Adv Sci (Weinh). 2026 May 26:e75839. doi: 10.1002/advs.75839. Online ahead of print.

ABSTRACT

Lung squamous cell carcinoma (LUSC) lacks clearly defined key drivers and effective targeted therapies, reflecting an incomplete understanding of its molecular pathogenesis. Here, we identify SMAD4 as a critical regulator of three-dimensional (3D) genome organization in LUSC and uncover a mechanistic link between tumor suppressor loss and oncogenic transcriptional activation. By integrating clinical datasets, genetically engineered mouse models, human and murine LUSC cell lines, and multi-omics analyses, we demonstrate that SMAD4 deficiency promotes LUSC progression by unleashing EP300-mediated enhancer-promoter looping at the SOX2 locus. Mechanistically, SMAD4 does not directly bind SOX2 regulatory elements but instead constrains chromatin looping by sequestering EP300 away from loop anchor regions. Loss of SMAD4 leads to enhanced H3K27ac deposition, aberrant SOX2 activation, and increased LUSC tumor cell proliferation. Together, these findings reveal a non-canonical role for a transcription factor (e.g., SMAD4) in regulating dysregulated 3D genome architecture to inhibit tumor development.

PMID:42189071 | DOI:10.1002/advs.75839

J Cardiovasc Dev Dis. 2026 Apr 30;13(5):195. doi: 10.3390/jcdd13050195.

ABSTRACT

(1) Aim: The incidence of high-altitude pulmonary hypertension (HAPH) has risen in recent years and is expected to continue increasing; however, its diagnosis remains challenging. In this study, we employed proteomics and metabolomics to identify the proteins and metabolic biomarkers that contribute to the development of HAPH. (2) Methods: We applied integrated proteomics and metabolomics to match blood samples from 40 HAPH patients and 40 healthy controls in Yunnan's high-altitude regions to characterize molecular profiles, identify biomarkers, and develop a predictive model. (3) Results: Proteomic analysis identified four proteins (A2IPH7, K1C14, PSME2, SERPINE2) commonly dysregulated in HAPH patients from two high-altitude regions. SERPINE2 was notably downregulated and showed a negative correlation with clinical severity, which was further validated in HAPH rat lung tissues and supported by UK Biobank data for idiopathic PAH. Concurrent metabolomics uncovered 11 shared metabolites, largely acyl fatty acids, enriched in pathways such as unsaturated fatty acid synthesis. Integration of these multi-omics data enabled the development of a robust predictive model. (4) Conclusion: Our study identified key protein and metabolic biomarkers involved in HAPH development, which were validated in animal models. Based on these findings, a predictive model was developed, highlighting SERPINE2 and 11 metabolites as promising targets for the prediction and prevention of HAPH.

PMID:42188081 | DOI:10.3390/jcdd13050195

Metabolites. 2026 May 15;16(5):333. doi: 10.3390/metabo16050333.

ABSTRACT

Background: Children with obesity-related asthma exhibit poorer symptom control and more frequent exacerbations than their normal-weight peers, but the underlying metabolic mechanisms are unclear. This study aimed to identify drivers of obesity-related asthma through untargeted plasma metabolomic and lipidomic profiling. Methods: Plasma was obtained from normal weight (NW) asthmatic (n = 95) and non-asthmatic (n = 67) and overweight/obese (OO) asthmatic (n = 99) and non-asthmatic (n = 100) children (6-17 years). We assessed metabolic and lipidomic differences between asthmatics and controls within each BMI group using orthogonal partial least squares discriminant analysis (OPLS-DA), examined overlap with the adult Qatar Biobank cohort, and mapped metabolic-clinical interactions using Gaussian Graphical Models. Results: In the fitted OPLS-DA models, separation between asthmatic and control groups was stronger in the NW group (R²Y = 0.72/0.52) than in OO (R²Y = 0.65/0.63) children. Asthma was associated with altered tricarboxylic acid (TCA) intermediates, ether-linked phosphatidylethanolamines, and sphingomyelins (SM) in NW, and with phosphatidylcholines, lysophosphatidylcholines, and phosphatidylethanolamines in OO. Integrating metabolomic, lipidomic, and clinical data revealed connections between altered SMs and interleukins, and TCA intermediates and electrolytes, all associated with elevated leptin in NW. An increased residual volume to total lung capacity ratio in OO was associated with phospholipid shifts. The overall dynamics in lipid metabolism with asthma, conditioned on BMI, was also observed in the adult Qatar Biobank cohort. Conclusions: Among NW children with asthma, we found enhanced TCA cycle activity and inflammation linked to altered SM metabolism, whereas in OO, the findings suggest oxidative stress arising from chronic obesity-related inflammation. These data reveal BMI-specific metabolic mechanisms of pediatric asthma that might inform precision approaches to disease management.

PMID:42188042 | DOI:10.3390/metabo16050333

Clin Epigenetics. 2026 May 26;18(1):90. doi: 10.1186/s13148-026-02084-2.

ABSTRACT

BACKGROUND: Non-invasive biomarkers offer potential to improve risk stratification and early diagnosis of lung cancer, complementing low-dose computed tomography (LDCT) screening. This study employed bibliometric analysis to identify global research trends, collaborative networks, and future directions in lung cancer biomarker research. Publications on lung cancer biomarkers for screening were retrieved from the Web of Science Core Collection (WoSCC). Data processing and visualisation were performed using Citespace, VOSviewer, KH Coder, Latent Dirichlet Allocation (LDA) topic modelling, and the online bibliometric analysis platform. Burst detection analysis was performed to predict emerging research trends.

RESULTS: Analysis of 3636 publications revealed exponential growth in research output since 2014. International collaboration demonstrated a dual-core structure centred on China and the United States, with Chinese institutions showing high publication volumes and American institutions demonstrating greater citation influence. Journal citation mapping revealed three evolutionary phases: basic mechanisms-clinical translation-intelligent integration. LDA topic modelling identified 22 topics grouped into five core research directions: imaging and pathological diagnostic techniques; molecular and omics marker research; liquid biopsy and new detection technologies; clinical and translational medicine research; and tumour biology and treatment mechanisms. Burst detection analysis predicted future four priority areas: epigenetic studies centred on DNA methylation for risk prediction; treatment resistance and invasion mechanisms; liquid biopsy technology development; and targeted therapy clinical trials.

CONCLUSIONS: Lung cancer biomarker research has evolved towards multimodal, intelligent screening approaches. Future research priorities include DNA methylation-based markers, circulating microRNA signatures, and artificial intelligence-assisted diagnostic platforms to improve early detection accuracy and complement LDCT screening.

PMID:42185923 | DOI:10.1186/s13148-026-02084-2

J Transl Med. 2026 May 25. doi: 10.1186/s12967-026-08312-w. Online ahead of print.

ABSTRACT

BACKGROUND: Liver fibrosis is a dynamic and reversible pathological process underlying chronic liver diseases, characterized by excessive extracellular matrix deposition and progressive hepatic architectural distortion. It acts as a critical precursor to cirrhosis, hepatic decompensation, and hepatocellular carcinoma, imposing a substantial global disease burden.

MAIN BODY: Accumulating evidence indicates that liver fibrosis is a highly plastic process governed by multicellular crosstalk, immune microenvironment remodeling, epigenetic-metabolic coupling, and mechanotransduction. This review outlines core cellular effectors and their heterogeneity revealed by single-cell omics, and highlights key regulatory layers including circadian rhythm, epigenetic imprinting, metabolic reprogramming, and the gut-liver axis, as well as etiology-specific differences in fibrosis progression, reversibility, and therapeutic response. We also summarize advances in non-invasive diagnosis and clinical translation of anti-fibrotic therapies, and discuss key bottlenecks leading to clinical trial failures.

CONCLUSION: A deeper understanding of cell fate regulation and multicellular ecosystem remodeling will facilitate the development of precise strategies to achieve meaningful fibrosis regression and improve long-term clinical outcomes in chronic liver diseases.

PMID:42185911 | DOI:10.1186/s12967-026-08312-w

Adv Sci (Weinh). 2026 May 26:e75839. doi: 10.1002/advs.75839. Online ahead of print.

ABSTRACT

Lung squamous cell carcinoma (LUSC) lacks clearly defined key drivers and effective targeted therapies, reflecting an incomplete understanding of its molecular pathogenesis. Here, we identify SMAD4 as a critical regulator of three-dimensional (3D) genome organization in LUSC and uncover a mechanistic link between tumor suppressor loss and oncogenic transcriptional activation. By integrating clinical datasets, genetically engineered mouse models, human and murine LUSC cell lines, and multi-omics analyses, we demonstrate that SMAD4 deficiency promotes LUSC progression by unleashing EP300-mediated enhancer-promoter looping at the SOX2 locus. Mechanistically, SMAD4 does not directly bind SOX2 regulatory elements but instead constrains chromatin looping by sequestering EP300 away from loop anchor regions. Loss of SMAD4 leads to enhanced H3K27ac deposition, aberrant SOX2 activation, and increased LUSC tumor cell proliferation. Together, these findings reveal a non-canonical role for a transcription factor (e.g., SMAD4) in regulating dysregulated 3D genome architecture to inhibit tumor development.

PMID:42189071 | DOI:10.1002/advs.75839

J Cardiovasc Dev Dis. 2026 Apr 30;13(5):195. doi: 10.3390/jcdd13050195.

ABSTRACT

(1) Aim: The incidence of high-altitude pulmonary hypertension (HAPH) has risen in recent years and is expected to continue increasing; however, its diagnosis remains challenging. In this study, we employed proteomics and metabolomics to identify the proteins and metabolic biomarkers that contribute to the development of HAPH. (2) Methods: We applied integrated proteomics and metabolomics to match blood samples from 40 HAPH patients and 40 healthy controls in Yunnan's high-altitude regions to characterize molecular profiles, identify biomarkers, and develop a predictive model. (3) Results: Proteomic analysis identified four proteins (A2IPH7, K1C14, PSME2, SERPINE2) commonly dysregulated in HAPH patients from two high-altitude regions. SERPINE2 was notably downregulated and showed a negative correlation with clinical severity, which was further validated in HAPH rat lung tissues and supported by UK Biobank data for idiopathic PAH. Concurrent metabolomics uncovered 11 shared metabolites, largely acyl fatty acids, enriched in pathways such as unsaturated fatty acid synthesis. Integration of these multi-omics data enabled the development of a robust predictive model. (4) Conclusion: Our study identified key protein and metabolic biomarkers involved in HAPH development, which were validated in animal models. Based on these findings, a predictive model was developed, highlighting SERPINE2 and 11 metabolites as promising targets for the prediction and prevention of HAPH.

PMID:42188081 | DOI:10.3390/jcdd13050195

Metabolites. 2026 May 15;16(5):333. doi: 10.3390/metabo16050333.

ABSTRACT

Background: Children with obesity-related asthma exhibit poorer symptom control and more frequent exacerbations than their normal-weight peers, but the underlying metabolic mechanisms are unclear. This study aimed to identify drivers of obesity-related asthma through untargeted plasma metabolomic and lipidomic profiling. Methods: Plasma was obtained from normal weight (NW) asthmatic (n = 95) and non-asthmatic (n = 67) and overweight/obese (OO) asthmatic (n = 99) and non-asthmatic (n = 100) children (6-17 years). We assessed metabolic and lipidomic differences between asthmatics and controls within each BMI group using orthogonal partial least squares discriminant analysis (OPLS-DA), examined overlap with the adult Qatar Biobank cohort, and mapped metabolic-clinical interactions using Gaussian Graphical Models. Results: In the fitted OPLS-DA models, separation between asthmatic and control groups was stronger in the NW group (R²Y = 0.72/0.52) than in OO (R²Y = 0.65/0.63) children. Asthma was associated with altered tricarboxylic acid (TCA) intermediates, ether-linked phosphatidylethanolamines, and sphingomyelins (SM) in NW, and with phosphatidylcholines, lysophosphatidylcholines, and phosphatidylethanolamines in OO. Integrating metabolomic, lipidomic, and clinical data revealed connections between altered SMs and interleukins, and TCA intermediates and electrolytes, all associated with elevated leptin in NW. An increased residual volume to total lung capacity ratio in OO was associated with phospholipid shifts. The overall dynamics in lipid metabolism with asthma, conditioned on BMI, was also observed in the adult Qatar Biobank cohort. Conclusions: Among NW children with asthma, we found enhanced TCA cycle activity and inflammation linked to altered SM metabolism, whereas in OO, the findings suggest oxidative stress arising from chronic obesity-related inflammation. These data reveal BMI-specific metabolic mechanisms of pediatric asthma that might inform precision approaches to disease management.

PMID:42188042 | DOI:10.3390/metabo16050333

J Thorac Dis. 2026 Apr 30;18(4):415. doi: 10.21037/jtd-2026-1-0025. Epub 2026 Apr 24.

ABSTRACT

BACKGROUND AND OBJECTIVE: Circulating tumor cells (CTCs) are malignant cells shed into blood that enable noninvasive, longitudinal assessment of lung cancer. Increasing evidence frames CTCs within a circulating tumor microenvironment (cTME) and broader circulating tumor-associated cell (CTAC) ecosystems that include multicellular clusters and circulating tumor endothelial cells (CTECs). We summarize definitions, detection approaches, and clinical applications of CTC-centered liquid biopsy in non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC).

METHODS: A comprehensive literature search was conducted in PubMed, Embase, Web of Science, and Google Scholar using the terms "non-small cell lung cancer", "small cell lung cancer", and "circulating tumor cells". Relevant clinical, basic, and translational studies were selected and synthesized to outline current knowledge and future directions.

KEY CONTENT AND FINDINGS: CTCs can be enriched by immunoaffinity, size, or microfluidic platforms, enabling enumeration and downstream profiling. In both NSCLC and SCLC, CTC positivity and higher burden are associated with worse survival, with the strongest effects in SCLC and with circulating tumor emboli (CTE). Serial monitoring provides early signals of response or failure; and post-treatment supports minimal residual disease (MRD) detection and relapse prediction. Molecular and phenotypic profiling enables driver and resistance tracking, including epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK), while CTECs may add vascular and immune-relevant information.

CONCLUSIONS: CTC-based assays have the potential to complement imaging and tissue biopsy across screening research, prognostication, therapeutic monitoring, MRD assessment, and personalized care. Clinical translation requires standardized preanalytical workflows, harmonized thresholds, and prospective trials testing CTC-guided management.

PMID:42182710 | PMC:PMC13190041 | DOI:10.21037/jtd-2026-1-0025

Int J Gen Med. 2026 May 18;19:602509. doi: 10.2147/IJGM.S602509. eCollection 2026.

ABSTRACT

Thyroid cancer (TC), the most prevalent endocrine malignancy worldwide, encompasses a broad spectrum of biological behaviors ranging from indolent microcarcinomas to lethal anaplastic variants. Despite advancements in standard care, critical clinical "bottlenecks" persist, including the diagnostic ambiguity of Bethesda III/IV nodules, the rising prevalence of radioiodine-refractory (RAI-R) differentiated TC, and the dismal survival rates of anaplastic thyroid carcinoma (ATC). The rapid evolution of biomarkers has catalyzed a paradigm shift from traditional anatomical-pathological staging to a sophisticated "Molecular Taxonomy" model, providing the cornerstone for precision oncology. This review systematically delineates the multi-dimensional landscape of TC biomarkers, encompassing genomic and transcriptomic drivers (eg, BRAF, RAS, TERT, RET, NTRK), epigenetic regulators (miRNAs, lncRNAs, circRNAs, and DNA methylation), and the proteomic interface. We highlight the transformative role of Liquid Biopsy 2.0-including ctDNA-based minimal residual disease (MRD) detection and exosomal multi-omics-in enabling non-invasive, longitudinal surveillance. Furthermore, we explore how cutting-edge technologies, such as single-cell sequencing and spatial transcriptomics, are deciphering intratumoral heterogeneity and redefining the "functional invasive front". Clinical translation is addressed through the lens of personalized management: from the use of genomic classifiers (eg, ThyroSeq v3) in preoperative triage to biomarker-guided "de-escalation" or "intensification" of therapy. Finally, we discuss the imperative of addressing ancestry-specific molecular divergence (specifically in Asian cohorts). However, significant challenges remain, including the high cost of multi-omics integration and the lack of standardized protocols for clinical implementation. We conclude by envisioning a future integrated with multimodal AI models, patient-derived organoids (PDOs), and metabolic reprogramming markers, aiming to provide a holistic framework for the "early screening-precise diagnosis-tailored therapy-dynamic monitoring" continuum in thyroid oncology.

PMID:42179850 | PMC:PMC13196814 | DOI:10.2147/IJGM.S602509

J Transl Med. 2026 May 25. doi: 10.1186/s12967-026-08301-z. Online ahead of print.

ABSTRACT

BACKGROUND: Hepatocellular carcinoma (HCC) remains a major global health burden and a leading cause of cancer-related mortality. Advanced disease is characterized by a profoundly immunosuppressive tumor microenvironment (TME) and limited durable responses to therapy. However, the upstream genetic determinants that drive tumor-associated macrophage (TAM) dysfunction in HCC remain poorly defined. Using an integrative genetic and multi-omics framework, we investigated complement receptor 1 (CR1) as a candidate regulator of this immunosuppressive niche.

METHODS: We combined Mendelian randomization (MR) and metabolite mediation analyses with bulk, single-cell, and spatial transcriptomics to define the role of CR1 in HCC. Public datasets included the TCGA-HCC cohort, a single-cell RNA-sequencing dataset comprising 53,474 high-quality cells from 21 samples, and two spatially profiled HCC sections. Clinical validation was performed in 30 paired HCC and adjacent liver tissues. Functional assays were conducted in THP-1-derived macrophages using CR1 gain- and loss-of-function approaches, phagocytosis assays, and macrophage-CD8⁺ T-cell co-culture experiments.

RESULTS: MR analyses implicated CR1 in HCC susceptibility at both the protein and transcript levels. pQTL analysis linked genetically predicted circulating CR1 levels to HCC risk (IVW OR = 1.403, p = 0.017), and mediation analysis identified specific metabolites as candidate intermediates. Integrative multi-omics analyses showed that CR1 was preferentially enriched in TAMs, spatially co-localized with the M2 marker CD206, and associated with reduced CD8⁺ T-cell infiltration, enhanced T-cell exhaustion signatures, advanced clinicopathological features, and poorer survival. In 30 paired clinical samples, CR1-high tumors exhibited increased M2-like macrophage accumulation and reduced CD8⁺ T-cell infiltration. Functionally, CR1 overexpression drove macrophages toward an M2-like phenotype, enhanced phagocytic activity, increased PD-L1 expression, and suppressed CD8⁺ T-cell proliferation as well as IFN-gamma and granzyme B production, whereas CR1 knockdown produced the opposite phenotype.

CONCLUSIONS: Our study provides the first integrated genetic, spatial, and functional evidence that CR1⁺ TAMs constitute a clinically relevant immunoregulatory axis in HCC. These findings extend current understanding of complement-associated immunosuppression beyond canonical complement cascade activity and support CR1 as a candidate biomarker and therapeutic target for macrophage reprogramming, with potential translational relevance for combination strategies involving immune checkpoint blockade.

PMID:42185899 | DOI:10.1186/s12967-026-08301-z

Phytomedicine. 2026 May 15;157:158305. doi: 10.1016/j.phymed.2026.158305. Online ahead of print.

ABSTRACT

BACKGROUND: Severe acute pancreatitis (SAP) lacks targeted therapies, and massive loss of functional pancreatic acinar cells (PAC) drives mortality. Kaempferol (KA) possesses well-established anti-inflammatory and cytoprotective activities and is derived from herbal medicinal plants, but its direct molecular targets and mechanism of action in SAP remain undefined.

PURPOSE: To evaluate the protective effects of KA against SAP and to elucidate its molecular mechanism of specific action, with a focus on identifying the direct cellular target through which KA exerts its cytoprotective effects.

STUDY DESIGN: Gain‑/loss‑of‑function in vitro and PAC‑specific CD47 SAP mouse models, combined with multi‑omics screening and biophysical assays.

METHODS: CD47 manipulation (siRNA/overexpression) was performed in primary PACs and cell lines, combined with WT/CD47^-/-/Mist1‑CD47‑iOE (PAC‑specific) mouse models. Network pharmacology, transcriptomics and proteomics were integrated to screen and validate KA's protective effects. Computational‑experimental approaches (molecular docking/dynamics, CETSA, SPR, co‑IP, pharmacological epistasis) characterized KA's allosteric modulation of CD47 signaling.

RESULTS: CD47 was upregulated in SAP; its knockout reduced PAC death via KEAP1/PGAM5/AIFM1-driven oxeiptosis. KA reduced PAC death across genotypes, afforded no extra benefit in CD47-KO, and was not overridden by CD47‑OE. Mechanistically, KA allosterically binds CD47 ectodomain, stabilizes the CD47‑ UBQLN1 complex, and redirects signaling from Gαi‑mediated death to Gβγ/ ERK/NRF2‑mediated survival. ERK inhibition attenuated KA's protection. KA's action was CD47‑dependent.

CONCLUSION: This study identifies anti-oxeiptosis as a novel pharmacological activity of KA in SAP. This is achieved through allosteric modulation of CD47, redirecting its signaling from death‑promoting to a protective axis via activating Gβγ/ERK/NRF2 to suppress oxeiptosis. These findings reveal the CD47‑oxeiptosis axis as a therapeutic target and position KA as a promising candidate for SAP therapy, adding a new mechanistic dimension to KA's known pharmacological profile.

PMID:42184499 | DOI:10.1016/j.phymed.2026.158305

Front Pharmacol. 2026 May 8;17:1804673. doi: 10.3389/fphar.2026.1804673. eCollection 2026.

ABSTRACT

Advanced pancreatic ductal adenocarcinoma (PDAC) remains among the most formidable challenges in oncology, driven by a profoundly immunosuppressive tumor microenvironment (TME) and pervasive resistance to systemic and local therapies. Although immune checkpoint inhibitors (ICIs) can synergize with radiotherapy (RT) in several malignancies, the clinical benefit of immunoradiotherapy (iRT) in PDAC has been modest, highlighting the limitations of population-averaged paradigms that fail to capture extensive inter- and intratumoral heterogeneity. Here, we synthesize an artificial intelligence (AI)-enabled framework to refine both the biological rationale and clinical implementation of iRT for advanced PDAC through integrative analysis of multimodal data (clinical variables, imaging, RT dose distributions, and multi-omics). We highlight advances in three domains. First, AI-based deconvolution of TME heterogeneity can delineate clinically relevant molecular subtypes and spatial immune architectures that may be therapeutically tractable. Second, AI-driven modeling can optimize spatiotemporal RT-immunotherapy interactions, informing individualized dose, fractionation, and biologically guided target definition. Third, AI-supported predictive modeling and adaptive feedback can enable response-guided treatment adjustment beyond static planning. We also discuss unresolved clinical questions and key translational barriers, including data scarcity, lack of standardization, and limited interpretability. Finally, we outline priorities for translation-prospective digital biobanks, hybrid mechanistic-data-driven modeling, and adaptive trial designs-to enable rigorous validation and clinical deployment. Collectively, these developments position AI as a catalyst to move iRT for PDAC from empiricism toward real-time, individualized precision medicine.

PMID:42181887 | PMC:PMC13194001 | DOI:10.3389/fphar.2026.1804673

J Transl Med. 2026 May 25. doi: 10.1186/s12967-026-08301-z. Online ahead of print.

ABSTRACT

BACKGROUND: Hepatocellular carcinoma (HCC) remains a major global health burden and a leading cause of cancer-related mortality. Advanced disease is characterized by a profoundly immunosuppressive tumor microenvironment (TME) and limited durable responses to therapy. However, the upstream genetic determinants that drive tumor-associated macrophage (TAM) dysfunction in HCC remain poorly defined. Using an integrative genetic and multi-omics framework, we investigated complement receptor 1 (CR1) as a candidate regulator of this immunosuppressive niche.

METHODS: We combined Mendelian randomization (MR) and metabolite mediation analyses with bulk, single-cell, and spatial transcriptomics to define the role of CR1 in HCC. Public datasets included the TCGA-HCC cohort, a single-cell RNA-sequencing dataset comprising 53,474 high-quality cells from 21 samples, and two spatially profiled HCC sections. Clinical validation was performed in 30 paired HCC and adjacent liver tissues. Functional assays were conducted in THP-1-derived macrophages using CR1 gain- and loss-of-function approaches, phagocytosis assays, and macrophage-CD8⁺ T-cell co-culture experiments.

RESULTS: MR analyses implicated CR1 in HCC susceptibility at both the protein and transcript levels. pQTL analysis linked genetically predicted circulating CR1 levels to HCC risk (IVW OR = 1.403, p = 0.017), and mediation analysis identified specific metabolites as candidate intermediates. Integrative multi-omics analyses showed that CR1 was preferentially enriched in TAMs, spatially co-localized with the M2 marker CD206, and associated with reduced CD8⁺ T-cell infiltration, enhanced T-cell exhaustion signatures, advanced clinicopathological features, and poorer survival. In 30 paired clinical samples, CR1-high tumors exhibited increased M2-like macrophage accumulation and reduced CD8⁺ T-cell infiltration. Functionally, CR1 overexpression drove macrophages toward an M2-like phenotype, enhanced phagocytic activity, increased PD-L1 expression, and suppressed CD8⁺ T-cell proliferation as well as IFN-gamma and granzyme B production, whereas CR1 knockdown produced the opposite phenotype.

CONCLUSIONS: Our study provides the first integrated genetic, spatial, and functional evidence that CR1⁺ TAMs constitute a clinically relevant immunoregulatory axis in HCC. These findings extend current understanding of complement-associated immunosuppression beyond canonical complement cascade activity and support CR1 as a candidate biomarker and therapeutic target for macrophage reprogramming, with potential translational relevance for combination strategies involving immune checkpoint blockade.

PMID:42185899 | DOI:10.1186/s12967-026-08301-z

Front Immunol. 2026 May 8;17:1762222. doi: 10.3389/fimmu.2026.1762222. eCollection 2026.

ABSTRACT

BACKGROUND: Hepatocellular carcinoma (HCC) exhibits profound molecular heterogeneity and aberrant cellular senescence. This study systematically dissects the senescence-associated molecular landscape to identify key regulators driving HCC progression and immune evasion.

METHODS: Integrating multi-cohort transcriptomic datasets, we developed a robust prognostic signature using 101 machine-learning models, identifying prognostic signature. We employed preliminary proteomic, exploratory metabolomic, and single-cell RNA sequencing (scRNA-seq) analyses to explore multi-omics alterations. The functional senescence status and MCM7 were validated in a clinical HCC cohort by RT-qPCR, Western blotting, immunohistochemistry, and multiplex immunofluorescence (mIF). Causality was established using in vitro functional assays in HepG2 cells.

RESULTS: A 12-gene random survival forest (RSF) signature accurately predicted patient survival across independent cohorts. MCM7 emerged as a central senescence-associated driver. ScRNA-seq and mIF confirmed MCM7 characterizes a highly proliferative, clonally expanding subset of CD8⁺ T cells within the tumor microenvironment. In vitro, MCM7 knockdown significantly inhibited HepG2 cell proliferation and upregulated senescence enforcers p16 and p21, whereas overexpression facilitated evasion. Additionally, TIDE analysis revealed that high-risk patients exhibited elevated immune evasion potential, predicting poor immunotherapy response.

CONCLUSION: This integrative multi-omics framework uncovers an MCM7 MCM7-driven senescence-associated axis promising HCC progression and immune dysfunction, offering a robust tool for prognostic stratification and novel therapeutic insights.

PMID:42183188 | PMC:PMC13195000 | DOI:10.3389/fimmu.2026.1762222

J Clin Transl Hepatol. 2026 Apr 28;14(4):462-477. doi: 10.14218/JCTH.2025.00589. Epub 2026 Apr 8.

ABSTRACT

Hepatocellular carcinoma (HCC) is one of the most prevalent and aggressive malignant tumors globally, with a notably low five-year survival rate. Its high mortality is largely attributed to challenges in early detection. Extracellular vesicles (EVs) are naturally occurring nanoparticles secreted by nearly all cell types and carry a diverse array of bioactive molecules, including proteins, nucleic acids (particularly non-coding RNAs), and lipids. EVs play pivotal roles in remodeling the tumor microenvironment and driving cancer progression through intercellular communication. Accumulating evidence has established that EVs are critically involved in the pathogenesis of HCC and are emerging as promising biomarkers for its early detection. With advances in EV isolation technologies, these vesicles have garnered considerable attention in the field of liquid biopsy for HCC. This review provides a comprehensive overview of the diagnostic potential of EV-derived biomarkers in HCC, including DNA, RNA, proteins, and lipids. Additionally, it discusses the advantages of integrating multi-omics approaches for HCC diagnosis. Furthermore, the review highlights the technical challenges in EV isolation and characterization, as well as the crucial role of reference genes in the standardization of EV data. These insights underscore the potential of EVs as novel, minimally invasive liquid biopsy biomarkers for the early diagnosis of HCC.

PMID:42181837 | PMC:PMC13195390 | DOI:10.14218/JCTH.2025.00589

J Thorac Dis. 2026 Apr 30;18(4):417. doi: 10.21037/jtd-2025-1-2697. Epub 2026 Mar 26.

ABSTRACT

BACKGROUND AND OBJECTIVE: Lung cancer remains the leading cause of cancer related mortality worldwide, and early detection and precise stratified management are crucial for improving patient outcomes. Tumor growth kinetics, as a characterization of its proliferation and malignant differentiation, is a key decision-making factor and research hotspot in clinical practice today. This study aimed to elucidate the growth kinetics of solid nodular non-small cell lung cancer (NSCLC) as a critical determinant of early diagnosis, prognostic evaluation, and treatment strategy selection, and to address the challenge that significant heterogeneity in tumor growth poses to risk stratification and clinical decision-making.

METHODS: We conducted a retrospective search of PubMed, Embase, Web of Science, and Scopus databases, focusing on the current research status of solid nodular NSCLC, particularly in terms of molecular mechanisms, prognosis, modeling prediction, and management strategies related to its growth heterogeneity, with the aim of exploring future research directions.

KEY CONTENT AND FINDINGS: Volume doubling time (VDT) serves as a key metric for evaluating nodule dynamics. While earlier studies suggested a generally rapid growth pattern (VDT <400 days) in solid nodular NSCLC, recent evidence reveals considerable heterogeneity, with some tumors demonstrating indolent growth pattern (VDT >40-600 days). The prognosis of rapidly growing nodules is usually poor, so nodule management recommendations should be personalized based on growth dynamics and patient characteristics. Traditional radiological features, and deep learning models show promise for growth risk stratification but require large-scale external validation and refinement. Molecular and pathological studies suggest that the tumor microenvironment and immune cell infiltration may contribute to growth heterogeneity, though direct mechanistic evidence remains limited. Artificial intelligence (AI) based approaches exhibit significant potential in predicting individual tumor growth behavior.

CONCLUSIONS: Growth heterogeneity in solid nodular NSCLC carries substantial clinical significance but remains insufficiently studied. Future research should prioritize imaging based modeling to predict individualized growth dynamics. Integrating multi-omics analyses may help elucidate the molecular factors underlying growth heterogeneity. AI driven risk stratification based on large-scale multi center sequence data can achieve truly personalized and growth oriented management strategies.

PMID:42182806 | PMC:PMC13190150 | DOI:10.21037/jtd-2025-1-2697

Transl Cancer Res. 2026 Apr 30;15(4):314. doi: 10.21037/tcr-2025-aw-2503. Epub 2026 Mar 20.

ABSTRACT

BACKGROUND: Lung adenocarcinoma (LUAD) is one of the most common lung cancer subtypes worldwide, and its aggressive subtype invasive adenocarcinoma (IAC) has low survival rates. The precise identification of IAC is vital for the clinical diagnosis and treatment. The purpose of this study is to identify novel biomarkers for LUAD using single-cell and bulk RNA sequencing, so as to provide theoretical basis and practical support for the diagnosis, treatment and prognosis evaluation of lung invasive adenocarcinoma.

METHODS: We employed a combination of transcriptomic analysis and single-cell analysis to investigate the molecular characteristics and immune microenvironment of four subtypes of LUAD, including atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA), and IAC, with the aim of screening for biomarkers to differentiate pre-invasive lesions from invasive lesions.

RESULTS: Transcriptomic and single-cell analyses revealed that IAC subtypes demonstrated the most substantial molecular differences, particularly in immune cell infiltration and immune-related gene expression. Three genes-CD27, TIGIT, and TNFRSF18-that were significantly upregulated in IAC, predominantly expressed in immune cells and closely linked to immune regulatory pathways. We further analyzed T cell subpopulations in the IAC subtype and explored the expression of transcription factors (TFs) corresponding to these three genes, revealing their critical roles in immune cell function. Additionally, communication between T cells and other cells showed significantly enhanced signaling pathways, particularly those related to immune co-stimulatory molecules and inflammation pathways. Immunohistochemical validation of clinical samples showed that these three genes have high diagnostic value in IAC subtypes. These findings establish a crucial biological foundation for diagnosis, classification, and immunotherapy of LUAD, which contributes to the development of individualized treatment strategies.

CONCLUSIONS: This study identifies a three-gene signature (CD27, TIGIT, and TNFRSF18) that not only distinguishes invasive from pre-invasive LUAD with high precision by capturing the immune checkpoint disequilibrium characteristic of IAC, but also provides a clinically actionable biomarker panel for preoperative diagnosis and personalized immunotherapy strategies.

PMID:42180871 | PMC:PMC13190665 | DOI:10.21037/tcr-2025-aw-2503

J Transl Med. 2026 May 25. doi: 10.1186/s12967-026-08301-z. Online ahead of print.

ABSTRACT

BACKGROUND: Hepatocellular carcinoma (HCC) remains a major global health burden and a leading cause of cancer-related mortality. Advanced disease is characterized by a profoundly immunosuppressive tumor microenvironment (TME) and limited durable responses to therapy. However, the upstream genetic determinants that drive tumor-associated macrophage (TAM) dysfunction in HCC remain poorly defined. Using an integrative genetic and multi-omics framework, we investigated complement receptor 1 (CR1) as a candidate regulator of this immunosuppressive niche.

METHODS: We combined Mendelian randomization (MR) and metabolite mediation analyses with bulk, single-cell, and spatial transcriptomics to define the role of CR1 in HCC. Public datasets included the TCGA-HCC cohort, a single-cell RNA-sequencing dataset comprising 53,474 high-quality cells from 21 samples, and two spatially profiled HCC sections. Clinical validation was performed in 30 paired HCC and adjacent liver tissues. Functional assays were conducted in THP-1-derived macrophages using CR1 gain- and loss-of-function approaches, phagocytosis assays, and macrophage-CD8⁺ T-cell co-culture experiments.

RESULTS: MR analyses implicated CR1 in HCC susceptibility at both the protein and transcript levels. pQTL analysis linked genetically predicted circulating CR1 levels to HCC risk (IVW OR = 1.403, p = 0.017), and mediation analysis identified specific metabolites as candidate intermediates. Integrative multi-omics analyses showed that CR1 was preferentially enriched in TAMs, spatially co-localized with the M2 marker CD206, and associated with reduced CD8⁺ T-cell infiltration, enhanced T-cell exhaustion signatures, advanced clinicopathological features, and poorer survival. In 30 paired clinical samples, CR1-high tumors exhibited increased M2-like macrophage accumulation and reduced CD8⁺ T-cell infiltration. Functionally, CR1 overexpression drove macrophages toward an M2-like phenotype, enhanced phagocytic activity, increased PD-L1 expression, and suppressed CD8⁺ T-cell proliferation as well as IFN-gamma and granzyme B production, whereas CR1 knockdown produced the opposite phenotype.

CONCLUSIONS: Our study provides the first integrated genetic, spatial, and functional evidence that CR1⁺ TAMs constitute a clinically relevant immunoregulatory axis in HCC. These findings extend current understanding of complement-associated immunosuppression beyond canonical complement cascade activity and support CR1 as a candidate biomarker and therapeutic target for macrophage reprogramming, with potential translational relevance for combination strategies involving immune checkpoint blockade.

PMID:42185899 | DOI:10.1186/s12967-026-08301-z

Ecotoxicol Environ Saf. 2026 May 25;319:120306. doi: 10.1016/j.ecoenv.2026.120306. Online ahead of print.

ABSTRACT

The respiratory toxicity of heated tobacco products (HTPs) remains incompletely characterized, and traditional models often fail to capture human-specific responses. Here, we established a human pluripotent stem cell (hPSC)-derived airway organoid (AO) platform and systematically compared the toxicological profiles of two HTP aerosols using an integrated framework encompassing conventional cytotoxicity assays, lineage-specific analysis, network perturbation modeling and multi-omics profiling. Both HTPs induced time- and concentration-dependent cytotoxicity, oxidative stress, DNA damage, and apoptosis in AOs. Exposure also triggered epithelial chemokine response characterized by elevated IL-8, MCP-1, MIP-1β, GM-CSF, and RANTES, with concomitant suppression of IP-10, indicating epithelial-derived inflammatory alarm signals. Lineage-specific transcriptional changes revealed mucociliary dysfunction characterized by goblet cell hyperplasia (MUC5AC upregulation) and ciliated cell impairment (FOXJ1 downregulation), key features of airway remodeling in chronic respiratory diseases. To delineate underlying mechanisms, we employed Network Perturbation Amplitude (NPA) analysis, which uncovered qualitatively distinct toxicity architectures: HTP-1 exhibited higher overall toxicity and elicited broad-spectrum network perturbations involving cell stress, proliferation, and immune regulation, correlating with greater apoptotic induction; HTP-2 triggered focused activation of damage-sensing pathways, consistent with its earlier membrane disruption and more pronounced genotoxicity. Multi-omics analysis further linked these mechanistic perturbations to human disease-relevant pathways, with HTP-1 showing stronger enrichment for COPD-associated expression patterns and HTP-2 for lung cancer-related signatures, suggesting the acute molecular response to each product exhibits similarity to specific pulmonary disease-associated molecular signatures. These findings establish human-derived airway organoids as a sensitive, human-relevant platform within the New Approach Methodologies‌ (NAMs) framework for qualitative comparison and mechanistic interrogation of product-specific toxicity.

PMID:42184653 | DOI:10.1016/j.ecoenv.2026.120306