Diagnostics (Basel). 2026 Feb 24;16(5):645. doi: 10.3390/diagnostics16050645.

ABSTRACT

Background/Objectives: Colorectal cancer (CRC) liver metastases present a significant clinical challenge due to high recurrence risks post-resection. Traditional diagnostics often fail to detect early-stage minimal residual disease (MRD). This preliminary pilot study evaluated ctDNA dynamics in 10 patients with liver metastases using a personalized multistep approach. Methods: Following primary tumor Next-Generation Sequencing (NGS) to identify somatic mutations in KRAS, NRAS, TP53, RET, APC, and WRN, custom TaqMan assays were designed for longitudinal plasma analysis. Four methodologies were compared: HRM-PCR, PNA-enhanced qPCR, and two digital platforms (dPCR and ddPCR). Results: While HRM-PCR sensitivity was limited in plasma, digital platforms demonstrated 100% qualitative concordance. MRD-negative status (VAF 0.00%) was identified in 70% of cases (P01, P03, P06, P07, P08, P09, P10), while detectable ctDNA in patients P02, P04, and P05 strongly correlated with aggressive progression. Digital PCR enabled the ultra-low detection of Variant Allele Frequencies (VAFs), identifying high molecular burdens (e.g., P05, VAF 49%) correlating with rapid decline, and capturing early molecular residue in P04 (VAF 0.62%). Conclusions: Our preliminary findings confirm that personalized longitudinal VAF tracking via digital PCR provides superior prognostic value, serving as a robust tool for recurrence monitoring in personalized CRC therapy.

PMID:41827921 | PMC:PMC12984390 | DOI:10.3390/diagnostics16050645

Cancers (Basel). 2026 Feb 28;18(5):800. doi: 10.3390/cancers18050800.

ABSTRACT

BACKGROUND AND OBJECTIVE: Liquid biopsy has transformed the management of advanced prostate cancer, yet its clinical role in non-metastatic disease remains uncertain. Conventional biomarkers such as PSA, imaging, and pathology have limited ability to capture minimal residual disease and biological aggressiveness. The objective of this review was to critically evaluate the current evidence on circulating tumor cells (CTCs) and circulating tumor DNA (ctDNA) in non-metastatic prostate cancer, focusing on feasibility, prognostic value, and potential clinical applications.

METHODS: A narrative review of PubMed-indexed original studies evaluating liquid biopsy in clinically localized or non-metastatic prostate cancer was performed. Eligible studies included patients treated with curative-intent local therapy or experiencing biochemical recurrence without radiologic metastases. Study designs were predominantly prospective or retrospective observational cohorts. Liquid biopsy analytes included CTCs and ctDNA assessed from peripheral blood plasma using EpCAM-based enrichment, targeted next-generation sequencing, whole-genome sequencing, or ultra-sensitive tumor-informed assays. Primary outcomes included detection rates, associations with clinicopathologic features, biochemical recurrence, metastasis-free survival, and overall survival. Key Findings and Limitations: Across 11 studies, CTC detection using EpCAM-based platforms was infrequent in localized disease and biochemical recurrence and showed limited prognostic value (10-11% in preoperative settings). In contrast, ctDNA was detectable in a minority of patients but consistently identified biologically aggressive disease and a higher risk of recurrence when present, particularly using tumor-informed ultra-sensitive assays. Limitations include low detection rates, heterogeneous methodologies, small sample sizes, and predominantly exploratory study designs.

CONCLUSIONS AND CLINICAL IMPLICATIONS: Currently, its most promising application is not broad screening, but as a selective, biology-driven tool for detecting minimal residual disease and refining risk assessment. CtDNA acts as a biological risk modifier, potentially guiding the escalation or de-escalation of adjuvant therapy. However, prospective biomarker-driven trials are required to validate these strategies before routine clinical implementation.

PMID:41827734 | PMC:PMC12984391 | DOI:10.3390/cancers18050800

Animals (Basel). 2026 Mar 6;16(5):825. doi: 10.3390/ani16050825.

ABSTRACT

BACKGROUND: Respiratory bacterial infections represent a major health challenge in swine production, highlighting the need for novel immunomodulatory strategies that enhance host resistance. In this study, we investigated whether porcine intestinal lactobacilli could modulate the gut-lung axis and improve respiratory innate immunity in a mouse model of Streptococcus pneumoniae infection, as a surrogate of Streptococcus suis pneumonia.

METHODS: Three strains of Ligilactobacillus salivarius (LAFF998, LAFF1071, and LAFF1095) were orally administered to Swiss mice prior to pneumococcal challenge. The resistance to the infection, the lung damage and the respiratory innate immune response were evaluated.

RESULTS: Only strain LAFF998 significantly reduced pulmonary bacterial loads, prevented bacteremia, and attenuated lung injury. This protective effect was associated with selective modulation of respiratory immunity, characterized by reduced neutrophilic inflammation, increased lymphocyte recruitment, and enhanced activation of alveolar macrophages expressing MHC-II. LAFF998 markedly increased the production of IFN-β, IFN-γ, IL-6, IL-10, and IL-27 in the respiratory tract, without inducing excessive inflammatory damage. Ex vivo and in vitro analyses confirmed that alveolar macrophages from LAFF998-treated mice exhibited a primed phenotype with heightened cytokine responses to pneumococcal stimulation. In contrast, strains LAFF1071 and LAFF1095 failed to confer protection or significantly modulate respiratory immune responses.

CONCLUSIONS: These findings demonstrate a strict strain-dependent effect among porcine L. salivarius isolates and identify LAFF998 as a potent immunobiotic capable of enhancing respiratory innate immunity through the gut-lung axis. This work supports further studies of LAFF998 as an immunobiotic strategy for the prevention of respiratory infections in pigs.

PMID:41829035 | PMC:PMC12985233 | DOI:10.3390/ani16050825

Int J Mol Sci. 2026 Feb 28;27(5):2271. doi: 10.3390/ijms27052271.

ABSTRACT

Chronic obstructive pulmonary disease (COPD) is a leading cause of mortality worldwide, yet only a fraction of smokers develops the disease, suggesting protective mechanisms in resilient individuals. Identifying airway-localized molecular signatures may improve our understanding of disease pathomechanisms and support hypothesis generation for biomarker research. In this pilot study, induced sputum from smokers with COPD (n = 28) and smokers without COPD (n = 16; Global Initiative for Chronic Obstructive Lung Disease (GOLD)-defined pre-COPD) was analyzed by untargeted proteomics, metabolomics, and lipidomics. After quality control, 1180 proteins, 187 metabolites, and 1234 lipids were retained. Analyses included univariate models with false discovery rate adjustment and multivariate analyses (PCA, PLS-DA), followed by pathway enrichment and protein interaction network analysis. While few features remained significant after FDR correction, consistent cross-omics patterns were observed. COPD was characterized by ↑ glutathione, creatine, and L-arginine; ↓ CCDC88A and ↑ STAT3 and SYDE2; and broad lipid remodeling involving phosphatidylcholines, sphingolipids, and eicosanoids. Network analysis highlighted STAT3 as a highly connected node linking COPD-related genes. These findings suggest that the multi-omic profiling of induced sputum can capture coherent airway-localized molecular signatures such as oxidative stress, cytoskeletal remodeling, and Rho-family GTPase signaling. However, the results should be interpreted as exploratory and require validation in functional studies.

PMID:41828494 | PMC:PMC12984585 | DOI:10.3390/ijms27052271

Int J Mol Sci. 2026 Feb 25;27(5):2137. doi: 10.3390/ijms27052137.

ABSTRACT

Protein Kinase N1 (PKN1) is a PKC-related serine/threonine kinase of the AGC group within the eukaryotic protein kinase superfamily (ePK) that orchestrates oncogenic, metabolic, and cytoskeletal signaling. Despite these critical roles, the phosphorylation-dependent regulatory network of PKN1 remains largely undefined. We performed a large-scale phosphoproteomic data integration of publicly available human datasets (892 profiling datasets and 191 differential datasets) to identify recurrent PKN1 phosphorylation sites. This analysis identified two predominant PKN1 phosphosites, S562 and S916, that were frequently observed and differentially regulated across studies. The S916 maps to a turn motif (TM) in the AGC group of kinases, which is evolutionarily conserved among PKN paralogs, while S562 is non-conserved and appears to be PKN1-specific. Co-regulation and enrichment analyses suggest that S916 is associated with insulin/AMPK signaling and metabolic pathways, whereas S562 co-occurs with phosphosites involved in cell division, cytoskeletal regulation, and microtubule cytoskeleton organization. Integrating predicted and experimentally validated kinases, substrates, and interactors, we reconstructed a phospho-regulatory network that positions PKN1 at the crossroads of cytoskeleton organization and metabolic signaling. To assess the disease relevance of these phosphorylation events, we integrated transcriptomic and phosphoproteomic data from the hepatocellular carcinoma database (HCCDB). PKN1 was markedly up-regulated in HCC, and its phosphorylation at S916 was positively co-regulated with multiple oncogenic and proliferation-associated protein phosphosites. These results predict S562 and S916 as potential sites for targeted biochemical validation and functional experiments. The identification of S562 and S916 as key regulatory sites provides new mechanistic insight into PKN1 activation and highlights potential avenues for therapeutic targeting.

PMID:41828364 | PMC:PMC12984926 | DOI:10.3390/ijms27052137

Cancers (Basel). 2026 Mar 9;18(5):878. doi: 10.3390/cancers18050878.

ABSTRACT

BACKGROUND: Lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC), the major subtypes of non-small cell lung cancer (NSCLC), exhibit distinct molecular landscapes that demand precision in prognosis and therapy. While deep learning models can achieve high predictive accuracy, their black-box nature limits clinical translation.

METHODS: We introduce AttentioFuse, an interpretable deep learning framework employing a Reactome-guided mid-fusion strategy for multi-omics integration. AttentioFuse builds on three pillars: (i) dual-phase learning with omics-specific encoders to preserve modality-unique patterns, (ii) hierarchical attention mechanisms (cross-omics, feature-level, and fusion-layer) to quantify layer contributions dynamically, and (iii) integrated explainability combining DeepSHAP and global attention weights for gene-to-pathway interpretation. Two depth variants are instantiated under identical priors: a three-layer configuration (3F) for main discrimination and a five-layer configuration (AttentioFuse-5X) for deeper hierarchical interpretation; the 5X variant is trained end-to-end and yields comparable accuracy while enhancing pathway-level resolution.

RESULTS: Evaluated on The Cancer Genome Atlas (TCGA) LUAD/LUSC cohorts, AttentioFuse matches state-of-the-art performance in TNM staging while uncovering actionable biological insights, including pan-NSCLC AKT/mTOR metabolic control, histology-divergent Notch signaling roles, and additional pathways related to developmental reactivation, microbiota-associated metastasis, and extracellular matrix remodeling.

CONCLUSIONS: By design, AttentioFuse-5X bridges predictive performance with hierarchical, pathway-resolved explanations, advancing oncology by transforming black-box predictions into biologically grounded decision support.

PMID:41827812 | PMC:PMC12985206 | DOI:10.3390/cancers18050878

Int J Mol Sci. 2026 Feb 28;27(5):2271. doi: 10.3390/ijms27052271.

ABSTRACT

Chronic obstructive pulmonary disease (COPD) is a leading cause of mortality worldwide, yet only a fraction of smokers develops the disease, suggesting protective mechanisms in resilient individuals. Identifying airway-localized molecular signatures may improve our understanding of disease pathomechanisms and support hypothesis generation for biomarker research. In this pilot study, induced sputum from smokers with COPD (n = 28) and smokers without COPD (n = 16; Global Initiative for Chronic Obstructive Lung Disease (GOLD)-defined pre-COPD) was analyzed by untargeted proteomics, metabolomics, and lipidomics. After quality control, 1180 proteins, 187 metabolites, and 1234 lipids were retained. Analyses included univariate models with false discovery rate adjustment and multivariate analyses (PCA, PLS-DA), followed by pathway enrichment and protein interaction network analysis. While few features remained significant after FDR correction, consistent cross-omics patterns were observed. COPD was characterized by ↑ glutathione, creatine, and L-arginine; ↓ CCDC88A and ↑ STAT3 and SYDE2; and broad lipid remodeling involving phosphatidylcholines, sphingolipids, and eicosanoids. Network analysis highlighted STAT3 as a highly connected node linking COPD-related genes. These findings suggest that the multi-omic profiling of induced sputum can capture coherent airway-localized molecular signatures such as oxidative stress, cytoskeletal remodeling, and Rho-family GTPase signaling. However, the results should be interpreted as exploratory and require validation in functional studies.

PMID:41828494 | PMC:PMC12984585 | DOI:10.3390/ijms27052271

Cancers (Basel). 2026 Mar 9;18(5):878. doi: 10.3390/cancers18050878.

ABSTRACT

BACKGROUND: Lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC), the major subtypes of non-small cell lung cancer (NSCLC), exhibit distinct molecular landscapes that demand precision in prognosis and therapy. While deep learning models can achieve high predictive accuracy, their black-box nature limits clinical translation.

METHODS: We introduce AttentioFuse, an interpretable deep learning framework employing a Reactome-guided mid-fusion strategy for multi-omics integration. AttentioFuse builds on three pillars: (i) dual-phase learning with omics-specific encoders to preserve modality-unique patterns, (ii) hierarchical attention mechanisms (cross-omics, feature-level, and fusion-layer) to quantify layer contributions dynamically, and (iii) integrated explainability combining DeepSHAP and global attention weights for gene-to-pathway interpretation. Two depth variants are instantiated under identical priors: a three-layer configuration (3F) for main discrimination and a five-layer configuration (AttentioFuse-5X) for deeper hierarchical interpretation; the 5X variant is trained end-to-end and yields comparable accuracy while enhancing pathway-level resolution.

RESULTS: Evaluated on The Cancer Genome Atlas (TCGA) LUAD/LUSC cohorts, AttentioFuse matches state-of-the-art performance in TNM staging while uncovering actionable biological insights, including pan-NSCLC AKT/mTOR metabolic control, histology-divergent Notch signaling roles, and additional pathways related to developmental reactivation, microbiota-associated metastasis, and extracellular matrix remodeling.

CONCLUSIONS: By design, AttentioFuse-5X bridges predictive performance with hierarchical, pathway-resolved explanations, advancing oncology by transforming black-box predictions into biologically grounded decision support.

PMID:41827812 | PMC:PMC12985206 | DOI:10.3390/cancers18050878

Crit Care Explor. 2026 Mar 12;8(3):e1390. doi: 10.1097/CCE.0000000000001390. eCollection 2026 Mar 1.

ABSTRACT

IMPORTANCE: Inflammation, endothelial dysfunction, and complement activation are associated with COVID-19 acute lung injury (ALI) and acute respiratory distress syndrome (ARDS).

OBJECTIVES: We hypothesized that higher levels of inflammation, endothelial dysfunction, and complement activation implicated in more severe COVID-19 ALI/ARDS are associated with post-acute sequelae of COVID-19 (PASC) phenotypes in the 3 years after hospitalization.

DESIGN, SETTING, AND PARTICIPANTS: A single-center prospective cohort of 150 adult survivors of severe and critical COVID-19 from the first wave of the pandemic with sampling weighted to include 50% survivors of mechanical ventilation.

MAIN OUTCOMES AND MEASURES: Eleven serum biomarkers at hospital discharge, 4 months, 15 months, and 3 years, and symptoms and physical function at 15 months and 3 years. PASC presence was defined using the 12 symptoms and scoring from the Researching COVID to Enhance Recovery (RECOVER) definition. We tested associations of biomarkers with PASC and symptom phenotypes of post-exertional malaise, fatigue, and brain fog while adjusting for age, sex, body mass index, comorbidities, and days since COVID-19 diagnosis.

RESULTS: The mean (sd) age of the cohort was 56 years (13); 67% were Hispanic and 25% were Black. PASC was present in 26% of participants at both 15 months and 3 years. PASC and symptom phenotypes at 15 months and 3 years were consistently associated with higher frailty phenotype category, worse short physical performance battery scores, and shorter 6-minute walk distance. Biomarkers of inflammation, including interleukin-6 and soluble tumor necrosis factor receptor-1, endothelial function, including angiopoietin, and complement, including C2, C4b, and C5, were not associated with PASC or symptom phenotypes in cross-sectional or longitudinal analyses.

CONCLUSIONS AND RELEVANCE: PASC persists for 3 years after acute COVID-19 ALI/ARDS, is associated with frailty, but not associated with persistently higher levels of inflammatory, endothelial, and complement biomarkers implicated in worse short-term outcomes in acute COVID-19, non-COVID-19 ARDS, and sepsis. Future studies should employ multiomics to elucidate potential mechanisms of PASC.

PMID:41824803 | DOI:10.1097/CCE.0000000000001390

Crit Care Explor. 2026 Mar 12;8(3):e1390. doi: 10.1097/CCE.0000000000001390. eCollection 2026 Mar 1.

ABSTRACT

IMPORTANCE: Inflammation, endothelial dysfunction, and complement activation are associated with COVID-19 acute lung injury (ALI) and acute respiratory distress syndrome (ARDS).

OBJECTIVES: We hypothesized that higher levels of inflammation, endothelial dysfunction, and complement activation implicated in more severe COVID-19 ALI/ARDS are associated with post-acute sequelae of COVID-19 (PASC) phenotypes in the 3 years after hospitalization.

DESIGN, SETTING, AND PARTICIPANTS: A single-center prospective cohort of 150 adult survivors of severe and critical COVID-19 from the first wave of the pandemic with sampling weighted to include 50% survivors of mechanical ventilation.

MAIN OUTCOMES AND MEASURES: Eleven serum biomarkers at hospital discharge, 4 months, 15 months, and 3 years, and symptoms and physical function at 15 months and 3 years. PASC presence was defined using the 12 symptoms and scoring from the Researching COVID to Enhance Recovery (RECOVER) definition. We tested associations of biomarkers with PASC and symptom phenotypes of post-exertional malaise, fatigue, and brain fog while adjusting for age, sex, body mass index, comorbidities, and days since COVID-19 diagnosis.

RESULTS: The mean (sd) age of the cohort was 56 years (13); 67% were Hispanic and 25% were Black. PASC was present in 26% of participants at both 15 months and 3 years. PASC and symptom phenotypes at 15 months and 3 years were consistently associated with higher frailty phenotype category, worse short physical performance battery scores, and shorter 6-minute walk distance. Biomarkers of inflammation, including interleukin-6 and soluble tumor necrosis factor receptor-1, endothelial function, including angiopoietin, and complement, including C2, C4b, and C5, were not associated with PASC or symptom phenotypes in cross-sectional or longitudinal analyses.

CONCLUSIONS AND RELEVANCE: PASC persists for 3 years after acute COVID-19 ALI/ARDS, is associated with frailty, but not associated with persistently higher levels of inflammatory, endothelial, and complement biomarkers implicated in worse short-term outcomes in acute COVID-19, non-COVID-19 ARDS, and sepsis. Future studies should employ multiomics to elucidate potential mechanisms of PASC.

PMID:41824803 | PMC:PMC12987405 | DOI:10.1097/CCE.0000000000001390

Front Oncol. 2026 Feb 25;16:1743620. doi: 10.3389/fonc.2026.1743620. eCollection 2026.

ABSTRACT

Lung cancer remains the leading cause of cancer-related mortality, yet current precision oncology approaches remain overwhelmingly tumor-centric, guided by genomic alterations and immune biomarkers, while largely neglecting the profound impact of aging biology on treatment response. While emerging evidence suggests that aging biology can modify therapeutic benefit and toxicity, its clinical integration remains uneven and largely investigational. In this review, we explicitly distinguish the chronological aging from biological aging to clarify how host biology modifies therapeutic benefit and toxicity. We synthesize mechanistic, translational, and early clinical evidence, while explicitly noting areas where prospective validation is lacking, to reframe personalization of lung cancer therapy through an age-conscious lens. We summarize data indicating that immunosenescence is associated with T-cell exhaustion, myeloid dominance, and extracellular matrix stiffening, features that may contribute to immune-evasive tumor phenotypes and attenuated responses to immune checkpoint blockade in subsets of patients, while pediatric cases, though rare, illustrate how global precision initiatives like iTHER and ZERO enable cautious adaptation of adult therapies. Moving beyond chronological age, we discuss biological age biomarkers, including PhenoAgeAccel, epigenetic clocks, telomere length, and frailty indices, which outperform traditional metrics in predicting risk, resistance, and toxicity, and propose integrating these tools into trial design, screening, and care planning which show promise for risk stratification and toxicity prediction but are not yet validated for routine treatment selection. Looking forward, we outline investigational strategies at the intersection of geroscience and oncology, including immune engineering, senolytics, microenvironmental modulation, and AI-driven multi-omic modeling. Overall, this review argues that biological age represents a critical but still underdeveloped dimension of precision oncology, and highlights key evidence gaps that must be addressed before age-aware personalization can be implemented in routine lung cancer care.

PMID:41821888 | PMC:PMC12975599 | DOI:10.3389/fonc.2026.1743620

Nat Commun. 2026 Mar 12. doi: 10.1038/s41467-026-70376-5. Online ahead of print.

ABSTRACT

Myasthenia gravis (MG) is an autoimmune disorder characterized by impaired neuromuscular transmission and motor symptoms. Its genetic background remains unclear, particularly beyond specific subtypes reported in European populations. Here, we perform a genome-wide association study (GWAS) of 1,434 MG cases covering all disease subtypes and 42,913 controls of Japanese, which newly identify the TERT locus (odds ratio [OR] = 1.31, P = 1.7×10^-10). Subtype-stratified GWASs show stronger signals for generalized MG (gMG; OR = 1.38, P = 1.6×10^-12), anti AChR antibody-positive gMG (g-AChR-Ab(+)MG; OR= 1.49, P = 2.1×10^-15), and thymoma-associated gMG (g-TAMG; OR = 1.92, P = 1.1×10^-15). Fine-mapping of the major histocompatibility complex region reveal distinct associations of HLA-DRB1 with late onset gMG (g-LOMG) and HLA-A with early onset gMG (g-EOMG). The MG risk TERT lead variant rs2736099 is associated with poor treatment response, especially in g-AChR-Ab(+)MG and g-EOMG (P < 0.0042). The biobank-based phenome-wide association study identify pleiotropic effects on lung cancer, hematological traits, and telomere length. Single cell transcriptomics and immunohistochemistry identified immature lymphocyte-specific TERT expression in thymoma specimens. Full-length transcriptomics reveal allele-specific decreasing effect of rs2736099-A on TERT expression. Our study unveils genetics of MG distinctly across disease subtypes, and involvement of TERT in its pathogenesis.

PMID:41820352 | DOI:10.1038/s41467-026-70376-5

Transl Cancer Res. 2026 Feb 28;15(2):77. doi: 10.21037/tcr-2025-aw-2179. Epub 2026 Feb 11.

ABSTRACT

BACKGROUND: Hepatocellular carcinoma (HCC) exhibits notable characteristics, encompassing frequent recurrence, weak immunotherapeutic outcomes and unfavorable prognosis. BTF3L4 has been identified as a critical factor in the progression of various malignancies. However, its specific role in HCC remains to be elucidated. This investigation sought to examine BTF3L4 levels in HCC and BTF3L4's connection with clinical prognosis and immune infiltration.

METHODS: We performed an extensive multi-omics evaluation in the course of our research. Bioinformatics tools were utilized to assess BTF3L4 messenger RNA (mRNA) expression in HCC. Multiplex immunohistochemistry (mIHC) was utilized to examine BTF3L4 protein expression and to explore its correlation with tumor-infiltrating immune cells (TIICs). Cox regression analysis and Kaplan-Meier survival curves were applied to determine BTF3L4's impact on patient outcomes.

RESULTS: Our analysis revealed markedly elevated levels of both BTF3L4 mRNA and protein in HCC tissues. BTF3L4 protein abundance emerged as an independent predictor of reduced survival in patients with HCC. Furthermore, elevated BTF3L4 protein expression was positively associated with cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) expression and markedly negatively correlated with CD4⁺ T cells and CD66b⁺ neutrophils in HCC tissues.

CONCLUSIONS: This evidence indicates that BTF3L4 functions as a predictive indicator and is a potential candidate for HCC immunotherapy.

PMID:41815168 | PMC:PMC12971597 | DOI:10.21037/tcr-2025-aw-2179

NPJ Precis Oncol. 2026 Mar 11. doi: 10.1038/s41698-026-01372-7. Online ahead of print.

ABSTRACT

Hepatocellular carcinoma (HCC) is one of the most lethal malignancies worldwide, and its progression is closely linked to the establishment of an immunosuppressive tumor microenvironment. Myristoylated alanine-rich C kinase substrate (MARCKS) has been implicated in tumor biology; however, its role in regulating immune interactions in HCC remains poorly defined. Here, we performed an integrated multi-omics analysis combining bulk transcriptomics, single-cell RNA sequencing, and spatial transcriptomics to systematically investigate the expression pattern and functional relevance of MARCKS in HCC. We found that MARCKS was significantly upregulated in HCC tissues and that high MARCKS expression was associated with aggressive clinicopathological features and unfavorable prognosis. Single-cell and spatial analyses revealed that MARCKS expression was enriched in myeloid cell populations within the tumor microenvironment. Functional annotation and mIF(Multiple immunofluorescence) validation demonstrated that MARCKS expression was associated with enhanced JAK/STAT3 signaling and M2-like macrophage polarization. Consistently, MARCKS silencing in HCC cell lines reduced STAT3 phosphorylation, suppressed malignant phenotypes in vitro, inhibited tumor growth in vivo, and diminished the capacity of tumor-derived conditioned media to promote macrophage M2 polarization. Together, these findings identify MARCKS as a key regulator of the immunosuppressive tumor microenvironment in HCC and highlight its potential as a therapeutic target for overcoming immune evasion.

PMID:41813922 | DOI:10.1038/s41698-026-01372-7