A Deep Learning Enabled Single Cell Morpholomic Atlas of Nasal Swabs Distinguishes Chronic Inflammation from Sinonasal Malignancy

ABSTRACT

Background: Sinonasal malignancies frequently present with symptoms overlapping chronic inflammatory conditions such as chronic rhinosinusitis (CRS), complicating early detection and delaying treatment. A fast, scalable, non-invasive approach capable of resolving immune and epithelial cell states across inflammatory and malignant disease from routine nasal swabs could substantially improve clinical screening, leading to the initiation of appropriate treatment.

Methods: We developed a deep learning–enabled single-cell morpholomic framework using the REM-I platform to generate a reference atlas of >641K cell brightfield images from purified immune cell populations. This reference atlas was applied to >2.5 million images obtained from nasal swabs spanning a clinical spectrum of health, CRS, and sinonasal carcinoma. Embeddings were integrated using dimensionality reduction for differential feature testing and comparative feature enrichment across disease states.

Findings Across the disease continuum, sinonasal carcinoma samples exhibited distinct immune remodeling, including increased myeloid-like cell abundance and elevated small dark pixel intensity consistent with enhanced granulocyte activity. Basophil/NK-enriched clusters contained tumor-associated cells with deep learning–derived morphologic signatures not observed in CRS or healthy samples. Tumor-associated epithelial cells were significantly smaller and displayed disease-specific morpholomic patterns distinct from chronic inflammation.

Conclusions This study establishes a deep learning–enabled single-cell morpholomic atlas of nasal swabs spanning healthy epithelium, chronic inflammation and sinonasal malignancies. Morpholomic cytology reveals reproducible immune and epithelial states associated with inflammatory and malignant disease and provides a scalable, non-invasive framework for cellular stratification in sinonasal pathology, supporting future applications in early point-of-care diagnostics.

Competing Interest Statement

K.M.B., B.T.R. and Q.T.E. are all active members of the Human Cell Atlas. Furthermore, K.M.B. is a scientific advisor at Arcato Laboratories (Durham, NC) as well as the CEO and co-founder of Stratica Biosciences (Durham, NC). A.J., K.S. and M.B are employees of Deepcell, Inc. All other authors declare no competing financial interests.

Funding Statement

The authors acknowledge funding support from the American Dental Association Science and Research Institute (Startup funds), the Chan Zuckerberg Initiative (2021-237918), and Virginia Commonwealth University (Startup funds from Philips Institute for Oral Health Research and Massey Comprehensive Cancer Center, and Massey Cancer Center Harrison Scholars Award).

Author Declarations

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The institutional review board (IRB) of the University of North Carolina gave ethical approval for this work (#UNC-IRB-17-2677)

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

Yes

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Yes

Data Availability

All data produced in the present study are available upon reasonable request to the authors

Comments (0)

No login
gif