Oral tongue squamous cell carcinoma diagnosis from tissue metabolic profiling

Shuai Wang; Ke Li; Tong Zhao; Yawei Sun; Tao Zeng; Yan Wu; Liang Ding; Xiaofeng Huang; Antonio Celentano; Xihu Yang; Qingang Hu; Yanhong Ni

doi:10.1111/odi.14696

Oral tongue squamous cell carcinoma diagnosis from tissue metabolic profiling

Oral Dis. 2023 Jul 24. doi: 10.1111/odi.14696. Online ahead of print.

Authors

Shuai Wang^{1

2}, Ke Li^{1

2}, Tong Zhao¹, Yawei Sun², Tao Zeng³, Yan Wu^{1

4}, Liang Ding¹, Xiaofeng Huang⁴, Antonio Celentano⁵, Xihu Yang⁶, Qingang Hu², Yanhong Ni^{1

2}

Affiliations

¹ Central Laboratory of Stomatology, Nanjing Stomatological Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, China.
² Department of Oral and Maxillofacial Surgery, Nanjing Stomatological Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, China.
³ State Key Lab of Pharmaceutical Biotechnology, College of Life Sciences, Nanjing University, Nanjing, Jiangsu, China.
⁴ Department of Oral Pathology, Nanjing Stomatological Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, Jiangsu, China.
⁵ Melbourne Dental School, The University of Melbourne, Carlton, Victoria, Australia.
⁶ Department of Oral and Maxillofacial Surgery, Affiliated Hospital of Jiangsu University, Zhenjiang, Jiangsu, China.

PMID: 37486619
DOI: 10.1111/odi.14696

Abstract

Objective: Disease metabolomes have been studied for identifying diagnostic and predictive biomarkers of pathology. Oral tongue squamous cell carcinoma (OTSCC) is one of the most prevalent subtypes of head and neck squamous cell carcinoma, yet the profile and diagnostic value of its tissue metabolite are unclear.

Subjects and methods: Tumor tissue samples and matched normal mucosal tissue samples were collected from 40 OTSCC patients. Untargeted metabolic analysis by liquid chromatography-mass spectrometry/mass spectrometry, in positive and negative ion modes, was used to identify dysregulated metabolites in OTSCC. Further, utilizing LASSO regression and receiver operating characteristic analyses, biomarker metabolites were selected and validated, and a diagnostic model was established.

Results: One hundred and ninety metabolites were detected. The OTSCC had a total of 89 dysregulated metabolites, of which 73 were elevated. A diagnostic panel of nine metabolites was subsequently created that could accurately identify OTSCC with 100% sensitivity of 100%, 100% specificity and an AUC of 1.00.

Conclusions: This study identified distinct metabolic characteristics of OTSCC and established a diagnostic model. Our research also contributes to the investigation of the pathogenesis of OTSCC.

Keywords: biomarkers; cancer tissue; diagnostic model; metabolomics; oral tongue squamous cell carcinoma.

Abstract

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