TY - JOUR
T1 - Metabolomics of head and neck cancer in biofluids
T2 - an integrative systematic review
AU - Chuchueva, Natalia
AU - Carta, Filippo
AU - Nguyen, Hoang N.
AU - Luevano, Jennifer
AU - Lewis, Isaiah A.
AU - Rios-Castillo, Israel
AU - Fanos, Vassilios
AU - King, Emma
AU - Swistushkin, Valery
AU - Reshetov, Igor
AU - Rusetsky, Yury
AU - Shestakova, Ksenia
AU - Moskaleva, Natalia
AU - Mariani, Cinzia
AU - Castillo-Carniglia, Alvaro
AU - Grapov, Dmitry
AU - Fahrmann, Johannes
AU - La Frano, Michael R.
AU - Puxeddu, Roberto
AU - Appolonova, Svetlana A.
AU - Brito, Alex
N1 - Funding Information:
The work was financed by the Ministry of Science and Higher Education of the Russian Federation within the framework of state support for the creation and development of World-Class Research Centers “Digital Biodesign and Personalized Healthcare” Nº075-15–2022-304. ACC received funding from the Millennium Science Initiative Program, Nº NCS2021_003 and Nº NCS2021_013.
Publisher Copyright:
© 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2023/9
Y1 - 2023/9
N2 - Introduction: Head and neck cancer (HNC) is the fifth most common cancer globally. Diagnosis at early stages are critical to reduce mortality and improve functional and esthetic outcomes associated with HNC. Metabolomics is a promising approach for discovery of biomarkers and metabolic pathways for risk assessment and early detection of HNC. Objectives: To summarize and consolidate the available evidence on metabolomics and HNC in plasma/serum, saliva, and urine. Methods: A systematic search of experimental research was executed using PubMed and Web of Science. Available data on areas under the curve was extracted. Metabolic pathway enrichment analysis were performed to identify metabolic pathways altered in HNC. Fifty-four studies were eligible for data extraction (33 performed in plasma/serum, 15 in saliva and 6 in urine). Results: Metabolites with high discriminatory performance for detection of HNC included single metabolites and combination panels of several lysoPCs, pyroglutamate, glutamic acid, glucose, tartronic acid, arachidonic acid, norvaline, linoleic acid, propionate, acetone, acetate, choline, glutamate and others. The glucose-alanine cycle and the urea cycle were the most altered pathways in HNC, among other pathways (i.e. gluconeogenesis, glycine and serine metabolism, alanine metabolism, etc.). Specific metabolites that can potentially serve as complementary less- or non-invasive biomarkers, as well as metabolic pathways integrating the data from the available studies, are presented. Conclusion: The present work highlights utility of metabolite-based biomarkers for risk assessment, early detection, and prognostication of HNC, as well as facilitates incorporation of available metabolomics studies into multi-omics data integration and big data analytics for personalized health.
AB - Introduction: Head and neck cancer (HNC) is the fifth most common cancer globally. Diagnosis at early stages are critical to reduce mortality and improve functional and esthetic outcomes associated with HNC. Metabolomics is a promising approach for discovery of biomarkers and metabolic pathways for risk assessment and early detection of HNC. Objectives: To summarize and consolidate the available evidence on metabolomics and HNC in plasma/serum, saliva, and urine. Methods: A systematic search of experimental research was executed using PubMed and Web of Science. Available data on areas under the curve was extracted. Metabolic pathway enrichment analysis were performed to identify metabolic pathways altered in HNC. Fifty-four studies were eligible for data extraction (33 performed in plasma/serum, 15 in saliva and 6 in urine). Results: Metabolites with high discriminatory performance for detection of HNC included single metabolites and combination panels of several lysoPCs, pyroglutamate, glutamic acid, glucose, tartronic acid, arachidonic acid, norvaline, linoleic acid, propionate, acetone, acetate, choline, glutamate and others. The glucose-alanine cycle and the urea cycle were the most altered pathways in HNC, among other pathways (i.e. gluconeogenesis, glycine and serine metabolism, alanine metabolism, etc.). Specific metabolites that can potentially serve as complementary less- or non-invasive biomarkers, as well as metabolic pathways integrating the data from the available studies, are presented. Conclusion: The present work highlights utility of metabolite-based biomarkers for risk assessment, early detection, and prognostication of HNC, as well as facilitates incorporation of available metabolomics studies into multi-omics data integration and big data analytics for personalized health.
KW - Big data
KW - Biomarkers
KW - Head and neck cancer
KW - Malignancies
KW - Metabolites
KW - Metabolome
KW - Metabolomics
KW - Omics
KW - Oncology
KW - Personalized health
KW - Squamous cell carcinoma
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U2 - 10.1007/s11306-023-02038-2
DO - 10.1007/s11306-023-02038-2
M3 - Review article
C2 - 37644353
AN - SCOPUS:85168963927
SN - 1573-3882
VL - 19
JO - Metabolomics
JF - Metabolomics
IS - 9
M1 - 77
ER -