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PubMed2026

Multi-omics Approaches to CCAAT/Enhancer-Binding Protein Beta in Oral Squamous Cell Carcinoma: Crosstalk Between Tumor Cells and Tumor-Associated Macrophages Driving Disease Progression.

BACKGROUND: CCAAT/Enhancer-Binding Protein Beta (CEBPB) is an important transcription factor that regulates tumor progression. However, the mechanism by which CEBPB regulates the progression of Oral Squamous Cell Carcinoma (OSCC) remains incompletely understood. Tumor progression depends on complex intercellular interactions within the tumor microenvironment. The purpose of this study was to investigate the role and epigenetic regulatory mechanisms of CEBPB in interactions between OSCC cells and tumor-infiltrating immune cells. METHODS: Bulk RNA-seq, ChIP-seq, and scRNA-seq data were obtained from The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. The HOMER algorithm was employed to identify enhancers and predict the CEBPB-binding motif. Cell cluster analysis, functional enrichment, and intercellular interaction analysis were performed using the "Seurat" R package. H3K27ac enrichment at GAS6 enhancers was validated by ChIP-qPCR. Metastatic OSCC cells with CEBPB knockdown or GAS6 overexpression were established and co-cultured with THP-1 cells. IL-10 and IL-6 secretion from co-cultured THP-1 cells was detected via ELISA. Chemotaxis of OSCC cells toward THP-1 cells was assessed through a Transwell assay. RESULTS: CEBPB was upregulated in OSCC and correlated with poor prognosis. By integrating H3K27ac ChIP-seq and bulk RNA-seq data, 131 CEBPB-regulated enhancer-controlled genes were identified in lymph node metastatic OSCC cells. scRNA-seq analysis revealed eight major cell clusters in primary foci and lymph node metastases, including T/NK cells, malignant epithelial cells, B/plasma cells, macrophages, fibroblasts, dendritic cells, endothelial cells, and mast cells, with the malignant epithelial cells stratified into distinct sub-clusters. CEBPB expression was elevated in malignant epithelial cells of lymph node metastases compared to primary foci. Furthermore, 15 pairs of enhanced ligand-receptor interactions were identified in lymph node metastases relative to primary foci. GAS6 was a CEBPB-regulated enhancer-controlled gene, primarily mediating interactions between malignant cells and macrophages. CEBPB knockdown in metastatic OSCC cells significantly impaired their chemotaxis toward cocultured THP-1 cells, and downregulated IL-10/IL-6 secretion and CD206 expression in cocultured THP-1 cells. Conversely, GAS6 overexpression reversed these inhibitory effects. CONCLUSION: CEBPB activated GAS6 transcription in metastatic OSCC cells. The CEBPB/ GAS6 axis in metastatic OSCC cells enhanced their chemotaxis toward macrophages and promoted the M2 polarization of macrophages, thereby facilitating the establishment of an immunosuppressive microenvironment.

Humans↗

PubMed2025

Integrative multi-omics profiling deciphers tumor microenvironment heterogeneity and immunotherapy vulnerabilities in lung neuroendocrine carcinomas.

INTRODUCTION: Lung neuroendocrine carcinomas (Lu-NECs) are rare, highly aggressive lung tumors with poor prognosis and limited therapeutic options. Understanding the tumor immune microenvironment (TIME) is crucial towards personalized therapeutic strategies. OBJECTIVES: This study aims to systematically characterize the heterogeneity and complexity of the TIME in Lu-NECs by integrating proteomic, transcriptomic, and genomic data. METHODS: We performed comprehensive immune-proteomic profiling of 76 Lu-NECs across diverse histopathological subtypes to elucidate intra-tumoral TIME heterogeneity at the proteomic level. Validation was conducted in multiple independent cohorts, including 112 Lu-NECs using immunohistochemistry, 147 Lu-NECs, and 17 small cell lung carcinoma samples using transcriptomics. We integrated proteomic, transcriptomic, genomic, and clinical data to assess molecular, immunological, and clinical features, as well as therapeutic vulnerabilities across different immune subtypes. RESULTS: We delineated the immuno-proteomic landscape of Lu-NECs and identified two major immuno-proteomic clusters with distinct immunological, molecular, and clinical characteristics. IPC1 was characterized by high immune cell infiltration, while IPC2 exhibited sparse immune cell presence. Genomic analysis revealed distinct mutational patterns, with IPC1 showing a higher incidence of APOBEC-associated mutation signatures and IPC2 being enriched for mutations associated with defective DNA mismatch repair and tobacco-related mutagens. Functional analyses indicated that IPC1 was related to immune and oncogenic signaling activity, whereas IPC2 was associated with cancer stemness and proliferation-related features. Furthermore, IPC1 and IPC2 demonstrated histological subtype-specific clinical benefits from postoperative chemotherapy. Finally, we developed a machine learning model (iPROM) to predict Lu-NECs immune classification and improve risk stratification, which was validated across multiple independent cohorts. CONCLUSIONS: This study advances the understanding of the tumor immune microenvironment in Lu-NECs through multi-omics characterization and highlights potential personalized therapeutic vulnerabilities tailored to the specific immune landscapes of Lu-NECs.

Humans↗

PubMed2026

Multi-omics identifies lipid accumulation in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome cell lines: a case-control study.

BACKGROUND: In recent years, evidence has indicated a metabolic shift towards increased demand for lipids in various lymphoid cell populations from people with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS). We previously screened the mitochondrial function and gene expression of B cell-derived lymphoblastoid cell lines (LCLs) generated from the blood of people with ME/CFS to characterise a model for hypothesis discovery and testing, observing elevated expression of gene products facilitating amino acid and fatty acid degradation for energy. METHOD: In this follow-up study we have expanded this characterisation by profiling the polar metabolomes and non-polar lipidomes of an all-female cohort of 17 healthy control and 15 ME/CFS LCLs, and we integrated this new data with the previously generated proteomic and transcriptomic data. RESULTS: In the polar metabolome we detected no significantly altered individual features, while integrated multi-omic analysis by MetaboAnalyst indicated 15 dysregulated pathways. Next, in the non-polar lipidome, we identified that PC(O-38:4) had significantly reduced levels in ME/CFS LCLs and was almost entirely discriminative of ME/CFS status. Among all detected classes of lipids we found that triradylglycerolipids ("triglycerides"), diradylglycerolipids and fatty acids were the most significantly affected and were elevated, and that most lipids exhibited average levels higher than in healthy controls. BioPAN pathway analysis of the lipidomic data predicted a more-active gene product that we confirmed to be significantly elevated in both our proteomic and transcriptomic data, this being phosphatidylserine synthase 1 (PTDSS1), plus 7 other gene products that were concordantly altered in expression in the transcriptomic data. We also found that ME/CFS LCLs exhibited a significant tendency towards more saturated lipid content. CONCLUSIONS: LCLs generated from circulating B cells from people with ME/CFS show accumulation of lipids, skewed lipid profiles and altered activity of related metabolic enzymes such as PTDSS1. These findings will inform future hypothesis-driven studies of primary lymphoid cell populations from people with ME/CFS to dissect specific immunometabolic mechanisms that may be involved in the syndrome, particularly relating to intersections between lipid abnormalities and potential effects on immune cell effector functions.

Fatigue Syndrome, Chronic↗

PubMed2026

Decoding Primary Open-Angle Glaucoma: A Multi-Omics Approach to Identify Druggable Effector Genes.

PURPOSE: Genomewide association studies (GWAS) have identified numerous primary open angle glaucoma (POAG) risk loci, yet most reside in non-coding regions with unclear function. Mapping these loci to effector genes can elucidate disease mechanisms, identify functionally conserved variants, improve cross-ancestry risk prediction by reducing population-specific noise, and uncover shared therapeutic targets. METHODS: Here, we integrate European POAG GWAS with six types of multi-omics molecular Quantitative Trait Locis (xQTLs) using multi-trait colocalization to identify candidate effector variants and evaluate their cross-population relevance using genetic risk score (GRS) analysis, and their therapeutic potential through drug target prioritization. RESULTS: We identified 25 POAG effector variants colocalized with at least one xQTLs. In non-European populations, effector variants showed stronger effect size correlations with Europeans than non-colocalized variants (Pearson r2 = African 0.85 vs. 0.71; East Asian 0.81 vs. 0.69; and Latin American 0.91 vs. 0.75). Effector variants also had smaller allele frequency variations across populations (average interquartile range [IQR] = 0.15 vs. 0.20). The genetic risk score based on effector variants performed comparably to the genome-wide significant single-nucleotide polymorphism (SNP)-based GRS in non-European populations. Drug prioritization identified zinc, copper, sunitinib, probucol, and astemizole as potential common therapeutic agents for POAG and its subtypes. CONCLUSIONS: Our findings offer deeper insight into the molecular mechanisms underlying glaucoma and effector variants for developing more robust GRS models and broadly effective therapeutic strategies for POAG.

Humans↗

PubMed2026

Dynamic lysine acetylation and succinylation of platelet proteins regulates platelet storage lesion: mechanistic insights from multi-omics.

OBJECTIVES: Platelet storage lesion (PSL) severely impairs platelet function during storage, presenting a major hurdle in transfusion medicine; however, the dynamic interplay between global proteomic changes and post-translational modifications (PTMs) underlying these functional deteriorations remains insufficiently characterized. Here, we report the first comprehensive multi-omics analysis integrating global proteomics, acetylomics, and succinylomics to dissect the molecular dynamics during platelet storage. METHODS: We performed quantification of global proteomics, acetylome and succinylome based on TMT-labeled LC-MS/MS analysis, combined with antibody-affinity enrichment and purification. Dynamic molecular changes and functional transformation of platelet were also characterized under proper conditions stored for 1, 3, 5, 7 days, respectively. RESULTS: We systematically characterized 3,609 proteins, 1,308 acetylation sites, and 1,947 succinylation sites across multiple storage time points (D1, D3, D5, D7). We distinct temporal patterns of post-translational modifications, with succinylation showing more extensive coverage than acetylation in platelets. Pathway enrichment analysis revealed extensive metabolic reprogramming involving complement activation, energy metabolism, and cellular detoxification processes. The identification of specific motif patterns provided mechanistic insights into the functional specificity of these modifications. Random forest machine learning identified 20 core regulatory proteins representing critical nodes in PSL development. Furthermore, we employed real - time quantitative polymerase chain reaction (RT - QPCR) to measure the expression levels of key genes related to platelet function and PTM - associated pathways. CONCLUSION: By mapping the interplay between proteomic abundance shifts and PTM dynamics, this study provides a multidimensional understanding of PSL, establishing a foundational framework for optimizing storage protocols and enhancing transfusion safety.

Blood Platelets↗

PubMed2024

A framework for block-wise missing data in multi-omics.

High-throughput technologies have generated vast amounts of omic data. It is a consensus that the integration of diverse omics sources improves predictive models and biomarker discovery. However, managing multiple omics data poses challenges such as data heterogeneity, noise, high-dimensionality and missing data, especially in block-wise patterns. This study addresses the challenges of high dimensionality and block-wise missing data through a regularization and constrained-based approach. The methodology is implemented in the R package bwm for binary and continuous response variables, and applied to breast cancer and exposome multi-omics datasets, achieving strong performance even in scenarios with missing data present in all omics. In binary classification task, our proposed model achieves accuracy in the range of 86% to 92%, and F1 in the range of 68% to 79%. And, in regression task the correlation between true and predicted responses is in the range of 72% to 76%. However, there is a slight decline in performance metrics as the percentage of missing data increases. In scenarios where block-wise missing data affects multiple omics, the model performance actually surpasses that of scenarios where missing data is present in only one omics. One possible explanation for this might be that the other scenarios introduce a greater diversity of observation profiles, leading to a more robust model. Depending on the specific omics being studied, there is greater consistency in feature selection when comparing block-wise missing data scenarios.

Humans↗

PubMed2026

Integrative Analysis Uncover the Effects and Multi-Omics Features of Thigh Muscle Fat Infiltration.

The health impacts and underlying biological pathways of thigh muscle fat infiltration (TMFI) remain incompletely understood. In this study, we analyzed TMFI measured by magnetic resonance imaging in 55,120 UK Biobank participants and found that higher TMFI was significantly associated with all-cause mortality as well as with all major system-specific diseases examined (p values ranged from 2.50 × 10-88 to 9.97 × 10-04). TMFI also mediated the effects of lifestyle factors on health-related outcomes, with mediation proportions ranging from 6.7% to 71.7%. A genome-wide association study (GWAS) identified 79 lead single nucleotide polymorphisms (SNPs) linked to TMFI, and the polygenic risk score for TMFI was significantly associated with mortality and all incident diseases across examined organ systems in an independent subset of UK Biobank participants of European ancestry who were not included in the TMFI GWAS (n = 362,286, all p < 0.05). Gene-drug interactions identified multiple drugs that could potentially modulate TMFI. Analysis of single-cell transcriptomic data indicated that myogenic cells were strongly linked to TMFI (p = 7.08 × 10-08). Summary-data-based Mendelian randomization and Transcriptome-Wide Association Study analyses revealed numerous genes whose expression in specific tissues was associated with TMFI. Proteomic and metabolomic profiling uncovered a broad array of circulating biomarkers associated with TMFI, many of which mediated the effects of modifiable factors and genetic risk on TMFI. Overall, our results highlight the biological relevance of TMFI to human health and provide insights into the multi-omics mechanisms underlying TMFI, identifying potential targets for interventions.

Humans↗

PubMed2024

Relationship between inflammation/immunity and epilepsy: A multi-omics mendelian randomization study integrating GWAS, eQTL, and mQTL data.

OBJECTIVES: Increasing evidence suggests that activated innate/adaptive immunity induces an inflammatory response, thereby participating in epileptogenesis. However, the biological explanation of inflammation/immunity as a potential cause for epilepsy remains largely unknown. This research aimed to determine the causal effects of inflammation/immune-related genes in epilepsy based on multi-omics mendelian randomization (MR). METHODS: We employed summary-data-based MR (SMR) approach to combine GWAS for epilepsy (12,891 cases and 312,803 control) with gene expression quantitative trait loci (cis-eQTL, 31,684 participants) and DNA methylation QTL (cis-mQTL, 1,980 participants) data. Five additional MR methods were then used for sensitivity analyses to confirm the reliability of causal associations. In addition, enrichment analysis of key genes was conducted to provide insight into the biological functions of epilepsy risk variants. RESULTS: A total of 386 inflammation/immune-related genes were selected for further analyses. Primary SMR analysis indicated that 37 DNA methylation sites and six genes regulated by them had potential causal relationship with epilepsy. MR analysis further refined the results, identifying three genes that had a causal effect on epilepsy. Notably, VEGFA (OR: 0.925; 95 % CI: 0.862-0.994) expression was negatively correlated with epilepsy risk, whereas IL16 (OR: 1.076; 95 % CI: 1.028-1.126) and HLA-DPA1 (OR: 1.041; 95 % CI: 1.009-1.074) expressions were positively associated with epilepsy risk. Functional enrichment analysis revealed that the identified genes were involved in GO-BP terms related to VEGF activation signaling and chemotaxis regulation. CONCLUSION: This analysis confirms the causal role of inflammation/immunity in epilepsy, and the identified candidate genes provide clues for drug development in clinical practice.

Humans↗

PubMed2026

Multi-omics insights into the physiological mechanisms of bile acid accumulation in the gallbladder in brumation-like snakes.

Hibernation/brumation represents an important physiological adaptation for animals to cope with seasonal environmental changes. Field observations suggested increased gallbladder weight in the Five-pacer viper (Deinagkistrodon acutus) during brumation, and our quantitative measurements confirmed this increase together with bile acid accumulation. By integrating a multi-omic approach, this study elucidates the regulatory mechanisms of bile acid accumulation in the gallbladder during brumation. Results showed that taurocholic acid (TCA) and taurodeoxycholic acid (TDCA) were the major components in the gallbladder of the brumation-like group, with significantly elevated concentrations of bile acids, whereas bile acid concentrations in serum and intestinal contents were markedly reduced, indicating suppression of the enterohepatic circulation and consequent accumulation of bile acids in the gallbladder. Hepatic transcriptomic analysis revealed significant downregulation of bile acid synthesis and regulatory genes in brumation-like snakes. In contrast, the alternative synthesis pathway gene sterol 27-hydroxylase (CYP27A1) and some transporter genes were slightly upregulated. Further, some modification genes and regulatory genes showed no significant differences between active and brumation-like states. Gut microbiota analysis demonstrated Akkermansia muciniphila, Bacteroides fragilis, and Citrobacter freundii were more enriched in the active group, which were common microbes related to bile acid metabolism, and the correlation analysis confirmed this relationship. Taken together, these findings indicate that the "physiological bile acid accumulation" observed in snakes during brumation-like state is jointly driven by suppressed hepatic synthesis, reduced enterohepatic circulation, and remodeled microbial community structure. The study provides novel comparative physiological insights into extreme metabolic homeostasis in animals.

Animals↗

PubMed2025

Multi-omics analysis of ubiquitin E2 genes in Setaria: evidence for the roles of E2 genes in various aspects of plant development, stress tolerance, and domestication.

Ubiquitin E2 enzymes (E2s) are critical mediators in the ubiquitination cascade, a post-translational modification process that regulates protein stability, activity, localization, and degradation. Here, we analyzed the E2 gene family in foxtail millet (Setaria italica), integrating comparative genomics, transcriptomics, and functional studies. A total of 52 E2 genes were identified and classified into four subfamilies (UBC, UEV, SCE, and RCE) based on phylogenetic analysis across 49 species. Notably, foxtail millet exhibited significant gene expansion. Tissue-specific expression profiling revealed distinct roles of E2 genes in growth and development. Haplotype and quantitative trait loci analyses demonstrated that several E2 genes, including SiUBC39, are associated with key agronomic traits, such as plant height, flowering time, and stress tolerance. Using CRISPR/Cas9, we validated the functional role of SiUBC39, finding that its disruption led to phenotypes resembling wild species (Setaria viridis), such as early flowering and reduced plant height and grain yield. IP-MS and transcriptome analysis revealed SiUBC39's involvement in growth and development regulation, drought stress response, and immune response. SiPIP2;1 and SiEhd2 were identified as interactors of SiUBC39, explaining its roles in blast resistance and flowering time control. Furthermore, domestication analysis identified an A/G mutation in the SiUBC39 promoter TATA box, distinguishing domesticated and wild haplotypes and highlighting its role in domestication selection. This study underscores the essential roles of E2 genes in regulating crop agronomic traits and stress responses, providing valuable insights for genetic improvement in foxtail millet and other cereals.

Setaria Plant↗

PubMed2026

In vivo porcine multi-omics integration identifies microbiome-driven histamine elevation and lasting gut perturbations following Ascaris suum infection and fenbendazole treatment.

Ascaris roundworms impair human and swine health. While treatments using anthelmintic drugs are generally effective in eliminating worms, their effects on the gut microenvironment remain poorly understood. Here we applied integrated multi-omics to characterize infection- and treatment-associated alterations in the pig-Ascaris system. In vitro anaerobic cultures were conducted as supportive validation of selected observations. Ascaris suum infection altered microbial composition and dysregulated 182 serum and fecal metabolites, including histamine and p-cresol sulfate. Compared with time-matched uninfected controls, infected pigs treated with fenbendazole showed marked differences in gut microbial composition 13 days after confirmed worm clearance. Eleven microbial pathways were enriched in successfully treated pigs, including peptidoglycan biosynthesis and histidine metabolism, indicating that infection-associated alterations may persist after treatment. In vitro co-exposure of Lactobacillus reuteri to fenbendazole and A. suum proteins increased histamine production by approximately 79% at 48 h (p < 0.05), serving as supportive evidence of a microbiome contribution. Collectively, our in vivo findings support that host-microbiota-parasite interactions are multifaceted. Microbiota-derived metabolites were associated with regulation of host gene expression, such as TFF2 and IL8. Microbiota plasticity allows the exploitation of the niche differentiated upon infection, resulting in the proliferation of certain Lactobacillus strains in treated animals. Nevertheless, interpretations of treatment effects are made cautiously given the absence of an uninfected drug-only group and the cross-sectional design. Understanding these complex interactions will be important for the design of next-generation functional anthelmintics.

Animals↗

PubMed2025

MO-GCAN: multi-omics integration based on graph convolutional and attention networks.

MOTIVATION: Cancer subtypes play a critical role in disease progression, prognosis, and treatment, making their detection essential for tailoring precision medicine. Studies have shown that multi-omics integration outperforms single-omics approaches in cancer subtyping tasks. However, due to the high-dimensionality of multi-omics data, many existing studies either fail to capture the correlation between true labels and learned features, or lack sufficient capacity to model complex biological representations. These limitations hinder the full potential of leveraging the rich and complementary information embedded in multi-omics datasets. RESULT: We propose a framework that leverages supervised feature learning and classification based on a graph-based learning approach with attention mechanism for cancer subtyping. More specifically, we train graph convolutional network models on each omics dataset to extract latent representations, which are then concatenated to form a comprehensive multi-omics feature embedding. We further develop sample fusion network based on the omics-specific graphs, incorporating the derived features and feeding them into a graph attention model for subtype classification. This two-stage multi-omics framework is applied to eight cancer types, with performance evaluated in terms of test accuracy, training time, macro-averaged precision, recall, and F-score. Experimental results show that the proposed method outperforms state-of-the-art approaches across various cancer types. Additionally, we provide empirical evidence supporting the hypothesis that retaining a limited number of high-confidence edges and utilizing enriched embeddings from intermediate graph neural network layers can improve predictive performance. AVAILABILITY AND IMPLEMENTATION: Data and the code are available at https://github.com/YD-00/MO-GCAN-Updated.git.

Neoplasms↗

PubMed2025

Genetic predisposition to systemic inflammatory proteins is causally associated with inflammatory bowel disease: Insights from multi-omics association study and single-cell RNA-sequencing analysis.

Systemic inflammatory proteins have been reported to be related to inflammatory bowel disease (IBD) in previous observational research. However, their causal links remain obscure. Herein, we performed a Mendelian randomization (MR) analysis to analyze the causality between systemic inflammatory proteins and IBD. Genetic variants related to systemic inflammatory proteins were extracted from a meta-analysis of genome-wide association study (GWAS) data of 8293 European participants. Summary statistics of IBD diverse subtypes were obtained from the international IBD genetic consortium (IIBDGC). We conducted multi-omics method and MR study to detect the causal links through integrating GWAS and protein quantity trait loci (pQTL) data. Inverse variance weighted (IVW) approach was utilized as the dominated analysis method. Moreover, complementary approaches such as MR-Egger intercept test, Cochran Q test and leave-one-out analysis were utilized to validate pleiotropy and heterogeneity. Finally, single-cell RNA-sequencing analysis was performed to detect the expression of significant genes. For IBD, IVW estimates suggested that genetically predicted IL-10 and IL-13 were suggestively associated with an elevated risk of IBD (IL-10: OR: 1.12, 95% CI: 1.00-1.24, P = .04; IL-13: OR: 1.09, 95% CI: 1.01-1.18, P = .023), while CXCL10 was suggestively linked to a lower risk of IBD (CXCL10: OR: 0.90, 95% CI: 0.82-0.99, P = .037). For Crohn disease (CD), the IVW approach provided evidence to sustain that genetically determined IL-13 and CCL3 had a suggestive association with a higher risk of CD (IL-13: OR: 1.13, 95% CI: 1.02-1.26, P = .023; CCL3: OR: 1.22, 95% CI: 1.03-1.45, P = .018). Sensitivity analysis did not explore any heterogeneity and pleiotropy. Our findings supported the causal relationships between 4 specific inflammatory proteins (IL-10, IL-13, CXCL10, and CCL3) and the risk of IBD and CD, thereby providing promising biomarkers of various subtypes stratification and new insights for the prevention and therapeutic target of IBD.

Humans↗

PubMed2026

Integrative Transcriptomic and Proteomic Profiling Identifies S100P as a Potential Functional Biomarker for Sessile Serrated Lesions.

BACKGROUND: Sessile serrated lesions (SSLs) account for 15% of colorectal cancers (CRCs) but detection remains difficult due to flat morphology, mucinous features, and subtle histology. AIMS: This study aimed to identify novel and functionally relevant biomarkers of SSLs using transcriptomic screening and multi-omics validation. METHODS: Paired SSL and normal mucosa specimens (n = 6) underwent RNA sequencing. Differentially expressed genes (DEGs) were filtered for membrane or secretory proteins and validated across TCGA and adenoma transcriptomes. Functional significance was assessed using CRISPR dependency profiling, proteotranscriptomic concordance, pharmacogenomic sensitivity, and connectivity map analysis. RESULTS: We identified 216 upregulated genes in SSLs, including 68 encoding secretory/membrane proteins that better discriminated SSLs from controls and were enriched for adhesion and neuronal signaling while suppressing TNFα-NFκB inflammatory pathways. Cross-cohort comparison revealed five overlapping candidates between SSLs and TCGA CMS1 tumors. Among them, S100P emerged as the primary biomarker candidate, showing consistent upregulation in SSLs and CMS1 tumors while remaining low in normal mucosa and conventional adenomas. TFF1 also showed RNA-level upregulation but appeared more context-dependent. S100P demonstrated strong RNA-protein concordance in CRC cell-line profiling, supporting its detectability as a biomarker candidate. Pharmacogenomic profiling of LS411N cells revealed marked sensitivity to SN-38 and fluoropyrimidines, consistent with serrated CRC vulnerabilities. Connectivity map analysis identified perturbations, including MAPK1 and histone acetyltransferase suppression, that may reverse parts of the SSL transcriptional program. CONCLUSION: These findings prioritize S100P as a promising biomarker candidate for SSLs that warrants further validation in larger cohorts and clinically applicable platforms.

Humans↗

PubMed2026

Integrating transcriptomics and metabolomics reveals the molecular landscape of sperm maturation driven by regional differentiation in the epididymis of Guizhou-Guiqian semi-fine wool sheep.

Epididymal regionalized differentiation is crucial for sperm maturation. However, little is known about the synergistic remodeling mechanisms of different epididymal segments at the transcriptional and metabolic levels during sexual maturation in ruminants (especially sheep). We investigated the caput, corpus, and cauda epididymidis of pre-pubertal (2-month-old) and post-pubertal (7-month-old) Guizhou-Guiqian semi-fine wool sheep using histology, RNA sequencing, and metabolomics. Post-pubertal tissues exhibited increased luminal diameters, cilia lengths, and abundant cauda spermatozoa. Transcriptomic analysis revealed increasing differentially expressed genes (DEGs) along the caput-corpus-cauda axis (4642, 6103, and 7698 DEGs, respectively). Metabolomics detected 786 unique differentially accumulated metabolites (DAMs). Region-specific analysis showed that in the caput, up-regulated pathways (fructose/mannose metabolism; HK2, ALDOA, HKDC1) provide energy and substrates for initial sperm motility. In the corpus, down-regulated genes associated with extracellular matrix and tight junctions suggested epithelial barrier remodeling to establish an immune-tolerant microenvironment. The cauda specifically up-regulated the pentose phosphate pathway (FBP1, GPI) and glutathione metabolism, maintaining redox homeostasis for long-term sperm storage. Additionally, glycerophospholipid metabolism was enriched across all segments, where PEMT, AGPAT5, and LCAT likely regulate sperm plasma membrane fluidity. In conclusion, during sexual maturation, the caput drives energy metabolism and glycosylation, the corpus establishes immune tolerance, and the cauda maintains antioxidant homeostasis. The glycerophospholipid network throughout the across all epididymal segments synergistically remodels sperm membrane. This study reveals the underlying multi-omics regulatory mechanisms of epididymal functional differentiation, providing a theoretical basis for elucidating the molecular mechanisms of sperm maturation in this breed and for the molecular breeding of early reproductive performance in rams.

Animals↗

PubMed2026

Multi-omics identification and functional validation of signal regulatory protein gamma as a prognostic biomarker and immune regulator in head and neck squamous cell carcinoma.

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) comprises biologically diverse tumors, and durable responses to immune-checkpoint blockade are achieved by only a subset of patients. There remains a need for markers that connect clinical outcome with malignant-cell phenotypes and tissue-level immune organization. METHODS: We integrated The Cancer Genome Atlas HNSCC cohort (TCGA-HNSC), five Gene Expression Omnibus (GEO) validation cohorts, single-cell RNA sequencing, Visium spatial transcriptomics, cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq)-informed protein-potential inference, pharmacogenomic screening, genetic-risk analysis and experimental validation. A reconstructed 296-pipeline survival modelling framework was used to prioritize prognostic hub genes across validation-cohort-specific analyses. RESULTS: SIRPG was repeatedly ranked among the top ten selected genes in all five validation cohorts. At single-cell resolution, SIRPG-high tumor cells showed stronger malignant-cell features, immune-inhibitory and metabolic programs, Scissor-positive risk association, CLCA2/P53-related perturbation signals and inferred SIRPG-CD47/signal regulatory protein (SIRP) communication. Spatial analyses placed this axis within an immune-checkpoint-coupled niche, supported by Maxspin/multiview intercellular spatial modelling (MISTy) spatial coupling, communication analysis by optimal transport (COMMOT)-inferred CD47-SIRPG communication and scProTrans-inferred CD47/SIRPG protein-potential overlap. Functionally, SIRPG knockdown reduced HNSCC cell viability and increased apoptosis, whereas re-expression of short hairpin RNA (shRNA)-resistant SIRPG restored the CLCA2-BAX/BCL2 protein response. CONCLUSION: Together, these findings identify SIRPG as an immune-related prognostic hub and context-dependent tumor-cell regulator associated with apoptosis, immune communication and spatial microenvironmental organization in HNSCC.

Humans↗

PubMed2026

Integrative multi-omics analysis of metabolite-protein interaction networks across different stages of coronary heart disease.

To elucidate the molecular characteristics of synergistic interactions across the clinical stages of coronary heart disease (CHD)-specifically stable angina pectoris (SAP), unstable angina pectoris (UAP), and acute myocardial infarction (AMI)-through integrated metabolomic and proteomic analyses. Based on a cohort including SAP, UAP, AMI, and healthy controls, metabolomic and proteomic analyses were performed to identify differentially expressed molecules, followed by KEGG pathway enrichment analysis. Pathways co-enriched across both omics platforms were selected to construct metabolite-protein interaction networks. The number of pathways co-enriched in both metabolomic and proteomic analyses increased markedly with disease stage. Only two pathways (histidine metabolism and arginine and proline metabolism) were identified in the SAP stage; this number increased to five in the UAP stage (including ferroptosis and efferocytosis) and expanded to 25 in the AMI stage, encompassing three major functional modules: immune inflammation, metabolic reprogramming, and cell signaling. The core network exhibited a stepwise increase in connectivity, shifting from a sparse structure in the SAP stage to a highly interconnected architecture in the AMI stage, with L-glutamate and KNG1 identified as the central hubs in this cross-sectional network. In addition, CNDP1 exhibited a stage-dependent functional transition, shifting from downregulation in SAP to upregulation in AMI. In this cross-sectional analysis, metabolic dysregulation and immune activation exhibited stepwise increases in interconnectivity across the SAP, UAP, and AMI groups, with the most extensive crosstalk observed in the AMI stage-a network configuration consistent with a tightly coupled "molecular storm". These findings provide novel insights into stage-associated molecular signatures of CHD and identify candidate hub molecules for stage-oriented therapeutic investigation.

Humans↗

PubMed2026

Prioritizing Parkinson's disease risk-associated mitochondrial candidate genes via multi-omics integrative analysis.

BACKGROUND: Mitochondrial dysfunction has been implicated in Parkinson's disease (PD), but the genetically regulated mitochondrial genes associated with PD risk remain incompletely defined. METHODS: We conducted a summary-data-based genetic epidemiology study integrating summary-based Mendelian randomization (SMR), Heterogeneity in dependent instruments (HEIDI) filtering, and Bayesian colocalization to prioritize mitochondrial-related molecular features associated with PD risk. Mitochondrial-related genes were defined using MitoCarta3.0. Genetically predicted gene expression and plasma protein abundance were evaluated using expression quantitative trait loci (eQTL) data from eQTLGen and GTEx v8, and protein quantitative trait loci (pQTL) data was assessed using International Parkinson's Disease Genomics Consortium (IPDGC) as the discovery genome-wide association study (GWAS) and FinnGen as the replication dataset. Prespecified QTL analyses were interpreted using FDR correction, HEIDI filtering, and colocalization support. DNA methylation QTL analysis, mitochondrial phenotype MR, and single-nucleus RNA-seq analysis were performed as complementary analyses. RESULTS: In the primary eQTL analysis, higher genetically predicted TTC19 expression was associated with lower PD risk (OR = 0.80, 95% CI: 0.74-0.87, PPH4 = 0.80), whereas higher MALSU1 expression was associated with increased PD risk (OR = 2.21, 95% CI: 1.59-3.06, PPH4 = 0.96). Both associations survived FDR correction, passed HEIDI filtering, and showed colocalization support. GTEx whole-blood data supported the direction of the TTC19 association. No mitochondrial protein reached significance after FDR correction and colocalization filtering in the primary pQTL analysis. Complementary methylation analysis highlighted cg06270993 as an exploratory regulatory signal for MALSU1. CONCLUSIONS: This MR-colocalization study prioritizes TTC19 and MALSU1 as genetically supported mitochondrial-related candidate genes associated with PD risk. Further validation is required to define their functional roles in PD pathogenesis.

Humans↗