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Results for “bulk RNA-seq”

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62 records · Page 4Linked to original sources
PubMed2026

A contextual activity score (CAS) for inferring ADAR-associated transcriptional activity across RNA-seq, single-cell, and spatial transcriptomics.

BACKGROUND AND OBJECTIVE: Adenosine-to-inosine RNA editing, catalyzed by Adenosine Deaminases Acting on RNA (ADARs), is a widespread modification involved in neural function, immune regulation, and cancer. The Alu Editing Index (AEI) is the standard metric to estimate ADAR activity but requires raw sequencing reads and is poorly suited for single-cell and spatial transcriptomic data. This study aimed to develop an alternative framework for inferring ADAR-associated transcriptional activity from gene expression data across diverse transcriptomic technologies. METHODS: We developed the Contextual Activity Score (CAS), a framework based on transcriptional signatures from ADAR perturbation experiments. Context-specific signatures were generated for human neurons, mouse neurons, and cancer models to infer ADAR1 and ADAR2 activity. CAS was computed from normalized gene expression matrices using regulon-based enrichment analysis. Performance was evaluated by comparing with the Alu Editing Index across bulk RNA sequencing datasets, simulated sequencing depths, and library preparation protocols. RESULTS: CAS showed strong concordance with the Alu Editing Index across multiple datasets, while remaining robust to reduced sequencing depth and different library protocols. Unlike the Alu Editing Index, CAS can be applied to single-cell and spatial transcriptomic data and enables the independent assessment of ADAR2 activity. In cancer and neuronal contexts, CAS captured biologically meaningful variations in ADAR-associated transcriptional activity at sample, cell-type, and spatial levels. CONCLUSION: CAS provides a scalable approach applicable across multiple RNA-seq protocols for estimating ADAR-associated transcriptional activity using gene expression data. This method, implemented in an open-source R package for broad adoption, expands the ability to study ADAR-associated transcriptional activity across transcriptomic modalities where direct editing quantification is challenging, such as single-cell and spatial transcriptomics.

Adenosine Deaminase↗
PubMed2026

Dysregulation of U12-Type Splicing in Lupus Neutrophils.

OBJECTIVE: Neutrophil dysfunction is a hallmark of systemic lupus erythematosus (SLE), but its molecular basis remains unclear. This study explores transcriptional and posttranscriptional changes in low-density granulocytes (LDGs), a proinflammatory neutrophil subset expanded in SLE, focusing on NADPH oxidase (Nox) function and minor intron splicing. METHODS: LDGs and normal-density granulocytes (NDGs) were isolated from patients with SLE and healthy controls (HCs). CYBA (p22phox) expression was evaluated at transcript and protein levels. Nox activity was measured using luminol assays. Bulk RNA sequencing (RNA-seq) and rMATS software were used to assess alternative splicing, particularly of U12-type intron-containing genes. RESULTS: CYBA expression was reduced in SLE LDGs (n = 11) compared to SLE and HC NDGs (n = 6), with levels resembling those in chronic granulomatous disease neutrophils. SLE LDGs exhibited impaired Nox activity (n = 7 SLE, n = 12 HC). CYBA is a U12 intron-containing gene, and transcriptomic analysis revealed broad down-regulation of this gene class in SLE LDGs, suggesting minor spliceosome dysfunction. rMATS analysis showed increased U12-type intron retention and widespread splicing defects-including exon skipping and mutually exclusive exon use-in genes such as GBP5, MAEA, and STX10. These abnormalities were validated in an independent long-read RNA-seq data set from SLE peripheral blood mononuclear cells. Importantly, splicing disruptions correlated with disease activity and autoantibody profiles. CONCLUSION: Impaired U12-dependent splicing may contribute to neutrophil dysfunction in SLE, potentially via defective oxidative burst and altered immune regulation. These findings highlight the minor spliceosome as a novel player in lupus pathogenesis.

Humans↗
PubMed2026

Single-cell multiomics reveals exosome-mediated reprogramming and clonotypic remodeling of T cells in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is an aggressive and immunogenic subtype lacking targeted therapies. While tumor-derived exosomes are known to modulate immune function, their direct impact on human T cell plasticity and antigen specificity remains poorly defined. Here, we conducted a comprehensive single-cell multiomic analysis of primary human T cells exposed to exosomes derived from 17 genomically diverse TNBC cell lines and 35 patient samples. Integrating single-cell RNA-seq, V(D)J sequencing, non-coding RNA profiling, bulk and single-cell cytokine analyses, we uncovered conserved and subtype-specific immunomodulatory programs induced by TNBC exosomes. Exosome-treated T cells displayed skewing toward regulatory and dysfunctional phenotypes, including Th17-like, Treg, and PD-1⁺/PD-L1⁺ Tfh cells. Functional profiling revealed suppression of early activation markers and cytokine responses, alongside selective preservation of cytotoxic features in γδ T and NKT subsets. Transcriptomic and miRNA network analyses demonstrated widespread downregulation of immune effector genes (e.g., HBEGF and TNFSF9) mediated by exosome-delivered regulatory miRNAs (has-miR-98-5p). Notably, exosome-stimulated T cells displayed distinct clonotypic expansions, characterized by the emergence of five tumor-specific γδ TCR clonotypes and 30 unique αβ TCR CDR3 sequences that were absent in mock-treated controls, underscoring the role of exosomes in shaping TCR repertoire dynamics.

Humans↗
PubMed2026

Translation of scRNA-seq to a clinical blood test for infection diagnostics.

INTRODUCTION: Early and accurate triage of patients with febrile illness is crucial for appropriate treatment. While standard inflammatory biomarkers are often nonspecific, transcriptome analysis of peripheral blood has diagnostic potential. However, bulk gene expression data is often confounded by changes in cell count proportions, a more robust quantification of gene expression in specific single-cell types, such as monocytes, is required to serve as a reliable clinical biomarker. AREAS COVERED: Various methods to obtain single-cell-type gene expression results, including the gold standard of gene expression analysis after cell sorting and single-cell RNA sequencing, which are difficult to implement in the routine settings are discussed. Other method to interrogate gene expression of a single cell-type is needed. Finally, monocyte cell-type specific ratio-based biomarker (RBB, called Direct Leukocyte Single cell-type Transcript Abundance, or DIRECT LS-TA) which can estimate single cell-type (monocyte) specific gene expression without cell sorting is introduced. EXPERT OPINION: Traditional diagnostic test for differentiating infection has several limitations requiring breakthrough including turn-around time and cost. DIRECT LS-TA provides a reliable way to quantify monocyte-specific gene expression that strongly correlates with gold-standard methods. It is more affordable than single-cell RNA sequencing and can be readily implemented in clinical laboratories using widely available quantitative PCR or digital PCR machines.

Humans↗
PubMed2026

Multiomics approaches reveal direct NF-κB p65 target genes in pancreatic islets during cytokine exposure and in type 1 diabetes.

Autoimmune diseases, including Type 1 diabetes (T1D), are often characterized by overactive inflammatory signaling pathways. The proinflammatory cytokine interleukin-1β (IL-1β) elicits global gene expression changes in islet β-cells which overlap with islets obtained from human donors with T1D. The direct transcriptional link between NF-κB subunit p65 and target genes involved with autoimmune events was investigated. We used a multiomics approach including bulk RNA-sequencing (RNA-Seq), single-cell RNA-sequencing (scRNA-Seq), and chromatin immunoprecipitation coupled to deep sequencing (ChIP-Seq), alongside molecular docking simulations, and transcriptional assays. Through the various experimental modalities, we identified early response genes driven by IL-1β that were differentially expressed in pancreatic islets from human T1D donors and also conserved across mouse, rat, and human tissues. ChIP-Seq revealed genes that are direct genomic targets of the NF-κB p65 transcription factor. Moreover, regions that gained RNA polymerase II binding following cellular exposure to IL-1β were identified, complementing the early response gene profile induced by β-cell exposure to IL-1β. Molecular docking simulations predicted that mutations reducing p65 transcriptional capacity do not alter DNA binding ability. These findings clearly show that IL-1β signaling in pancreatic β-cells directs p65 to specific genomic regions congruent with increased gene expression relevant to T1D in β-cell lines as well as mouse and human islets exposed to cytokines. Islets from human donors with T1D express genes identified as direct p65 targets using unbiased approaches, implicating heightened NF-κB activity as a critical component of autoimmune disease etiology.NEW & NOTEWORTHY Using multiple Seq-based approaches, this study identified genes expressed in human pancreatic tissue from donors with Type 1 diabetes that are regulated acutely by exposure to the cytokine interleukin-1beta. The NF-kB transcription factor p65 (RelA) was determined via ChIP-Seq to be a major control node regulating this immediate early response. These collective datasets are consistent with a paradigm of overactive NF-kB signaling as a critical component of autoimmunity in both rodents and humans.

Humans↗
PubMed2026

FZD5 drives macrophage-mediated immunomodulation and predicts prognosis in glioma: evidence from single-cell sequencing.

BACKGROUND: Gliomas are highly malignant brain tumors characterized by an immunosuppressive microenvironment, which limits therapeutic efficacy and contributes to poor clinical outcomes. The WNT/β-catenin signaling pathway is critically involved in tumor progression, and FZD5, a key receptor within this pathway, may participate in immune regulation. However, its specific role and underlying mechanisms in glioma remain unclear. METHODS: RNA-seq and microarray datasets from the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA), together with single-cell RNA sequencing (scRNA-seq) datasets from GEO, were comprehensively analyzed. The Seurat package was used to identify macrophage-related clusters and mitophagy-associated pathways. Cox and LASSO regression analyses, along with a prognostic nomogram, were applied to evaluate the prognostic significance of FZD5. Immune infiltration, functional enrichment, and immunotherapy response analyses were conducted, followed by validation using spatial transcriptomics, immunohistochemistry, and in vitro assays. RESULTS: In bulk glioma transcriptomes, FZD5 emerged as an independent predictor of poor prognosis. Crucially, single-cell and spatial analyses revealed that the biologically significant FZD5 signal originated predominantly within tumor-associated macrophages (TAMs), where it colocalized with the M2 marker CD163. Consistently, elevated FZD5 levels correlated with increased myeloid infiltration and an immunosuppressive tumor microenvironment. Functionally, macrophage-expressed FZD5 was associated with mitophagy-related programs and promoted an M2-skewed phenotype, thereby enhancing glioma cell proliferation, migration, and invasion via macrophage-glioma crosstalk. CONCLUSION: FZD5 is a TAM-enriched marker in glioma tissues and a potential regulator of macrophage-associated immunosuppressive programs, supporting its utility as a prognostic biomarker and a candidate target for microenvironment-oriented interventions in glioma.

Humans↗
PubMed2026

Radiogenomics predicts immune microenvironment heterogeneity and response to combination immunotherapy in hepatocellular carcinoma.

BACKGROUND: The combination of immune checkpoint inhibitors (ICIs) with anti-angiogenic agents is the preferred first-line therapy option for patients with advanced hepatocellular carcinoma (HCC), yet only a subset of patients responds, urging the quest for prediction biomarkers. We aimed to integrate genomics with radiology to propose an immune-derived radiogenomics biomarker of response to such combination immunotherapy and evaluate its added value in clinical context. METHODS: We integrated bulk RNA sequencing (RNA-seq) and proteomics data of 994 HCC patients with single-cell RNA-seq data of 11 samples across multiple datasets to identify an immune-related signature (IRS) that may influence sensitivity or resistance to such combined immunotherapy strategy, followed by verification of selected marker genes using immunohistochemistry and cytological experiments. We then trained/validated a cross-modality radiogenomics biomarker using machine learning based on TCIA database that was further tested in multi-scale independent cohorts covering 754 HCC patients. RESULTS: Integrative multi-omics analysis identifed a parsimonious 2-gene prognostic signature including KPNA2 and SMG5 that was significantly associated with immune heterogeneity and response to combination immunotherapy. Machine-learning pipeline exported the optimal 4-feature radiogenomics biomarker using support vector machine that significantly discriminated prognosis (hazard ratio 1.415&#x2013;1.890; p&#x2009;<&#x2009;0.05 for all) and modestly predicted response to ICI plus anti-angiogenic therapy (area under the curve 0.720&#x2013;0.829) in independent retrospective series across major imaging modalities (computed tomography/magnetic resonance imaging). In a prospective neoadjuvant cohort, this biomarker also showed favorable performance for predicting pathological response and tumor recurrence, accompanied by biological validation through single-cell RNA-seq analysis of pre-treatment biopsies. CONCLUSIONS: Our study provides a cross-device-cross-modal radiogenomics biomarker that can improve patient selection for emerging ICI plus anti-angiogenic therapy with novel potential therapeutic targets in HCC.

Humans↗
PubMed2026

Multimodal Analysis Reveals Aberrant Expression of SUMO2 and Its Significant Association With Key Mechanisms of Metabolic Pathways in Hepatocellular Carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related deaths worldwide. However, the role of small ubiquitin-like modifier 2 (SUMO2), a core member of the small ubiquitin-like modifier (SUMO) family, regarding its expression patterns and metabolism-related functions in HCC remains inadequately understood. METHODS: A multidimensional analytical framework was applied, integrating immunohistochemistry (153 HCC vs. 21 non-HCC samples), proteomics (159 paired samples), bulk transcriptomics (3240 HCC vs. 2267 non-HCC samples), single-cell RNA sequencing (RNA-seq) (10 HCC vs. 8 non-HCC samples), spatial transcriptomics, and external CRISPR/Cas9 functional genomics data. Systematic analyses included standardized mean difference (SMD), pathway enrichment, pseudotime trajectory inference, in silico knockout, cell-cell communication, metabolic flux scoring, immune infiltration, clinical correlation, drug sensitivity prediction, and molecular docking. RESULTS: At the protein level, immunohistochemistry (nuclear positivity) and external proteomic data collectively demonstrated consistent SUMO2 overexpression in HCC. Consistent upregulation was also observed at the mRNA level across large-scale cohorts. Single-cell RNA-seq and spatial transcriptomics localized SUMO2 enrichment to malignant hepatocytes and tumor-dominant regions. CRISPR-mediated SUMO2 knockout suppressed proliferation in multiple HCC cell lines. Mechanistically, high SUMO2 expression was significantly associated with metabolic reprogramming involving glycolysis/gluconeogenesis, pyruvate metabolism, and the tricarboxylic acid cycle. SUMO2-high malignant hepatocyte subpopulations exhibited enhanced activity of the macrophage migration inhibitory factor signaling axis and enhanced iron-sensor interactions. Further, the immune infiltration analysis revealed a negative correlation between SUMO2 expression and M1 macrophages and a positive correlation between follicular helper T cells and regulatory T cells. Clinically, elevated SUMO2 levels were found to be associated with adverse prognostic features. Furthermore, high SUMO2 expression was associated with increased sensitivity to dasatinib, and molecular docking simulations predicted potential binding between SUMO2 and dasatinib, with a Vina score of -8.5 kcal/mol. CONCLUSIONS: SUMO2 is aberrantly expressed at the protein, mRNA, single-cell, and spatial transcriptomic levels in HCC and is significantly associated with metabolic reprogramming and altered migration inhibitory factor (MIF)-mediated intercellular communication, suggesting its potential as a novel biomarker for diagnosis and treatment.

Humans↗