Adapting the MasSpec Pen for noninvasive detection of oral cavity squamous cell carcinoma

Oral Cavity Squamous Cell Carcinoma (OCSCC) is a common and deadly form of head and neck cancer which disproportionately afflicts low- and middle-income communities. Since the majority of OCSCC lesions are visible within the oral cavity, visual exam-guided biopsy remains the standard method for detection. However, visual examination can be subjective, biopsy can be painful, and pathological evaluation can be time consuming. With the goal of developing an accessible and noninvasive platform for OCSCC detection, we adapted the MSPen technology as a modular system for direct molecular analysis of OCSCC in vivo. The modular MSPen (Mod-MSPen) system consists of a controller unit and a disposable handheld device that directly contacts tissues, performs gentle liquid extraction of molecules, and collects the sample in a vial for subsequent mass spectrometric analysis. We have used the Mod-MSPen to analyze OCSCC and normal oral tissues spanning various anatomical areas: tongue, buccal mucosa, gingiva, and floor of mouth. The molecular data obtained presented distinct trends in the abundances of metabolites such as glutamate, which was consistently observed in higher relative abundances in OCSCC tissues when compared to normal oral tissues. These trends were corroborated using mass spectrometry imaging, which revealed clear spatio-molecular differences in OCSCC and adjacent normal oral mucosa tissues. Statistical classifiers built from the data provided high performance for disease detection, with >95% agreement with standard histopathology. To evaluate clinical suitability, we also deployed the Mod-MSPen for in vivo analysis of OCSCC and normal oral tissues alongside clinical procedures.

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Journal
Proceedings of the National Academy of Sciences
Published
2026-08-03
DOI
https://doi.org/10.1073/pnas.2603602123
Primary Topic
Advanced Proteomics Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Adapting the MasSpec Pen for noninvasive detection of oral cavity squamous cell carcinoma

Faith Jackobs, Brian Armijo, Charles A. Wolfe, Erich M. Sturgis et al.
Proceedings of the National Academy of Sciences
Advanced Proteomics Techniques and Applications
article

Adapting the MasSpec Pen for noninvasive detection of oral cavity squamous cell carcinoma

Faith Jackobs, Brian Armijo, Charles A. Wolfe, Erich M. Sturgis, Junaid Ibrahim, C.J.R. DE CARVALHO, Marcos N. Eberlin, Sarah Bench, Ashley E. Montgomery, Andrew T. Huang, Carlos T. Chone, Nelson E. Liou, Livia S. Eberlin, Renan V. de Brito, Tassia V. Mendes, Robert Tibshirani, Emily X. Ma
article en

Abstract

Oral Cavity Squamous Cell Carcinoma (OCSCC) is a common and deadly form of head and neck cancer which disproportionately afflicts low- and middle-income communities. Since the majority of OCSCC lesions are visible within the oral cavity, visual exam-guided biopsy remains the standard method for detection. However, visual examination can be subjective, biopsy can be painful, and pathological evaluation can be time consuming. With the goal of developing an accessible and noninvasive platform for OCSCC detection, we adapted the MSPen technology as a modular system for direct molecular analysis of OCSCC in vivo. The modular MSPen (Mod-MSPen) system consists of a controller unit and a disposable handheld device that directly contacts tissues, performs gentle liquid extraction of molecules, and collects the sample in a vial for subsequent mass spectrometric analysis. We have used the Mod-MSPen to analyze OCSCC and normal oral tissues spanning various anatomical areas: tongue, buccal mucosa, gingiva, and floor of mouth. The molecular data obtained presented distinct trends in the abundances of metabolites such as glutamate, which was consistently observed in higher relative abundances in OCSCC tissues when compared to normal oral tissues. These trends were corroborated using mass spectrometry imaging, which revealed clear spatio-molecular differences in OCSCC and adjacent normal oral mucosa tissues. Statistical classifiers built from the data provided high performance for disease detection, with >95% agreement with standard histopathology. To evaluate clinical suitability, we also deployed the Mod-MSPen for in vivo analysis of OCSCC and normal oral tissues alongside clinical procedures.

Proceedings of the National Academy of SciencesVol. 123(32)
Universidade Estadual de Campinas (UNICAMP) (BR), Baylor College of Medicine (US), Universidade Presbiteriana Mackenzie (BR), Stanford University (US)
Welch Foundation
No poverty
Openalex Percentile: Top 18%
Advanced Proteomics Techniques and Applications
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