Evaluation of the Sensitivity of Metabolic Profiling by Rapid Evaporative Ionization Mass Spectrometry: Toward More Radical Oral Cavity Cancer Resections

Abstract

Radical resection for patients with oral cavity cancer remains challenging. Rapid evaporative ionization mass spectrometry (REIMS) of electrosurgical vapors has been reported for real-time classification of normal and tumor tissues for numerous surgical applications. However, the infiltrative pattern of invasion of oral squamous cell carcinomas (OSCC) challenges the ability of REIMS to detect low amounts of tumor cells. We evaluate REIMS sensitivity to determine the minimal amount of detected tumors cells during oral cavity cancer surgery. A total of 11 OSCC patients were included in this study. The tissue classification based on 185 REIMS ex vivo metabolic profiles from five patients was compared to histopathology classification using multivariate analysis and leave-one-patient-out cross-validation. Vapors were analyzed in vivo by REIMS during four glossectomies. Complementary desorption electrospray ionization–mass spectrometry imaging (DESI-MSI) was employed to map tissue heterogeneity on six oral cavity sections to support REIMS findings. REIMS sensitivity was assessed with a new cell-based assay consisting of mixtures of cell lines (tumor, myoblasts, keratinocytes). Our results depict REIMS classified tumor and soft tissues with 96.8% accuracy. In vivo REIMS generated intense mass spectrometric signals. REIMS detected 10% of tumor cells mixed with 90% myoblasts with 83% sensitivity and 82% specificity. DESI-MSI underlined distinct metabolic profiles of nerve features and a metabolic shift phosphatidylethanolamine PE(O-16:1/18:2))/cholesterol sulfate common to both mucosal maturation and OSCC differentiation. In conclusion, the assessment of tissue heterogeneity with DESI-MSI and REIMS sensitivity with cell mixtures characterized sensitive metabolic profiles toward in vivo tissue recognition during oral cavity cancer surgeries.

Applications of ambient ionization mass spectrometry in 2022: An annual review

“…SESI-MS is particularly suited to the analysis of volatile compounds (VOCs) and was recently used to study the VOC profiles of different lung cancer cells (non-small cell and small cell). 60 The REIMS has been applied to the analysis of tissue during glossectomy surgeries 67 and basal cell carcinoma resections 68 in the operating theatre, whereas a method for analyzing brain tumours was also developed outside of the operating theatre through the use of tissue biopsies. 69 Furthermore, REIMS has also been applied to the analysis of canine tissue samples for potential use in veterinary surgery.…”

Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) in disease diagnosis: an overview

“…This study included a total of 11 OSCC patients. 36 The tissue was categorized using 185 REIMS ex vivo metabolic characteristics from patients ( n = 5), and the tissue categorization was compared to histopathology results using multivariate statistical analysis and cross-validation. 36 During four glossectomies, vapors were examined in vivo by REIMS.…”

“…36 The tissue was categorized using 185 REIMS ex vivo metabolic characteristics from patients ( n = 5), and the tissue categorization was compared to histopathology results using multivariate statistical analysis and cross-validation. 36 During four glossectomies, vapors were examined in vivo by REIMS. Six sections of the oral cavity were subjected to DESI-MSI, which was used to map tissue variability and support REIMS findings.…”

“…Six sections of the oral cavity were subjected to DESI-MSI, which was used to map tissue variability and support REIMS findings. 36 A novel cell-based assay made up of different cell lines (keratinocytes, myoblasts, and tumors) was used to evaluate the REIMS' sensitivity. 36 With 96.8% accuracy, REIMS classified soft tissues and tumors.…”

“…36 A novel cell-based assay made up of different cell lines (keratinocytes, myoblasts, and tumors) was used to evaluate the REIMS' sensitivity. 36 With 96.8% accuracy, REIMS classified soft tissues and tumors. Strong mass spectrometric signals were produced in vivo by REIMS.…”