The molecule at the center of the study is CXCL9, a chemokine that acts as a beacon for effector CD8-positive T cells. Higher CXCL9 expression has been linked to better responses to immunotherapy across multiple cancer types, making it an attractive lever for converting cold tumors into inflamed ones. The problem is that the signaling circuitry governing CXCL9 production inside tumor cells is poorly understood. The two best-known inducers, the inflammatory cytokines interferon-gamma and TNF-alpha, activate the JAK-STAT and NF-kappaB pathways respectively, but these pathways crosstalk extensively with PI3K-AKT, MAPK and p53 signaling, all of which are frequently rewired in cancer. Untangling which of these interactions actually matter in a given tumor cell is a combinatorial nightmare.

The Eindhoven team’s solution was to build interpretable mechanistic models of the signaling network and then let an active learning algorithm decide which experiments to run next. They started by curating a prior knowledge network specific to CXCL9 regulation, drawing on literature and the DoRothEA database of transcription factors. The network spans five major pathways: JAK-STAT, NF-kappaB, PI3K-AKT, MAPK and p53, connected to upstream cytokines including IFN-gamma, TNF-alpha, IFN-alpha and EGF. This scaffold was converted into a set of logic-based ordinary differential equations, a formalism that turns qualitative wiring diagrams into continuous dynamical systems without requiring the detailed kinetic parameters that are usually unknown in cancer signaling. Each edge in the network carries an adjustable strength parameter, which makes the fitted models biologically interpretable rather than black boxes.

To train these models, the researchers worked with two pancreatic cancer cell lines, AsPC1 and BxPC3, chosen because reanalysis of the Genomics of Drug Sensitivity in Cancer database showed they respond very differently to drugs. They exposed the cells to the two cytokines alone and in combination, alongside five clinically relevant inhibitors targeting JAK, IKK, PI3K, MEK and RAS, and measured secreted CXCL9 protein using a bead-based immunoassay with flow cytometry readout. The results confirmed the central role of JAK-STAT signaling: the JAK inhibitor momelotinib strongly suppressed CXCL9 in both lines, while IFN-gamma drove robust induction. More intriguingly, the PI3K inhibitor taselisib and the MEK inhibitor trametinib boosted CXCL9 expression, especially when combined with dual cytokine stimulation, pointing to previously underappreciated regulatory routes.

The fitted models, ensembles of ten optimizations per cell line, reproduced the experimental data with striking accuracy, achieving Pearson correlations of 0.998 for AsPC1 and 0.995 for BxPC3. In silico knockout experiments, in which individual regulatory edges were systematically removed from the models, then revealed context-specific control points. Deleting the ERK-AR interaction reduced CXCL9 in BxPC3 but not AsPC1, while JAK-STAT1 and STAT1-CXCL9 knockouts affected only AsPC1. The NF-kappaB pathway emerged as the key mediator of synergy between IFN-gamma and TNF-alpha in both cell lines, whereas JAK-STAT interactions contributed to synergy specifically in BxPC3. Bootstrapped parameter comparisons quantified these differences, showing that eight pathway parameters were significantly stronger in BxPC3 while two, including IFNGR-JAK, were stronger in AsPC1, providing a mechanistic explanation for the cell lines’ divergent drug responses.

The truly novel element, however, was the active learning pipeline coupled directly to these mechanistic models. Active learning is well established in drug discovery, where it helps algorithms pick the most informative compounds to test next, but it had never before been integrated with mechanistic biological models of this kind. The workflow is elegantly cyclical: the model ensemble predicts CXCL9 responses for all untested perturbation conditions, an acquisition function selects a small batch of the most valuable candidates, those are measured in the wet lab, and the models are retrained on the expanded dataset. The researchers benchmarked four acquisition strategies on synthetic data: greedy sampling, which chases conditions predicted to produce the highest CXCL9; uncertainty sampling, which targets conditions where the model ensemble disagrees most; a hybrid of the two; and random selection as a baseline.

The benchmarking produced a clear and practically useful picture. Greedy and the hybrid strategy discovered 1.4 to 1.9 times more CXCL9-inducing conditions than random sampling after five rounds, but they also generated more false positives when too many conditions were added per round. Uncertainty sampling was less aggressive at finding hits but delivered the best model generalization, reaching a mean R-squared of 0.93 across all conditions, including unseen ones, significantly outperforming every other strategy. The choice of initial training set also mattered: a carefully hand-picked set of ten conditions yielded seventeen final hits on average compared with nine for the worst random set, though the pipeline proved capable of recovering from suboptimal starts. These findings offer concrete design guidance for anyone attempting similar iterative experiments under real resource constraints.

Crucially, the team then took the pipeline back into the laboratory, running two rounds of active learning with real measurements in both cell lines. The qualitative differences between strategies seen in silico reproduced experimentally. Greedy and hybrid selections produced the strongest CXCL9 induction, while uncertainty-guided choices explored a broader response range and most consistently shrank the model’s prediction uncertainty. One complication surfaced: some greedy-selected drug combinations, such as PI3K plus ERK inhibition, yielded lower CXCL9 than expected because the high cumulative drug concentration triggered apoptosis. A Caspase-3 assay confirmed strong negative correlations between cell death and chemokine secretion, and after correcting for apoptosis, the expected hierarchy of acquisition strategies re-emerged. This observation may also help explain conflicting reports in the literature linking CXCL9 to both favorable and unfavorable prognosis in pancreatic cancer, since cytotoxicity can mask genuine immunostimulatory effects.

The study’s broader significance lies in demonstrating that mechanistic modeling and active learning, usually pursued on separate tracks, can be fused into a data-efficient engine for biological discovery. The interpretable logic-ODE framework kept the experimental design grounded in prior biological knowledge, while the learning loop squeezed maximum information from minimal measurements. Among the most tantalizing findings were the frequent selections of AKT and p53 inhibitors by the hybrid strategy, both validated as CXCL9 inducers despite sitting outside the canonical JAK-STAT and NF-kappaB regulatory axes, suggesting that less-characterized signaling mechanisms may hold untapped potential for immunomodulation. The authors caution that predictions remain constrained by the structure of the prior knowledge network, and that future work could expand it with transcriptomic data, add multiplexed readouts such as PD-L1 or TGF-beta, and employ Bayesian parameter inference for better-calibrated uncertainty. But the proof of principle stands: rational, mechanism-driven design of combination therapies aimed at warming up cold tumors is no longer a distant aspiration, but an iterative workflow that a small lab can start running today.

Subject of Research: Active learning-guided mechanistic modeling of CXCL9 chemokine regulation in pancreatic cancer cells

Article Title: Active learning-guided mechanistic modeling reveals context-specific regulators of CXCL9 expression in pancreatic cancer cells

Article References: Wang, B.-R., Yelleswarapu, M., Descamps, L., & Eduati, F. (2026). Active learning-guided mechanistic modeling reveals context-specific regulators of CXCL9 expression in pancreatic cancer cells. Molecular Systems Biology, 22(8), 1360-1375. https://doi.org/10.1038/s44320-026-00221-w

Image Credits: AI Generated

DOI: 10.1038/s44320-026-00221-w

Keywords: pancreatic cancer, CXCL9, active learning, mechanistic modeling, logic-ODE, immunotherapy, JAK-STAT, NF-kappaB, chemokines, cold tumors, drug combinations, systems biology

The research team, led by investigators at Nationwide Children’s Hospital and Cincinnati Children’s Hospital Medical Center, began with a resource that few groups possess: autopsy-derived tumor specimens from twenty-six DIPG patients, each paired with matched normal frontal lobe tissue obtained through the Pediatric Brain Tumor Repository under institutional review board-approved protocols with informed consent from families. Bulk RNA sequencing of these paired samples revealed a transcriptome in upheaval. More than two thousand genes were significantly upregulated in tumor tissue, and among them were signatures of immune modulatory factors, including checkpoint genes such as PDCD1 and LAG3 and myeloid-associated genes including CSF1, CD163, CD86, and CCL2. Gene Ontology analysis showed that five of the top enriched pathways involved MHC-mediated antigen presentation, indicating that despite their reputation as immunologically cold tumors, DIPG tissues retain active immunological interfaces.

The apparent paradox, in which antigen presentation machinery is broadly induced while cytotoxic T cells remain scarce, likely reflects a dysfunctional immune interface rather than a functional anti-tumor response. Indeed, when the researchers correlated the expression of macrophage lineage markers such as CD11b, CD14, and STAT6 with patient survival, higher expression of each was significantly associated with shorter survival duration. This finding reinforced a growing consensus that tumor-associated myeloid cells, rather than functioning as anti-tumor sentinels, actively promote disease progression in DIPG. Consistent with earlier work showing sparse lymphocyte infiltration in these tumors, the data painted a portrait of a microenvironment dominated by microglia and monocyte-derived macrophages that have been recruited and shaped by the tumor itself.

To probe how that recruitment happens, the team turned to laboratory experiments with four patient-derived DIPG cell lines and THP-1 human monocytes in transwell migration assays. The results were striking in their asymmetry. SU-DIPG-IV and SU-DIPG-XXXVI, both carrying the H3.1K27M mutation, markedly enhanced monocyte migration and drove the cells toward an immunosuppressive CD11b-positive CD163-positive phenotype, while CCHMC-DIPG-1 and CCHMC-DIPG-2 showed no such capacity. Multiplex cytokine assays revealed that the two potent lines secreted far higher levels of CCL2, IL-10, and TGF-beta1. Yet when the investigators analyzed RNA sequencing data from forty-six pediatric high-grade glioma cell lines in the Childhood Cancer Model Atlas, they found that chemokine expression did not track with histone mutation status at all.

Instead, the decisive variable was the tumor cell’s lineage state. Pediatric glioma cells oscillate among four transcriptional identities, resembling neural progenitor cells, astrocytes, oligodendrocyte precursors, or mesenchymal cells. Using single-sample gene set enrichment analysis, the researchers computed chemokine scores and lineage scores for every cell line and found a strong positive correlation between chemokine expression and the mesenchymal-like program, with a Pearson coefficient of 0.73 and a p-value of 6.5 times ten to the minus nine. Chemokine scores correlated negatively with both the neural progenitor-like and oligodendrocyte precursor-like scores and showed no significant relationship with the astrocyte-like state. Mesenchymal-like cell lines expressed significantly higher levels of CCL2, CCL5, and CCL7 than their counterparts. This suggests that the mesenchymal program, potentially driven by NF-kappaB and STAT3 signaling, is the engine of myeloid recruitment, and it hints at a self-reinforcing loop in which mesenchymal tumor cells summon macrophages that in turn stabilize the mesenchymal phenotype.

Single-cell RNA sequencing of eight DIPG patients, integrated with public datasets spanning H3K27M-mutant, G34R/V-mutant, and wildtype pediatric high-grade gliomas, then allowed the team to reconstruct cellular communication networks across more than twenty-two thousand cells. CellChat analysis revealed that tumor-associated macrophages were present in every histone subtype examined and were the sole recipients of several incoming signals, including TGF-beta, semaphorin-3, and, most intriguingly, the amyloid precursor protein signaling pathway transmitted through the CD74 receptor. Immunofluorescence staining of tumor sections confirmed that APP and CD74-expressing cells occupy spatial proximity within the tumor, consistent with a real ligand-receptor interaction occurring in the microenvironment. APP was broadly expressed across most cell populations, whereas CD74 was restricted to tumor-associated macrophages, defining a one-way channel of communication from tumor to immune cell.

The most consequential observation, however, was what was missing. APP expression was significantly reduced in DIPG tumor tissue compared with matched normal brain at both the RNA and protein levels, a result confirmed by western blotting and mirrored by decreased expression of the related family members APLP1 and APLP2. To understand what this loss means for macrophage behavior, the researchers treated THP-1-derived macrophages with recombinant human APP protein. The stimulation triggered a robust proinflammatory transformation: interferon-stimulated genes such as IFIT1 and IFIT2 were induced, inflammatory cytokines including IL1B, CCL2, and CXCL10 rose, and immunosuppressive markers such as CD163, CD206, and ARG2 were suppressed. Gene set enrichment analysis confirmed strong activation of interferon alpha, interferon gamma, and TNF alpha signaling via NF-kappaB, and multiplex cytokine assays showed time-dependent increases in secreted IFN-gamma, TNF-alpha, IL-1beta, and IL-6.

These functional data support a compelling hypothesis: when APP levels fall in the tumor, macrophages lose a signal that would otherwise push them toward an inflammatory, potentially anti-tumor state, and instead settle into the non-inflammatory, immunosuppressive phenotype that characterizes DIPG. The authors caution that the causal relationship remains to be established, and they note an apparent discrepancy with a recent glioblastoma study in which APP appeared to suppress macrophage phagocytosis via CD74, suggesting that context and the specific cellular readout matter. To lay groundwork for therapeutic intervention, the team went further, building three-dimensional structural models of membrane-bound APP and the CD74 trimer using I-TASSER-MTD, refining them in GROMACS, and performing protein-protein docking with HADDOCK. Membrane-restrained Gaussian network modeling then identified a mechanically rigid binding interface in which APP residues 19 through 24 engage a hydrophobic pocket in CD74 centered on residues 118 through 122.

That structurally defined interface offers an actionable target. Peptides engineered to engage the CD74 hydrophobic pocket could, in principle, mimic APP signaling and reprogram tumor-associated macrophages toward proinflammatory phenotypes with anti-tumor capacity, complementing emerging CAR-T cell therapies directed against GD2, B7-H3, and IL13-Ralpha2. The authors acknowledge important limitations: the sequencing work relied on post-mortem tissue from patients who had received varied treatments, the THP-1 model does not fully recapitulate the complexity of primary human macrophages, and the computational docking will require validation through site-directed mutagenesis and co-immunoprecipitation. Still, the study represents a substantial advance in understanding how lineage identity governs immune recruitment in pediatric high-grade glioma and how a protein famous in neurodegeneration may hold the key to thawing one of childhood cancer’s coldest tumors. Future studies using biopsy specimens, primary human systems, and syngeneic preclinical models will determine whether restoring APP-CD74 signaling can genuinely convert the immunosuppressive microenvironment of DIPG into one that fights back.

Subject of Research: Tumor-associated macrophage recruitment and the APP-CD74 signaling axis in pediatric high-grade glioma

Article Title: Integrated multi-omics identifies lineage-dependent myeloid cells recruitment and the APP-CD74 axis as an immunoregulatory target in pediatric high-grade glioma

Article References: Wang, Z., Kumar, A., Umaru, B., Iyer, A. M., Khan, K., Pang, H.-H., Fouladi, M., & Drissi, R. (2026). Integrated multi-omics identifies lineage-dependent myeloid cells recruitment and the APP-CD74 axis as an immunoregulatory target in pediatric high-grade glioma. Acta Neuropathologica, 152(1), Article 39. https://doi.org/10.1007/s00401-026-03089-0

Image Credits: AI Generated

DOI: 10.1007/s00401-026-03089-0

Keywords: diffuse intrinsic pontine glioma, pediatric high-grade glioma, tumor-associated macrophages, APP-CD74 axis, amyloid precursor protein, CD74, tumor microenvironment, single-cell RNA sequencing, mesenchymal-like lineage state, chemokines, immunotherapy, multi-omics

The study, published in the Journal of Cancer Research and Clinical Oncology, set out to answer a deceptively simple question. If natural killer cells are to be used as a living drug against oesophagogastric adenocarcinoma, a cancer whose incidence is rising steeply in parallel with obesity, will they still work once they arrive in the patient’s body? The tumour microenvironment is a chemically hostile neighbourhood, saturated with immunosuppressive metabolites, cytokines and lipids, and in patients with obesity the omentum, a fatty apron of visceral adipose tissue draped over the abdominal organs, adds its own inflammatory and lipid-rich milieu. Any adoptive cell therapy must not only survive these conditions but also navigate them, migrating to the tumour rather than being lured elsewhere.

To model this terrain in the laboratory, the researchers collected tissue from patients undergoing surgery for oesophagogastric adenocarcinoma and prepared conditioned media, nutrient-rich fluids in which pieces of tumour or omental adipose tissue had been cultured. These adipose-conditioned media and tumour-conditioned media recapitulate the soluble cocktail of signalling molecules, chemokines, fatty acids and metabolites that a therapeutic cell would encounter in vivo. The team then bathed KHYG-1 cells in these fluids and measured what happened to their phenotype and function using flow cytometry, a technique that reads the fluorescent signatures of proteins on and inside individual cells.

The central finding was one of resilience. Neither the adipose-conditioned media nor the tumour-conditioned media derived from patients with obesity significantly suppressed the effector function of KHYG-1 cells. In other words, the cells’ capacity to kill was not meaningfully blunted by the soluble factors secreted by either the fat or the tumour. This stands in contrast to the well-documented dysfunction seen in natural killer cells taken from the blood and tissues of patients with obesity and cancer, and it suggests that KHYG-1 cells, an immortalised human natural killer cell line widely used as a research model and a candidate for cellular therapy, carry an intrinsic resistance to the immunosuppressive pressures of this disease setting.

Intriguingly, the study also found that exposure to the conditioned media altered the expression of phenotypic and functional markers on the KHYG-1 cells, and that adipose-conditioned media actually increased their killing capacity. Rather than being worn down by the fatty environment, the cells appeared in some respects to be primed by it. The researchers compared KHYG-1 cells with natural killer cells derived from the peripheral blood of healthy donors, providing a benchmark against which the cell line’s robustness could be judged. The comparison matters because blood-derived natural killer cells are the more conventional starting material for adoptive cell therapy, and their known susceptibility to obesity-associated dysfunction is precisely the problem a cell line such as KHYG-1 might sidestep.

Function, however, is only half the battle. A therapeutic cell that cannot find the tumour is a weapon without a target. The team therefore tested whether KHYG-1 cells could migrate towards the chemical signals emanating from omental fat and tumour tissue, using a Boyden chamber assay, a classic technique in which cells are placed in an upper chamber and their movement through a membrane towards chemoattractants in a lower chamber is counted. The result was a cautionary one. KHYG-1 cells migrated in significantly higher numbers towards the chemotactic signals of the omentum than towards those of the tumour. In a patient’s abdomen, where the omentum lies in close anatomical proximity to oesophagogastric tumours, this bias could draw therapeutic cells into fat tissue rather than into the malignancy they are meant to attack.

This migratory misdirection is not a trivial technicality. Obesity-associated cancers arise in a landscape where visceral adipose tissue is abundant, and the chemokine gradients produced by omental fat can act as siren songs for immune cells. The Dublin group’s data suggest that erroneous homing towards the omentum would present a genuine challenge for the effective delivery of KHYG-1 cells to oesophagogastric tumours in living patients. Yet the study did not stop at identifying the problem; it also pointed towards a solution rooted in the chemistry of attraction.

When the researchers supplemented the tumour-conditioned media with IP-10, a chemokine also known as interferon-gamma-inducible protein 10 that is naturally produced during inflammatory responses and is known to attract natural killer cells through the CXCR3 receptor, the chemoattraction of KHYG-1 cells to the tumour environment increased. This proof-of-principle experiment supports the concept of chemokine profile remodelling: deliberately reshaping the signalling landscape of the tumour microenvironment so that therapeutic cells are guided towards the cancer rather than into the surrounding fat. Such remodelling could be achieved through local delivery of chemokines, oncolytic viral vectors engineered to secrete attractants, or other strategies that physicians and bioengineers are already exploring in related contexts.

The broader significance of the work lies in its ex vivo rigour. By using patient-derived materials rather than simplified cell culture systems, the study captured a realistic snapshot of the obesity-associated cancer environment, and by testing both function and migration it addressed the two properties that determine whether adoptive cell therapy can succeed. Oesophagogastric adenocarcinoma carries a poor prognosis, and patients with obesity face compounded immunological disadvantages, making the search for effective immunotherapies in this population particularly urgent. The findings suggest that KHYG-1 cells, or cell lines and engineered derivatives modelled on them, could form the basis of therapies that augment anti-tumour immunity where the patient’s own natural killer cells have faltered.

Considerable work remains before any clinical translation. The experiments were conducted outside the body, and the full complexity of the in vivo environment, including vascular trafficking, stromal barriers and interactions with other immune populations, cannot be fully reproduced in a dish. The authors themselves emphasise that the migratory bias towards omentum will need to be overcome, likely through the chemokine-remodelling approaches their data support. Nonetheless, the study offers a dual gift to the field: evidence that a candidate therapeutic cell can retain its cytotoxic potency in one of the most immunologically challenging disease settings, and a mechanistically grounded roadmap for steering those cells to where they are needed most. For a cancer whose burden grows with the global obesity epidemic, that combination of resilience and navigability may prove to be exactly what the next generation of natural killer cell therapies requires.

Subject of Research: The functional resilience and migratory behaviour of KHYG-1 natural killer cells in the tumour and omental microenvironments of obesity-associated oesophagogastric adenocarcinoma.

Article Title: KHYG-1 cells retain functionality following exposure to the tumour and omental microenvironments of patients with obesity-associated cancer

Article References: Marion, C., Barry, J. C., Mylod, E., Smith, L., Menon, M. S., O’Connor, N., Butler, C., Deac, O. M., Donohoe, C. L., Elliott, J. A., Lowery, M., Reynolds, J. V., Lysaght, J., & Conroy, M. J. (2026). KHYG-1 cells retain functionality following exposure to the tumour and omental microenvironments of patients with obesity-associated cancer. Journal of Cancer Research and Clinical Oncology. https://doi.org/10.1007/s00432-026-06617-3

Image Credits: AI Generated

DOI: 10.1007/s00432-026-06617-3

Keywords: natural killer cells, KHYG-1, oesophagogastric adenocarcinoma, obesity, tumour microenvironment, omentum, chemokines, IP-10, cell migration, immunotherapy, cancer research, adoptive cell therapy

Strongyloides stercoralis is a soil-transmitted helminth that infects an estimated 300 to 600 million people worldwide, yet it remains notoriously difficult to diagnose because the parasite persists at low levels in the intestine and sheds larvae intermittently. What makes the infection clinically dangerous is its unique ability to complete its life cycle entirely within the human host through autoinfection, allowing the worm to survive for decades. In individuals whose immunity becomes suppressed, for example by corticosteroid therapy or other conditions, the parasite can multiply uncontrollably and cause hyperinfection syndrome, a frequently fatal complication. Understanding the immune landscape of chronic infection is therefore not merely an academic exercise; it is central to identifying who is at risk and how the disease can be detected earlier.

The research team enrolled 82 individuals with confirmed S. stercoralis infection and 48 uninfected controls living in the same endemic region of Khuzestan province, a design that allowed them to distinguish infection-specific immune changes from background environmental exposures common to both groups. All infected participants presented with eosinophilia, an elevated count of eosinophils, the white blood cells classically associated with defense against parasitic worms. To probe the immune response, the investigators developed in-house enzyme-linked immunosorbent assays to measure antibodies directed against Strongyloides antigens, together with bead-based multiplex assays capable of quantifying a broad panel of cytokines and chemokines in serum.

The antibody results were striking in their subclass specificity. Infected individuals showed significantly elevated Strongyloides-specific immunoglobulin G responses compared with endemic healthy controls, but this elevation was not uniform across all IgG classes. Instead, IgG4 and IgG1 emerged as the dominant subclasses, while IgG2 responses were minimal. This pattern is immunologically meaningful: IgG4 is the subclass most consistently induced by chronic helminth exposure and is often interpreted as a marker of prolonged, repeated antigenic stimulation under a regulatory immune environment. The prominence of IgG1 alongside it suggests a robust, active antibody response to the parasite rather than a purely dampened one, painting a picture of coexisting activation and regulation that is characteristic of long-term worm carriage.

The cytokine data reinforced this type 2 orientation. Infected participants displayed significantly increased serum concentrations of interleukin-4, interleukin-5, interleukin-13, and interleukin-9, the canonical cytokines produced by type 2 helper T cells and, in the case of IL-9, by the increasingly recognized type 9 lineage. IL-4 drives class switching toward IgG4 and IgE, IL-5 recruits and activates eosinophils, and IL-13 promotes mucus production and tissue remodeling at mucosal barriers, all mechanisms directly relevant to expelling intestinal worms. The elevation of IL-9 adds an interesting dimension, as this cytokine has been implicated in mast cell responses and barrier immunity, processes thought to contribute to controlling helminth establishment in the gut.

Perhaps the most unexpected finding concerned the chemokine CXCL9, an interferon-inducible chemokine typically associated with type 1 inflammatory responses and the recruitment of T cells and natural killer cells. The researchers recorded a striking increase in CXCL9 among infected subjects, standing in apparent contrast to the dominant type 2 profile. Meanwhile, the majority of Th1- and Th17-associated cytokines, along with several pro-inflammatory chemokines, were either reduced during infection or increased after treatment and parasite clearance. This suggests that S. stercoralis actively suppresses inflammatory pathways while leaving, or even provoking, a specific interferon-driven chemokine signal, a combination that may reflect the parasite’s strategy of securing long-term survival while the host retains enough immune pressure to keep worm numbers in check.

A longitudinal component of the study strengthened the causal interpretation of these immune signatures. Eighteen patients were reassessed at least six months after receiving albendazole, one of the standard anthelmintic drugs used against strongyloidiasis. Following treatment and presumed parasite clearance, the researchers documented significant reductions in eosinophil counts, parasite-specific IgG1, IgG2, and IgG4 levels, and serum concentrations of both IL-9 and IL-10, the latter being an immunoregulatory cytokine often elevated during chronic helminth infection. In contrast, systemic IL-4 concentrations increased after therapy, an intriguing reversal that the authors note alongside the broader normalization of the infection-associated immune profile. The parallel decline of antibodies, type 2 cytokines, and regulatory signals after cure indicates that these markers track active infection rather than permanent immune reprogramming.

The clinical implications of this work are considerable. Serological diagnosis of strongyloidiasis already relies heavily on detecting parasite-specific antibodies, and the demonstration that IgG4 and IgG1 dominate the response supports the use of subclass-specific assays to improve sensitivity and specificity, particularly in endemic regions where cross-reactivity with other helminths complicates interpretation. Moreover, the finding that antibody levels and type 2 and type 9 cytokines fall measurably after successful treatment raises the possibility of using these immune markers as indicators of cure, something parasitological methods alone have struggled to provide given the intermittent shedding of larvae. In an era of increasing immunosuppressive therapy worldwide, reliable tools to verify parasite elimination before immunosuppression could save lives.

The study also contributes to a broader scientific conversation about how helminths modulate human immunity. Chronic worm infections are widely studied for their immunoregulatory effects, which some researchers hope to harness for treating autoimmune and inflammatory diseases. By documenting, in a well-characterized human cohort, the coordinated suppression of Th1 and Th17 pathways alongside a preserved interferon-inducible chemokine response, the Iranian-German team provides a nuanced dataset that moves beyond the simple dichotomy of type 1 versus type 2 immunity. It shows that natural infection produces a layered and partially contradictory immune landscape whose resolution after treatment can now be followed over time.

Limitations remain, as with any field study conducted in an endemic setting. The number of longitudinally followed patients was modest, and the six-month follow-up window, while sufficient to observe significant immune changes, leaves open questions about the long-term durability of antibody and cytokine normalization. The endemic controls, though carefully selected, cannot fully exclude prior exposure or unrecognized low-level infection. Nevertheless, the study stands as a substantial advance for a disease that has long been overshadowed by better-known tropical parasites. For the millions of people carrying S. stercoralis, many of them unaware of their infection, this work brings the prospect of sharper diagnostics, clearer markers of therapeutic success, and a deeper understanding of the delicate immune equilibrium that this remarkable parasite has evolved to maintain within its human host.

Subject of Research: Immune response profiling in Strongyloides stercoralis infection

Article Title: Systemic profiles of Strongyloides-specific IgG subclass, cytokine, and chemokine response in an eosinophilic Iranian population infected with Strongyloides stercoralis

Article References: Beiromvand, M., Ashiri, A., Rafiei, A., Heepmann, L., Hartmann, W., Linnemann, L., Tappe, D., Veit, A., & Breloer, M. (2026). Systemic profiles of Strongyloides-specific IgG subclass, cytokine, and chemokine response in an eosinophilic Iranian population infected with Strongyloides stercoralis. Parasites & Vectors. https://doi.org/10.1186/s13071-026-07683-9

Image Credits: AI Generated

DOI: 10.1186/s13071-026-07683-9

Keywords: Strongyloides stercoralis, strongyloidiasis, IgG subclasses, cytokines, chemokines, eosinophils, type 2 immunity, albendazole, immunomodulation, Iran, neglected tropical disease, parasitic infection

The review, led by Kexun Li, Zilong Qian and Jie Mao with senior authors Yongtao Han and Xuefeng Leng, synthesises evidence across the major gastrointestinal malignancies: gastric and esophageal cancers, colorectal cancer, pancreatic ductal adenocarcinoma, hepatocellular carcinoma and biliary tract cancers. Its central claim is that the tumour secretome, the full complement of proteins released by tumour cells, stromal cells and immune cells into the extracellular space, functions as a dynamic signalling layer that determines whether immune cells are recruited to the tumour, whether they penetrate it, whether they function once they arrive, and whether they exhaust themselves in the struggle. When checkpoint blockade releases the brakes on T cells, the success of that manoeuvre depends on the state of the road ahead, and the secretome largely builds that road.

The authors catalogue an imposing roster of recurrent suppressive circuits. Transforming growth factor beta, long implicated in immune exclusion and fibroblast activation, appears across nearly every gastrointestinal tumour type as a driver of stromal barriers that physically wall off cytotoxic lymphocytes. Vascular endothelial growth factor, best known for promoting the chaotic, leaky vasculature of tumours, also actively repels T-cell infiltration and fosters immunosuppressive myeloid cells. The chemokine CXCL12, acting through its receptor CXCR4, excludes T cells from tumour nests in pancreatic and colorectal cancers, while CXCL8, also known as interleukin-8, signalling through CXCR1 and CXCR2, attracts neutrophils and suppresses T-cell function. The CCL2-CCR2 axis recruits inflammatory monocytes that can differentiate into tumour-promoting macrophages, and the CSF1-CSF1R pathway sustains those macrophages in a suppressive, pro-tumour state.

Beyond these canonical axes, the review highlights a second tier of secreted mediators whose roles have crystallised more recently. Interleukin-6 family cytokines drive chronic inflammatory programmes that blunt antitumour immunity and correlate with poor outcomes. SPP1, the gene encoding osteopontin, marks a distinctive population of tumour-associated macrophages and fibroblasts that sculpt an immunosuppressive niche. Periostin, secreted largely by cancer-associated fibroblasts, reinforces extracellular matrix barriers and promotes metastatic colonisation. Galectins, a family of beta-galactoside-binding lectins, can directly induce T-cell apoptosis and dysfunction. DKK1, a Wnt pathway antagonist, contributes to immune exclusion and stemness. Macrophage migration inhibitory factor, or MIF, sustains inflammatory suppression, while components of the complement cascade, traditionally viewed as blood-borne effectors of innate immunity, have been co-opted by tumours to remodel the microenvironment in their favour. Finally, soluble forms of PD-L1 and PD-L1 carried on extracellular vesicles circulate through the bloodstream, potentially mopping up therapeutic antibodies and dampening T-cell activity far from the tumour itself.

Against this suppressive chorus, the review sets out the secretome signatures of immune-permissive tumours. The chemokines CXCL9, CXCL10 and CXCL11, signalling through the receptor CXCR3, recruit effector T cells expressing that receptor, and their abundance consistently correlates with T-cell infiltration and responsiveness to checkpoint blockade. Even more striking is CXCL13, the chemokine that draws B cells and organises tertiary lymphoid structures, ectopic lymph-node-like aggregates that form within tumour tissue. Tumours rich in tertiary lymphoid structures, particularly in colorectal and gastric cancer, respond to immunotherapy at markedly higher rates, and CXCL13-associated signalling appears to be a key driver of their formation. The secretome, in other words, is not uniformly hostile; it can be reprogrammed toward a state that amplifies the effect of checkpoint inhibitors once stromal and myeloid barriers are relieved.

To bring analytical order to this complexity, the authors organise the suppressive and permissive circuits into four overlapping functional modules. The myeloid-enriched module encompasses the chemokines and colony-stimulating factors that flood tumours with suppressive macrophages, monocytes and granulocytes. The fibroblast-driven exclusion module centres on TGF-beta, periostin and matrix-remodelling signals that build physical and biochemical barriers to immune infiltration. The angiogenic-immunosuppressive module couples VEGF-driven vascular dysfunction to myeloid suppression and hypoxia. The immune-permissive module, by contrast, comprises the CXCR3 ligand axis and CXCL13-driven tertiary lymphoid structure programmes that characterise tumours primed for immunotherapy response. This modular framework allows clinicians and researchers to describe a tumour’s secretome state not as an undifferentiated list of molecules but as a pattern of dominant biological programmes with distinct therapeutic implications.

Perhaps the review’s most consequential methodological contribution is its insistence on a four-level evidence hierarchy that separates clinical validation from mechanistic inference. Many secreted proteins have been convincingly shown in cell culture and animal models to suppress or promote antitumour immunity, yet only a subset has been validated as predictive or prognostic biomarkers in large clinical cohorts, and fewer still have been targeted successfully in combination trials. TGF-beta, for example, has mechanistic support at every level, and signatures of TGF-beta-driven fibroblast activity have been shown to predict poor checkpoint response in multiple cancer types, yet TGF-beta inhibitors have delivered mixed results in the clinic, suggesting that timing, context and combination partners matter enormously. The hierarchy is designed to prevent over-interpretation of preclinical enthusiasm and to guide rational prioritisation of which secretome targets should advance toward biomarker-guided trials.

Equally important is the review’s argument that protein abundance alone is biologically meaningless without context. The same chemokine can recruit antitumour T cells or immunosuppressive myeloid cells depending on which receptor-bearing cells are present. The same cytokine can promote or restrain immunity depending on its spatial distribution within the tumour, whether it is produced by malignant epithelium, fibroblasts or infiltrating immune cells, and whether it is measured before treatment, during therapy or at the moment of acquired resistance. Metastatic sites differ from primary tumours in their secretome programmes, and host physiology, including liver function, microbiome composition and systemic inflammation, modulates the interpretation of circulating protein signals. A clinically useful secretome biomarker must therefore integrate cellular source, spatial localisation, receptor context, temporal dynamics and linkage to actionable immune-state transitions, a demand that far exceeds what a single blood test or immunohistochemical stain can deliver.

This contextual complexity helps explain why genomic biomarkers such as microsatellite instability and tumour mutational burden, while genuinely predictive in defined settings, leave most gastrointestinal cancer patients without a reliable answer. A colorectal tumour with high mutational burden may nonetheless be saturated with CXCL12-expressing fibroblasts and CSF1-dependent macrophages that render even reinvigorated T cells ineffective. A pancreatic cancer with modest genomic immunogenicity may be so thoroughly walled off by TGF-beta-driven stroma that no quantity of checkpoint blockade can achieve meaningful infiltration. Conversely, a gastric tumour with abundant tertiary lymphoid structures and a CXCL9-rich chemokine milieu may respond even with intermediate genomic predictors. The secretome is the layer at which these competing influences are integrated and expressed.

The therapeutic implications are substantial. Combination strategies already in clinical testing, including TGF-beta inhibition, CSF1R blockade, CXCR4 antagonism, VEGF pathway targeting and IL-6 pathway suppression, can be understood as attempts to dismantle specific suppressive modules and convert tumours from an excluded or suppressive secretome state into a permissive one. The review suggests that the rational design of such combinations should be guided by modular secretome profiling of individual tumours, with the goal of matching each patient to the barrier-removing strategy most likely to unmask checkpoint activity. Biomarker development, the authors argue, should focus on identifying actionable immune-state transitions, moments at which a tumour’s secretome programme is poised to flip from suppression to permissiveness, and on capturing that transition with spatially resolved, temporally informed measurements. As single-cell and spatial transcriptomic technologies mature and become clinically deployable, the prospect of reading a tumour’s secreted protein circuitry and intervening accordingly moves from aspiration toward practice. For the majority of gastrointestinal cancer patients who today derive little benefit from immunotherapy, that shift may ultimately determine whether the immunotherapy revolution reaches them at all.

Subject of Research: Secreted protein signalling circuits in the gastrointestinal tumour microenvironment that determine immunotherapy response and resistance

Article Title: Secreted protein circuits in the gastrointestinal tumour microenvironment: determinants of immunotherapy response and resistance

Article References: Li, K., Qian, Z., Mao, J., Han, Y., & Leng, X. (2026). Secreted protein circuits in the gastrointestinal tumour microenvironment: determinants of immunotherapy response and resistance. Journal of Translational Medicine. https://doi.org/10.1186/s12967-026-08945-x

Image Credits: AI Generated

DOI: 10.1186/s12967-026-08945-x

Keywords: gastrointestinal cancer, tumour microenvironment, secretome, immune checkpoint blockade, TGF-beta, VEGF, chemokines, tertiary lymphoid structures, cancer-associated fibroblasts, tumour-associated macrophages, immunotherapy resistance, biomarkers