ArticleHead & neck2026
Magnifying Glass on Sinonasal NUT Carcinoma Heterogeneity via Spatial Transcriptomics.
Article in Head & neck, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Immune biomarker landscape and fusion partner-phenotype associations in thoracic and head-and-neck NUT carcinoma.Frontiers in immunology · 2026Article
- Perspective on the integration of radiomics and spatial omics in the analysis of the tumor microenvironment of bladder cancer and prospects for precision diagnosis and treatment.Frontiers in immunology · 2026Review
- Magnifying Glass on Sinonasal NUT Carcinoma Heterogeneity via Spatial Transcriptomics.Head & neck · 2026Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundNuclear protein in testis (NUT) carcinomas (NCs) are rare, clinically aggressive tumors with characteristic translocation involving NUTM1 and BRD4 genes. While NCs are generally characterized by undifferentiated basaloid cells with focal/abrupt squamous differentiation, tumoral heterogeneity remains unexplored. This may have therapeutic implications as NC frequently develops drug resistance and metastasis. Spatial transcriptomics (ST) sequencing technology emerged as an approach to elucidate tumoral heterogeneity by integrating cellular transcriptome and spatial distributions within tissues, providing insights into the interactions among different cell types and overall tissue genomic architecture.
methodsThree cases of sinonasal NC with formalin-fixed paraffin embedded tissue formed the study material. A representative region of each NC was subjected to 10X Genomics Visium Spatial Gene Expression analysis. Resulting data were analyzed in 10X Genomics Loupe Browser.
resultsAll cases demonstrated statistically distinct (graph-neural network based) transcriptomic clusters. These clusters were correlated with histologic characteristics by parsing all spots by region types based on tissue distribution including tumor, limited stroma, and normal epithelium. Cluster constitution and transcriptomic pattern were consistent with the morphologic features of each tissue region. NC#3 had a relatively low number of tumor clusters in comparison to NC#1 and NC#2.
conclusionsSpatial transcriptomic profiling corresponds to histopathologic features in NC and yet highlights cell type diversity across tumors and in the case of NC#2, within a given tumor. Behavioral correlates are speculative, but NC#3 for which the patient had a rapidly lethal outcome showed a preponderance of neural gene expression which may be of interest in tumor cell progression/evolution.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.