Category: Imported News

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Presurgery Pembrolizumab May Be the Future for Some Operable CRCs

Groundbreaking data from the Phase II NEOPRISM-CRC trial show that patients given pembrolizumab prior to surgery for certain types of high-risk, operable colorectal cancer (CRC) remain relapse-free for almost three years.

Furthermore, the response to treatment can be predicted by DNA and T cell biomarkers.

At present, the standard of care for people with high-risk stage II or III CRC with deficient DNA mismatch repair (dMMR) or microsatellite instability (MSI), like those included in the study, is surgery followed by chemotherapy, but relapse rates can range from 15% to 40% at three years.

Pembrolizumab is already given to patients with inoperable stage IV dMMR/MSI CRC to shrink the tumors and prolong life, but it is not yet available for patients with operable tumors.

The NEOPRISM-CRC trial investigated whether pembrolizumab could benefit such patients.

For the study, 32 people with large, high-risk stage II or III dMMR/MSI CRC were given three cycles of intravenous pembrolizumab 200 mg followed by surgery.

The researchers, led by Kai-Keen Shiu, from University College London (UCL) Cancer Institute, have previously reported that that 59% of participants had a pathologic complete response (pCR) to pembrolizumab, indicating that there were no cancer cells in tissue samples removed from these patients during surgery.

The data presented at the American Association for Cancer Research Annual Meeting 2026 by Yanrong Jiang, a PhD student at UCL Cancer Institute, focused on survival outcomes and whether biomarkers could predict which patients respond to pembrolizumab.

She reported that, after a mean of 33 months of follow-up, all patients were alive and relapse-free.

Shiu said: “Seeing that no patients have experienced a cancer recurrence after almost three years of follow-up is extremely encouraging and strengthens our confidence that pembrolizumab is a safe and highly effective treatment to improve outcomes in patients with high-risk bowel cancers.”

Blood samples taken throughout the study were assessed for circulating tumor (ct)DNA using the highly sensitive whole genome tumor-informed Personalis NeXT Personal assay, which can track up to 1800 patient-specific variants.

The team found that all 25 patients with evaluable data had detectable ctDNA at baseline.

Remarkably, after one round of treatment with pembrolizumab, 24% of participants no longer had detectable ctDNA. The proportion increased to 43% and 58% after rounds two and three, respectively. Post-surgery, ctDNA was undetectable in all 25 patients.

When the researchers analyzed the ctDNA clearance profiles, they identified three distinct patterns. They designated the first group “super molecular responders.” All six patients in this group had undetectable ctDNA after one cycle of pembrolizumab.

The “dynamic molecular responder” group included 11 patients who cleared ctDNA at different rates—four after cycle two of pembrolizumab, five after cycle three, and the remainder post-surgery, even though the level was decreasing rapidly during immunotherapy.

The final group, termed “poor molecular responders,” included eight patients who showed stable, high levels of ctDNA throughout immunotherapy, with levels only becoming undetectable post-surgery.

Interestingly, the pCR rate varied across the three groups: It was 100% among the super molecular responders and 82% among the dynamic molecular responders, but 0% among the poor molecular responders.

Shiu told Inside Precision Medicine that measuring ctDNA using the Next Personal assay could “potentially trump all standard tests when it comes to informing decision making.”

He suggested that the super molecular responders could potentially consider forgoing surgery altogether, while the poor molecular responders could be considered for treatment intensification, such as the addition of a second immunotherapy agent.

Although ctDNA gives information on how the tumor is responding to treatment, it doesn’t explain why some patients respond and others don’t.

The researchers, therefore, also carried out T cell receptor (TCR) sequencing, which provides a readout of the immune environment within the tumor, specifically whether there are expanded T cell populations that may recognize cancer, explained Marnix Jansen, MD, a clinician scientist and consultant histopathologist who led the translational research on the trial from UCL Cancer Institute.

“We found that patients who achieved a complete response had a higher proportion of expanded T cell clones in their tumors, suggesting a more focused and effective anti-tumor immune response at baseline,” he said.

When the team combined the ctDNA results with the TCR sequencing data, they improved the ability to predict outcomes compared with using either biomarker alone.

“The key implication is that integrating immune and tumor biomarkers in a dynamic model may allow early, data-driven treatment decisions, such as identifying patients who are highly likely to benefit or, conversely, those who may need a change in therapy,” Jansen told Inside Precision Medicine.

The post Presurgery Pembrolizumab May Be the Future for Some Operable CRCs appeared first on Inside Precision Medicine.

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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.

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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.

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<![CDATA[Psychedelic therapies surge, but a rushed FDA shortcut risks safety; learn why ibogaine claims need rigorous trials and oversight.]]>
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<![CDATA[Learn how antipsychotics and stress raise prolactin, what symptoms to spot, and when to test—plus practical options to lower levels.]]>
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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.

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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.

The post Viral Contamination Still a Challenge for CGT Industry appeared first on GEN – Genetic Engineering and Biotechnology News.

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AI Wizard Adapts Processes in a Self-Driving Lab

German researchers who run a self-driving laboratory have created an agentic AI wizard to help their students rapidly design and implement new processes.

The wizard, which uses N8N software, can guide a student through establishing experiments without the need for coding, allowing them to quickly set up a new process.

According to Matthias Franzreb, PhD, a professor and departmental leader in bioengineering and biosystems at the Karlsruhe Institute of Technology, developing wizards could help any autonomous laboratory where the experimental setup needs to change fast.

“Each of our bachelor’s and master’s students has their own type of experiment and, in the beginning, going into Python scripting, it used to take two months to have the whole thing programmed,” he says.

By contrast, he says, the AI agent can help the student develop a new process within one or two days. It has so far been used to develop around six processes, he says, for a slightly larger number of students, as the same template can be used more than once.

Bioprocessing, like many other areas of human endeavor, is experiencing disruptive change with the growing use of digital tools at both the laboratory and commercial scale, Franzreb explained in a talk at Bioprocessing Summit Europe.

Among these changes is the difference between classical labs, which have automated equipment, such as liquid handling stations, but where scientists must design and set up their own experiments, and self-driving labs. In the latter, he explains, machine learning uses a first set of experiments to autonomously decide what experiments should be next.

In his talk, Franzreb also showed how a wizard could be used for designing a chromatography experiment. An experiment was set up to determine batch parameters at a small-scale in 96-well plates. From this, the software used a chromatography simulation to find the optimal conditions for the experiment and then ran it in a real chromatography system to validate the results.

According to Franzreb, the next step for the self-driving laboratory will be working with the German Research Center for Artificial Intelligence (DFKI) and other research partners to develop ontological capabilities for the wizards so they can extract context for the experiments from Standard Operating Procedures (SOPs) or the academic literature.

“I think this is simple in principle,” he explains. “But at the moment we don’t have it, and it will be a challenge to roll out.”

The post AI Wizard Adapts Processes in a Self-Driving Lab appeared first on GEN – Genetic Engineering and Biotechnology News.

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Monitoring Mammalian and Microbial Bioprocesses in Real Time

At the 2026 BiOS conference in San Francisco, researchers presented a biosensing platform aimed at improving how living cells and tissues are monitored during drug bioprocessing. Known as TissueSense, the system provides continuous, real-time insight into cellular behavior without disrupting the biological environment.

In biopharmaceutical manufacturing, maintaining consistent cell health and productivity is essential. Yet many monitoring approaches still rely on intermittent sampling or endpoint measurements, offering only partial visibility into dynamic biological processes. TissueSense addresses this limitation by enabling continuous, in situ observation—capturing changes as they unfold.

The platform combines resonator-based photonic sensing with phase contrast microscopy, allowing simultaneous detection of biochemical activity and structural changes in cells. This dual approach provides a more complete picture of how cells respond to process conditions, such as nutrient shifts or environmental stress, which directly impact production outcomes.

A defining feature of the system is its label-free operation. Conventional biosensing methods often require fluorescent markers or reagents that might alter cell behavior or limit long-term monitoring. By removing these constraints, TissueSense supports extended observation of living systems in conditions closer to their natural state, an advantage for prolonged bioprocesses.

Data from the platform are analyzed using machine learning to simultaneously quantify up to 18 biomarkers, linking molecular outputs—such as secreted proteins—to tissue structure and function. This multiplexed capability is particularly relevant in drug manufacturing, where small variations in cellular activity can influence yield, quality, and reproducibility.

While TissueSense focuses on mammalian tissue models, parallel advances in microbial systems highlight a broader shift toward continuous, high-resolution monitoring across bioprocessing platforms. In yeast-based systems, for example, researchers have developed microbead-based cultivation methods that enable high-throughput, label-free screening of millions of individual mutants in extremely small volumes. These approaches can enrich desirable traits, such as resistance to metabolic inhibitors, by thousands-fold, supporting strain optimization for industrial bioproduction.

Similarly, in bacterial bioreactors, automated flow cytometry techniques now allow real-time tracking of population dynamics and physiological states. By combining DNA staining with indicators of active replication, these systems provide continuous insight into growth rates and cell cycle behavior, helping optimize feed strategies and overall process performance.

Together, these developments point toward a more integrated future for bioprocess monitoring—one that spans mammalian, yeast, and bacterial systems. Continuous, non-destructive sensing technologies are enabling researchers and manufacturers to move beyond static measurements toward dynamic control of biological production.

The post Monitoring Mammalian and Microbial Bioprocesses in Real Time appeared first on GEN – Genetic Engineering and Biotechnology News.