Front Immunol. 2026 Aug 25;17:1902981. doi: 10.3389/fimmu.2026.1902981. eCollection 2026.

ABSTRACT

BACKGROUND: Coronaviruses (CoVs), including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and Middle East respiratory syndrome (MERS-CoV), cause respiratory infections with distinct clinical outcomes and case fatality rates. However, the molecular basis of these differences remains unclear. In this study, we sought to define virus-specific host metabolic programs by directly comparing multiomics profiles of the lungs of lethally infected mouse models.

METHODS: We performed integrated multiomics analyses, including untargeted metabolomics, transcriptomics, and targeted lipidomics, of lung tissues from human angiotensin-converting enzyme 2 (hiACE2)-human dipeptidyl peptidase 4 (hDPP4) double-knock-in (DKI) mice infected in SARS-CoV-2 or MERS-CoV. Data Integration Analysis and Biomarker discovery using Latent cOmponents (DIABLO) was applied across all three omics layers to identify key distinguishing molecular patterns. Additionally, in vitro lipid droplet kinetics were examined in infected Vero E6 cells to validate temporal differences in lipid remodeling.

RESULTS: We identified two distinct strategies for lipid utilization. SARS-CoV-2 infection showed strong activation of energy and amino acid metabolism at an early stage of infection (3 days post infection, DPI), whereas MERS-CoV infection was characterized by sustained alterations in lipid and nucleotide metabolism. Integrative DIABLO analysis of all three omics layers revealed that the key distinguishing features clustered into virus-specific molecular signatures: a triacylglycerol-lipid droplet-interferon axis for SARS-CoV-2 and a phospholipid-sphingolipid-membrane hub for MERS-CoV. In vitro lipid droplet kinetics in infected Vero E6 cells confirmed this temporal difference, with SARS-CoV-2 peaking earlier than MERS-CoV.

CONCLUSION: These findings show that β-CoVs exploit host lipid metabolism through virus-specific and time-dependent remodeling programs, providing a framework for understanding differential pathogenesis and developing host-directed antiviral strategies.

PMID:42712680 | PMC:PMC13550176 | DOI:10.3389/fimmu.2026.1902981

Front Immunol. 2026 Aug 25;17:1902981. doi: 10.3389/fimmu.2026.1902981. eCollection 2026.

ABSTRACT

BACKGROUND: Coronaviruses (CoVs), including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and Middle East respiratory syndrome (MERS-CoV), cause respiratory infections with distinct clinical outcomes and case fatality rates. However, the molecular basis of these differences remains unclear. In this study, we sought to define virus-specific host metabolic programs by directly comparing multiomics profiles of the lungs of lethally infected mouse models.

METHODS: We performed integrated multiomics analyses, including untargeted metabolomics, transcriptomics, and targeted lipidomics, of lung tissues from human angiotensin-converting enzyme 2 (hiACE2)-human dipeptidyl peptidase 4 (hDPP4) double-knock-in (DKI) mice infected in SARS-CoV-2 or MERS-CoV. Data Integration Analysis and Biomarker discovery using Latent cOmponents (DIABLO) was applied across all three omics layers to identify key distinguishing molecular patterns. Additionally, in vitro lipid droplet kinetics were examined in infected Vero E6 cells to validate temporal differences in lipid remodeling.

RESULTS: We identified two distinct strategies for lipid utilization. SARS-CoV-2 infection showed strong activation of energy and amino acid metabolism at an early stage of infection (3 days post infection, DPI), whereas MERS-CoV infection was characterized by sustained alterations in lipid and nucleotide metabolism. Integrative DIABLO analysis of all three omics layers revealed that the key distinguishing features clustered into virus-specific molecular signatures: a triacylglycerol-lipid droplet-interferon axis for SARS-CoV-2 and a phospholipid-sphingolipid-membrane hub for MERS-CoV. In vitro lipid droplet kinetics in infected Vero E6 cells confirmed this temporal difference, with SARS-CoV-2 peaking earlier than MERS-CoV.

CONCLUSION: These findings show that β-CoVs exploit host lipid metabolism through virus-specific and time-dependent remodeling programs, providing a framework for understanding differential pathogenesis and developing host-directed antiviral strategies.

PMID:42712680 | PMC:PMC13550176 | DOI:10.3389/fimmu.2026.1902981

EPMA J. 2026 Aug 21;17(3):665-700. doi: 10.1007/s13167-026-00465-4. eCollection 2026 Sep.

ABSTRACT

Chronic atrophic gastritis (CAG) is a critical precancerous stage in the development of gastric cancer (GC). Circadian rhythm disruption perturbs the core clock gene network, including circadian locomotor output cycles kaput (CLOCK), brain and muscle ARNT-like 1 (BMAL1), period circadian protein homolog (PER), and cryptochrome (CRY). These alterations contribute to a multi-layered pathological cascade involving DNA damage accumulation, epigenetic remodeling, altered epithelial cell plasticity, cellular senescence, microbiota dysbiosis, tumor microenvironment remodeling, metabolic reprogramming, aberrant angiogenesis, and dysregulated cell death, thereby accelerating CAG to GC progression. However, existing studies have predominantly treated the circadian rhythm as a passive risk factor for disease onset and have yet to elevate it to an actionable interventional target within the full-course management of gastric precancerous lesions. Building on a systematic synthesis of the mechanistic evidence outlined above, this review proposes a predictive, preventive and personalised medicine (PPPM/3PM) three-tier management framework grounded in circadian-based individualised protection. At the predictive level, digital biomarkers (sleep-wake rhythms, light exposure, physical activity, and dietary behavior), multi-omics profiles, and circadian-related molecular signatures are integrated to achieve dynamic risk stratification of CAG populations. At the targeted prevention level, pharmacological agents and natural compounds with circadian-regulating potential are deployed to develop proactive protective strategies tailored to distinct pathological stages and circadian phenotypes. At the personalised treatment level, lifestyle interventions, chronotherapy, nano-carrier-based circadian-synchronised delivery, and dynamic biomarker monitoring are combined to formulate precision intervention regimens informed by individual circadian phenotypes. This framework repositions the circadian rhythm from a latent risk factor to a protectable and therapeutically targetable axis, offering new insights into time-optimised intervention strategies for the inflammation to cancer transition in CAG.

PMID:42682657 | PMC:PMC13530114 | DOI:10.1007/s13167-026-00465-4

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

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

Cancer Discov. 2026 Apr 15. doi: 10.1158/2159-8290.CD-25-1663. Online ahead of print.

ABSTRACT

Brain metastases (BM) remain a devastating disease with dismal prognosis. How circulating tumor cells (CTCs) penetrate the blood brain barrier (BBB) and reprogram the brain microenvironment remain unclear. Using spatially resolved multi-omic profiling of CTCs and brain metastases, integrated with experimental and clinical analyses, we identified Glycoprotein Non-Metastatic Melanoma Protein B (GPNMB) as a CTC-secreted driver of vascular disruption and brain colonization. CBX3 upregulation induced GPNMB expression, which bound endothelial EGFR, triggering CBL-mediated ubiquitination and degradation. Attenuated EGFR signaling suppressed FTO and disrupted endothelial junctions via YTHDF2-dependent TJP1 m6A methylation. Remarkably, GPNMB-induced BBB remodeling promoted immune infiltration via CXCL12-CXCR4 axis, and induced time course-dependent T cell exhaustion within the brain microenvironment. Clinically, elevated CBX3⁺GPNMB⁺ CTCs and plasma CXCL12 were significantly associated with BM progression in lung cancer and melanoma. Therapeutically, dual blockade of GPNMB and PD1 enhanced anti-BM efficacy in mice, unveiling GPNMB as a promising target for precision immunotherapy.

PMID:41973996 | DOI:10.1158/2159-8290.CD-25-1663

J Pharm Biomed Anal. 2026 Mar 29;276:117486. doi: 10.1016/j.jpba.2026.117486. Online ahead of print.

ABSTRACT

Patients with polycystic ovary syndrome (PCOS) are at an elevated risk of depression, yet the underlying mechanisms remain elusive. Emerging evidence implicates the gut-brain axis and systemic lipid homeostasis alterations as potential key contributors. We profiled untargeted plasma lipidomes of PCOS patients with and without comorbid depression (PCOS-DP) and integrated these data with our prior gut microbial and host transcriptomic datasets to construct multi-omics interaction networks. The causal role of the candidate gut microbial was preliminary explored in a germ-free PCOS mouse model using fecal microbiota transplantation, followed by behavioral phenotyping and ELISA-based protein quantification. We identified a distinct plasma lipidomic signature differentiating PCOS-DP from PCOS alone, characterized primarily by the downregulation of 26 lipid species. Most of these altered lipids were triacylglycerols (TAGs) enriched with FA18:1 and FA18:2, whose levels correlated with coagulation dysfunction. Multi-omics network analysis revealed significant interconnections between depression-associated gut microbiota (including Bacteroides eggerthii), specific altered lipids such as TAG (60:12/FA22:6), and host genes involved in inflammation (e.g., IL22, NLRP7), metabolism, and neural processes. Animal validation demonstrated that B. eggerthii colonization in PCOS mice specifically exacerbated anhedonia and hyperlocomotion, alongside modulating plasma IL-22 expression, suggesting its context-dependent neurobehavioral effect role. This study delineates a TAG-downregulated lipid signature with diagnostic potential and reveals a novel "gut microbiota-lipid-host gene" interaction network underpinning PCOS-DP, with B. eggerthii as a key microbial modulator of neurobehavioral phenotypes in the context of PCOS. These findings provide new pathophysiological insights and highlights potential diagnostic biomarkers for PCOS-DP.

PMID:41924769 | DOI:10.1016/j.jpba.2026.117486