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PubMed2026

Longitudinal analysis of genomic and immune differences between primary and metastatic nasopharyngeal carcinoma for precision oncology.

INTRODUCTION: Nasopharyngeal carcinoma (NPC) is a common malignancy with a high incidence in Southern China and Southeast Asia. Distant metastasis remains a major cause of poor prognosis. This study aims to explore the genomic and immune microenvironmental changes in primary and metastatic NPC through longitudinal analysis, to provide insights for guiding precision treatment strategies. METHODS: We analyzed tumor samples from 11 male NPC patients with distant metastasis. Paired primary and metastatic samples underwent targeted whole-exome sequencing (551 genes) and RNA sequencing (289 genes). Multiplex immunohistochemistry was performed to assess immune cell composition and immune response markers. Genomic alterations and immune features were compared between primary and metastatic tumors, and their associations with clinical outcomes were evaluated. RESULTS: Metastatic tumors exhibited distinct chromosomal changes, including frequent 1q gain, while 6p gain showed a trend toward prolonged survival. Primary tumors showed stronger immune suppression characterized by increased B-cell and Treg infiltration and elevated CTLA4 and IDO1 expression, whereas metastatic lesions displayed more active immune responses. Liver metastases presented a distinct immune landscape with lower CD8+ T-cell density compared to non-liver metastases. In locoregionally advanced NPC, high expression of oncogenic genes such as EGFR and MYC correlated with shorter disease-free survival, while elevated PANCK expression and enhanced cytotoxicity were linked to better outcomes. These results delineate the molecular and immune evolution of NPC and provide a foundation for developing precision therapeutic strategies. CONCLUSION: This study identifies key molecular and immune features associated with NPC survival. Primary tumors show an immunosuppressive phenotype, suggesting potential benefits from combining CTLA4 or IDO1 inhibitors with PD-1 blockade. Liver metastases exhibit distinct immune features, supporting the need for site-specific precision therapies. These findings contribute to personalized management strategies in NPC, guiding treatment based on molecular and immune profiles.

distant metastasis↗

PubMed2026

Epigenetic and immunological alterations in umbilical cord blood of overweight/obese women with gestational diabetes mellitus: insights into DNA methylation signatures and immune cell dysregulation.

BACKGROUND: Gestational diabetes mellitus (GDM) is a common pregnancy complication associated with adverse maternal and neonatal outcomes. Epigenetic modifications may reflect intrauterine metabolic exposure and contribute to immune and metabolic alterations. This study aimed to explore DNA methylation profiles in umbilical cord blood from overweight and obese women with and without GDM. METHODS: Umbilical cord blood samples from 30 overweight/obese pregnant women (with and without GDM) were analyzed using the Illumina 850 K methylation array to identify differentially methylated positions (DMPs) and regions (DMRs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to assess the functional relevance of methylation changes. Immune cell composition was estimated using deconvolution analysis and further examined in an independent single-cell RNA sequencing (scRNA-seq) cohort. Lasso regression was applied to identify CpG sites associated with GDM status and construct a preliminary methylation-based classification model. RESULTS: A total of 23,331 hypermethylated and 29,501 hypomethylated DMPs were identified between women with and without GDM, with hypomethylation predominating. Enrichment analyses indicated associations with neurodevelopmental pathways, metabolic processes, immune regulation, and epigenetic modification. Immune deconvolution analysis suggested reduced proportions of CD4+ T cells (p < 0.05) and a trend toward decreased NK cells in the GDM group, alongside increased CD8+ T cells and neutrophils. Seven CpG sites were selected for model construction and demonstrated strong discriminatory performance within this cohort. CONCLUSION: This exploratory study identifies distinct cord blood DNA methylation patterns associated with GDM in overweight/obese pregnancies. The findings suggest potential links between epigenetic alterations and immune cell composition in GDM-exposed offspring. The identified CpG signature warrants further validation in larger, prospective cohorts to determine its clinical applicability.

Humans↗

PubMed2026

Spatial biology reveals altered macrophage states in immunosuppressed non-melanoma skin cancer.

Immunosuppressed patients with non-melanoma skin cancer experience worse clinical outcomes, yet the tumor immune microenvironment associated with systemic immunosuppression remains incompletely defined. Using integrated single-cell, spatial transcriptomic, multiplex immunofluorescence, and spatial epigenomic profiling across immunocompetent and immunosuppressed tumors, we found that overall immune-cell composition was largely preserved despite differences in immune-cell distribution, spatial organization, and T cell clonality. Immunosuppressed tumors demonstrated reduced intratumoral macrophage densities, decreased T cell clonal diversity, altered antigen-presenting cell and T cell spatial interactions, and distinct fibroblast- and macrophage-associated spatial niches. Multi-cohort validation across complementary spatial and single-cell platforms identified consistent alterations in innate-adaptive immune organization in immunosuppressed tumors. Together, these findings define spatial and functional remodeling of the tumor immune microenvironment under systemic immunosuppression and provide a framework for future therapeutic investigation in high-risk patients.

Humans↗

PubMed2023

Immunogenomics of cholangiocarcinoma.

The development of cholangiocarcinoma spans years, if not decades, during which the immune system becomes corrupted and permissive to primary tumor development and metastasis. This involves subversion of local immunity at tumor sites, as well as systemic immunity and the wider host response. While immune dysfunction is a hallmark of all cholangiocarcinoma, the specific steps of the cancer-immunity cycle that are perturbed differ between patients. Heterogeneous immune functionality impacts the evolutionary development, pathobiological behavior, and therapeutic response of these tumors. Integrative genomic analyses of thousands of primary tumors have supported a biological rationale for immune-based stratification of patients, encompassing immune cell composition and functionality. However, discerning immune alterations responsible for promoting tumor initiation, maintenance, and progression from those present as bystander events remains challenging. Functionally uncoupling the tumor-promoting or tumor-suppressing roles of immune profiles will be critical for identifying new immunomodulatory treatment strategies and associated biomarkers for patient stratification. This review will discuss the immunogenomics of cholangiocarcinoma, including the impact of genomic alterations on immune functionality, subversion of the cancer-immunity cycle, as well as clinical implications for existing and novel treatment strategies.

Humans↗

PubMed2025

Paradoxical Effect of Myosteatosis on the Immune Checkpoint Inhibitor Response in Metastatic Renal Cell Carcinoma.

BACKGROUND: Treatment for metastatic renal cell carcinoma (mRCC) has shifted from tyrosine kinase inhibitor (TKI) therapy to immune checkpoint inhibitor (ICI)-based therapy, improving outcomes but with variable individual responses. This study investigated the prognostic implications of pretreatment low skeletal muscle mass (LSMM) and myosteatosis in patients with mRCC undergoing first-line ICI-based therapies, comparing outcomes between PD-1 inhibitor + CTLA-4 inhibitor and PD-1 inhibitor + TKI, incorporating single-cell RNA sequencing. METHODS: A retrospective analysis was performed on 90 patients with mRCC treated with ICI-based therapies between November 2019 and March 2023. Patients were grouped based on whether they received PD-1 inhibitor + CTLA-4 inhibitor or PD-1 inhibitor + TKI combinations. LSMM was defined as skeletal muscle index below 40.8 cm2/m2 for men and 34.9 cm2/m2 for women. Myosteatosis was defined using skeletal muscle density, with cut-off values < 41 HU for BMI < 25 kg/m2 and < 33 HU for BMI ≥ 25 kg/m2. Progression-free survival (PFS) and overall survival (OS) were compared using Kaplan-Meier curves and multivariable models. Single-cell RNA sequencing was performed on pretreatment samples to compare the immune microenvironment between patients with and without myosteatosis. RESULTS: The study cohort (26.7% female; median age: 60.5 years) included 59 patients (65.6%) treated with PD-1 inhibitor + CTLA-4 inhibitor and 31 patients (34.4%) treated with PD-1 inhibitor + TKI. LSMM was present in 18.9% of patients, and myosteatosis in 41.1%, with comparable proportions across groups. During follow-up, 29 patients (32.2%) died: 16 in the PD-1 inhibitor + CTLA-4 inhibitor group and 13 in the PD-1 inhibitor + TKI group. The overall 1-year mortality rate was 22.2%, and PFS rate was 53.3%. Myosteatosis predicted poor OS (HR, 5.389; p = 0.008) and PFS (HR, 2.930; p = 0.022) in the PD-1 inhibitor + TKI group but was protective for PFS (HR, 0.461; p = 0.049) in the PD-1 inhibitor + CTLA-4 inhibitor group. LSMM did not significantly affect outcomes in either group. Single-cell RNA sequencing revealed higher CTLA-4 expression in regulatory T cells and more effector memory CD8+ T cells in patients with myosteatosis, whereas patients without myosteatosis had more anti-tumoural non-classical monocytes. CONCLUSIONS: Myosteatosis negatively impacts OS and PFS in patients with mRCC treated with PD-1 inhibitor + TKI therapy but is protective for PFS in those treated with PD-1 inhibitor + CTLA-4 inhibitor therapy. Altered checkpoint expression and immune cell composition associated with myosteatosis may contribute to these differential responses.

Humans↗

PubMed2026

Single-cell RNA sequencing of peripheral blood defines two immunological subtypes of Sjögren's disease distinguished by anti-SSA antibodies and aberrant B cell populations.

OBJECTIVES: Sjögren's disease (SjD) is a heterogeneous autoimmune disorder characterized by substantial clinical and molecular diversity. This heterogeneity raises key questions regarding the existence of distinct pathogenic mechanisms underlying disease subtypes. The objective of this study was to comprehensively characterize peripheral immune cell states associated with SjD and to identify features that could enable better patient stratification for targeted treatments. METHODS: We performed single-cell RNA sequencing with surface protein profiling on 1.5 million peripheral blood mononuclear cells (PBMCs) from 333 participants. Individuals were stratified by SjD diagnosis and anti-SSA status to enable comparative analyses between disease subgroups and controls. RESULTS: Our analysis identified two immunological endotypes of SjD, with SSA-positive participants exhibiting a dominant and persistent IFN-I signature that was also associated with altered immune cell composition. Transitional B cells were particularly affected, displaying altered developmental states, reduced BCR diversity, shorter CDR3 regions, and increased predicted interactions with activated immune cell populations, findings consistent with perturbations of early B-cell selection processes. By contrast, SSA-negative SjD participants exhibited limited transcriptional differences compared with symptomatic non-SjD controls, highlighting substantial biological heterogeneity within SjD. CONCLUSIONS: These findings support a two-disease model of SjD and highlight transitional B cells as both a key biomarker and a therapeutic target.

Journal Article↗

PubMed2026

Rationale and Study Design of the GUIDANCE trial: A Multicenter Phase II Trial of Maintenance Durvalumab and Olaparib After Standard Fist Line Treatment (Carboplatin/Cisplatin, Etoposide, and Durvalumab) in HRD Positive Extensive Disease (ED) Small-cell Lung Cancer (SCLC) (AIO-TRK-0124/ass).

BACKGROUND: Small-cell lung cancer (SCLC) is an aggressive malignancy with poor prognosis and limited therapeutic progress over recent decades. Although PD-L1 inhibitors have modestly improved survival, responses are not durable. There are no predictive biomarkers that would allow for a personalized treatment strategy. Targeting DNA damage repair deficiencies represents a promising treatment strategy in various solid tumors. Poly (ADP-ribose) polymerase (PARP) inhibitors such as olaparib have demonstrated efficacy in homologous recombination deficiency (HRD)-positive tumors, and preclinical data suggest synergistic activity with immune checkpoint blockade. METHODS: GUIDANCE is a biomarker-driven, multicenter, single-arm, open-label phase II trial evaluating maintenance therapy with durvalumab and olaparib in patients with advanced or metastatic SCLC without progression after first-line therapy with platinum, etoposide and durvalumab. Patients are prospectively selected for HRD based on homologous recombination repair gene alterations and/or a genomic instability score. Following central prescreening, 29 patients will be enrolled. Patients receive durvalumab (1500 mg every 4 weeks) and olaparib (300 mg twice daily) until progression or unacceptable toxicity. The primary endpoint is progression-free survival (PFS) by RECIST 1.1. Secondary endpoints are overall survival, safety and tolerability. Exploratory analyses include circulating tumor DNA (ctDNA) monitoring of individual TP53 mutations, assessment of SLFN11 expression, and characterization of immune cell composition via multiplex immunohistochemistry. DISCUSSION: This trial investigates a chemotherapy-free, genomically stratified maintenance strategy targeting both DNA damage repair deficiency and immune evasion in SCLC. By integrating HRD-based patient selection with concurrent PARP and immune checkpoint inhibition, GUIDANCE aims to establish a more individualized therapeutic approach and to generate a signal for further evaluation in biomarker-defined patient populations. Trial registration number EuraCT 2024-512373-27-00.

DNA-damage repair↗

PubMed2025

Multimodal profiling reveals tissue-directed signatures of human immune cells altered with age.

The immune system comprises multiple cell lineages and subsets maintained in tissues throughout the lifespan, with unknown effects of tissue and age on immune cell function. Here we comprehensively profiled RNA and surface protein expression of over 1.25 million immune cells from blood and lymphoid and mucosal tissues from 24 organ donors aged 20-75 years. We annotated major lineages (T cells, B cells, innate lymphoid cells and myeloid cells) and corresponding subsets using a multimodal classifier and probabilistic modeling for comparison across tissue sites and age. We identified dominant site-specific effects on immune cell composition and function across lineages; age-associated effects were manifested by site and lineage for macrophages in mucosal sites, B cells in lymphoid organs, and circulating T cells and natural killer cells across blood and tissues. Our results reveal tissue-specific signatures of immune homeostasis throughout the body, from which to define immune pathologies across the human lifespan.

Humans↗

PubMed2026

Exploring the Mechanism of Zhigancao Decoction in the Treatment of Chronic Heart Failure via Modulation of Oxidative Stress.

BACKGROUND: Zhigancao decoction has shown therapeutic potential in the management of chronic heart failure (CHF); however, the molecular mechanisms underlying its pharmacological effects remain incompletely understood. This study aimed to investigate its potential mechanisms, with a particular focus on oxidative stress-related pathways. METHODS: The chemical profile of Zhigancao decoction was characterized by LC-MS/MS, and putative targets were predicted using SwissTargetPrediction. A protein-protein interaction (PPI) network was established using the STRING database and Cytoscape software, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Differentially expressed genes from two GEO datasets (GSE9128 and GSE84796) were integrated with reactive oxygen species (ROS)-related genes to identify candidate targets. Network pharmacology and molecular docking were subsequently performed to investigate compound-target interactions. RESULTS: A total of 66 chemical constituents and 818 putative targets were characterized and collected, respectively. Among these targets, MMP9 emerged as a central candidate associated with the therapeutic effects of Zhigancao decoction. GO and KEGG enrichment analyses demonstrated that the core targets were significantly enriched in oxidative stress-related pathways, inflammatory signaling cascades, and cell fate regulatory pathways. Computational deconvolution of bulk transcriptomic data suggested marked alterations in the estimated immune cell composition of the CHF microenvironment. Network pharmacology analysis further indicated that multiple chemical constituents of Zhigancao decoction converge on MMP9 and its associated pathways. Molecular docking analysis demonstrated favorable binding affinities between 10 representative compounds and MMP9, with binding energies below -7.0 kcal/mol. CONCLUSIONS: In silico predictions suggest that Zhigancao decoction may exert potential therapeutic effects against CHF through computationally predicted targeting of MMP9 and associated oxidative stress- and immune-related pathways. These computational findings provide a theoretical foundation for future experimental investigations into the mechanisms of Zhigancao decoction in CHF, though clinical application would require confirmation through rigorous in vivo and clinical studies.

Oxidative Stress↗

PubMed2026

Single-cell multi-omics dissects transcript isoform and immune repertoire dynamics in human immunosenescence.

Immunosenescence, a major hallmark of systemic aging, refers to the progressive functional decline of the immune system. This decline not only compromises host defense and immunological memory but also fuels chronic inflammation and tissue degeneration (collectively known as inflammaging). While single-cell RNA sequencing (scRNA-seq) has revealed transcriptomic alterations associated with immune aging, analyses restricted to transcript abundance fail to capture deeper regulatory layers, such as transcript isoform diversity and the remodeling of immune receptor repertoires. To address this limitation, we present a human peripheral immune single-cell multi-omics atlas that integrates gene expression, transcript isoform diversity, and immune receptor repertoires. By combining single-cell full-length transcriptome sequencing (scCycloneSEQ), short-read scRNA-seq, and single-cell immune receptor sequencing (scTCR/BCR-seq), we systematically profiled peripheral blood mononuclear cells (PBMCs) from healthy donors aged 30-40 and 60-70 years. Our analyses uncovered extensive age-related remodeling of immune cell composition, functional states, and TCR/BCR diversity. Notably, we found that CD4+ effector memory T cells exhibited widespread differential isoform usage (DIU), 3'UTR length variation, and a marked reshaping of cytotoxic T lymphocyte (CTL) clonotypes-all of which were closely associated with aging-related inflammation and cellular senescence. This multi-omics atlas delineates key molecular features of immunosenescence and provides a high-resolution resource for deciphering the regulatory architecture underlying immune aging.

TCR/BCR↗

PubMed2026

phylobar: an R package for multiresolution compositional barplots in omics studies.

SUMMARY: Stacked barplots, though widely used in microbiome studies, can obscure important patterns in microbiome data. They omit rare taxa and can mask shifts that emerge at finer taxonomic levels. To address this issue, we introduce phylobar, an R package that interactively links stacked barplots with overview phylogenetic or taxonomic hierarchies. The interface allows users to collapse or expand subtrees, paint color palettes interactively, and search for specific taxa. This allows comparison across taxonomic resolutions that are hidden in static overviews. phylobar works with any omics data with hierarchical organization, including cell type hierarchies, as we demonstrate in a case study of immune cell composition in COVID-19 patients. AVAILABILITY AND IMPLEMENTATION: phylobar is available as an R package on GitHub. It uses the htmlwidgets library to link interactive D3 visualizations with R. The interactive plots can be embedded within R Markdown or Quarto notebooks, and views can be exported as vector graphics files. The package is open source and documented at https://mkdiro-O.github.io/phylobar.

Software↗

PubMed2025

Perinatal dysfunction of innate immunity in cystic fibrosis.

In patients with cystic fibrosis (CF), repeated cycles of infection and inflammation eventually lead to fatal lung damage. Although diminished mucus clearance can be restored by highly effective CFTR modulator therapy, inflammation and infection often persist. To elucidate the role of the innate immune system in CF etiology, we investigated a CF pig model and compared these results with those for preschool children with CF. In newborn CF pigs, we observed changes in lung immune cell composition before the onset of infection that were dominated by increased monocyte infiltration, whereas neutrophil numbers remained constant. Flow cytometric and transcriptomic profiling revealed that the infiltrating myeloid cells displayed a more immature status. Cells with comparably immature transcriptomic profiles were enriched in the blood of CF pigs at birth as well as in preschool children with CF. This pattern coincided with decreased CD16 expression in the myeloid cells of both pigs and humans, which translated into lower phagocytic activity and reduced production of reactive oxygen species in both species. These results were indicative of a congenital, translationally conserved, and functionally relevant aberration of the immune system in CF. In newborn wild-type pigs, CFTR transcription in immune cells, including lung-derived and circulating monocytes, isolated from the bone marrow, thymus, spleen, and blood was below the detection limits of highly sensitive assays, suggesting an indirect etiology of the observed effects. Our findings highlight the need for additional immunological treatments to target innate immune deficits in patients with CF.

Cystic Fibrosis↗

PubMed2025

Construction of a prognostic model for gastric cancer based on immune infiltration and microenvironment, and exploration of MEF2C gene function.

BACKGROUND: Advanced gastric cancer (GC) exhibits a high recurrence rate and a dismal prognosis. Myocyte enhancer factor 2c (MEF2C) was found to contribute to the development of various types of cancer. Therefore, our aim is to develop a prognostic model that predicts the prognosis of GC patients and initially explore the role of MEF2C in immunotherapy for GC. METHODS: Transcriptome sequence data of GC was obtained from The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO) and PRJEB25780 cohort for subsequent immune infiltration analysis, immune microenvironment analysis, consensus clustering analysis and feature selection for definition and classification of gene M and N. Principal component analysis (PCA) modeling was performed based on gene M and N for the calculation of immune checkpoint inhibitor (ICI) Score. Then, a Nomogram was constructed and evaluated for predicting the prognosis of GC patients, based on univariate and multivariate Cox regression. Functional enrichment analysis was performed to initially investigate the potential biological mechanisms. Through Genomics of Drug Sensitivity in Cancer (GDSC) dataset, the estimated IC50 values of several chemotherapeutic drugs were calculated. Tumor-related transcription factors (TFs) were retrieved from the Cistrome Cancer database and utilized our model to screen these TFs, and weighted correlation network analysis (WGCNA) was performed to identify transcription factors strongly associated with immunotherapy in GC. Finally, 10 patients with advanced GC were enrolled from Sun Yat-sen University Cancer Center, including paired tumor tissues, paracancerous tissues and peritoneal metastases, for preparing sequencing library, in order to perform external validation. RESULTS: Lower ICI Score was correlated with improved prognosis in both the training and validation cohorts. First, lower mutant-allele tumor heterogeneity (MATH) was associated with lower ICI Score, and those GC patients with lower MATH and lower ICI Score had the best prognosis. Second, regardless of the T or N staging, the low ICI Score group had significantly higher overall survival (OS) compared to the high ICI Score group. For its mechanisms, consistently, for Camptothecin, Doxorubicin, Mitomycin, Docetaxel, Cisplatin, Vinblastine, Sorafenib and Paclitaxel, all of the IC50 values were significantly lower in the low ICI Score group compared to the high ICI Score group. As a result, based on univariate and multivariate Cox regression, ICI Score was considered to be an independent prognostic factor for GC. And our Nomogram showed good agreement between predicted and actual probabilities. Based on CIBERSORT deconvolution analysis, there was difference of immune cell composition found between high and low ICI Score groups, probably affecting the efficacy of immunotherapy. Then, MEF2C, a tumor-related transcription factor, was screened out by WGCNA analysis. Higher MEF2C expression is significantly correlated with a worse OS. Moreover, its higher expression is also negatively correlated with tumor mutation burden (TMB) and microsatellite instability (MSI), but positively correlated with several immunosuppressive molecules, indicating MEF2C may exert its influence on tumor development by upregulating immunosuppressive molecules. Finally, based on transcriptome sequencing data on 10 paired tumor tissues from Sun Yat-sen University Cancer Center, MEF2C expression was significantly lower in paracancerous tissues compared to tumor tissues and peritoneal metastases, and it was also lower in tumor tissues compared to peritoneal metastases, indicating a potential positive association between MEF2C expression and tumor invasiveness. CONCLUSIONS: Our prognostic model can effectively predict outcomes and facilitate stratification GC patients, offering valuable insights for clinical decision-making. The identified transcription factor MEF2C can serve as a biomarker for assessing the efficacy of immunotherapy for GC.

Humans↗

PubMed2025

MPAC: a computational framework for inferring pathway activities from multi-omic data.

MOTIVATION: Fully capturing cellular state requires examining genomic, epigenomic, transcriptomic, proteomic, and other assays for a biological sample and comprehensive computational modeling to reason with the complex and sometimes conflicting measurements. Modeling these so-called multi-omic data is especially beneficial in disease analysis, where observations across omic data types may reveal unexpected patient groupings and inform clinical outcomes and treatments. RESULTS: We present Multi-omic Pathway Analysis of Cells (MPAC), a computational framework that interprets multi-omic data through prior knowledge from biological pathways. MPAC leverages network relationships encoded in pathways through a factor graph to infer consensus activity levels for proteins and associated pathway entities from multi-omic data, runs permutation testing to eliminate spurious activity predictions, and groups biological samples by pathway activities to allow identifying and prioritizing proteins with potential clinical relevance, e.g. associated with patient prognosis. Using DNA copy number alteration and RNA-seq data from head and neck squamous cell carcinoma patients from The Cancer Genome Atlas as an example, we demonstrate that MPAC predicts a patient subgroup related to immune responses not identified by analysis with either input omic data type alone. Key proteins identified via this subgroup have pathway activities related to clinical outcome as well as immune cell composition. Our MPAC R package enables similar multi-omic analyses on new datasets. AVAILABILITY AND IMPLEMENTATION: The MPAC package is available at Bioconductor https://bioconductor.org/packages/MPAC.

Humans↗

PubMed2025

MPAC: a computational framework for inferring pathway activities from multi-omic data.

Fully capturing cellular state requires examining genomic, epigenomic, transcriptomic, proteomic, and other assays for a biological sample and comprehensive computational modeling to reason with the complex and sometimes conflicting measurements. Modeling these so-called multi-omic data is especially beneficial in disease analysis, where observations across omic data types may reveal unexpected patient groupings and inform clinical outcomes and treatments. We present Multi-omic Pathway Analysis of Cells (MPAC), a computational framework that interprets multi-omic data through prior knowledge from biological pathways. MPAC leverages network relationships encoded in pathways through a factor graph to infer consensus activity levels for proteins and associated pathway entities from multi-omic data, runs permutation testing to eliminate spurious activity predictions, and groups biological samples by pathway activities to allow identifying and prioritizing proteins with potential clinical relevance, e.g., associated with patient prognosis. Using DNA copy number alteration and RNA-seq data from head and neck squamous cell carcinoma patients from The Cancer Genome Atlas as an example, we demonstrate that MPAC predicts a patient subgroup related to immune responses not identified by analysis with either input omic data type alone. Key proteins identified via this subgroup have pathway activities related to clinical outcome as well as immune cell compositions. Our MPAC R package, available at https://bioconductor.org/packages/MPAC, enables similar multi-omic analyses on new datasets.

Journal Article↗

PubMed2026

Detection of House Dust Mite-derived DNA in Human Lung Tumors by Whole-Genome Sequencing.

Lung cancer in never-smokers (LCINS) accounts for an increasing proportion of lung cancer cases, yet its risk factors remain poorly understood. House dust mites (HDM) are common aeroallergens that induce airway inflammation, but their potential contribution to lung cancer is unknown. We analyzed unmapped whole-genome sequencing reads from 783 lung cancers from the Sherlock-Lung (n = 621 never-smokers) and EAGLE (n = 162 smokers) cohorts, including 328 matched adjacent normal lung tissues. After removal of human sequences, reads were aligned to reference genomes from the two major HDM species and confirmed by BLAST. Samples with top BLAST matches were classified as HDM-detected. Associations between HDM detection and genomic, microbiome, and bulk RNA-seq-derived immune features were evaluated. HDM-derived DNA was detected at low abundance in a subset of tumors and adjacent normal tissues, with higher detection frequencies in tumors than matched normal tissues and in smokers than never-smokers. In LCINS tumors, HDM detection was not associated with tumor mutational burden or recurrent driver alterations but was associated with modest differences in immune cell composition and a limited but reproducible bacterial co-detection pattern. These findings provide a foundation for investigating aeroallergen-derived DNA signatures and their potential relationship to the lung tumor microenvironment.

Environmental exposure↗

PubMed2026

Integrated multi-omics identification of m6A-SNP-related diagnostic biomarkers in amyotrophic lateral sclerosis.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) lacks reliable and minimally invasive biomarkers for early diagnosis. m6A-associated single-nucleotide polymorphisms (m6A-SNPs) may influence RNA methylation and gene expression, offering opportunities to identify clinically relevant diagnostic markers. METHODS: We integrated eQTLGen cis-eQTL data, RMVar m6A-SNP annotations, and ALS transcriptomic datasets to identify m6A-SNP-related genes. Random Forest and LASSO regression were combined to screen robust diagnostic markers. A nomogram was constructed and validated using independent cohorts. Immune infiltration, predicted m6A modification sites, and potential RBP-SNP interactions were assessed. Peripheral blood samples from ALS patients were used for exploratory validation of gene expression and global m6A levels. RESULTS: We identified 109 ALS-associated m6A-SNP-related genes with cis-eQTL signals and narrowed these to seven candidate diagnostic markers (TMED5, OXR1, BRI3, FEM1C, SUZ12, EIF2AK4, and TJAP1). The seven-gene model outperformed the individual markers in the training cohort and retained moderate discrimination in the independent validation cohort. ALS samples showed differences in inferred immune-cell composition, including monocytes, neutrophils, and T-cell subsets. The selected SNP loci were located near predicted m6A sites and annotated RBP-binding regions. Exploratory clinical validation showed significant upregulation of FEM1C and SUZ12 at both mRNA and protein levels, accompanied by reduced global m6A modification. CONCLUSIONS: Through multi-omics integration and exploratory clinical validation, this study identifies m6A-SNP-related candidate markers associated with ALS. The findings support further evaluation of m6A-related signatures for ALS discrimination and molecular characterization, while larger independent cohorts and additional calibration are required before clinical application.

Humans↗

PubMed2026

Admission whole-blood transcriptomic characterization of a neutrophil-predominant systemic immune response in patients with acute traumatic brain injury.

BACKGROUND: Acute traumatic brain injury (TBI) is accompanied by systemic immune responses, but their whole-blood transcriptomic features at hospital arrival remain incompletely characterized. We aimed to characterize these features in patients with acute TBI compared with healthy controls. METHODS: In this single-center prospective observational study, we performed whole-blood RNA sequencing on hospital-arrival samples from 42 patients with acute TBI and 21 healthy controls. Analyses included differential expression (limma-voom; FDR < 0.05, |log2FC| > 0.7), functional enrichment, Ingenuity Pathway Analysis, CIBERSORTx LM22 deconvolution, and per-sample neutrophil degranulation signature scoring. RESULTS: Differential expression analysis identified 996 upregulated and 863 downregulated genes, with marked upregulation of inflammation-, innate immunity-, and neutrophil-related genes including DUSP1, HMGB2, MMP9, and S100A8. Canonical pathways with positive IPA z-scores included Neutrophil degranulation, Neutrophil Extracellular Trap Signaling Pathway, and Toll-like Receptor Signaling; upstream regulators included TNF, IL1B, IFNG, and STAT3. Deconvolution identified 7 of 22 differing subsets (q < 0.05), with relatively higher myeloid and lower lymphoid fractions in TBI. The Neutrophil degranulation signature score correlated with Injury Severity Score within TBI (Spearman ρ = +0.55; q < 0.001). CONCLUSIONS: Admission whole-blood transcriptomics characterized a neutrophil-predominant systemic transcriptional response in patients with acute TBI. This response was also evident among patients without major extracranial injury and was associated with total ISS. However, because the study lacked an appropriately matched non-TBI trauma comparator, the findings should be interpreted as a descriptive characterization of a systemic injury response accompanying TBI and do not establish a TBI-specific molecular signature or mechanism.

gene expression↗