Integrated Non-targeted and Targeted Metabolomics Uncovers Amino Acid Markers of Oral Squamous Cell Carcinoma

Abstract

Purpose: It is very important to develop potential molecular associated with oral squamous cell carcinoma (OSCC) malignant transformation and progression. Thus, the aim of our study was to determine the amino acid metabolic characteristics of OSCC patients and test their diagnostic value.Experimental Design: Eight pairs of matched tumor and normal samples were collected for gas chromatography-mass spectrometry (GC-MS) high-throughput untargeted analysis. Another 20 cases (each case including tumor and normal tissues) were also enrolled for ultrahigh-performance liquid chromatography-tandem mass spectrometer (UHPLC-MS/MS) amino acid quantitative analysis. T-test and receiver operating characteristic (ROC) curve analysis were used to determine candidate markers. Principal component analysis, partial least squares discriminant analysis, and heat map analysis were used to verify the ability of candidate markers to distinguish tumors from normal tissues.Results: A total of 10 amino acids biomarker were selected as OSCC candidate diagnostic biomarkers by GC-MS high-throughput untargeted metabolomics analyses [area under the curve (AUC) >0.80]. We further measured the specific concentration of these candidate amino acids biomarkers in another batch of 20 cases by UHPLC-MS/MS quantitative analysis. The result validated that nine amino acids had been detected, which had statistically significant difference (t-test, p < 0.05). Moreover, three of nine amino acid markers (glutamate, aspartic acid, and proline) displayed high sensitivity and specificity (AUC >0.90) by ROC curve analysis and obtained optimal sensitivity and specificity by binary logistic regression in the Glmnet package (AUC = 0.942). Conclusions:In conclusion, a panel including three amino acids (glutamate, aspartic acid, and proline) was identified as potential diagnostic biomarkers of OSCC by a combination of non-targeted and targeted metabolomics methods.

Identification of a Transcriptional Prognostic Signature From Five Metabolic Pathways in Oral Squamous Cell Carcinoma

“…Moreover, high expression of CA9 and PGAM1 were associated with inferior prognosis in OSCC, which in part strengthened our data (33,35). Noticeably, Yang et al utilized gas chromatography-mass spectrometry highthroughput analysis to determine the amino acid metabolic characteristics of OSCC and found that a panel including three amino acids (glutamate, aspartic acid, and proline) was identified as potential diagnostic biomarkers of OSCC (37). These findings may add further support to the key roles of dysregulated metabolism responsible for OSCC initiation and progression, thus ultimately impacting patient prognosis.…”

Asparagine Synthetase-Mediated l-Asparagine Metabolism Disorder Promotes the Perineural Invasion of Oral Squamous Cell Carcinoma

“…Although a combination of non-targeted and targeted metabolomics have revealed the aberrant levels of several amino acids from normal epithelium to OSCC, the potential function of dysregulated amino acids metabolism behind OSCC metastasis is still unclear ( 17 ). PNI, as a third route for tumor dissemination besides the local invasion and lymphovascular metastasis, was demonstrated in this study to have correlations with the amino acids metabolism disorder.…”

“…In addition to increased glucose and fatty acids metabolism during cancer progression, amino acid metabolism also increases to match demands for cancer cells growth and metastasis ( 16 ). For example, by a combination of non-targeted and targeted metabolomics, a panel including three amino acids ( l -glutamate, l -aspartic acid, and l -proline) was identified as potential diagnostic biomarkers of OSCC ( 17 ). l -tryptophan metabolism promotes tumor invasion, metastasis and dysregulates immune cells infiltration thereby accelerating cancer progression ( 18 , 19 ).…”

Targeted Metabolomics Identifies Plasma Biomarkers in Mice with Metabolically Heterogeneous Melanoma Xenografts

“…Targeted metabolomics uses reference standards for metabolite identification, making it more sensitive and accurate compared to untargeted metabolomics, thereby allowing absolute quantification of metabolites of interest [ 34 ]. Numerous studies of various cancer types have used both untargeted and targeted metabolomics for the discovery of biomarkers or the evaluation of cancer therapies [ 36 , 37 , 38 , 39 ].…”