Development of point-of-care spectroscopic technology for the noninvasive diagnosis of skin diseases: Epidermolysis bullosa and cutaneous squamous cell carcinoma

Noninvasive molecular profiling technologies have the potential to transform the diagnosis and management of dermatological disease by enabling rapid, objective assessment of tissue pathology directly at the point-of-care. Following our recent mini-review on "Raman Spectroscopy and SERS for the Detection of Rare Diseases in Clinical Practice", J. L.Thomas, P. Goldberg Oppenheimer et al., Applied Spectroscopy Reviews, 2026), we have developed an advanced portable spectroscopic technology integrated with machine-learning analytics for label-free molecular phenotyping of skin at the point-of-care. The technology was validated in epidermolysis bullosa, a group of skin disorders characterized by tissue fragility, chronic wounds, and diagnostic and monitoring challenges. We identified disease-associated biochemical signatures reflecting extracellular matrix remodeling, collagen organization, lipids, and inflammatory microenvironment changes, while discriminating dystrophic EB from healthy tissue with 99%-diagnostic accuracy from intact ex-vivo tissues, as a proof-of-concept. Our uniquely developed AI algorithm further associated key-discriminatory spectral features with molecular alterations linked to dermal–epidermal junction disruption. We also demonstrate the ability to diagnose cutaneous squamous cell carcinoma (cSCCs) arising in EB patients and distinguish them from non-EB SCCs, highlighting exclusive spectral and biomolecular underpinnings, and evidencing a unique tumor microenvironment. The technology is inherently disease-agnostic and readily adaptable to a broad range of dermatological conditions characterized by molecular heterogeneity and overlapping clinical presentation. By combining the portable device, bedside-compatible acquisition, and AI-driven molecular interpretation, this technology could provide a scalable framework for the potential noninvasive skin phenotyping, patient-stratification and longitudinal-monitoring, establishing it as a powerful platform for precision dermatology with broad translational potential across skin diseases.

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Publication Details

Journal
Applied Spectroscopy Reviews
Published
2026-10-29
DOI
https://doi.org/10.1080/05704928.2026.2745629
Primary Topic
Spectroscopy Techniques in Biomedical and Chemical Research
Type
article
Field-Weighted Citation Impact
0.00

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article

Development of point-of-care spectroscopic technology for the noninvasive diagnosis of skin diseases: Epidermolysis bullosa and cutaneous squamous cell carcinoma

Adrian Heagerty, Pola Goldberg Oppenheimer, Ajoy Bardhan, Divya Khanna et al.
1 links
Applied Spectroscopy Reviews
Spectroscopy Techniques in Biomedical and Chemical Research
article

Development of point-of-care spectroscopic technology for the noninvasive diagnosis of skin diseases: Epidermolysis bullosa and cutaneous squamous cell carcinoma

Adrian Heagerty, Pola Goldberg Oppenheimer, Ajoy Bardhan, Divya Khanna, Jarrod L Thomas, L. S. Yiu Daniel, Jonathan J. S. Rickard
article en

Abstract

Noninvasive molecular profiling technologies have the potential to transform the diagnosis and management of dermatological disease by enabling rapid, objective assessment of tissue pathology directly at the point-of-care. Following our recent mini-review on "Raman Spectroscopy and SERS for the Detection of Rare Diseases in Clinical Practice", J. L.Thomas, P. Goldberg Oppenheimer et al., Applied Spectroscopy Reviews, 2026), we have developed an advanced portable spectroscopic technology integrated with machine-learning analytics for label-free molecular phenotyping of skin at the point-of-care. The technology was validated in epidermolysis bullosa, a group of skin disorders characterized by tissue fragility, chronic wounds, and diagnostic and monitoring challenges. We identified disease-associated biochemical signatures reflecting extracellular matrix remodeling, collagen organization, lipids, and inflammatory microenvironment changes, while discriminating dystrophic EB from healthy tissue with 99%-diagnostic accuracy from intact ex-vivo tissues, as a proof-of-concept. Our uniquely developed AI algorithm further associated key-discriminatory spectral features with molecular alterations linked to dermal–epidermal junction disruption. We also demonstrate the ability to diagnose cutaneous squamous cell carcinoma (cSCCs) arising in EB patients and distinguish them from non-EB SCCs, highlighting exclusive spectral and biomolecular underpinnings, and evidencing a unique tumor microenvironment. The technology is inherently disease-agnostic and readily adaptable to a broad range of dermatological conditions characterized by molecular heterogeneity and overlapping clinical presentation. By combining the portable device, bedside-compatible acquisition, and AI-driven molecular interpretation, this technology could provide a scalable framework for the potential noninvasive skin phenotyping, patient-stratification and longitudinal-monitoring, establishing it as a powerful platform for precision dermatology with broad translational potential across skin diseases.

Applied Spectroscopy Reviews
University Hospitals Birmingham NHS Foundation Trust (GB), University of Cambridge (GB), Solihull Hospital (GB), University of Birmingham (GB)
Wellcome Trust, National Institute for Health and Care Research, Engineering and Physical Sciences Research Council
Good health and well-being
Openalex Percentile: Top 20%
Spectroscopy Techniques in Biomedical and Chemical Research
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