Big cohort metabolomic profiling of serum for oral squamous cell carcinoma screening and diagnosis. Issue 1 (15th November 2021)

• Record Type: Journal Article
• Authors: Yang, Xihu; Song, Xiaowei; Yang, Xudong; Han, Wei; Fu, Yong; Wang, Shuai; Zhang, Xiaoxin; Sun, Guowen; Lu, Yong; Wang, Zhiyong; Ni, Yanhong; Zare, Richard N.; Hu, Qingang
• Is Part Of: Natural sciences. Volume 2:Issue 1(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-11-15
• Subjects: conductive polymer spray ionization mass spectrometry -- machine learning -- oral squamous cell carcinoma -- screening -- and in vitro diagnosis -- serum metabolic profiling; Science -- Periodicals; 505
• DOI: 10.1002/ntls.20210071
• Languages: English
• ISSNs: 2698-6248

Abstract

Abstract: The survival rate of oral squamous cell carcinoma (OSCC) can be greatly improved if intervention could be initiated as early as possible. This poses a technical demand for developing a sensitive screening and specific in vitro diagnosis method for OSCC. Herewith, a large cohort consisting of 241 healthy contrast (HC) and 578 OSCC patients were recruited for conducting the rapid metabolic profiling of trace volume serum using conductive polymer spray ionization mass spectrometry (CPSI‐MS). Statistical analysis picked out 65 metabolite ions as potential characteristic markers for differentiating OSCC from HC. With the aid of a supporting vector machine (SVM), OSCC can be distinguished from HC with an accuracy of 98.0% by cross‐validation in the discovery cohort and 89.6% accuracy in the validation cohort. Furthermore, orthogonal partial least square‐discriminant analysis (OPLS‐DA) also initially showed the potential for OSCC staging, especially between T1/T2 and T3/T4 stages with an accuracy of 90.1%. CPSI‐MS combined with SVM or OPLS‐DA can not only quickly distinguish OSCC from HC but also predict the OSCC progression from T1/2 to T3/4 stages in a few minutes, making it a promising tool for both screening and diagnosing high‐risk population. Key points: Sixty‐five characteristic metabolite ions significantly changed in OSCC serum metabolic profile compared to that in the HC group. CPSI‐MS combined with SVM achieved 89.6% accuracy on the validation cohort for OSCC prediction. CPSI‐MS/OPLS‐DA can distinguish T1/T2 from T3/T4 stages with an accuracy of 90.1% by cross‐validation. Abstract : Conductive polymer spray ionization mass spectrometry can conduct metabolic profiling from a trace volume of serum to serve as a sensitive screening and specific diagnostic method for oral squamous cell carcinoma