When surgeons remove a portion of a cancerous lung, one of the most frustrating complications they can face is air. A persistent leak from the lung’s cut surface or staple lines — known as prolonged air leak — keeps chest tubes in place far longer than anyone would like, extends hospital stays, inflates costs, and elevates the risk of infection and other downstream problems. Now, a research team in China has developed a machine learning tool that predicts, with striking accuracy, which older lung cancer patients are most likely to develop this complication before it ever occurs. The study, published in BMC Cancer, combines cardiopulmonary exercise testing data with an interpretable artificial intelligence model and could reshape how thoracic surgical teams prepare for and manage one of the most common postoperative challenges in lung surgery.

The research was led by Zixiao Wang, Jiabao Ding, Huagang Liang and colleagues at the First Hospital of Qinhuangdao, in collaboration with Kai Wang of Tianjin Chest Hospital. It addressed a well-recognized gap in thoracic surgical practice. While prolonged air leak — typically defined as air leaking from the chest drainage system for more than five days after surgery — is among the most frequent complications following video-assisted thoracoscopic anatomical lung resection, the prediction models available to clinicians have historically lacked rigorous external validation and, critically, interpretability. Surgeons have been asked to trust risk scores without understanding where those risks come from, a barrier that has limited clinical uptake of computational tools in the operating room planning process.

To build their model, the investigators enrolled patients aged 60 and older with lung cancer who underwent thoracoscopic anatomical lung resection — either lobectomy, the removal of an entire lung lobe, or segmentectomy, the removal of a smaller anatomical segment. The study was designed as a dual-centre cohort investigation with both retrospective and prospective components. A total of 471 patients treated at Qinhuangdao First Hospital between January 2024 and June 2025 formed the model development cohort. A separate group of 140 patients from Tianjin Chest Hospital, enrolled prospectively between June and August 2025, provided the external validation set — a crucial test of whether the model generalized beyond the institution where it was built.

The methodology followed the emerging best-practice playbook for clinical machine learning. After preliminary data processing, the development cohort was randomly split into a training set containing 70 percent of patients and an internal validation set holding the remaining 30 percent. Because prolonged air leak affects only a minority of surgical patients, the training data were inherently imbalanced, with far more non-leak cases than leak cases — a condition that can fool machine learning algorithms into simply predicting that no one is at risk. The researchers countered this with SMOTE, the Synthetic Minority Over-sampling Technique, which generates synthetic examples of the underrepresented class to rebalance the dataset and force the algorithms to learn the genuine signature of risk.

Feature selection was performed using LASSO regression — least absolute shrinkage and selection operator — a statistical technique that penalizes model complexity and drives the coefficients of irrelevant variables to zero, effectively filtering a large panel of candidate variables down to the most predictive few. From this process, four predictors of prolonged air leak emerged: a history of emphysema, the smoking index, a previous history of thoracic surgery or chest trauma, and the ventilatory equivalent for carbon dioxide, abbreviated VE/VCO₂. This last variable is drawn directly from cardiopulmonary exercise testing, a stress test performed on a bicycle or treadmill that measures how the heart, lungs, and circulatory system respond together to increasing exertion. VE/VCO₂ reflects the efficiency of ventilation during exercise — how much air a patient must move to eliminate a given amount of carbon dioxide — and elevated values signal impaired pulmonary gas exchange and often underlying parenchymal lung disease.

With the four features in hand, the team constructed six competing machine learning models: logistic regression, support vector machine, decision tree, extreme gradient boosting, and artificial neural networks, among others. Each was evaluated using a battery of metrics including the area under the receiver operating characteristic curve, or AUC, the F1 score, and the Brier score, which measures the accuracy of probabilistic predictions. The winner was XGBoost, an ensemble method that builds a sequence of decision trees, with each new tree trained to correct the residual errors of its predecessors. In internal validation, XGBoost achieved an AUC of 0.903 (95 percent confidence interval, 0.834 to 0.960) — well within the range conventionally considered excellent discrimination — along with the highest F1 score of 0.717 and the lowest Brier score of 0.092 among all six candidates.

The external validation was arguably the study’s most important test. A model can memorize the quirks of its home institution’s patient population, equipment, and surgical practices, only to falter elsewhere. Yet when applied to the 140 previously unseen patients from Tianjin Chest Hospital, the XGBoost model maintained an AUC of 0.800 (95 percent confidence interval, 0.656 to 0.913), with a sensitivity of 0.700, a specificity of 0.833, and a Brier score of 0.133. In practical terms, the model correctly flagged seven out of ten patients who went on to develop prolonged air leak while correctly reassuring more than eight out of ten of those who did not — performance that, if replicated in routine practice, would give surgeons a meaningful window to intervene preemptively.

Interpretability was treated not as an afterthought but as a core design requirement. The researchers applied SHAP — Shapley Additive Explanations — a technique borrowed from cooperative game theory that assigns each feature a contribution value for every individual prediction. Rather than presenting clinicians with an opaque probability, SHAP reveals how much each of the four variables pushed a given patient’s risk up or down, and in which direction. Through this analysis, VE/VCO₂ emerged as the single most influential feature, followed by the other three predictors ranked by correlation. The finding is physiologically plausible: patients whose lungs ventilate inefficiently under the stress of exercise are precisely those whose lung tissue is most fragile and least likely to seal spontaneously after surgical manipulation. A history of emphysema, a heavy smoking history, and prior chest surgery or trauma each independently compound this tissue vulnerability.

The clinical utility of the work extends beyond prediction to prevention. Armed with a preoperative risk estimate, surgical teams can tailor their approach for high-risk patients. Options include more meticulous staple-line reinforcement, the use of sealants or pledgeted sutures on fragile lung tissue, choosing segmentectomy over lobectomy where oncologically appropriate, planning for ambulatory drainage systems on discharge, or scheduling earlier follow-up to catch and manage leaks before they become complicated. To lower the barrier to bedside use, the team built a web-based risk calculator that allows clinicians to enter a patient’s four variables and receive an individualized probability of prolonged air leak — no programming expertise required.

The significance of incorporating cardiopulmonary exercise testing into a surgical prediction model deserves particular emphasis. Traditional preoperative pulmonary assessment in lung cancer surgery has relied on static spirometric measures such as forced expiratory volume in one second, or FEV1, and the diffusing capacity for carbon monoxide, DLCO. These tests measure lung function at rest and provide only a partial picture of cardiopulmonary reserve. CPET, by contrast, captures the integrated response of multiple organ systems under physiological stress, and the VE/VCO₂ slope in particular has gained recognition as a sensitive marker of ventilatory inefficiency in chronic obstructive pulmonary disease and heart failure. The present study suggests that this dynamic measure carries prognostic information for surgical outcomes that static tests do not fully capture — a finding with implications well beyond air leak prediction.

Several caveats frame the work appropriately. The study population was limited to Chinese patients aged 60 and above undergoing video-assisted thoracoscopic resection, and generalization to younger patients, other surgical techniques such as robotic-assisted resection, or different health care systems remains to be demonstrated. The external validation cohort, while methodologically essential, comprised 140 patients, and wider multicenter prospective trials would strengthen confidence in the model’s performance. The published article is an accepted, peer-reviewed author manuscript shared early ahead of the final version of record. The study was funded by the Beijing Kechuang Medical Development Foundation, with the funder playing no role in study design, analysis, or manuscript preparation, and the authors declare no competing interests.

Even so, the study stands as a compelling example of where predictive medicine is heading. By pairing a rigorous dual-centre validation strategy with explainable artificial intelligence and a physiologically grounded predictor, the researchers have moved machine learning in thoracic surgery closer to genuine clinical utility rather than proof-of-concept novelty. For the growing population of older patients facing lung cancer surgery, a simple preoperative test and a few clicks in a web calculator may soon determine who needs extra surgical vigilance — and spare many of them the days of tethered chest drainage that have long been an accepted, if unwelcome, part of recovery.

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Bat DNA may hold clues to a long and healthy life, according to an international team of researchers.

These small creatures grace the night skies with extremely long lifespans and low cancer rates—traits that may ultimately benefit humanity if scientists can figure out how bats achieve them. Now, in a recent paper published in Nature, scientists from the University of Vermont and Penn State University led an international team investigating bats’ immune systems.

The paper’s crucial discovery was that bat DNA reveals the creatures encode genomic changes to handle exposure to environmental pathogens.

The Miraculous Bat

“Pathogen adaptation, longevity, and cancer resistance—they are fundamentally linked,” explained co-lead author Elise Lauterbur, an assistant professor of evolutionary biology at the University of Vermont. “Many of the genes that have adapted to viruses in bats are genes that are also involved in longevity and cancer resistance.”

Bats make an ideal study subject as they are only second to rodents in diversity, allowing scientists to study a wide variety of features in a single order.

“If you look at two bats, the same size, one lives 3 years the other lives 30 years and they are very closely related, like humans and Neanderthals, you can essentially find a very small number of genetic changes that leads to a very big change in their lifespan,” said co-lead author Juan Manuel “Manny” Vazquez, an assistant professor at Penn State University. “And that is kind of the Holy Grail for evolutionary medicine.”

The work focused on Myotis, one of the largest bat genera, whose members are found across much of the globe outside Antarctica. Eight Myotis species came under the microscope, with the team experimenting on cultured cells and analyzing their genomes. Among the species sampled were little brown bats (Myotis lucifugus), known both for their long lifespans, even among bats, and their susceptibility to the deadly white-nose syndrome, a fungal disease.

Even the researchers’ sample-collection methods were novel. They developed a technique akin to ear-piercing to collect small tissue samples from bat wings, which were then used to establish cell cultures. The team says this both spared the animals’ lives and produced more scientifically useful samples.

Bat Evolution

In their detailed examination, the researchers identified evidence of past events in which Myotis bats encountered pathogens and how adaptations to those viruses were selected for during their evolution.

Their work identified specific genomic changes, including the duplication or deletion of genes, associated with adaptation to environmental pathogens. This illuminated important differences in bats’ responses to DNA and RNA viruses compared with humans and other primates, potentially contributing to bats’ long, healthy lifespans.

Comparatively, human evolution shows stronger selection involving proteins that interact with RNA viruses like influenza, while bats show stronger selection involving proteins that interact with DNA viruses such as herpesviruses. These differences may help explain the distinct ways bats and primates have adapted to viral threats.

Cancer Resistance

The team also identified genetic mechanisms that could help explain bats’ resistance to cancer and other age-related diseases. In some cases, duplicated genes can diversify their functions, allowing different copies to perform distinct roles. According to the researchers, this may provide immune advantages that help bats combat multiple viruses while also contributing to pathways associated with longevity.

Another important finding was that while most mammals contain one copy of the immune-related gene PRKN, some bat species contain two or even three copies, suggesting that additional copies may offer evolutionary advantages. The team says this could provide important insights for future cancer research, given bats’ unusual ability to repair or eliminate damaged cells.

The research doesn’t point to immediate treatments for humans, but it does provide starting points for reconsidering human illness in the context of bat immunology and evolution.

“Everything is connected,” Vazquez concluded. “Everything uses the same shared set of biology. … We don’t have to treat all of these different problems as silos. We can now start focusing on systems like bats to understand how we can solve multiple human age-related diseases.”

The paper, “Insights into Longevity and Virus-Driven Adaptation from Myotis Bat Genomes,” appeared in Nature on August 26, 2026.

Ryan Whalen covers science and technology for The Debrief. He holds an MA in History and a Master of Library and Information Science with a certificate in Data Science. He can be contacted at ryan@thedebrief.org, and follow him on Twitter @mdntwvlf.

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Animal testing has shaped modern drug development for decades, but its limitations become especially visible when scientists evaluate cancer immunotherapies. These treatments are designed to stimulate the immune system to recognize and destroy malignant cells, yet the same powerful immune activation can trigger life-threatening complications in patients. Researchers at the University of Rochester are developing a human-cell-based alternative: miniature tissue models known as organs-on-a-chip that could help predict these toxicities before experimental medicines reach clinical trials.

The work is being led through the university’s Translational Center for Barrier Microphysiological Systems, or TraCe-bMPS. The center is building drug-development tools around modular µSiM tissue chips, devices that contain ultrathin membranes populated with human cells. Unlike conventional laboratory cultures, these systems are engineered to reproduce key features of biological barriers, including the physical separation between tissues, controlled exposure to drugs, and measurable inflammatory responses. Their modular construction also allows the devices to be manufactured in large quantities with consistent dimensions and materials.

The platform is based primarily on acrylic components and incorporates membranes designed to mimic interfaces found in the human body. Such barriers regulate the movement of molecules and immune cells between compartments, making them central to drug absorption, toxicity, and inflammation. By assembling reproducible chips with human cells, researchers can study how a therapy affects a tissue under conditions that more closely approximate human biology than many animal models. The design also makes it possible to modify individual components for different organs or disease settings.

A major feature of the Rochester system is the integration of sensors directly into the chips. Developed in part through the work of biomedical engineering professor Benjamin Miller, these sensors can track barrier function and inflammatory signaling in real time. Instead of waiting until the end of an experiment to examine damaged cells, researchers can observe how a tissue responds as a drug is introduced. Changes in electrical or molecular signals may reveal that a barrier is becoming more permeable or that inflammatory pathways are being activated, providing an early warning of toxicity.

The immediate focus is on two severe complications associated with some cancer immunotherapies. Cytokine release syndrome, commonly called CRS, occurs when activated immune cells release large quantities of signaling proteins known as cytokines. The resulting systemic inflammation can cause fever, low blood pressure, breathing difficulties, and, in the most serious cases, organ failure. Immune effector cell-associated neurotoxicity syndrome, or ICANS, can affect the nervous system, producing confusion, seizures, impaired speech, or other neurological symptoms. Both conditions are difficult to predict reliably with animal testing because species differ in immune signaling networks and cell-surface receptors.

“The goal is to predict these toxicities from human cells on a chip, before a drug ever reaches a patient, and to do it without relying on animal models that have repeatedly failed to predict CRS in people,” says James McGrath, director of TraCe-bMPS and the William R. Kenan Jr. Professor of Biomedical Engineering. The approach does not simply attempt to reproduce a whole human body in miniature. Instead, it focuses on specific biological barriers and immune interactions that are directly relevant to the safety question being studied.

The project has now reached an important regulatory stage. The team was accepted into the US Food and Drug Administration’s Innovative Science and Technology Approaches for New Drugs, or ISTAND, pilot program. ISTAND is intended to help evaluate emerging methods that could improve drug development and eventually support regulatory decisions. Acceptance does not mean that the tissue-chip platform has already been approved for routine use, but it creates a formal pathway for the researchers to work with the FDA on defining the evidence needed for qualification.

The Rochester group is preparing a detailed qualification plan that will describe clinical considerations, timelines, data-sharing procedures, and statistical methods for evaluating the technology. If the platform ultimately receives FDA qualification, pharmaceutical companies could use its results as part of the evidence submitted in support of new drug applications. Such recognition would represent a significant step for organs-on-a-chip research, which has expanded rapidly but has only rarely progressed into formal regulatory programs.

The effort comes as US regulators seek alternatives to animal testing in preclinical safety studies. The FDA Modernization Act 2.0, enacted in 2022, opened the door for non-animal methods, while the agency’s 2025 roadmap outlined further efforts to reduce reliance on animal models. Researchers say pharmaceutical companies are showing strong interest because many immunotherapies are already in clinical development and carry risks of CRS or ICANS. The Rochester team collaborated with Graham Marsh of the Critical Path Institute and consulted with scientists at Pfizer about how the tool could fit into real-world drug development. If successful, the technology could give researchers a more human-relevant way to identify dangerous immune reactions early, helping developers eliminate unsafe candidates and refine promising treatments before patients are exposed.

Subject of Research: Human-cell tissue chips for predicting cancer immunotherapy toxicities.

Web References: University of Rochester; Translational Center for Barrier Microphysiological Systems; University of Rochester Biomedical Engineering; FDA ISTAND pilot program; FDA Modernization Act 2.0.

Image Credits: URochester photo / J. Adam Fenster.

Keywords: Drug discovery, tissue chips, organs-on-a-chip, cancer immunotherapy, cytokine release syndrome, CRS, ICANS, neurotoxicity, animal testing alternatives, biomedical engineering, microphysiological systems, human-cell models.

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Neuroblastoma, a cancer of the developing nervous system, has long challenged researchers because its behavior can vary dramatically from one patient to another. Some tumors respond well to treatment, while others grow aggressively, spread rapidly, and return despite intensive therapy. A new study published in the British Journal of Cancer examines one of the most important genetic features associated with this disease: changes affecting the long arm of chromosome 17, known as 17q. The research presents chromosome 17q as more than a passive marker of cancer progression, describing it as a functional region where the demands of rapid DNA replication collide with the cell’s need to preserve genomic stability.

Chromosome 17q is frequently altered in neuroblastoma, particularly through the gain of additional genetic material. In cancer biology, such gains can increase the dosage of genes that support tumor growth, survival, or resistance to treatment. Yet the consequences are not necessarily uniform across the entire chromosome. A duplicated region may contain genes with opposing effects: some may help malignant cells divide, while others may create vulnerabilities by placing excessive pressure on the machinery responsible for copying DNA. The study by Hilgert, Depestel, Van Roy and colleagues investigates this functional complexity rather than treating 17q gain as a single, indivisible event.

DNA replication is the process by which a cell copies its genome before dividing. This operation must proceed rapidly but with remarkable accuracy. When replication forks—the molecular structures that move along DNA during copying—slow down, stall, or collapse, cells experience replication stress. Replication stress can arise when cancer cells divide too quickly, when DNA contains difficult-to-copy sequences, or when the supply of nucleotides and other replication components becomes insufficient. If unresolved, stalled replication forks can generate DNA breaks and rearrangements, helping tumors evolve while also threatening the survival of the cells that carry them.

The new work focuses on how genetic elements within 17q influence this balance. A region that promotes proliferation may simultaneously intensify replication stress, creating a biological paradox. Tumor cells benefit from increased growth signals, but they must also develop mechanisms to tolerate the resulting damage. This dependence can become a weakness: cancer cells operating close to the limits of replication may rely heavily on DNA repair pathways and checkpoint systems that normal cells use less intensively. Disrupting those support systems could selectively harm tumor cells, an idea that has become central to the development of targeted cancer treatments.

The researchers describe a “functional landscape” for chromosome 17q, suggesting that the region should be understood through the combined activity of its genes and regulatory elements. Genes do not act in isolation. Their effects depend on gene dosage, cellular context, interactions with other genomic regions, and the stage of tumor development. In neuroblastoma, these relationships may determine whether a 17q alteration produces a viable, treatment-resistant cancer cell or instead creates so much replication difficulty that the cell becomes vulnerable to damage and death. Mapping these relationships offers a more precise view of why the same broad chromosomal change can have different consequences in individual tumors.

This perspective is especially important because neuroblastoma often develops from immature cells of the peripheral nervous system. During early development, these cells naturally undergo tightly regulated programs of growth, migration, and differentiation. Cancer can emerge when those programs are disrupted, allowing cells to continue dividing instead of maturing into specialized nerve-related cells. Additional chromosomal alterations may then reinforce the malignant state. By connecting 17q abnormalities with replication stress and genome maintenance, the study places a major neuroblastoma feature within the wider biology of developmental cancer.

Genomic stability refers to the ability of a cell to copy and preserve its DNA without accumulating excessive mutations or structural changes. Cancer cells frequently compromise this stability, producing an unstable genome that can accelerate adaptation. However, instability has limits. Too little DNA damage may not generate enough diversity for a tumor to evolve, while too much can trigger cell death or permanent growth arrest. The study’s central concept is that 17q alterations may push neuroblastoma cells toward this dangerous threshold, forcing them to balance accelerated growth against the risk of catastrophic replication failure.

The findings could influence how researchers think about treatment strategy. If specific 17q-associated activities make tumor cells dependent on replication-stress responses, therapies aimed at DNA damage checkpoints or repair enzymes might be especially effective in selected neuroblastomas. Such approaches could potentially be combined with existing treatments, including chemotherapy, which already damages DNA but can also harm healthy tissues. The challenge will be identifying which tumors truly depend on particular repair mechanisms and determining how to target those dependencies without increasing toxicity. A functional map of 17q could help move treatment decisions beyond the simple presence or absence of a chromosomal gain.

The study also highlights why cancer genomes should not be interpreted solely through large-scale structural changes. A chromosomal gain may be clinically useful as a prognostic signal, but its biological meaning depends on the genes and pathways it affects. By examining how chromosome 17q contributes to replication stress and genome protection, the researchers provide a framework for understanding why this region is repeatedly selected during neuroblastoma evolution. Their work points toward a future in which genetic alterations are assessed not only as labels of risk, but as clues to the specific pressures that keep cancer cells alive—and the vulnerabilities that may ultimately bring them down.

Subject of Research: Functional effects of chromosome 17q alterations, replication stress, and genomic stability in neuroblastoma

Article Title: A functional landscape for chromosome 17q in neuroblastoma: balancing replication stress and genomic stability

Article References: Hilgert, E., Depestel, L., Van Roy, N. et al. “A functional landscape for chromosome 17q in neuroblastoma.” British Journal of Cancer (2026). https://doi.org/10.1038/s41416-026-03569-w

Image Credits: AI Generated

DOI: 10.1038/s41416-026-03569-w

Keywords: Neuroblastoma, chromosome 17q, replication stress, genomic stability, DNA replication, DNA repair, cancer genetics, tumor evolution, developmental cancer

A new study published in the British Journal of Cancer is challenging the way lung-cancer risk is discussed among people who do not smoke conventional cigarettes. Researchers led by S. Vaja, J.L. Dickson and C. Horst examined the effects of cigar, cigarillo and pipe smoking, focusing on two questions with immediate public-health consequences: how these products influence the likelihood of developing lung cancer and whether their users are being identified as eligible for screening.

Lung-cancer prevention strategies have traditionally been built around cigarette consumption, especially the number of cigarette packs smoked per year. This measure, known as pack-years, combines smoking intensity and duration. One pack-year generally represents smoking 20 cigarettes a day for one year. Because cigars, cigarillos and pipes are used differently from cigarettes, their tobacco exposure is harder to convert into the same standardized measurement. That difference can leave regular users outside the systems designed to identify people at high risk.

The study addresses a persistent misconception: that alternative combustible tobacco products are inherently safer because they are not smoked in the same way as cigarettes. Cigar and pipe users may inhale less deeply or less frequently, but the smoke still contains carcinogenic compounds produced by burning tobacco. These include polycyclic aromatic hydrocarbons, tobacco-specific nitrosamines, volatile organic compounds and fine particulate matter. The precise dose entering the lungs can vary substantially, yet repeated exposure can still damage airway cells and contribute to mutations associated with cancer development.

Cigarillos occupy a particularly complicated position because they range from small, cigarette-like products to larger cigars that may be smoked over a longer period. Their nicotine content and smoke volume can also differ widely. Some users inhale cigarillo smoke deeply, while others do not. Pipes introduce another set of variables, including the duration of a smoking session, the amount of tobacco burned and the frequency with which the pipe is used. These differences make simple comparisons difficult, but they do not eliminate the biological hazards of combustion.

According to the research, the central concern is not only whether cigar, cigarillo and pipe smoking increases lung-cancer risk, but also whether current screening rules recognize that risk. Lung-cancer screening commonly relies on age and a history of cigarette smoking measured in pack-years. People who have smoked other combustible tobacco products may therefore be classified as having insufficient exposure, even when their cumulative tobacco use has been substantial. If risk is underestimated at the eligibility stage, some people could miss the opportunity to detect a tumour before symptoms appear.

Screening works by identifying disease at an earlier and more treatable stage, often using low-dose computed tomography, or LDCT. Unlike a conventional CT scan, LDCT uses a lower radiation dose to create detailed images of the lungs. Its effectiveness depends on selecting people whose probability of developing lung cancer is high enough to justify the benefits and potential harms of testing. Those harms include false-positive findings, unnecessary follow-up procedures, anxiety and cumulative radiation exposure. The challenge is to expand access without encouraging indiscriminate scanning.

The researchers’ analysis highlights why tobacco history needs to be recorded in greater detail. A questionnaire that asks only whether someone smokes cigarettes can overlook the frequency, duration and type of cigar, cigarillo or pipe use. It may also fail to capture former users whose exposure occurred years earlier. More comprehensive risk models could incorporate the number of products used, smoking intensity, years since quitting, inhalation patterns and additional factors such as age, occupational exposure, air pollution and family history.

The findings also carry a message for people who use these products socially or intermittently. Risk is not determined solely by whether smoking occurs every day. The biological impact depends on cumulative exposure, the composition of the product and how smoke is inhaled. Occasional use may carry less risk than heavy, long-term use, but “less” does not mean “none.” Combustible tobacco remains fundamentally different from non-combustible nicotine products because burning creates the toxic mixture responsible for much of the damage to the respiratory system.

The study does not suggest that every cigar or pipe smoker should automatically undergo a CT scan. Instead, it points to a gap between real-world tobacco exposure and the simplified categories used in many screening policies. The authors’ work could encourage clinicians and policymakers to assess alternative tobacco use more systematically and to investigate whether existing eligibility thresholds should be adapted. Any change would require careful validation, because screening recommendations must balance earlier diagnosis against the risks of testing people who are unlikely to benefit.

The broader lesson is that lung-cancer risk cannot be reduced to a single cigarette-based number. As smoking patterns evolve and tobacco products diversify, prevention programmes must keep pace with the ways people actually consume tobacco. The study by Vaja and colleagues adds evidence that cigar, cigarillo and pipe smoking deserve a more visible place in lung-health research and clinical risk assessment. For now, the clearest preventive message remains unchanged: avoiding all combustible tobacco products offers the strongest protection, while anyone with a history of substantial use should discuss their individual risk with a healthcare professional.

Subject of Research: The effects of cigar, cigarillo and pipe smoking on lung-cancer risk and eligibility for lung-cancer screening.

Article Title: The effect of cigar, cigarillo and pipe smoking on lung cancer risk and screening eligibility.

Article References: Vaja, S., Dickson, J.L., Horst, C. et al. “The effect of cigar, cigarillo and pipe smoking on lung cancer risk and screening eligibility.” British Journal of Cancer (2026). https://doi.org/10.1038/s41416-026-03578-9

Image Credits: AI Generated

DOI: 10.1038/s41416-026-03578-9

Keywords: lung cancer, cigar smoking, cigarillo smoking, pipe smoking, tobacco exposure, cancer screening, low-dose CT, smoking-related cancer, public health, epidemiology

Cancer researchers have reported a new strategy that combines bacterial tumor targeting, nutrient deprivation and immune stimulation in a single therapeutic design. The approach uses an engineered conjugate built from L-asparaginase and flagellin, linked to a system that directs the treatment toward calreticulin-bearing cancer cells. In experiments involving Salmonella-mediated tumor therapy, the conjugate enhanced antitumor activity compared with bacterial treatment alone, according to a study published in Cell Death Discovery.

The work addresses a long-standing challenge in cancer therapy: how to make powerful treatments concentrate inside tumors while limiting damage to healthy tissues. Attenuated strains of Salmonella have attracted interest because they can preferentially accumulate in the abnormal environment of solid tumors. Tumors often contain regions with poor oxygen levels, disorganized blood vessels and local immune suppression, conditions that can support bacterial growth. Once inside these sites, therapeutic Salmonella can act as a biological delivery platform and stimulate immune responses against malignant cells.

The researchers focused on calreticulin, a protein normally found inside the endoplasmic reticulum, where it helps regulate calcium storage and protein folding. Under cellular stress, including stress caused by chemotherapy, radiation or other anticancer treatments, calreticulin can move to the outer surface of a cancer cell. There, it functions as an “eat-me” signal, alerting immune cells that the damaged cell should be engulfed. Because surface-exposed calreticulin is associated with immunogenic forms of cell death, it provides a potential molecular address for directing therapeutic agents toward stressed tumor cells.

The experimental construct combines this targeting concept with L-asparaginase, an enzyme already used in clinical oncology, especially in the treatment of acute lymphoblastic leukemia. L-asparaginase breaks down circulating L-asparagine into aspartic acid and ammonia. Some cancer cells, particularly those with limited capacity to synthesize their own asparagine, depend heavily on the amino acid supplied through the bloodstream. Depleting extracellular asparagine can therefore interrupt protein production, trigger metabolic stress and promote cancer-cell death. The enzyme’s effectiveness, however, can be limited by immune reactions, pharmacological instability and toxicity, making targeted delivery an important goal.

The second component, flagellin, is the structural protein that forms the filament of bacterial flagella. It is also a potent molecular signal for the innate immune system. Immune cells recognize flagellin primarily through Toll-like receptor 5, while intracellular sensing pathways can activate inflammasome components such as NLRC4. These signals can promote the release of inflammatory mediators, stimulate antigen-presenting cells and help convert an immunologically “cold” tumor into one more visible to the immune system. By incorporating flagellin into the therapeutic design, the researchers sought to make the treatment not only directly toxic to tumor cells but also capable of amplifying antitumor immunity.

The study’s central finding was that the calreticulin-targeting L-asparaginase–flagellin conjugate strengthened the antitumor effects of Salmonella-based therapy. Rather than relying on a single mechanism, the treatment brings together several forms of pressure on the tumor. Salmonella can concentrate within the tumor microenvironment, the targeting component can help associate the conjugate with calreticulin-exposing cancer cells, L-asparaginase can deprive vulnerable cells of an essential nutrient, and flagellin can activate immune surveillance. The resulting combination is designed to produce a chain reaction in which metabolic stress and immune stimulation reinforce one another.

This type of combination may be particularly valuable because tumors frequently adapt when exposed to one therapeutic pressure. A cancer cell that survives nutrient deprivation may still be eliminated if immune recognition is intensified. Likewise, an immune response that is too weak to control a tumor may become more effective when bacterial localization and enzyme-mediated damage increase the number of abnormal antigens and danger signals released by dying cells. The researchers’ findings suggest that coordinating these mechanisms can improve the performance of bacteria-assisted cancer treatment in experimental settings.

The approach also reflects a broader shift in cancer research toward programmable biological medicines. Instead of treating bacteria only as infectious threats, scientists are redesigning them as localized delivery vehicles capable of carrying enzymes, immune activators or molecular probes. The advantage is spatial: a therapeutic payload can be produced or concentrated near the tumor rather than distributed uniformly throughout the body. The challenge is equally significant. Any clinical version would need precise control over bacterial attenuation, immune activation, enzyme exposure and potential inflammation, while also demonstrating reliable performance across genetically diverse tumors.

Calreticulin targeting may provide a useful way to address some of that complexity because the protein’s appearance on the cell surface is linked to cellular stress and treatment response. However, the extent and duration of calreticulin exposure can vary between tumor types and individual patients. Future studies will need to determine which cancers are most suitable for this strategy, how calreticulin levels predict treatment response and whether the conjugate can be combined safely with established immunotherapies such as immune-checkpoint inhibitors. Researchers will also need to assess pharmacology, manufacturing consistency and the possibility of immune reactions against the bacterial or enzymatic components.

The findings position the engineered conjugate as a promising experimental platform rather than an immediately available therapy. By merging tumor-homing bacteria with a calreticulin-directed enzyme and an innate immune stimulant, the study illustrates how cancer treatments can be designed to attack malignant cells on multiple biological fronts. If the results are confirmed in further preclinical testing and eventually in carefully controlled clinical trials, this strategy could help turn Salmonella from a passive carrier into an active, multifunctional partner in cancer immunotherapy.

Subject of Research: Calreticulin-targeted L-asparaginase–flagellin conjugate used with Salmonella-mediated cancer therapy.

Article Title: Calreticulin-targeting L-asparaginase-flagellin conjugate enhances Salmonella-mediated antitumor efficacy.

Article References: Nguyen, DH., Afzal, A.R., Nguyen, P.TM. et al. Calreticulin-targeting L-asparaginase-flagellin conjugate enhances Salmonella-mediated antitumor efficacy. Cell Death Discov. (2026). https://doi.org/10.1038/s41420-026-03300-x

Image Credits: AI Generated

DOI: https://doi.org/10.1038/s41420-026-03300-x

Keywords: cancer immunotherapy, Salmonella, calreticulin, L-asparaginase, flagellin, tumor targeting, bacterial therapy, antitumor efficacy, immunogenic cell death