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2701 results

Full text 2026

Non-destructive transcriptomics via vesicular export

Armbrust N, Grosshauser M, Geilenkeuser J, et al.

Transcriptomics enables comprehensive, multiplexed characterization of cellular states, yet prevailing methods typically require cell fixation or lysis, precluding longitudinal analysis of RNA expression in living cells. Here, we present non-destructive transcriptomics by vesicular export (NTVE), …

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Transcriptomics
Full text 2026

Differential expression analysis for spatially correlated data using smiDE

Vasconcelos AG, McGuire D, Simon N, et al.

Differential expression is a key application of imaging spatial transcriptomics, moving analysis beyond cell type localization to examining cell state responses to microenvironments. However, spatial data poses new challenges to differential expression: segmentation errors cause …

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Transcriptomics
Full text 2026

Prognostic genes in hepatocellular carcinoma and their function: an analysis integrating high-throughput-based spatial transcriptomics and single-cell RNA-sequencing

Zhang Y, Yao Y, Yan Z, et al.

<h4>Background</h4>Identifying novel prognostic indicators for patients with hepatocellular carcinoma (HCC) is critical to improving patient outcomes. Mapping the spatial composition of HCC tumors remains challenging. Therefore, this study aimed to identify prognostic genes and assess …

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Transcriptomics
Full text 2026

Single-cell transcriptomics reveals hair growth retardation mediated by aberrant connective tissue sheath contraction in male androgenetic alopecia

Li G, Yang L, Duan S, et al.

Androgenetic alopecia (AGA) manifests as progressive hair follicle (HF) miniaturization; however, its drivers remain poorly elucidated. Combining spatial and single-cell transcriptomics, we generate a concise single-cell atlas of anagen HFs in male AGA, revealing early …

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Single-Cell Transcriptomics
Full text 2026

CBX3:IL1RN Reflects Distinct Cellular States That Defines the Clinical Outcome of Oral Squamous Cell Carcinoma

Tian X, Mao J, Li D, et al.

<h4>Background</h4>Oral squamous cell carcinoma (OSCC) exhibits heterogeneous therapeutic outcomes owing to various tumor microenvironments (TMEs). Previous studies have classified OSCC according to its molecular characteristics; however, clinical practice is limited by technical complexity.<h4>Methods</h4>A total of …

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Bioinformatics Single-Cell Transcriptomics
Full text 2026

Metabolic reprogramming in the enterocytes of neonatal piglets infected with porcine epidemic diarrhea virus: integrated omics and multi-batch analysis highlight alterations in lipid metabolism and potential therapeutic targets

Wu M, Zhang Q, Shi X, et al.

Porcine epidemic diarrhea (PED) is a severe viral disease caused by the porcine epidemic diarrhea virus (PEDV), leading to huge economic losses in the swine industry. Identifying therapeutic targets has long been a critical challenge …

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Transcriptomics
Full text 2026

Toward Precision Health in Autoimmunity and Immune-Related Adverse Events: The Autoantibody Reactome, Spatial Omics, and Multimodal Data Integration

Stensballe A.

The autoantibody reactome refers to the multidimensional repertoire of antibody reactivities against self-antigens across the human proteome or selected antigenic compartments. This offers a scalable systemic layer for precision immunology across spontaneous autoimmunity and treatment-induced …

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Transcriptomics
Full text 2026

Single-cell and spatial profiling reveal cDC2A-CXCL13&lt;sup&gt;+&lt;/sup&gt;CD8&lt;sup&gt;+&lt;/sup&gt; T-epithelial cell crosstalk and cytotoxicity through TNFRSF9 in cutaneous and mucosal lichen planus

Jiang R, Bogle R, Xing X, et al.

Lichen planus (LP) is a chronic inflammatory disease of the skin and mucous membranes, marked by T cell infiltration and keratinocyte apoptosis. However, its immune microenvironment remains poorly understood. Using single-cell RNA sequencing, spatial transcriptomics, …

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Transcriptomics
Full text 2026

Translating spatial transcriptomic signatures in adenosquamous carcinoma into bulk prognostic biomarkers in lung adenocarcinoma: a bottom-up approach

Hatakeyama K, Kawata T, Muramatsu K, et al.

Spatial transcriptomics enables the detection of rare or transitional tumor states not captured by bulk transcriptomics or immunohistochemistry (IHC). However, translating these spatially defined states into clinically relevant biomarkers is challenging, because signals from minor …

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Transcriptomics