A mammogram does more than search for suspicious lumps. It can also show whether a woman’s breasts contain a large amount of dense tissue, a feature that has long been associated with a higher chance of developing breast cancer. For many years, breast density was especially important because it could hide small tumors on mammograms. […]

The post Dense Breasts May Create a Hidden Cancer-Friendly Environment appeared first on Knowridge Science Report.

North Carolina has secured $455 million in payments from Chemours, DuPont and Corteva over PFAS pollution, along with a separate $135 million reserve intended to protect future drinking water and cleanup work.

For more than four decades, pathologists have glimpsed something unsettling under the microscope in the earliest stages of certain cancers: cells with nuclei far larger than they should be, swollen and distorted, lurking in tissue that otherwise appears on the verge of catastrophe. These so-called giant-nucleus cells, or karyomegalic cells, were first spotted in the 1980s in animal experiments involving iron-induced oxidative stress, yet their biological identity and their role in the genesis of cancer remained stubbornly obscure. Now, a team of researchers in Japan has provided the most detailed portrait of these cells to date, and their findings suggest that the enormous nuclei may be far more than a curiosity—they could be the founding population of early cancer, visible before any tumor exists, and potentially useful as a predictor of patient outcomes.

The study, led by Shinya Toyokuni, professor emeritus at Nagoya University Graduate School of Medicine, together with assistant professor Yingyi Kong and colleagues, was published in Redox Biology. The work addresses a deceptively simple question: when iron overload kills most cells in a tissue through oxidative damage, who survives, and what do the survivors become? Iron is an essential micronutrient, but in excess it is a potent carcinogen. Its chemistry is both the reason we need it and the reason it can harm us. Iron catalyzes the formation of hydroxyl radicals from hydrogen peroxide through the Fenton reaction, and these radicals shred DNA, oxidize lipids, and damage proteins. When the damage is severe enough, a form of programmed cell death called ferroptosis is triggered—an iron-dependent demise characterized by lipid peroxidation cascades that rupture the cell membrane. Ferroptosis has become one of the hottest topics in cancer biology precisely because it links iron metabolism, oxidative stress, and cell fate in a single mechanism.

Toyokuni’s team reasoned that if ferroptosis sweeps through iron-damaged tissue, the cells that escape it must be exceptional in some way, and those exceptions might be the seed of malignancy. To find out, they turned to a well-established animal model in which ferric nitrilotriacetate, a carcinogenic iron compound, is injected into rats, delivering a bolus of iron to the kidneys. The compound accumulates in the proximal tubules, where it catalyzes oxidative damage and, over months, produces renal cell carcinoma. In the experiments, the researchers collected kidney tissue before the injection and again one and three weeks afterward. Crucially, they also included a second experimental group: rats carrying a single mutated copy of the BRCA1 gene, the same gene that, when mutated in humans, dramatically raises the risk of breast and ovarian cancers and is associated with renal carcinoma in certain contexts.

The methodological heart of the study lies in its marriage of two technologies. The first is spatial transcriptomics, a technique that maps gene activity across individual cells within a tissue section while preserving the tissue’s original architecture—so researchers can see not only which genes are active but where in the tissue those transcriptional programs are operating. The second is computational nuclear morphometry, which quantifies the size, shape, and density of cell nuclei in the same samples. By overlaying the two datasets, the team could link the physical appearance of each cell—above all, the size of its nucleus—to its underlying transcriptional state. This integration is important because morphological atypia has long been the currency of diagnostic pathology, but connecting that atypia to molecular signatures at single-cell resolution is a recent capability.

What emerged within a week of iron administration was striking. Giant-nucleus cells appeared in the damaged kidneys, and these cells were not simply wounded cells awaiting death. They showed elevated expression of potent oncogenes, including Myc and Met, and they had acquired resistance to ferroptosis—the very cell death pathway that was eliminating their neighbors. In other words, the extreme oxidative environment had functioned as a brutal selective pressure, and the cells best adapted to survive it had activated a program that resembles, in miniature, the hallmark machinery of cancer. The enrichment of Myc, a transcription factor that drives cell growth and proliferation, and Met, a receptor tyrosine kinase involved in invasive growth, paints a picture of cells that are not merely enduring damage but reorganizing themselves around it.

The BRCA1 connection proved equally consequential. BRCA1 is best known as a guardian of the genome, a scaffold for the homologous recombination machinery that repairs double-strand DNA breaks. In the BRCA1-mutant rats, giant-nucleus cells emerged with distinctly different biological profiles from those in wild-type animals. The interpretation the researchers offer is that BRCA1 deficiency cripples DNA repair, so more of the damaged cells that would otherwise die or be repaired instead survive in their injured, genome-compromised state—becoming precancerous giant-nucleus cells. Electron microscopy and cellular respiration measurements reinforced this idea at the subcellular level: cells from BRCA1-mutant rats showed mitochondrial remodeling, with impaired iron handling and compromised respiratory function. Mitochondria, long appreciated as power plants, are also central regulators of ferroptosis and iron metabolism, and their disarray in the mutant animals may be both a consequence of BRCA1 loss and a driver of the abnormal iron biology that feeds karyomegaly.

Using their combined gene-expression and nuclear-shape data, the researchers went further and classified the giant-nucleus cells into six distinct types. One type possessed extremely large nuclei and gene signatures of stress-induced growth arrest—cells that appear to have locked themselves into a senescent-like state, consistent with profiles reported in earlier studies. Another type, found more frequently in BRCA1-mutant kidneys, showed heightened activity of cancer-related genes alongside elongated nuclei, a combination the authors interpret as a potential precancerous state. The taxonomy matters because it reframes giant-nucleus cells from a single enigmatic category into a spectrum, some members of which may be harmless or even protective while others carry genuine malignant potential.

One of the most provocative findings concerns the cells surrounding the giants. Even morphologically normal cells near giant-nucleus cells exhibited gene expression changes that appear to promote survival, suggesting that the karyomegalic cells remodel their local microenvironment in ways that extend beyond their own borders. In BRCA1-mutant kidneys, the team also documented a substantial increase in stromal cells—non-cancerous supportive cells including immune and connective tissue elements—around the damaged regions. The local tissue environment, the tumor niche in the language of modern oncology, was being reshaped long before any tumor could be called a tumor. This raises the possibility that a single conspicuous cell, easily identified by its nucleus under a conventional microscope, could serve as a sentinel for a whole neighborhood of incipient malignancy.

The leap from rat kidneys to human medicine came through two complementary analyses. First, the researchers mined TCGA-KIRC, a large public database of kidney cancer patients, asking whether tumors carrying gene-expression patterns resembling the cancer-prone giant-nucleus cells were associated with different clinical trajectories. They were: patients whose tumors shared the gene patterns of the cancer-prone giant-nucleus cells had shorter survival times, while those with patterns resembling the healthier giant-nucleus cell types had better outcomes. Not all giant-nucleus cells, in other words, are created equal, and the transcriptional fingerprints defined in the rat model appear to carry prognostic weight in human disease. Second, in a small pilot study, the team examined breast tissue from seven individuals with inherited BRCA1 mutations and fifteen without, observing abnormal nuclear features similar to those in the animal model in the mutation carriers. While the sample size is modest, the parallel hints that karyomegaly may be a cross-tissue marker of BRCA1-linked precancerous change.

The broader implications run in two directions. Clinically, the promise is that giant-nucleus cells, being easy to spot under the microscope, could function as early indicators of cancer—visible warnings in tissue that would otherwise be classified as merely damaged or inflamed. The TCGA survival data suggest that their gene-expression signatures might even stratify patients by risk once a tumor has formed. Scientifically, the study offers a concrete mechanism connecting an environmental exposome factor—iron-catalyzed oxidative stress—to a defined, transcriptionally characterized precancerous population, with ferroptosis resistance as the pivot. It also implies testable therapeutic hypotheses: if blocking mitochondrial remodeling or reversing ferroptosis resistance could prevent the persistence of the precancerous cells, early intervention might stop cancer before it starts. Toyokuni and his colleagues are careful to note that long-term studies will be needed to determine how giant-nucleus cells actually progress into tumor cells, whether such interventions can work, and whether nuclear shape combined with gene patterns can be validated as a diagnostic in larger patient cohorts. But the central message is already legible: some of the earliest chapters of cancer may be written in cells that have grown too large to be ignored.

A newly identified link between amino acid metabolism and cholesterol production may help prostate tumors adapt to hormone therapy. Prostate cancer can find ways around treatments designed to deprive tumors of the hormones they need to grow. Weill Cornell Medicine investigators have now traced one possible route of resistance to amino acid metabolism, where a [...]

Pre-surgery immunotherapy kept a group of bowel cancer patients cancer-free for nearly three years, while personalized blood tests helped predict treatment response. Patients with a specific form of bowel cancer who received a short course of immunotherapy before surgery, rather than chemotherapy afterward, have remained cancer-free for nearly three years, according to updated findings from [...]

In a finding that could reshape the search for new treatments against one of the deadliest gynecologic malignancies, researchers in Shanghai have identified the approved lung cancer drug tepotinib as a potent inhibitor of ovarian cancer growth, acting through an unexpected molecular target known as LY75. The study, published in the Journal of Ovarian Research, combines large-scale computational screening, structural biology, and preclinical testing to make a case for repurposing an existing medicine against a disease that urgently needs new options.

Ovarian cancer remains one of the most lethal cancers affecting women, largely because it is often diagnosed at an advanced stage and because resistance to platinum-based chemotherapy and PARP inhibitors eventually develops in most patients. High-grade serous ovarian cancer, the most common and aggressive subtype, has proven particularly stubborn, and survival rates have improved only marginally over recent decades. Against this backdrop, the idea of finding new uses for drugs that have already passed safety testing in humans, a strategy known as drug repurposing, has gained considerable traction. The new study demonstrates how modern computational tools can accelerate that process dramatically.

The research team, led by Yang Xiao, Wei Xia, and Yanan Song of Pudong Gongli Hospital and the Shanghai University of Medicine and Health Sciences, began by focusing on LY75, also known as CD205 or DEC205, a C-type lectin receptor best known for its role in antigen uptake by dendritic cells. Mining data from The Cancer Genome Atlas and the Human Protein Atlas, the investigators found that LY75 was significantly upregulated in ovarian cancer tissues compared with healthy tissue. More importantly, elevated LY75 expression correlated with shorter progression-free survival, marking the protein as both a potential biomarker of aggressive disease and an attractive therapeutic target.

With the target in hand, the team turned to structure-based virtual screening. Rather than testing thousands of compounds in the laboratory, they used the published crystal structure of the LY75 protein, deposited in the Protein Data Bank under the identifier 8K8H, as a template to computationally dock molecules from the TargetMol compound library. Docking predicts how well a small molecule fits into a binding pocket on a protein, but the researchers went considerably further. They applied MM/GBSA calculations, a method that estimates binding free energy by combining molecular mechanics forces with implicit solvent models, to rescore candidate poses. They also employed protein-ligand interaction fingerprints, or PLIF analysis, to compare the binding patterns of candidates against known interaction motifs, and ran ADMET predictions to filter out compounds likely to fail on absorption, metabolism, or toxicity grounds before any experiment was performed.

From this computational funnel, tepotinib emerged as the leading candidate. Tepotinib is an orally available small molecule approved in several countries for the treatment of non-small cell lung cancer harboring MET exon 14 skipping mutations, where it acts as a MET kinase inhibitor. Its appearance as a strong LY75 binder raised an obvious question: was any anti-cancer effect simply a consequence of MET inhibition? The team anticipated this concern and designed their study around it, measuring c-MET expression in their cell models, examining MET–LY75 co-expression patterns, and running parallel pharmacological controls with capmatinib, another selective MET inhibitor, to disentangle the two mechanisms.

The laboratory experiments delivered striking results. Tepotinib preferentially inhibited ovarian cancer cell lines with high LY75 expression, achieving half-maximal inhibitory concentrations, or IC₅₀ values, of 16.31 micromolar in SKOV3 cells and 18.91 micromolar in OVCAR-8 cells. In contrast, the drug showed markedly weaker activity against HO8910 cells, which express low levels of LY75, a dose-response pattern consistent with LY75 serving as the drug’s relevant target rather than an incidental one. To confirm a direct physical interaction, the researchers turned to surface plasmon resonance, a label-free optical technique that measures real-time binding between molecules immobilized on a sensor surface. The experiments confirmed that tepotinib binds LY75 directly, with a kinetic dissociation constant of 2.52 micromolar and a steady-state K_D of 3.74 micromolar, values indicating a specific and measurable interaction.

Perhaps the most intriguing mechanistic finding concerns what tepotinib does to the LY75 protein once bound. Treatment with the drug induced apoptosis in the sensitive cell lines, suppressed their migratory capacity, a process closely tied to metastatic spread, and downregulated LY75 protein levels. When the team probed how this downregulation occurred, they found that tepotinib accelerated LY75 degradation through a pathway that does not depend on the ubiquitin-proteasome system, the cell’s standard machinery for tagging unwanted proteins for destruction. Cycloheximide chase experiments, which block new protein synthesis and allow the decay rate of existing proteins to be measured, supported this conclusion. The identity of the alternative degradation route remains an open question, but the observation suggests tepotinib may engage lysosomal or autophagic pathways, a hypothesis that will require further work to confirm.

The in vivo evidence proved even more compelling. In mouse xenograft models implanted with SKOV3 ovarian cancer cells, oral administration of tepotinib markedly suppressed tumor growth, achieving a tumor inhibition rate of 79.6 percent. Analysis of the excised tumors showed reduced LY75 expression in the treated animals, consistent with the drug engaging its target in living tissue. All animal procedures were approved by the Institutional Animal Care and Use Committee of Shanghai Health Medical College and conducted in accordance with the ARRIVE guidelines for reporting animal research.

Crucially, the MET controls strengthened rather than weakened the case for LY75 as the operative target. Capmatinib, a structurally distinct MET inhibitor, failed to reproduce the full anti-tumor activity of tepotinib in the ovarian cancer models, and analyses of c-MET expression and MET–LY75 co-expression in patient datasets suggested that MET inhibition alone could not account for the magnitude of benefit observed. The authors therefore conclude that tepotinib’s effect in ovarian cancer reflects a genuine dual pharmacology, with LY75 binding and subsequent LY75 protein downregulation contributing substantially to its activity.

The implications of the study extend in several directions. First, it elevates LY75 from an immunological curiosity to a candidate therapeutic target in ovarian cancer, a protein whose abundance in tumors and association with poor prognosis make it a marker worth tracking clinically. LY75 has already attracted attention in oncology as a target for antibody-drug conjugates, given its presence on the surface of certain tumor cells and its efficient internalization, and the new findings add a small-molecule dimension to that conversation. Second, the work offers a template for computational drug repurposing: crystal-structure-guided docking, energy-based rescoring, interaction fingerprinting, and ADMET filtering followed by rigorous biochemical and in vivo validation. The approach identifies candidates in silico in a fraction of the time and cost of conventional screening campaigns.

Third, and most immediately, the results argue for clinical exploration of tepotinib in ovarian cancer, particularly in patients whose tumors express high levels of LY75. Because the drug is already approved and its safety profile in humans is documented, the path from laboratory finding to clinical trial is potentially shorter than for a de novo compound. The micromolar potencies observed in cell culture are modest by the standards of modern targeted therapy, and patients would likely require careful dosing studies, biomarker-based selection, and possibly drug combinations to translate the xenograft results into human benefit. Questions also remain about whether the ubiquitin-proteasome-independent degradation mechanism operates identically in human tumors and about the precise structural features of the tepotinib–LY75 interaction that could be optimized in next-generation analogs.

The study is not without limitations, as its authors acknowledge. The work relies on cell lines and xenografts rather than patient-derived models, and the correlation between LY75 expression and drug sensitivity, while suggestive, has been established across only a handful of cell lines. Prospective validation in patient-derived xenografts and organoids, ideally stratified by LY75 expression, would sharpen the biomarker hypothesis considerably. Nonetheless, the convergence of computational prediction, biochemical confirmation, mechanistic insight, and animal efficacy data makes this one of the more complete preclinical repurposing cases published for ovarian cancer in recent memory.

For a disease in which the therapeutic arsenal has expanded slowly and resistance is nearly universal, the prospect that a drug already sitting on pharmacy shelves could be redirected against a newly validated molecular target is the kind of story that resonates far beyond the laboratory. If follow-up studies and early-phase trials bear out these findings, tepotinib’s second act may prove more consequential than its first, and LY75 may take its place among the actionable targets of precision oncology.

For many people referred to hospital because of blood in their urine, the next steps can be worrying. Blood in urine can be caused by infections, kidney stones and several other conditions, but it can also be an early warning sign of bladder cancer. Doctors therefore need a reliable way to find the smaller number […]

The post Urine Test Could Detect Bladder Cancer Faster appeared first on Knowridge Science Report.

An unusual immune signature in lung cancer has led researchers toward a potential therapy involving tumor microbes and MAIT cells. Bacteria living inside lung tumors may be doing more than simply occupying the tumor environment. In preclinical research from the Johns Hopkins Kimmel Cancer Center and its Bloomberg~Kimmel Institute for Cancer Immunotherapy, researchers found that [...]

Most men are unaware that a widely consumed part of the American diet has been linked to prostate cancer risk. A new national survey found that only 20% of men knew about the reported association between dairy consumption and prostate cancer. After learning about it, 66% said they would be likely to avoid dairy products. [...]

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.

The number of victims receiving aid has tripled in recent years, a Post analysis finds, as the illness’s toll becomes more apparent.

Australian researchers have identified a promising new approach that could help stop one of the most aggressive forms of breast cancer from spreading. Triple-negative breast cancer becomes especially dangerous once tumor cells escape the breast and establish themselves elsewhere in the body. Australian researchers have now identified a molecular weakness that could eventually help determine [...]

Les aliments ultra-transformés occupent une place croissante dans notre alimentation et leur impact sur la santé interroge. Leur consommation pourrait-elle être associée à un risque accru de cancer chez les hommes ? Des chercheurs ont tenté d’y répondre en analysant les habitudes alimentaires de...

A newly discovered bacterial pathway turns a common steroid precursor into testosterone.

The preliminary research was conducted in mice, but scientists were optimistic the results would apply to humans. Clinical trials begin this month.

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.

Dolly Parton, the beloved country music icon, passed away on August 25, 2026, at 80, after battling cancer, perhaps linked to the mRNA COVID-19 vaccine she openly promoted. Dr. Joe Sansone argues that the bioweapon shots are biological and technological weapons of mass destruction.

A long-running study suggests that chemicals formed during drinking water disinfection may play a role in uterine cancer risk. Scientists tracked more than 53,000 California teachers and school administrators for nearly two decades and found that women exposed to higher levels of certain water treatment byproducts were more likely to develop uterine cancer. The findings […]

The post Can Tap Water Increase Uterine Cancer Risk? appeared first on Knowridge Science Report.

As Trump’s agencies shrink, narrow their role, and reduce enforcement, politically connected Energy Transfer is steering a slow cleanup of fuel it spilled into drinking water near the Delaware River.

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.