Triple-negative breast cancer (TNBC) remains an aggressive disease with limited treatment options. Oncolytic adenoviruses represent a promising platform, but their efficacy as single agents is often insufficient. This study examined whether an oncolytic adenovirus co-delivering decorin (DCN) and CD40 ligand (CD40L), designated rAd.DCN.CD40L, could enhance antitumor activity and immune activation against TNBC. Recombinant adenoviruses expressing DCN (rAd.DCN), CD40L (rAd.CD40L), or both proteins were constructed and evaluated in breast cancer cells using cell viability, apoptosis, migration, invasion, and damage-associated molecular pattern (DAMP) release assays. Compared with rAd.DCN or rAd.CD40L alone, rAd.DCN.CD40L triggered greater apoptosis and tumor cell death and elicited more pronounced DAMP release. Co-culture experiments also revealed enhanced dendritic cell function following rAd.DCN.CD40L treatment. For in vivo evaluation, syngeneic 4T1 and EMT-6 subcutaneous tumor models and a 4T1 lung metastasis model were employed. rAd.DCN.CD40L substantially delayed tumor growth and improved survival in tumor-bearing mice. Flow cytometric and histological analyses further confirmed enhanced local and systemic T-cell responses, elevated CD8⁺ T-cell activity, and modulated inflammatory macrophage phenotypes. Mechanistically, western blot analysis showed that rAd.DCN.CD40L may contribute to extracellular matrix remodeling and the down-regulation of the expression of epithelial-mesenchymal transition (EMT)-associated genes. Notably, CD8⁺ T-cell depletion markedly attenuated the therapeutic efficacy of rAd.DCN.CD40L, demonstrating that CD8⁺ T cells are critical functional effectors of tumor control. Collectively, these findings indicate that a DCN- and CD40L-armed oncolytic adenovirus represents a promising combinatorial strategy for TNBC immunotherapy, and warrants further preclinical and clinical investigation.

Tertiary lymphoid structures (TLS) are local immune microenvironments within tumors housing T cells and B cells, are often coordinating anti-tumor immunity and associated with better responses to immunotherapy. Here, we use H&E morphological assessment and multiplex immunofluorescence to analyze surgical tumor specimens from 71 patients with gastric cancer (GC) after treatment with neoadjuvant anti-PD-1 therapy, chemotherapy, and subsequent gastrectomy. We find increased TLS density and area in the muscularis propria of treatment-resistant GCs. These muscularis TLS are structurally and functionally impaired, with increased naïve B cell presence but reduced germinal center B cell infiltration. Mechanistically, PLA2G2A⁺ tumor cells accumulate adjacent to disrupted muscularis TLS, and PLA2G2A treatment in vitro increases differentiation of a fibroblast cell line into PDGFRA⁺ inflammatory cancer-associated fibroblasts (iCAF), which are linked to CXCL14 secretion and recruitment of naïve B cells. In vitro, PLA2G2A also impairs B cell differentiation and induces T follicular helper cell death, potentially contributing to muscularis TLS dysfunction. Taken together, we propose a tumor cell-iCAF-B cell axis disrupting TLS function, with this axis serving as a potential therapeutic target to overcome immunotherapy resistance.

Neuroendocrine cervical carcinoma (NECC) is an aggressive and rare malignancy comprising 0.9-1.5% of cervical cancers. Its molecular basis remains poorly understood, limiting treatment options. A national multicenter cohort survival analysis showed that NECC patients had a 5.17-fold higher death risk than non-NECC patients and demonstrated broad chemotherapy resistance, which was further validated in both NECC cell lines and patient-derived organoids. To identify therapeutic targets, multi‑omics profiling of NECC tumors and matched normal adjacent tissues revealed pronounced DNA replication stress and hyperactivation of homologous recombination repair (HRR). These findings were validated in cells and patient-derived organoids using DR-GFP reporter and pRPA32 assays, suggesting that NECC may be susceptible to PARP inhibitor therapy. NECC cells exhibited moderate PARP inhibitor sensitivity, greater than that of resistant non‑NECC lines but less than that of highly sensitive A2780 cells. However, combining PARP inhibitors with cisplatin/carboplatin did not enhance efficacy, prompting the exploration of alternative combinatorial targets. Multi-omics analysis and in vitro validation identified Bloom syndrome helicase (BLM) as a key factor overexpressed in NECC that modulates PARP inhibitor sensitivity. Further in vitro and in vivo experiments confirmed that combining PARP and BLM inhibitors achieved potent anticancer effects. Mechanistically, cancer-associated fibroblasts (CAFs) infiltration in the tumor microenvironment upregulated the transcription factor E2F1 via IL6, with ChIP‒qPCR verifying that activated E2F1 directly binds the BLM promoter (hg38, chr15:90,715,346-90,717,346) to drive its expression, suppressing PARP inhibitor sensitivity. Our findings establish dual PARP and BLM inhibition as a promising therapeutic strategy for NECC by blocking HRR pathway compensation.

Colorectal cancer (CRC) is one of the most lethal malignancies worldwide, and the precise identification of biomarkers from colonic adenoma to cancer is of great significance for preventing the development of adenocarcinoma. Given that existing methods inadequately capture the topological network relationships among genes, this study proposes a graph neural network model based on multifeature learning, named ChebTs, to investigate the correlation between key genes involved in the colorectal "adenoma-cancer" transition. The GSE41657 and GSE31905 datasets from the GEO database were stratified into normal, adenoma, and colorectal cancer groups. Feature encoding was introduced to enhance node features, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of differentially expressed genes (DEGs). A protein-protein interaction (PPI) network was constructed using Cytoscape software, and the aggregated information was embedded into the model for training to generate a list of key genes with corresponding importance scores. An attention pooling mechanism aggregated node-level representations into graph level representations for sample classification, and a two layer fully connected network, following activation and regularization, produced predicted probabilities. Furthermore, we provided interpretable analyses at the gene level using GNNExplainer. The results were validated through virtual knockout techniques. The eight screened genes, Fibronectin 1 (FN1), Claudin 2 (CLDN2), Interleukin-33 (IL-33), Matrix Metallopeptidase 1 (MMP1), Stanniocalcin 2 (STC2), Insulin-Like Growth Factor-Binding Protein 7 (IGFBP7), NADPH Oxidase 4 (NOX4), and Secreted Frizzled Related Protein 1 (SFRP1), were all found to be associated with overall survival (OS) in CRC. In this study, eight molecules closely related to the development of colorectal adenocarcinoma were screened out, and they may be diagnostic biomarkers of colorectal cancer. These genes affect the prognosis of patients by participating in biological processes such as remodeling of extracellular mechanisms, and are of great significance for preventing the carcinogenesis of adenoma.

Pulmonary hypertension (PH) is a progressive vasculopathy characterized by pulmonary vascular remodeling, right ventricular maladaptation, and premature death. Exosomes, an endosome-derived subset of small extracellular vesicles, mediate intercellular communication through the transfer of selected RNAs, proteins, and lipids. In PH, they can modulate endothelial dysfunction, pulmonary artery smooth muscle cell proliferation and phenotypic switching, immune dysregulation, and right ventricular remodeling, implicating them in key aspects of disease pathobiology. These properties have prompted interest in exosomes as minimally invasive biomarkers and as candidates for cell-free therapeutic delivery. However, clinical translation remains at an early stage. Most evidence supporting exosome-based therapeutic strategies in PH is preclinical, whereas current clinical data are largely limited to exploratory biomarker studies. Important gaps also remain in distinguishing exosomes from other extracellular vesicle populations and in addressing methodological standardization, heterogeneity, cargo attribution, biodistribution, dosing, and clinical validation. This review summarizes current evidence on exosome biology in PH and discusses both translational opportunities and the major barriers to clinical implementation.

Chronic obstructive pulmonary disease (COPD) is increasingly recognized as a systemic inflammatory syndrome in which forced expiratory volume in 1 s expressed as a percentage of predicted value (FEV1% predicted) may dissociate from patient-reported symptom burden. This study evaluated an Integrated Inflammatory Profile Score (IIPS) as a potential biological correlate for a more holistic assessment of stable COPD.

Serum concentrations of 11 cytokines were measured in 62 patients with stable COPD. The IIPS was derived using automated linear modeling with forward stepwise selection guided by the corrected Akaike information criterion (AICc). Associations of the IIPS with COPD Assessment Test (CAT) scores were compared with those of FEV1% predicted.

The optimized IIPS, comprising interferon-gamma (IFN-γ), interleukin-2 (IL-2), and interleukin-10 (IL-10), was significantly associated with FEV1% predicted (R² = 0.1867, p = 0.0005) and outperformed the individual cytokines in discriminating spirometric severity (area under the receiver operating characteristic curve (AUC) = 0.7381). For symptom burden, FEV1% predicted showed greater explanatory power for exertional domains, particularly breathlessness (R² = 0.0832) and activities (R² = 0.1280). By contrast, the IIPS showed numerically stronger trend-level associations for sleep (R² = 0.0519, p = 0.0750) and energy (R² = 0.0511, p = 0.0773), although these associations did not reach conventional statistical significance.

The IIPS reflects Global Initiative for Chronic Obstructive Lung Disease (GOLD)-defined physiological severity more effectively than any single cytokine measured in this study. Its associations with patient-reported systemic symptoms were modest and exploratory, suggesting that integrated inflammatory profiling may complement spirometry in characterizing COPD burden but requires external and longitudinal validation before clinical application.

The "DescribinG bUrden of COPD and occurrence of mortaLity in a cohort of Italian Patients" (GULP) study was conducted to investigate the potential of biological treatments for patients with severe chronic obstructive pulmonary disease (COPD). The purpose of this article was to perform a narrative review highlighting the role of type 2 inflammation in the mechanism of disease for COPD, summarizing the efficacy data of the Phase III RCTs that investigated biologics in COPD, and exploring the potential role for biological treatment in this setting with a particular focus on Italian patients with COPD. To this end, we conducted an exploratory analysis of GULP study data to identify patients at high risk of exacerbations, with high symoptom burden and classify them based upon the eosinophilic counts, to provide further insights into the potential use of biologics in this cohort. Out of the 1111 patients of the GULP cohort, we retrieved in total 286 (25.7%) GULP participants with ≥2 moderate or ≥1 severe exacerbation per year. Of them, despite maintenance therapy with dual bronchodilators or triple therapy, a high symptom burden (dyspnea, cough and chronic sputum production) was present in between 51.1 and 74.8%, while patients that presented with eosinophilic COPD accounted for the 7.2% of the patients at risk. This indicates that biological agents, specifically those that target the type 2 inflammatory response in COPD, should be considered in symptomatic patients with COPD and unstable disease, but that careful and pro-active phenotyping through clinical and biomarker evaluation is mandatory. Dupilumab is currently approved in Italy for eosinophilc exacerbating COPD patients, and through its favorable efficacy and safety profile, could represent a valid opportunity for these patients.

The value of exercise cardiovascular magnetic resonance (CMR) has been shown in many clinical scenarios. We have developed a novel MR-compatible exercise device and aim to validate it against the reference standard MR-conventional ergometer. The novel device consisted of two half-pipes fixed to a wooden base, with participants wearing knee-length socks with a 0.5 kg weight in each sock. Increased workload was achieved by increasing the rate of alternating leg flexion and extension in time with a bleep sound of increasing frequency. Twenty subjects (10 healthy volunteers, 10 patients with pulmonary arterial hypertension) performed two CMR-augmented cardiopulmonary exercise tests (CMR/CPET) using the novel exercise device and a conventional ergometer in a randomised order. Comparing peak metrics elicited on both exercise devices, there was a moderate correlation in peak oxygen consumption (VO₂, r = 0.86, p < 0.001), cardiac output (CO, r = 0.73, p < 0.001), stroke volume (SV, r = 0.90, p < 0.001), peak heart rate (HR, r = 0.65, p = 0.002) and peak arteriovenous oxygen content gradient (ΔavO₂, r = 0.71, p < 0.001). However, all metrics were significantly lower with the novel device. Both devices were able to elicit statistically significant differences in VO₂, HR and right ventricular ejection fraction (RVEF) between patients and healthy subjects (p ≤ 0.04). We have created a simple, easy to use and affordable exercise device for the CMR environment. This may encourage greater dissemination of exercise CMR in clinical and research practice.

The COVID-19 pandemic dramatically reduced early-life respiratory viral exposures, yet the long-term respiratory consequences for pandemic-born children remain unclear. We aimed to compare respiratory morbidity at age 4 between children born during versus before the pandemic and assess whether atopic risk modifies this association. This single-center birth cohort follow-up study included children born in February-March 2020 (COVID-19 cohort) and pre-pandemic controls born during the same period in 2019. Respiratory outcomes at age 4 were assessed using a structured telephone questionnaire (The International Study of Wheezing in Infants). The primary outcome was composite respiratory morbidity (CRM), defined as use of a short-acting bronchodilator (SABA), inhaled and/or oral corticosteroids, and/or emergency room visits for respiratory symptoms. Of 588 eligible children, 329 (55.9%) completed follow-up (139 COVID-19, 190 controls); baseline characteristics, including atopy prevalence, were comparable between cohorts. CRM during the fourth year of life was significantly more common in the COVID-19 cohort (39.6% vs. 27.4%, p = 0.02). In stratified analyses, CRM was markedly higher among atopic-risk pandemic-born children (atopic subgroup: n = 47 COVID-19, n = 68 controls) (66% vs. 27.9%, p < 0.001), but not among non-atopic children (26.1% vs. 27%). Multivariable logistic regression confirmed a significant COVID-19 cohort × atopy interaction for CRM (OR 5.04, 95% CI 1.83-13.89, p = 0.002), while neither factor alone was independently associated with the outcome.

 Birth during the COVID-19 pandemic was associated with increased preschool respiratory morbidity, particularly among children with atopic risk. These findings suggest that altered early-life microbial exposures may modify respiratory morbidity trajectories according to host atopic susceptibility.

• Children born during the COVID-19 pandemic had fewer respiratory infections and wheezing episodes in infancy due to reduced viral circulation. • Atopic predisposition is among the strongest risk factors for recurrent wheezing and persistent asthma in preschool children.

• Pandemic-born children show significantly higher composite respiratory morbidity at age 4, but exclusively among those with atopic risk (OR 5.04). • Neither pandemic birth nor atopy alone predicts excess morbidity-only their combination does, suggesting host susceptibility shapes long-term respiratory trajectories.

Influenza, a prevalent disease, significantly threatens public health. Accurately predicting severe influenza occurrences is crucial for developing personalized prevention strategies and treatment plans.

This study aimed to construct a highly interpretable model to assess the risk of severe influenza in hospitalized children, using the SHapley Additive exPlanation (SHAP) method to interpret the Random Forest (RF) model and identify risk factors for severe influenza.

A retrospective cohort study was conducted, collecting hospitalization records of influenza patients from the Electronic Medical Records (EMR) system for model development and performance evaluation. Data were collected within the first 24 h after patient admission and the dataset was randomly divided into two parts: 70% for model training and 30% for model accuracy verification.

A total of 436 eligible influenza patients were included in the study analysis. The RF model demonstrated the highest predictive accuracy among the six models compared, with an area under the receiver-operating-characteristiccurve(AUROC) of 0.88. The decision curve analysis (DCA) indicated that the net benefit of the RF model surpassed that of other machine learning models. According to the importance ranking by the SHAP method, blood glucose was identified as the most significant predictive variable.

The study established a RF model capable of predicting severe influenza occurrence in hospitalized children. The model, interpreted through the SHAP method, assists physicians in providing better treatment plans.