mediators of functional connectivity among brain regions,” the authors wrote, and the role of communication mediated by astrocytes has been largely underappreciated. “This communication occurs through gap junctions—membrane channels that connect the cytoplasm of neighboring cells, enabling them to redistribute resources and share biochemical signals,” the team continued. “Studies using mice lacking astrocyte gap junctions have shown that these gap junctions are necessary for memory formation, synaptic plasticity, coordination of neuronal signaling, and closing the visual and motor critical periods.”
In earlier work, Cooper reported that in a mouse model of the visual neurodegenerative disease glaucoma, astrocytes can redistribute resources from astrocytes around healthy neurons to damaged neurons. Yet the team had no way to see whether this kind of support-cell network extended across the entire brain.
Cooper said the newly reported study is the first to map active, brain-wide communication networks built by astrocytes and to show that these pathways are highly specific. The research relied on a custom-built tracing tool that let the team follow the cells’ connections in far greater detail than had been possible using past methods. “Despite the importance of astrocyte gap junctional networks, studying them has been challenging,” the investigators noted. “Current methods such as slice electrophysiology disrupt network connectivity and introduce artefacts due to tissue damage.”
For their study, the researchers used a harmless virus to deliver “network tracers” into astrocytes in selected brain regions of lab mice. These tracers tagged small molecules as the molecules passed through the gap junctions linking one astrocyte to another, allowing the team to see which cells were part of the same signaling pathway.
The scientists then made the mice’s brains transparent and used a specialized microscope to capture three-dimensional images of every tagged astrocyte. By doing this across hundreds of mice, they could map astrocyte webs across brain areas. “These networks selectively connect specific regions, rather than diffusing indiscriminately, and vary in size and organization,” they reported. “We observe local networks that are confined to single brain regions and long-range networks that robustly interconnect multiple regions across hemispheres, often exhibiting patterns distinct from known neuronal networks.”
![A 3D network of interconnected astrocytes imaged inside a whole, transparent mouse brain. Each astrocyte's color shows its distance from the viewer; closer astrocytes are blue, while more distant astrocytes are red. [Cooper et al. Astrocytes connect specific brain regions through plastic networks. Nature. 2026. doi:10.1038/s41586-026-10426-6.]](https://www.genengnews.com/wp-content/uploads/2026/04/Low-Res_Cover-Image-224x300.jpg)
The tracing tool and brain-clearing method were designed to be relatively low-cost and easy to reproduce so that other labs could use them to study the networks in many brain diseases.
In another part of the study, the team assessed mice that were genetically engineered with astrocytes that lacked gap junctions. The communication networks largely disappeared, suggesting that the pathways are active and depend on these physical bridges.
“By challenging our understanding of how the brain communicates over long distances, our results may offer fresh insight into how it develops, ages, and behaves in conditions such as Alzheimer’s and Parkinson’s diseases,” said study co-senior author Shane A. Liddelow, PhD, an associate professor in the neuroscience and ophthalmology departments at NYU Grossman School of Medicine.
Another key finding was that astrocyte networks are dynamic. When the team trimmed whiskers on one side of the mice’s faces—“this manipulation is known to induce robust structural remodeling in neurons,” the team noted—a pathway from the region that processes whisker touch got smaller and reconnected to different astrocyte partners.
“The fact that astrocyte networks shrink and reroute after a loss of sensory signals suggests they may be shaped by experience,” said study co-senior author Moses V. Chao, PhD, a professor in the cell biology, neuroscience, and psychiatry departments at NYU Grossman School of Medicine. “It also raises the possibility that each of us has a somewhat unique pattern of connections molded by what our brains have learned and lived through.”
The authors plan to investigate which molecules move through the networks and to apply their tracing tool to models of brain disorders. They also hope to examine how these webs change during development and aging, said Chao.
Liddelow emphasized that while gap junctions and astrocytes exist in humans, it remains unknown whether the networks link the same regions in the same way as in mice. Nevertheless, in their paper, the team concluded that their findings “… establish foundation for future exploration of how astrocyte network structure and function are shaped by injury, disease, development, aging and experience-dependent processes such as learning and memory.”
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<![CDATA[AFSP and JED plan a 2026 merger to form the largest US suicide prevention nonprofit, uniting research, youth mental health programs, advocacy, and community support.]]>
Breast Cancer Cell Metastatic State Characterized by Prrx1 Levels
A new study published in Nature Communications is reshaping how researchers think about metastasis, showing that the cells most likely to spread are not defined by extremes, but by a precise balance of biological states within the primary tumor.
The work, led by Raúl Jiménez Castaño, PhD, and colleagues in the Cell Plasticity in Development and Disease Laboratory headed by Ángela Nieto at the Instituto de Neurociencias in Spain, identifies a nonlinear relationship between expression of the transcription factor Prrx1 and metastatic potential in breast cancer. Tumors with intermediate levels of Prrx1—not low or high—were found to be the most metastatic.
“This is unusual,” Jiménez Castaño said. “You normally expect a linear correlation—either low or high expression being the most relevant. But here, the peak of metastasis is in the intermediate levels.”
From paradox to mechanism
The study builds on longstanding efforts to understand the epithelial-to-mesenchymal transition (EMT), a developmental program that enables cells to migrate and is co-opted by cancer cells during metastasis. While EMT has been widely linked to tumor dissemination, the new findings show that metastatic potential is not simply a function of how invasive a cell becomes. Instead, it depends on a finely tuned balance between invasion and proliferation—two processes that are often at odds.
Previous work from the group and others had produced conflicting results regarding the role of Prrx1. In some models, removing the gene reduced metastasis; in others, it appeared necessary for dissemination. To resolve this contradiction, the researchers turned to patient tumor samples, where they observed that metastatic incidence peaked in tumors with intermediate Prrx1 expression.
Modeling a metastatic “sweet spot”
To investigate, the team engineered mouse models with graded levels of Prrx1 expression, mimicking the spectrum observed in human tumors. The results closely mirrored patient data. Tumors lacking Prrx1 showed little ability to metastasize, while those with high expression were capable of invasion but produced relatively few metastases. In contrast, tumors with intermediate levels generated the highest metastatic burden.
At the invasive front of these tumors, the researchers identified a distinct population of cells capable of both migrating and adopting divergent fates—either proliferating or entering a dormant state. This balance proved to be the critical determinant of metastatic success.
To understand the underlying biology, the team applied a range of advanced techniques, including single-cell RNA sequencing, chromatin profiling, and spatial transcriptomics. These approaches allowed them to map cellular states within tumors and link Prrx1 expression levels to functional behavior.
The analyses revealed that Prrx1 plays a dual role: it promotes invasion while simultaneously activating a dormancy program that suppresses cell division.
“At the same time that Prrx1 is necessary for cancer cells to be invasive, it also activates a dormancy program,” Jiménez Castaño explained.
This creates a biological trade-off. At high Prrx1 levels, cells are highly invasive but largely non-proliferative, limiting their ability to form metastases. At low levels, cells retain proliferative capacity but cannot effectively disseminate. Only at intermediate levels do cells achieve both capabilities.
“If the cancer cell has these intermediate levels, it is both invasive and proliferative,” he said. “And therefore, these cells will create a lot of metastasis.”
Metastatic potential begins in the primary tumor
One of the study’s most significant implications is that metastatic potential is determined earlier than previously appreciated. Rather than being dictated solely by conditions at distant sites, the ability of cancer cells to form metastases appears to be encoded within specific cell states in the primary tumor.
“The big conclusion is that already in the primary tumor, the potential of the cancer cells to metastasize is defined,” Jiménez Castaño said.
This finding aligns with broader observations from the field that tumors contain heterogeneous populations of cells with distinct functional properties. In this case, a subset of cells with intermediate Prrx1 expression represents a particularly dangerous state—one that combines mobility with the capacity for sustained growth.
Implications for biomarkers and therapy
Although the study identifies Prrx1 as a potential marker of metastatic risk, translating this insight into clinical practice will require further validation. The researchers were able to stratify tumors into low, intermediate, and high expression groups using staining intensity and computational analysis, but defining precise thresholds remains a challenge.
“We cannot say at this moment it is a biomarker,” Jiménez Castaño noted.
Even so, the findings provide a conceptual framework for improving patient stratification and identifying tumors with a higher likelihood of metastasis.
They also suggest new therapeutic strategies. Rather than attempting to eliminate invasive behavior entirely, it may be possible to push tumor cells into states that are less capable of forming metastases. For example, maintaining high Prrx1 expression could promote invasion while simultaneously enforcing dormancy, preventing metastatic outgrowth.
The post Breast Cancer Cell Metastatic State Characterized by Prrx1 Levels appeared first on Inside Precision Medicine.
mRNA Uses Unconventional Pathways in CD8+T Cell Priming to Help Vaccines Work
mRNA vaccines scored a stunning win against SARS-CoV-2 in 2020, and now the Nobel-prize–winning technology is out to conquer some cancers. Several mRNA vaccines are already in clinical trials for melanoma, small cell lung cancer, and bladder cancer, among others. Recently, a pancreatic cancer vaccine grabbed headlines after researchers shared that most Phase I trial participants were still alive after several years—unprecedented in a disease that is considered incurable, and usually kills patients quickly.
But how exactly does mRNA work? A new study suggests a broader role for how T cells become activated after an mRNA vaccine. It’s a process that engages both cDC1 and cDC2 cells redundantly. The study was led by researchers at Washington University School of Medicine in St. Louis (WashU) and could lead to improvements in mRNA vaccine design. The findings were published in Nature. The work was powered by a novel mouse model developed by the WashU team.
“My lab made them in 2019 and 2022. We put all of them in Jackson labs [database] so anyone can get them, no strings, and study them,” senior author Kenneth M. Murphy, MD, PhD, told Inside Precision Medicine. “Thanks to them, we saw the question and were able to address it most quickly.”
Until now, scientists assumed that cDC1, which is a classical type 1 dendritic cell, was required for mRNA vaccination to activate the immune system. But, in a lab study, these researchers found that even without cDC1 cells, the mRNA vaccine still triggers strong cancer‑killing responses. That’s because they determined that cDC2, a cousin to cDC1, can also stimulate anti-tumor immune activity—an unexpected finding given that this related subtype is not involved in responses to other vaccines.
“There is a lot of interest in applying the mRNA vaccine approaches used during the COVID-19 pandemic to the problem of inducing anti-tumor immunity,” said Murphy, the Eugene Opie Centennial Professor in the department of pathology & immunology at WashU Medicine. “By dissecting which immune cells are involved and how they coordinate the response, we’re offering vaccine developers some additional mechanistic insights to consider in their goal of optimizing these vaccines against tumor proteins.”
Murphy is also a research member at Siteman Cancer Center, based at Barnes-Jewish Hospital and WashU Medicine.
mRNA vaccines work by delivering instructions, in the form of messenger RNA, for immune cells to produce bits of protein that trigger the immune system to destroy cells bearing these proteins. Dendritic cells produce the protein bits from the mRNA instructions, and T cells then find and destroy the invading proteins. To treat cancer, mRNA vaccines can be designed to generate protein bits unique to a tumor.
The work was done in collaboration with the study’s co-corresponding author, William E. Gillanders, MD, the Mary Culver Professor of Surgery at WashU Medicine. Gillanders, a physician-scientist and surgical oncologist who has also developed an investigational vaccine against triple-negative breast cancer, treats patients at Siteman Cancer Center.
Murphy and members of his lab used their mouse models, which lacked cDC1 or cDC2, to tease out the role that different groups of dendritic cells play in priming T cells after mRNA cancer vaccination.
One of their findings was that mice immunized with an mRNA vaccine generated strong T-cell responses even in the absence of cDC1s. In addition, they found that immunized mice without cDC1s were able to clear sarcoma tumors—cancers that develop in connective tissues such as fat, muscle, nerves, blood vessels, bone, and cartilage. This indicated that some other cell type must be stimulating the T-cell response.
Indeed, their study found that cDC2s also participate in generating an immune response from T cells and preventing tumor growth. Further, the study found that T cells turned on by cDC1s and cDC2s each showed slightly different molecular “fingerprints.” These differences could help scientists design better versions of vaccines in the future.
Similarly, immunized mice lacking cDC2s and mice that had both cell subtypes produced an immune response and rejected tumor growth, demonstrating that mRNA vaccination uses both dendritic cell subtypes to stop cancer.
“This work uncovers a new way mRNA vaccines engage the immune system—through both cDC1 and cDC2—which helps explain their power and gives researchers concrete targets for making future mRNA cancer vaccines more effective,” said Gillanders. “It could improve vaccine formulation and dosing, potentially explain why some patients respond better to vaccines than others, and guide strategies for making vaccines more effective.”
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STAT+: At AACR, talk of Chinese biotech, oncology’s comms issue, and more
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Overcoming resistance and RevMed’s next drug?
In case you missed it, Revolution Medicines’ sessions yesterday were jam-packed with conference attendees. While most of the media coverage focused on the daraxonrasib in frontline pancreatic cancer data, the company also revealed some activity in a new compound, RM-055. CEO Mark Goldsmith described it as being part of a new class of “catalytic inhibitors,” since it can slice off a phosphate from GTP-RAS, or the “on” form of RAS, and turn the protein off.
This generated a lot of interest because one of the main ways that cancer develops resistance to RAS inhibitors is by amplifying mutant RAS, basically flooding the cell with the oncoprotein and overwhelming the inhibitor. RM-055, with its catalytic ability to turn multiple mutant RAS proteins off, may be the next step in the arms race against RAS-addicted cancer.
AI Could Help More Donor Hearts Reach Transplant Patients
Integrating artificial intelligence (AI) tools into transplant infrastructure could save a significant amount of available donor hearts from being discarded, according to research presented at the International Society for Heart and Lung Transplantation (ISHLT) 46th Annual Meeting and Scientific Sessions.
“There is a massive shortage of heart donors in the United States, with patients waiting months—if not longer—for a transplant, often on life support in the ICU. So the stakes are very high,” said Brian Wayda, MD, transplant cardiologist and assistant professor of medicine at NYU Grossman School of Medicine.
Despite an ongoing shortage of donor hearts, only up to 40% of the hearts that become available are actually transplanted. Transplant teams will typically evaluate potential donors based on a series of donor risk factors, including the person’s age, disease history, and drug use record, among others. However, evidence is still limited on how each factor affects post-transplant outcomes, and decisions need to be made quickly to ensure any suitable hearts find a matching recipient on time.
“It’s an extremely complex judgment call that must be made in a very short time window, often in the middle of the night,” said Wayda. “AI can support these life‑and‑death decisions made under extreme time constraints.”
Together with scientists at Stanford and other leading U.S. research centers, Wayda has developed a web-based prediction tool called TOPHAT (Tool Predicting Heart Acceptance for Transplant). This machine learning algorithm evaluates 20 donor characteristics to estimate how likely a transplant center is to accept a donor heart, based on historical data from over 78,000 potential donors.
Using this tool could help experts make decisions in a more data-driven, consistent, and efficient way. This could reduce the likelihood that a suitable donor heart gets discarded due to time running out before a matching recipient is found.
“The tool doesn’t say ‘this is a good heart’ or ‘this is a bad heart,’” Wayda explained. “Instead, it quickly shows how a donor compares to the national experience. An older donor, or one with a single risk factor like cocaine use, may look high-risk at first glance. But when you consider all the variables at once, that donor may not be any riskier than a typical heart we already use.”
There are currently over 4,000 patients waiting for a heart transplant in the United States. Even a relative increase of 500 additional hearts becoming available each year would be enough to reduce wait time substantially, said Wayda.
Going forward, the researchers are working toward developing a unified decision support system that brings together output from TOPHAT and other AI tools, as well as the broader donor medical record, to generate a single, easy-to-digest summary for clinicians making time-sensitive decisions about a potential transplant.
“The real value of AI is helping us synthesize a huge amount of data quickly and objectively so clinicians can make better-informed choices,” said Wayda. “With this kind of integrated view, doctors would be less likely to anchor their decision on a single ‘red flag’—such as donor age over 50—and decline hearts that could have performed well.”
The post AI Could Help More Donor Hearts Reach Transplant Patients appeared first on Inside Precision Medicine.
Gut Microbiome Signatures Predict Melanoma Response to ICB Treatments
Researchers at NYU Langone Health’s Perlmutter Cancer Center have found that patterns in the populations of bacteria in the gut microbiome can predict which melanoma patients are more likely to benefit from immunotherapy. The study, published in Cell, showed that specific bacterial signatures, when analyzed in the context of a patient’s overall microbiome profile, can forecast cancer recurrence after immune checkpoint blockade (ICB) with accuracy as high as 94%. The findings suggest that using this information could help identify which patients will respond to ICB treatment and which are more likely to relapse.
“Our study identified for the first time gut bacterial types that can serve as markers of increased recurrence risk in these specific patients, which will help to tailor treatment,” said study senior author Jiyoung Ahn, PhD, a professor of population health at NYU Grossman School of Medicine and associate director of population research at NYU Langone’s Perlmutter Cancer Center.
ICB is a form of cancer treatment that enhances the immune system’s ability to recognize and attack tumor cells. Drugs such as nivolumab and ipilimumab work by inhibiting molecular “checkpoints” that normally restrain T cell activity to allow immune cells to mount an anti-tumor response. Because of the success of ICBs in advanced cancer, this form of treatment is now expanding into earlier-stage, higher-risk patients following surgery.
“Immune checkpoint blockade (ICB) therapy has transformed the management of advanced, unresectable melanoma,” the researchers wrote. However, it is not effective for all patients. “Clinical benefit remains unpredictable, with approximately 25%–40% of patients experiencing disease recurrence despite therapy,” they added.
In their search for biomarkers that could stratify responders from non-responders, the NYU investigators analyzed stool samples from 674 melanoma patients enrolled in the Phase III CheckMate 915 clinical trial. Participants had undergone surgical tumor removal and then received either a combination of nivolumab plus ipilimumab or nivolumab alone for up to one year. Using shotgun metagenomic sequencing, the researchers characterized the gut microbiome at strain-level resolution before treatment and, in a subset of the patients, during therapy.
Their analysis identified bacterial taxa, including Eubacterium, Ruminococcus, Firmicutes, and Clostridium, that were associated with recurrence risk.
An important finding was that predictive accuracy was dependent on matching patients by their overall microbiome composition. “Recurrence prediction was strongest when the validation cohort exhibited GMB profiles similar to those in the discovery cohort,” the researchers wrote. When patients were closely matched based on microbial similarity, prediction performance reached area under the curve (AUC) values between 0.78 and 0.94. “This evidence indicates that taxonomic markers for prediction of recurrence are generalizable across regions for individuals with similar GMB composition,” the researchers noted.
The study’s design sought to address a longstanding challenge in microbiome research, notably that earlier studies had shown bacterial markers linked to immunotherapy response varied widely by geography.
“Past studies have struggled because the gut bacteria that predict treatment success seemed to change from one region to another,” Ahn said. “Our study provides a new method that overcomes this barrier, showing that these markers are indeed generalizable if we account for the person’s underlying microbiome.”
The study also showed that the gut microbiome remains stable during treatment, a finding that suggests the potential to manipulate the gut microbiome before therapy begins. “This stability suggests an important window of opportunity before treatment begins,” Ahn told Inside Precision Medicine. “We are currently planning diet-based intervention trials aimed at actively modifying the microbiome prior to immunotherapy. The goal is to move beyond observational associations toward actionable strategies that can improve treatment response.”
The biological mechanisms underlying these associations may relate to how gut bacteria influence immune activity. “These taxa are largely fiber-metabolizing bacteria that produce short-chain fatty acids, such as butyrate,” Ahn said. “These metabolites are known to play important roles in modulating immune function, including enhancing anti-tumor immune responses and regulating inflammation.” The researchers also noted links between these bacteria and metabolic pathways such as “glycolysis/gluconeogenesis” and the “pentose phosphate pathway,” which prior research has shown can affect cancer treatment outcomes.
Evidence supporting the microbiome’s role in immunotherapy response has been accumulating. Prior studies in metastatic melanoma have shown that fecal microbiota transplantation can restore responsiveness to ICB in some patients, via activation of CD8+ T cells. But earlier research has been limited by small sample sizes and regional variability.
The current study, however, examines the influence of the microbiome during adjuvant therapy and provides a potential method for overcoming geographic differences.
“The main challenge is that prediction models may be limited to subsets of populations with similar underlying microbiome structures,” Ahn noted. “Moving forward, we will need well-characterized, large-scale microbiome reference datasets that allow appropriate matching across populations and regions.”
Additional work is needed in order to use these signatures in the clinic. “The next steps include validation in independent cohorts and prospective trials,” Ahn noted. “Ultimately, these biomarkers have the potential to guide patient stratification and optimize immunotherapy outcomes in clinical settings.”
The post Gut Microbiome Signatures Predict Melanoma Response to ICB Treatments appeared first on Inside Precision Medicine.
Hearing Loss Gene Therapy Lasts More than Two Years
A trial of a gene therapy to treat people with hearing loss related to recessive mutations in the OTOF gene shows the treatment is effective and safe for at least 2.5 years.
The study, published in Nature, showed around 90% of those who received the adeno-associated viral (AAV) vector gene therapy showed at least some restoration in hearing.
Improvement was rapid in the first six weeks, improved further by 26 weeks and in a small subset of patients remained stable for 2.5 years of follow-up.
“It’s remarkable to see patients go from complete deafness to being able to hear,” said the study’s co-lead author, Zheng-Yi Chen, PhD, the Ines and Fredrick Yeatts Chair in Otolaryngology and an associate scientist at Massachusetts Eye and Ear hospital, in a press statement. “For many patients, that also means the ability to develop and use speech.”
The OTOF gene encodes the otoferlin protein, which is critical for normal hearing. When otoferlin is missing or nonfunctional, inner‑ear hair cells can’t relay sound information to the brain, leading to severe or complete deafness. This kind of hearing loss is rare and inherited in a recessive manner, needing mutations from both parents for a child to be affected.
As of this year there are at least five gene therapies being developed to treat this kind of deafness, for example, by Akouos/Eli Lilly and Decibel/Regeneron in the U.S., Sensorion in France, and at least two additional programs in China.
The current study took place in China and included 42 people between the age of eight months and 32 years (average age six years) and is the largest cohort of OTOF gene‑therapy patients reported so far, as well as the longest study follow-up period.
The participants received one of three doses of the AAV gene therapy injected into their cochlea’s and were followed up for 13 weeks to 2.5 years (median 52 weeks) to assess the impact of the therapy on hearing and also to evaluate safety.
Overall no serious adverse events or dose-limiting toxicities occurred. Around 90% of participants experienced hearing restoration to some degree with fast improvements seen in the first six weeks after treatment and slower improvements after that. A subset of patients (seven ears from seven patients) were included in the 2.5 year follow-up group and results were similar to those seen at two years.
Some groups did better than others. For example, hearing restoration was 100% in children aged up to three years and 92% in those aged 3-8 years. Improvement was seen in older children and adults, but to a lesser degree than that seen in young children in the study. Participants with better outer hair cell function on enrollment also responded better to the therapy than those with greater functional loss.
“It is very encouraging to see meaningful improvements in some adult patients. It suggests there may be more flexibility in the human auditory system than we expected,” said Chen, who is also the scientific founder of Salubritas Therapeutics, a Massachusetts based biotech focusing on hearing loss correction.
The post Hearing Loss Gene Therapy Lasts More than Two Years appeared first on Inside Precision Medicine.
Viral Contamination Still a Challenge for CGT Industry
Raw material testing will remain the foundation of cell and gene therapy (CGT) sector quality control strategies for the foreseeable future, according to new analysis, which shows the industry still lacks suitable virus detection and inactivation methods.
Biopharmaceutical raw materials—the culture media ingredients, the reagents, and even the production cell lines themselves—are the biggest source of viral contamination in drug manufacturing.
To mitigate the risks, the protein drug industry has developed downstream virus detection, inactivation, and removal strategies to make sure products do not pose an infection risk.
For CGT firms, ensuring products are virus safe is more of a challenge, says Yoshiaki Maruyama, PhD, from the office of cellular and tissue-based products at Japan’s Pharmaceuticals and Medical Devices Agency (PMDA).
“Viral contamination of CGT products may arise from virus-contaminated raw materials or ancillary materials of human or animal origin or from the inadvertent introduction of viruses during the manufacturing process.
“Appropriate raw material controls and robust quality control parameters must be established and maintained throughout the manufacturing process to effectively manage the risk of viral contamination,” he tells GEN.
Inactivation and removal challenges
The big problem is that cell and gene therapies are too sensitive to survive current viral inactivation methods, most of which were developed with protein therapeutics in mind.
Maruyama says, “Most conventional virus inactivation or removal processes inevitably result in cell damage or loss in cell therapy and tissue-engineered products or adversely affect viral vectors in gene therapy products.”
As a result, CGT sector quality control efforts have focused on screening raw materials and finished products, according to Maruyama, who looked at current regulations and common approaches in a recent study.
“In the CGT sector, viral safety is achieved by implementing a comprehensive viral testing program. The use of inactivation and removal processes is challenging for CGT products and raw materials, so quality control strategies relying on screening are generally used,” he says.
Technological solutions?
In future, technologies may play a greater role, according to Maruyama, who says, “
“NGS technologies are expected to be applicable to the detection of adventitious viruses in human or animal cells. NGS offers a powerful, unbiased approach for detecting known and unknown viral contaminants,” they write.
However, as the authors point out, further development will be required as NGS systems detect nucleic acids rather than viable, infectious virus particles.
“Currently, there are no globally accepted NGS-based procedures or validated analytical methods that have reached a consensus on their use as substitutes for conventional viral tests. Therefore, the use of NGS as an alternative to conventional viral tests, including reducing the use of experimental animals, requires further evaluation depending on the specific test to be replaced,” they write.
And in the future, artificial intelligence (AI) systems may also play a role.
“This is largely speculative, and there are currently no concrete examples, but AI-based tools have been applied to manufacturing control for deviation prediction and similar approaches might also be useful for controlling viral contamination risks in CGT products and raw materials,” he says.
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