Inside every stressed cell, a quiet emergency response unfolds. When oxygen runs low, toxins accumulate, or nutrients grow scarce, mammalian cells assemble temporary structures known as stress granules, non-membranous aggregates of proteins and RNA that condense in the cytoplasm. In healthy tissue, these assemblies act as a protective pause button, halting protein production so the cell can weather the storm and resume normal function once conditions improve. But a new study suggests that in oral squamous cell carcinoma, one of the most common and disfiguring malignancies of the head and neck, this ancient survival machinery may be hijacked to serve a darker purpose: helping tumors grow and spread.

The research, conducted by a team at Kangwon National University in South Korea and published in Cell Death Discovery, examined how stress granule formation influences tumor progression and metastasis in oral squamous cell carcinoma, or OSCC. The findings point to a specific molecular switch, the phosphorylation of a protein called eIF2α, as a central driver of the process. When that switch is suppressed, the study reports, stress granule formation drops, and with it the growth and metastatic burden of tumors in mouse models. The work adds oral cancer to a growing list of malignancies in which the integrated stress response appears to fuel, rather than restrain, disease.

To understand why this matters, it helps to consider what stress granules actually do. Under stress, cells activate kinases that phosphorylate eIF2α, the alpha subunit of a translation initiation factor. Phosphorylated eIF2α dampens global protein synthesis, and the messenger RNAs that would otherwise be translated are instead sequestered, along with RNA-binding proteins, into dense cytoplasmic droplets. Key markers of these structures include G3BP1, TIAR, and PABP, proteins that researchers use to identify stress granules under the microscope. In normal cells, this translational arrest conserves energy and prevents the accumulation of damaged or misfolded proteins. The system is meant to be reversible: when the stress passes, the granules dissolve and translation restarts.

Cancer cells, however, live in a state of chronic stress. Tumors outgrow their blood supply, creating regions of hypoxia, low oxygen tension that would kill most normal cells. They also face nutrient deprivation, acidic microenvironments, and assault from chemotherapy and radiation. In this context, the stress response can become a liability for the patient rather than a safeguard for the cell. Previous work in other cancers has implicated stress granules in tumor progression and metastasis, partly through their interactions with key signaling pathways, but their role in oral squamous cell carcinoma had remained poorly understood, despite growing scientific interest in the topic.

The Korean team began by comparing human tumor tissue with adjacent normal tissue. They found that markers of stress granules, including G3BP1, eIF2α, TIAR, and PABP, were significantly overexpressed in OSCC tissues compared with their normal counterparts. This observation established that the stress granule machinery is not merely present in oral cancer but is amplified, suggesting that tumor cells may rely on it more heavily than the healthy cells around them. Overexpression of these markers alone does not prove causation, but it set the stage for the functional experiments that followed.

Those experiments turned to mouse models built from OSCC cells that had been preconditioned with hypoxia, deliberately exposing the cells to low oxygen before implantation. The logic was to mimic the stressful conditions tumor cells encounter in a real growing tumor and to ask whether cells that had already mounted a stress response behaved differently afterward. In parallel, the researchers used a compound called ISRIB, an inhibitor of the integrated stress response that acts downstream of eIF2α phosphorylation, in mice subjected to sodium arsenite-induced stress. Sodium arsenite is a classic laboratory trigger of oxidative stress and a reliable inducer of stress granule formation, making it a useful tool for probing the pathway.

The results were striking. In both experimental settings, suppression of eIF2α phosphorylation was associated with reduced stress granule formation, reduced tumor growth, and a reduced metastatic burden. In other words, when the researchers blocked the molecular event that nucleates stress granules, the tumors not only grew more slowly but also spread less aggressively. Conversely, the study found that stress granule formation was elevated during hypoxia-induced stress, underscoring a stress-responsive regulatory mechanism in which the harsh conditions of the tumor microenvironment actively promote the assembly of these granules. Together, the data sketch a coherent chain of causation: hypoxia and other stresses trigger eIF2α phosphorylation, phosphorylation drives stress granule assembly, and the granules support the cellular programs that allow OSCC cells to proliferate and colonize distant sites.

Why would a structure designed to protect cells become an engine of metastasis? The authors and other researchers in the field point to the selective nature of stress granules. While global translation is arrested, certain messenger RNAs are preferentially stored within the granules and protected from degradation. Among the transcripts sheltered this way are often those encoding proteins that promote survival, invasion, and epithelial-to-mesenchymal transition, the process by which stationary epithelial cancer cells acquire the motility needed to invade surrounding tissue and enter the bloodstream. By acting as temporary warehouses for pro-metastatic messages, stress granules may allow tumor cells to stockpile the tools of aggression, releasing them for translation once the acute stress subsides. In this view, the granule is not merely a damage-control structure but a staging ground for the next phase of tumor progression.

The therapeutic implications are considerable. Oral squamous cell carcinoma is frequently diagnosed at advanced stages, and metastasis to cervical lymph nodes is one of the strongest predictors of poor outcome. Existing treatments, surgery, radiation, and chemotherapy, remain limited in their ability to control disseminated disease. If stress granule formation genuinely drives metastatic behavior, then the pathway offers a new target. ISRIB, the compound used in the mouse experiments, has attracted attention in recent years for its ability to blunt the integrated stress response, and the new findings suggest that agents with a similar mechanism could be explored as anti-metastatic therapies in oral cancer. The authors conclude that stress granules promote OSCC progression via eIF2α phosphorylation and might serve as a novel therapeutic target, a formulation that is deliberately cautious but clinically suggestive.

As with any preclinical study, important caveats apply. The evidence comes from human tissue comparisons and mouse models, and translating these findings into patients will require further work to confirm that the same mechanism operates in human tumors in real time, to identify which patient subsets have the highest stress granule activity, and to develop inhibitors with acceptable safety profiles. Suppressing a fundamental cellular stress pathway carries risks, since normal tissues also rely on the integrated stress response during injury and inflammation. Still, the study fills a genuine gap in the literature by connecting a well-characterized cellular stress mechanism to one of the most clinically feared behaviors of oral cancer. It also adds to a broader shift in cancer biology: the recognition that tumors are not just collections of mutated genes but ecosystems shaped by physical and chemical stress, and that the survival programs cells use to endure hardship can be turned against the organism that hosts them. For patients with oral squamous cell carcinoma, whose disease too often spreads before it can be stopped, the humble stress granule may prove to be an unexpected and consequential adversary.

Subject of Research: The role of stress-induced eIF2α phosphorylation and stress granule formation in promoting metastasis of oral squamous cell carcinoma

Article Title: Stress-induced eIF2α phosphorylation promotes tumor metastasis in oral squamous cell carcinoma

Article References: Kim, S., Park, S., Lee, Y., Park, G., & Choi, J. (2026). Stress-induced eIF2α phosphorylation promotes tumor metastasis in oral squamous cell carcinoma. Cell Death Discovery. https://doi.org/10.1038/s41420-026-03412-4

Image Credits: AI Generated

DOI: 10.1038/s41420-026-03412-4

Keywords: stress granules, eIF2α phosphorylation, oral squamous cell carcinoma, metastasis, integrated stress response, ISRIB, hypoxia, G3BP1, tumor progression, translational arrest, cancer biology, therapeutic target

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.

Idiopathic pulmonary fibrosis, a relentlessly progressive and fatal scarring disease of the lungs, has long frustrated clinicians with only two approved drugs that slow but cannot reverse its course. Now, a team of researchers in Taiwan has identified a surprising new player in the disease’s destructive machinery: doublecortin-like kinase 1, or DCLK1, a kinase better known for its role in cancer stem cells. Their study, published in the Journal of Biomedical Science, demonstrates that DCLK1 drives fibroblast activation in the lung and that blocking it—either genetically or with an oral inhibitor—slows fibrosis and preserves lung function in mice. The findings position DCLK1 as a promising therapeutic target in one of medicine’s most stubborn diseases.

The research, led by Lee-Yuan Lin, Wun-Hao Cheng, Chien-Huang Lin and Bing-Chang Chen of Taipei Medical University, together with collaborators at National Taiwan University Hospital and Universitas Gadjah Mada, began with a question that has lingered in the literature. Gene expression analyses had previously hinted that DCLK1 might be implicated in IPF, and earlier work reported that the kinase is markedly enhanced in the alveolar epithelial cells of patients with pulmonary fibrosis and in mice with bleomycin-induced fibrosis. But its function in fibroblast activation—the cellular engine of fibrosis—had remained unexplained.

To begin untangling that role, the team mined a publicly available single-cell RNA sequencing data set containing more than 312,000 cells from healthy lungs, IPF lungs, and lungs with chronic obstructive pulmonary disease. After stringent quality control filtering, they focused on roughly 240,000 cells from the control and IPF groups and mapped DCLK1 expression across the major lung cell lineages: epithelial, endothelial, lymphoid, myeloid, and stromal cells. The signal was unmistakable. DCLK1 was expressed across many cell populations, but the highest expression appeared in the stromal compartment, particularly in myofibroblasts—the specialized, contractile fibroblasts that churn out the extracellular matrix and stiffen lung tissue in IPF.

Human tissue told the same story. The researchers examined lung samples from eleven patients with IPF, obtained during lung transplantation or surgery, alongside fourteen nonfibrotic control samples. Histological staining with hematoxylin and eosin and Masson trichrome confirmed the expected picture of interstitial consolidation and collagen deposition in the IPF specimens. More importantly, immunohistochemistry revealed that both total DCLK1 and its phosphorylated, activated form were significantly upregulated in the fibrotic lung interstitium compared with control tissue. DCLK1, in other words, was not merely present in scarred lungs—it was switched on.

DCLK1 is an intriguing molecule to find at the center of a fibrotic process. It is a serine/threonine kinase belonging to the calcium/calmodulin-dependent kinase family, distinguished by two microtubule-binding domains. In oncology, DCLK1 overexpression has been documented in colorectal, pancreatic, gastric, renal, and hepatocellular carcinomas, where it correlates with poor prognosis, high recurrence, and metastasis, promoting tumor initiation and the epithelial–mesenchymal transition in cancer stem cells. It has also been linked to inflammatory signaling in SARS-CoV-2 infection, where inhibiting it blocks proinflammatory caspase-1/interleukin-1β signaling. The new study extends this portfolio of mischief to the fibrotic lung.

To test causality rather than mere correlation, the researchers turned to mice. They crossed animals carrying loxP sites flanking exon 3 of the DCLK1 locus with Pgk1-RFP-Cre/ERT2 transgenic mice, generating a system in which tamoxifen administration triggers global deletion of the Dclk1 gene. When these DCLK1 knockout mice and littermate controls were given intratracheal bleomycin, a chemotherapy drug used to induce pulmonary fibrosis in laboratory animals, the difference was striking. Knockout mice showed far less lung infiltration and collagen deposition, reduced numbers of cells staining positive for DCLK1 together with fibroblast surface protein and alpha-smooth muscle actin, and significantly lower levels of the profibrotic proteins fibronectin, α-SMA, and connective tissue growth factor, or CTGF.

The protective effect extended well beyond molecular markers. Using the FlexiVent FX system to measure lung mechanics, the team found that bleomycin treatment significantly reduced respiratory system compliance and pressure–volume performance and increased the normalized work of breathing in control mice—hallmarks of a stiffening, fibrotic lung. In the DCLK1 knockout animals, these functional deficits were substantially attenuated. In vivo microcomputed tomography, acquired at 34.75-micrometer voxel resolution, painted the morphological counterpart: bleomycin caused parenchymal destruction and volume loss in control lungs, while knockout mice retained lung structure and volume. Density histograms shifted toward fibrotic tissue in wild-type animals but stayed largely preserved in the knockouts, and peripheral blood neutrophil percentages, which climbed after bleomycin injury, were significantly reduced in the knockout group.

With the in vivo evidence established, the investigators dissected the molecular wiring in cultured normal human lung fibroblasts. Transforming growth factor beta, the master profibrotic cytokine, induced DCLK1 phosphorylation within 30 minutes and DCLK1 expression within 8 hours. Chromatin immunoprecipitation assays showed that after TGF-β stimulation, both Smad3—the canonical transcriptional mediator of TGF-β signaling—and the nuclear factor kappa B subunit p65 enriched at the DCLK1 promoter, indicating that TGF-β switches on DCLK1 through both Smad-dependent and noncanonical NF-κB pathways. Silencing DCLK1 with small interfering RNA then blunted the fibroblast’s profibrotic response, reducing TGF-β-induced expression of fibronectin, collagen 1A1, α-SMA, and CTGF.

The pathway, however, does not stop there. The team found that TGF-β also phosphorylated Akt, and that transfecting fibroblasts with a dominant-negative Akt construct reduced TGF-β-induced DCLK1 phosphorylation and the expression of fibronectin and CTGF—placing Akt upstream of DCLK1. Downstream, DCLK1 knockdown reduced Smad3 phosphorylation while DCLK1 overexpression enhanced it. Coimmunoprecipitation revealed a physical association between DCLK1 and Smad3, and immunofluorescence microscopy showed the two proteins colocalizing in the nucleus within 30 minutes of TGF-β treatment. A ChIP assay using a DCLK1 antibody pulled down DNA from the Smad3-binding region of the CTGF promoter, and pretreatment with the selective DCLK1 inhibitor DCLK1-IN-1 reduced TGF-β-induced CTGF expression. Together, the results sketch an Akt/DCLK1/Smad3 axis through which TGF-β drives the production of connective tissue growth factor, a potent profibrotic mediator.

The clinical payoff came in the pharmacological arm of the study. Mice receiving oral DCLK1-IN-1 at 10 milligrams per kilogram daily, beginning on day 7 after bleomycin instillation and continuing until day 28, showed visibly reduced fibrotic progression on histology, lower expression of fibronectin, α-SMA, and CTGF in lung tissue and lysates, preserved pulmonary compliance, improved pressure–volume loops, and reduced work of breathing. Serial microCT scans on days 7, 17, and 27 documented less severe fibrotic remodeling in the treated animals, with lung attenuation histograms showing a smaller fraction of dense, nonaerated voxels. Blood neutrophil counts were also lower. In short, a pill-like oral inhibitor measurably slowed the disease in a model that mirrors the human condition.

The implications are significant because the current therapeutic landscape for IPF is so thin. Only nintedanib, a tyrosine kinase inhibitor targeting growth factor receptors, and pirfenidone, which suppresses TGF-β production and activity, are approved by the US Food and Drug Administration, and both merely slow progression. The recent failure of pamrevlumab, a monoclonal antibody against CTGF, in the phase 3 ZEPHYRUS-1 trial suggested that targeting downstream fibrotic end products alone may be insufficient—pointing to the value of upstream signaling regulators such as DCLK1. Adding to the appeal, a DCLK1 inhibitor has already been shown to prevent inflammatory responses in acute lung injury, hinting at dual anti-fibrotic and anti-inflammatory potential.

The authors are careful to note limitations. DCLK1 is expressed across multiple lung cell types, and the tamoxifen-inducible knockout used here was global rather than cell-type-specific, so the contributions of fibroblasts versus epithelial, endothelial, and immune cells could not be fully separated. Human control tissue, as in most fibrosis studies, came from heterogeneous sources, including tumor-adjacent lung. The precise subcellular mechanics of the DCLK1–Smad3 interaction, whether DCLK1 inhibition can promote fibrosis resolution rather than merely slow progression, and the systemic safety of long-term DCLK1 blockade—all relevant given the kinase’s role in cancer and other processes—remain open questions.

Even so, the convergence of evidence is striking: DCLK1 is upregulated in human IPF, amplified in experimental fibrosis, mechanistically coupled to the TGF-β–Smad3 engine of fibroblast activation, and its suppression by both genetics and a small molecule preserves lung structure and function. What began as a cancer stem cell marker has now emerged, unexpectedly, as a central node in the scarring of the lung—offering fresh hope that a disease long considered irreversible may one day be stopped at its molecular source.

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.

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.