Evidence map›Paper›PMID 42332074›Full record

ArticleNPJ precision oncology2026

Deep learning-enabled single-cell morpholomic atlas of nasal swabs distinguishes chronic inflammation from sinonasal malignancy.

Brittany T Rupp, Andreja Jovic, Theresa Weaver, Kiran Saini, Meghan Burr, W Jared Martin, Quinn T Easter, Adam J Kimple, Kevin Matthew Byrd

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Article in NPJ precision oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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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.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Brittany T RuppDepartment of Oral and Craniofacial Molecular Biology, Philips Institute for Oral Health Research, Virginia Commonwealth University, Richmond, VA, USA.
Andreja JovicDeepcell Inc., Menlo Park, CA, USA.
Theresa WeaverDepartment of Oral and Craniofacial Molecular Biology, Philips Institute for Oral Health Research, Virginia Commonwealth University, Richmond, VA, USA.
Kiran SainiDeepcell Inc., Menlo Park, CA, USA.
Meghan BurrDeepcell Inc., Menlo Park, CA, USA.
W Jared MartinDepartment of Otolaryngology-Head and Neck Surgery, University of North Carolina School of Medicine, Chapel Hill, NC, USA.
Quinn T EasterDepartment of Oral and Craniofacial Molecular Biology, Philips Institute for Oral Health Research, Virginia Commonwealth University, Richmond, VA, USA.
Adam J KimpleDepartment of Otolaryngology-Head and Neck Surgery, University of North Carolina School of Medicine, Chapel Hill, NC, USA.
Kevin Matthew ByrdDepartment of Oral and Craniofacial Molecular Biology, Philips Institute for Oral Health Research, Virginia Commonwealth University, Richmond, VA, USA. byrdk6@vcu.edu.

Funding

American Dental Association Science and Research Institute Startup fundsChan Zuckerberg Initiative 2021-237918Virginia Commonwealth University Startup funds from Philips Institute for Oral Health Research and Massey Comprehensive Cancer Center
6 · The paper itself

Abstract

Sinonasal malignancies frequently present with symptoms overlapping chronic inflammatory conditions, complicating early detection and delaying treatment. A fast, non-invasive approach capable of resolving cell states across inflammatory and malignant disease from routine nasal swabs could substantially improve clinical screening. Using the REM-I platform, we generated a reference atlas of deep learning-enabled single-cell morpholomic features from >641K immune cell brightfield images. This reference atlas was integrated with >2.5 M images obtained from nasal swabs spanning health, chronic rhinosinusitis (CRS), and sinonasal carcinoma to perform differential feature testing and comparative feature enrichment across disease states. Sinonasal carcinoma samples exhibited distinct immune remodeling, including increased myeloid-enriched cell abundance and elevated small dark pixel intensity consistent with enhanced granulocyte activity. Basophil/NK-enriched clusters and epithelial clusters contained tumor-associated cells with deep learning-derived morphologic signatures not observed in CRS or healthy samples. These findings support the potential use of nasal swabs in early point-of-care diagnostics.

Identifiers

PMID42332074

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