Radically different
Nature Medicine, Published online: 04 June 2026; doi:10.1038/s41591-026-04441-3
After preclinical testing, a phase 1 trial involving three individuals with familial hypercholesterolemia demonstrated preliminary evidence for the safety and efficacy of AAV8-mediated LDL receptor gene therapy.
Nature Medicine, Published online: 04 June 2026; doi:10.1038/s41591-026-04435-1
In this feasibility clinical trial, the authors show that epidural stimulation of the cervical spinal cord safely improved strength, function and spasticity in seven people with arm hemiparesis.
Nature Medicine, Published online: 04 June 2026; doi:10.1038/s41591-026-04393-8
Microglia cellular changes underlie divergent resilience-associated mechanisms in human aging.
CAR T-cell therapy has enabled two patients who had been waiting for years for a kidney transplantation to find a match. Published today in the New England Journal of Medicine, preliminary results from a Phase I clinical trial show that CAR T therapy can significantly increase the chances of a match for people whose immune system would otherwise reject over 99% of kidneys available for transplant.
“This is the first demonstration that CAR T cells can be used not only to treat cancer, but also to help patients who previously had no opportunity to receive a compatible donor kidney,” said Ali Naji, MD, PhD, professor of surgery at the University of Pennsylvania and principal investigator of the study. “For patients who have spent years on the kidney transplant waiting list, this approach could be transformative.”
More than 91,000 people in the U.S. are currently waiting for a kidney transplant. Physicians assess each patient’s likelihood of finding a compatible donor using the calculated panel reactive antibody (cPRA) score, which measures how broadly the immune system is primed to attack foreign tissues. For instance, a cPRA score of 90% means the patient is expected to reject 90% of kidneys available for transplant, leaving only a small pool of potential matches available to them.
The ongoing CTOT-46 clinical trial is recruiting kidney transplant candidates with a cPRA score of 99.5% or higher who have been waiting for a kidney transplant for at least one year. Although the study will continue until up to 20 highly sensitized candidates have been recruited, preliminary results from the first two patients enrolled show promise for this innovative approach.
Both participants were treated with a dual CAR T therapy designed to remove the immune cells responsible for making antibodies that lead to organ rejection after a kidney transplant. The CAR T cells are engineered to target the CD19 and BCMA proteins, leading to the depletion of memory B cells and antibody-producing plasma cells, respectively. This strategy significantly reduced the levels of circulating antibodies produced by these cells, enabling both patients to receive kidneys from donors that would have previously been incompatible.
One of the patients had been diagnosed with focal glomerulosclerosis at age 14, leading to kidney failure at a young age. His cPRA score had reached nearly 100% after his immune system rejected a second kidney transplant, making a third transplantation next to impossible. After years of waiting for an extremely unlikely match, the CAR T cells lowered his antibody levels enough to find a match within months.
Importantly, the depletion of immune cells was temporary, and the population of B cells and plasma cells returned to normal levels over time. Neither of the patients has shown signs of organ rejection or antibody rebound months after transplantation. Additionally, no cases of severe cytokine release syndrome or neurotoxicity were reported—two common complications of CAR T-cell therapy.
“In this early trial, the CAR T-cell treatment was tolerated well, with no severe side effects, and the immune system began to recover as expected,” said Robert Montgomery, MD, PhD, chair of the department of surgery at NYU Grossman School of Medicine and director of the NYU Langone Transplant Institute. “This early success reflects what cell therapy can do for transplant medicine and opens up new options for patients that could save thousands more lives every year.”
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Researchers at the University of Missouri School of Medicine have developed a method to transplant insulin-producing islets for type 1 diabetes (T1D) treatment that illuminate the need for immunosuppressive drugs. The approach, details of which are published in JCI Insight, uses ex vivo engineering of donor islets with immune-regulating molecules that reduce both innate and adaptive immune rejection after transplantation. By adding thrombomodulin (TM) and CD47 to the surface of islets, the team created a localized immune-modulating barrier that allowed transplanted cells to survive and function while still responding to glucose and producing insulin.
“Immunosuppressant medications affect and weaken the whole body, so we instead focused on how we could improve our delivery of the transplanted islets,” said study senior author Haval Shirwan, PhD, a professor of molecular microbiology and immunology at University of Missouri. “We provided islets with a protective shield consisting of two molecules that help the transplants evade rejection from the immune system, a solution that lengthens the survival of islet cells with minimal side effects.”
To create the islets, the researchers used a surface-engineering approach known as a ProtEx platform. Islets were biotinylated and then coated with streptavidin-fused immune ligands (SA-TM and SA-CD47), allowing transient display of immune-regulating proteins without genetic modification. The purpose of this design was to reduce early inflammatory injury and block immune cell activation signals that normally lead to graft destruction following transplantation.
To discover whether these engineered cells reduced immune response, the cells were testing in allogenic mouse models. The data showed that in eight of the 11 mice tested the grafts survived from 120 to 330 days without resulting immunosuppression. By comparison unmodified islets were rejected quickly in the mouse models with survival time averaging 12 days.
The team also showed that islets engineered with only one of the molecules had limited benefit, while islets with both TM and CD47 produced the strongest effect. In recipients receiving modified islets, normal blood glucose levels were achieved in more than 72% of the mice, and the grafts maintained glucose-responsive insulin secretion.
The inclusion of two different molecules on the islets served different purposes. TM was used to reduce early inflammatory and coagulation-driven damage that occurs immediately after transplantation, while CD47 signaled to immune cells to inhibit phagocytosis and dampen adaptive immune activation.
“The double-engineered islets generated a localized tolerogenic immune environment characterized by low frequencies of inflammatory innate immune cells and increased frequencies of M2 macrophages, myeloid-derived suppressor cells, and CD4+FoxP3+ T regulatory cells,” the researchers wrote.
This new approach builds on the team’s prior work which showed that single-molecule engineering of islets with either CD47 or TM could partially improve graft survival. Earlier studies demonstrated that CD47 signaling reduced immune cell–mediated killing and that TM reduced early inflammatory injury linked to coagulation and cytokine release.
Importantly, the researchers noted that the engineering process does not impair islet function, viability, or metabolic activity, which can frequently happen as a result of cell engineering. Because the proteins are displayed transiently on the islet surface rather than permanently encoded, the methods does not produce long-term genetic alteration but still reshapes early immune responses during transplantation.
The researchers said that additional work now needs to evaluate the safety and effectiveness of these cells in humans and to determine whether the approach can reduce or eliminate the need for multiple donor islet sources, which are needed in current approaches due to early immune loss. The study also suggests that the modular nature of the platform could allow additional immune-regulating molecules to be added to further improve outcomes or tailor responses in different patients.
The post Engineered Islets Could Eliminate Need for Immunosuppression in Type 1 Diabetes appeared first on Inside Precision Medicine.
Traditionally, antibiotic discovery has involved the isolation of natural products from fungi and bacteria—largely actinomycetes. However, the perception that antibiotic-producing actinomycetes have yielded all they can, with little left to give, has motivated a recent shift toward novel antibiotic discovery processes.
However, a new study from researchers at McMaster University presents the isolation of a novel antibiotic from Streptomyces rimosus that showed efficacy against multiple bacteria, including multidrug-resistant Enterobacteriaceae. In addition, the compound—known as manikomycin—is the first antibacterial agent known to target the E-site in the large ribosomal subunit, opening the door to an entirely new class of treatments.
“Not a single antibiotic prescribed in clinics today does what manikomycin does,” says Gerry Wright, PhD, professor in the department of biochemistry and biomedical sciences at McMaster University in Ontario, Canada. “Not azithromycin, not tetracycline—none of them. So, we’ve not only found a brand-new drug candidate, but we’ve also established a brand-new target in bacteria that could potentially be exploited with other new drugs.”
This work, published in Nature in the paper, “A natural depsipeptide antibiotic binds the E-site of the bacterial ribosome.”
This discovery marks the fourth new antibiotic candidate from the Wright lab in just over a year, underscoring a promising new approach to drug discovery at a time when antibiotic resistance is a growing global threat.
Given that many antibiotics used today target the ribosome, bacteria have evolved broad defense strategies against them. However, a drug targeting a different part of the ribosome will not face the same resistance mechanisms.
Manikomycin binds in the E-site of the large subunit of the bacterial ribosome, the authors write, “preventing entry of the 3′ end of the tRNA into the E-site and effectively hindering the translocation step of protein synthesis in a sequence-context-specific manner.”
“Even newly discovered drugs that attack those same old targets may quickly face resistance,” says Wright. “But, over the history of medicine, we’ve put absolutely no selective pressure on this particular target, so bacteria have no existing resistance mechanisms for manikomycin.”
The discovery of manikomycin builds on work that began more than 75 years ago, when scientists first discovered that the soil bacterium Streptomyces rimosus produced oxytetracycline, a powerful new drug that would help usher medicine into the antibiotic age.
While the breakthrough was one of several like discoveries made in the mid-1900s, S. rimosus and related bacteria have long since been abandoned as a potential source of new antibiotics.
“There is an overwhelming perception in science that these bacteria have been mined completely dry—that we’ve found all there is to find,” Wright says. “Our lab has found that this is not at all the case.”
Wright’s group, working with collaborators at the University of Illinois Chicago and the University of Hamburg in Germany, used an advanced fractionation method to uncover the new antibiotic. By filtering out oxytetracycline and other abundant compounds from the chemical mixtures produced by S. rimosus, the researchers were able to isolate scarcer molecules that had gone unnoticed over the years.
“There is likely so much still to be discovered through fractionation,” says Manpreet Kaur, PhD, a postdoctoral fellow in Wright’s lab. “Revisiting the extracts of even-well studied bacteria like Streptomyces may lead to similar discoveries in the future.”
Wright’s team is now advancing manikomycin toward clinical development. They have already shown that the new antibiotic is not toxic to human cells, and that it works well in a lab-controlled model of infection—key milestones on the early development pathway.
The team is now working on optimizing the drug’s “residency time”—or how long it stays active in the body—and have produced 60 different derivatives with plans to push the best one forward.
“We’re excited about this molecule’s potential,” Wright says. “There’s a clear path forward, and we may even be able to expand its spectrum so that it eventually affects even more bacteria, too.”
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Buoyed by the remarkable results of the OPTIMA trial presented at the ASCO Annual Meeting, Veracyte this week announced the U.S. launch of the Prosigna Breast Risk of Recurrence (ROR) test, a genomic test for patients diagnosed with early-stage hormone-receptor positive (HR+) breast cancer.
“Prosigna is the only test proven to be predictive for chemotherapy benefit in a Phase III prospective trial for patients with up to nine positive lymph nodes, including premenopausal women, all of whom were recommended to receive ovarian suppression,” Phillip G. Febbo, MD, chief scientific and medical officer at Veracyte, told Inside Precision Medicine.
The Prosigna test determines a patient’s ROR score and estimates the 10-year probability of distant recurrence. It thus help guide treatment decisions, including predicting whether high risk patients are likely to benefit from chemotherapy or may safely achieve optimal outcomes with endocrine therapy alone, helping clinicians to make personalized care plans for their patients.
Prosigna will be available to order starting June 8, 2026.
“Every patient diagnosed with breast cancer deserves answers they can trust about what their cancer means and what comes next,” said John Leite, PhD, chief commercial officer, Veracyte.
“Prosigna gives patients and their oncologists a deeper understanding of their individual risk of recurrence, and, for many, whether chemotherapy will truly benefit them or whether they can safely avoid it. That kind of personalized insight can bring greater confidence and reassurance as patients navigate decisions that will shape their care and future health.”
In the U.S., more than 225,000 new HR+/HER2- breast cancer cases are diagnosed each year. When breast cancer is diagnosed early and treated appropriately, five-year survival rates reach 92%.
“For decades, clinical staging just comprised tumor size and nodal status together with pathology. This was the standard approach to determining whether patients with HR+/HER2- breast cancer need chemotherapy. Many node-positive patients routinely receive chemotherapy as standard of care,” Febbo said.
He added, “And yet, chemotherapy is likely to only benefit a relatively small fraction of these patients.”
The OPTIMA trial uses the Prosigna test to guide therapy and testing. Those patients with a low Prosigna ROR (<60) can safely avoid chemotherapy. OPTIMA shows that tumor biology, as evaluated by the Prosigna test, provides information beyond traditional clinical factors.
Prosigna is based on the PAM50 genomic classifier, which classifies tumors into four intrinsic subtypes. Prosigna, the company said in a press release, “uniquely combines intrinsic subtypes and proliferation score with clinical pathological factors into a single comprehensive analysis to calculate a patient’s Risk of Recurrence (ROR) score and predict 10-year probability of distant recurrence.”
Veracyte’s portfolio includes multiple cancer types, including tests for prostate cancer (Decipher Prostate), bladder cancer (Decipher Bladder and TrueMRD for muscle invasive bladder cancer monitoring), and others. The company said, “Prosigna’s intrinsic subtyping data positions us well for future expansion. While ROR scoring is specific to HR+/HER2- disease, the underlying intrinsic subtyping information spans all breast cancer types.”
More than 225,000 new HR+/HER2- breast cancer cases are diagnosed annually, with approximately 75,000 patients having node-positive disease annually. The OPTIMA trial demonstrated that more than two-thirds of clinically high-risk patients (68%) can safely avoid chemotherapy—a significant population previously assumed to require treatment based solely on nodal status.
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A machine learning-based model that integrates imaging uptake features, radiomics, and biomarkers accurately predicts how much radiation is absorbed by patients undergoing prostate-specific membrane antigen (PSMA) radioligand therapy (RLT) for metastatic castration-resistant prostate cancer (mCRPC).
“One of the biggest challenges in radioligand therapy is that patients can receive very different radiation doses despite being prescribed the same treatment activity,” said Amit Nautiyal, PhD, scientist and National Institute for Health and Care Research fellow at University Hospital Southampton and the University of Southampton in the U.K.
“Our findings suggest that information already available before treatment, such as 18F-PSMA PET/CT imaging and routine clinical biomarkers, may help predict how radiation will be distributed within tumors and healthy organs.”
Nautiyal told Inside Precision Medicine that, in the future, the model “could support more personalized treatment planning, helping to maximize radiation delivery to tumors while minimizing unnecessary radiation exposure to healthy tissues. Ultimately, the goal is to improve treatment effectiveness while reducing the risk of side effects.”
At present, the only way to determine how much radiation has been absorbed by the tumor and surrounding organs such as the kidneys and salivary glands is to use post-treatment imaging and dosimetry calculations, which can be time-consuming and resource intensive.
“Our approach aims to use information already available before treatment, such as positron emission tomography/computed tomography (PET/CT) scans and routine clinical data, to estimate likely absorbed doses before therapy begins,” said Nautiyal.
He and his team integrated 18F-PSMA PET/CT uptake data (total lesion uptake, tumor-to-organ ratios), radiomics features (Gray-Level Co-Occurrence Matrix), and biomarker information (estimated glomerular filtration rate) into a machine learning-based hierarchical mixed-effects model to provide pretherapy predictions of absorbed dose in tumors and organs at risk during ¹⁷⁷Lu-PSMA RLT.
The model, which was presented at the Society of Nuclear Medicine and Molecular Imaging 2026 Annual Meeting, incorporated data from nine patients with mCRPC referred for ¹⁷⁷Lu-PSMA RLT, contributing 57 tumors, 36 salivary glands, and 18 kidneys for analysis.
At the end of cycle 1, ¹⁷⁷Lu-PSMA dosimetry showed that the mean absorbed dose was 11.0 Gy for tumors, 1.8 Gy for salivary glands, and 3.9 Gy for kidneys.
For tumors, the models achieved a mean absolute error (MAE) of 3.2 Gy for the prediction of absorbed dose, meaning that, on average, the predicted tumor dose differed from the measured dose by approximately 3.2 Gy.
By comparison, the MAE was 0.3 Gy for salivary glands and 0.1 Gy for kidneys.
“Given the biological complexity of metastatic prostate cancer and the relatively small study cohort, we consider this an encouraging result,” said Nautiyal, “Tumor dose prediction is inherently challenging because different tumor lesions can behave quite differently, even within the same patient. By contrast, organs such as the kidneys and salivary glands generally exhibit more consistent uptake patterns, which likely contributed to the higher predictive accuracy observed.”
The Bayesian R² values, which indicate how much of the variation in absorbed dose can be explained by the model, were 0.73 for tumors, 0.93 for salivary glands, and 0.99 for kidneys.
The researchers also calculated the 95% Highest Density Interval (HDI) for the model, which indicates whether the uncertainty estimates produced by the model are realistic. The HDIs were 0.89, 1, and 1, for tumors, salivary glands and kidneys, respectively, meaning that, for tumors, about 89% of observed absorbed doses fell within the range predicted by the model.
“This suggests that the model is not only making reasonable predictions but is also providing realistic estimates of how confident it is in those predictions, said Nautiyal. “This is particularly important in healthcare, where understanding uncertainty is often as important as the prediction itself.”
The researchers say that, taken together, the findings support the robustness of the model. They also carried out a leave-one-patient-out analysis, which showed that performance remained stable even when individual patients were excluded from model development and then used for testing.
“This suggests that the model is learning broader patterns rather than simply memorizing the training data,” noted Nautiyal.
Although the results are promising, the researchers acknowledge that this was an early proof-of-concept study and further work is needed before the model can be used routinely in clinical practice.
They now plan to evaluate the model in larger patient populations from multiple centers in the U.K., perform independent external validation, and investigate how predicted absorbed doses correlate with clinical outcomes.
Nautiyal concluded: “If future studies continue to show promising results, predictive tools of this type could eventually support treatment planning and patient stratification in molecular radiotherapy. The aim is to help clinicians make more informed treatment decisions before therapy begins and move towards more personalized radioligand therapy.”
The post AI Model Predicts Radiation Uptake Before Treatment in Advanced Prostate Cancer appeared first on Inside Precision Medicine.
The race to commercialize cell therapies is forcing bioprocessing innovators to confront one of the field’s most persistent manufacturing bottlenecks: isolating fragile hematopoietic stem cells (HSCs) without compromising their therapeutic potential. “HSCs are extremely rare and extremely delicate,” says Sophie He, PhD, vice president of cell therapy and head of mergers and acquisitions at Bracco. “Trying to isolate HSCs while preserving their therapeutic function is extremely difficult.”
The challenge begins with biology itself. CD34+ hematopoietic stem and progenitor cells typically account for just one to three percent of mobilized apheresis collections and one to four percent of bone marrow populations, while the most primitive long-term HSCs can represent less than one-tenth of a percent of total marrow cells. That rarity means every processing step matters.
For manufacturers scaling autologous and allogeneic therapies, the result is a difficult balancing act between purity and yield. Conventional enrichment workflows often sacrifice one to achieve the other. “To get higher purity, traditionally one gets lower yield,” He explains. “Every wash or transfer step in the isolation process results in cell loss.” The problem is magnified by the fact that HSCs rely on preserving self-renewal, multipotency, and engraftment capability—functions that can easily be disrupted during processing, ultimately reducing clinical effectiveness.
As developers move toward commercial-scale manufacturing, traditional magnetic separation systems are facing growing scrutiny. According to He, magnetic columns can expose HSCs to damaging shear forces, compression, and membrane stress because of their fragile membranes and cytoskeletons. Processing times can also become a major operational burden. “Magnetic columns can require more than 10 hours to completely process larger mobilized apheresis starting material,” she says. “That could lead to apoptosis and metabolic stress.” The lengthy workflows create additional challenges for scalability and reproducibility across manufacturing sites, particularly as companies transition from small clinical batches to commercial production runs.
Newer approaches are gaining attention for their ability to handle cells more gently while supporting larger-scale workflows. Among them, microbubble-based separation uses buoyancy rather than magnetic force to isolate HSCs. He says the technology reduces mechanical stress on cells while also minimizing concerns about residual materials left behind during processing. The broader industry goal, however, extends beyond replacing one technology with another. Developers are searching for a platform simultaneously capable of delivering high purity, high yield, preserved cell functionality, and proven scalability.
He describes the search for an ideal HSC isolation platform as “the holy grail” for cell-therapy bioprocessing at a commercial scale. In addition to biological performance, future systems must reduce operator dependency, integrate efficiently into manufacturing workflows, and support reproducibility across donors, sites, and operators. Regulatory clarity will also be essential before any technology can achieve widespread adoption. As regenerative medicine advances toward broader commercialization, the ability to isolate healthy stem cells consistently and at scale might determine which therapies successfully transition from experimental promise to industrial reality.
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