Oral cancer is one of the most frequently occurring cancers. Metabolic reprogramming is an important hallmark of cancer. Metabolomics characterizes all the small molecules in a biological sample, and a complete set of small molecules in such sample is referred as metabolome. Nuclear magnetic resonance spectroscopy and mass spectrometry are two widely used techniques in metabolomics studies. Increasing evidence demonstrates that metabolomics techniques can be used to explore the metabolic signatures in oral cancer. Elucidation of metabolic alterations in oral cancer is also important for the understanding of its pathological mechanisms.
Aim of review
In this paper, we summarize the latest progress of metabolomics study in oral cancer and provide the suggestions for the future studies.
Key scientific concepts of review
The metabolomics studies in saliva, serum, and tumor tissues revealed the existence of metabolic signatures in bio-fluids and tissues of oral cancer, and several tumor-specific metabolites identified in individual study could discriminate oral cancer from healthy controls or precancerous lesions, which are potential biomarkers for the screening or early diagnosis of oral cancer. Metabolomics study of oral cancers in the future should aim to establish a routine procedure with high sensitivity, profile intracellular metabolites to find out the metabolic characteristics of tumor cells, and investigate the mechanism behind metabolomic alterations and the metabolic response of cancer cells to chemotherapy.
This is a preview of subscription content, log in to check access.
Buy single article
Instant access to the full article PDF.
Price includes VAT for USA
Subscribe to journal
Immediate online access to all issues from 2019. Subscription will auto renew annually.
This is the net price. Taxes to be calculated in checkout.
Asai, Y., et al. (2018). Elevated polyamines in saliva of pancreatic cancer. Cancers, 10, E43. https://doi.org/10.3390/cancers10020043.
Backshall, A., Sharma, R., Clarke, S. J., & Keun, H. C. (2011). Pharmacometabonomic profiling as a predictor of toxicity in patients with inoperable colorectal cancer treated with capecitabine. Clinical Cancer Research, 17, 3019–3028. https://doi.org/10.1158/1078-0432.CCR-10-2474.
Bag, S., et al. (2015). NMR ((1)H and (13)C) based signatures of abnormal choline metabolism in oral squamous cell carcinoma with no prominent Warburg effect. Biochemical and Biophysical Research Communications, 459, 574–578. https://doi.org/10.1016/j.bbrc.2015.02.149.
Bag, S., et al. (2016). NanoLC MALDI MS/MS based quantitative metabolomics reveals the alteration of membrane biogenesis in oral cancer. Rsc Advances, 6, 62420–62433. https://doi.org/10.1039/c6ra07001a.
Bezabeh, T., et al. (2005). Prediction of treatment response in head and neck cancer by magnetic resonance spectroscopy. AJNR American Journal of Neuroradiology, 26, 2108–2113.
Cardoso, M. R., Santos, J. C., Ribeiro, M. L., Talarico, M. C. R., Viana, L. R., & Derchain, S. F. M. (2018). A metabolomic approach to predict breast cancer behavior and chemotherapy response. International Journal of Molecular Sciences, 19, E617. https://doi.org/10.3390/ijms19020617.
Chen, H. W., Zhou, W., Liao, Y., Hu, S. C., Chen, T. L., & Song, Z. C. (2018). Analysis of metabolic profiles of generalized aggressive periodontitis. Journal of Periodontal Research, 53, 894–901. https://doi.org/10.1111/jre.12579.
Chen, X., & Zhao, Y. (2017). Human papillomavirus infection in oral potentially malignant disorders and cancer. Archives of Oral Biology, 83, 334–339. https://doi.org/10.1016/j.archoralbio.2017.08.011.
Cooke, M., Leeves, N., & White, C. (2003). Time profile of putrescine, cadaverine, indole and skatole in human saliva. Archives of Oral Biology, 48, 323–327.
El-Sayed, S., et al. (2002). An ex vivo study exploring the diagnostic potential of 1H magnetic resonance spectroscopy in squamous cell carcinoma of the head and neck region. Head and Neck, 24, 766–772. https://doi.org/10.1002/hed.10125.
Gerner, E. W., & Meyskens, F. L. Jr. (2004). Polyamines and cancer: old molecules, new understanding. Nature Reviews Cancer, 4, 781–792. https://doi.org/10.1038/nrc1454.
Glunde, K., Bhujwalla, Z. M., & Ronen, S. M. (2011). Choline metabolism in malignant transformation. Nature Reviews Cancer, 11, 835–848. https://doi.org/10.1038/nrc3162.
Goldberg, S., Kozlovsky, A., Gordon, D., Gelernter, I., Sintov, A., & Rosenberg, M. (1994). Cadaverine as a putative component of oral malodor. Journal of Dental Research, 73, 1168–1172. https://doi.org/10.1177/00220345940730060701.
Gupta, A., Gupta, S., & Mahdi, A. A. (2015). (1)H NMR-derived serum metabolomics of leukoplakia and squamous cell carcinoma. Clinica Chimica Acta, 441, 47–55. https://doi.org/10.1016/j.cca.2014.12.003.
Hirayama, A., et al. (2015). Effects of processing and storage conditions on charged metabolomic profiles in blood. Electrophoresis, 36, 2148–2155. https://doi.org/10.1002/elps.201400600.
Ishikawa, S., et al. (2016). Identification of salivary metabolomic biomarkers for oral cancer screening. Scientific Reports, 6, 31520. https://doi.org/10.1038/srep31520.
Ishikawa, S., et al. (2017). Effect of timing of collection of salivary metabolomic biomarkers on oral cancer detection. Amino Acids, 49, 761–770. https://doi.org/10.1007/s00726-017-2378-5.
Ji, E. H., et al. (2017). Metabolomic analysis of human oral cancer cells with adenylate kinase 2 or phosphorylate glycerol kinase 1 inhibition. Journal of Cancer, 8, 298–304. https://doi.org/10.7150/jca.17521.
Kawanishi, N., et al. (2018). Effects of inter-day and intra-day variation on salivary metabolomic profiles. Clinica Chimica Acta, 489, 41–48. https://doi.org/10.1016/j.cca.2018.11.030.
Kong, X., et al. (2015). Analysis of plasma metabolic biomarkers in the development of 4-nitroquinoline-1-oxide-induced oral carcinogenesis in rats. Oncology Letters, 9, 283–289. https://doi.org/10.3892/ol.2014.2619.
Kuboniwa, M., Sakanaka, A., Hashino, E., Bamba, T., Fukusaki, E., & Amano, A. (2016). Prediction of periodontal inflammation via metabolic profiling of saliva. Journal of Dental Research, 95, 1381–1386. https://doi.org/10.1177/0022034516661142.
Lau, C., et al. (2013). Role of pancreatic cancer-derived exosomes in salivary biomarker development. Journal of Biological Chemistry, 288, 26888–26897. https://doi.org/10.1074/jbc.M113.452458.
Liu, R., et al. (2013). Identification of plasma metabolomic profiling for diagnosis of esophageal squamous-cell carcinoma using an UPLC/TOF/MS platform. International Journal of Molecular Sciences, 14, 8899–8911. https://doi.org/10.3390/ijms14058899.
Markley, J. L., et al. (2017). The future of NMR-based metabolomics. Current Opinion in Biotechnology, 43, 34–40. https://doi.org/10.1016/j.copbio.2016.08.001.
Mikkonen, J. J., Singh, S. P., Herrala, M., Lappalainen, R., Myllymaa, S., & Kullaa, A. M. (2016). Salivary metabolomics in the diagnosis of oral cancer and periodontal diseases. Journal of Periodontal Research, 51, 431–437. https://doi.org/10.1111/jre.12327.
Mukherjee, P. K., et al. (2017). Metabolomic analysis identifies differentially produced oral metabolites, including the oncometabolite 2-hydroxyglutarate, in patients with head and neck squamous cell carcinoma. BBA Clinical, 7, 8–15. https://doi.org/10.1016/j.bbacli.2016.12.001.
Mukherji, S. K., Schiro, S., Castillo, M., Kwock, L., Muller, K. E., & Blackstock, W. (1997). Proton MR spectroscopy of squamous cell carcinoma of the extracranial head and neck: in vitro and in vivo studies. AJNR American Journal of Neuroradiology, 18, 1057–1072.
Musharraf, S. G., Shahid, N., Naqvi, S. M., Saleem, M., Siddiqui, A. J., & Ali, A. (2016). Metabolite profiling of preneoplastic and neoplastic lesions of oral cavity tissue samples revealed a biomarker pattern. Science Reports, 6, 38985. https://doi.org/10.1038/srep38985.
Nakagawa, H., Hayata, Y., Kawamura, S., Yamada, T., Fujiwara, N., & Koike, K. (2018). Lipid metabolic reprogramming in hepatocellular carcinoma. Cancers, 10, E447. https://doi.org/10.3390/cancers10110447.
Nicholson, J. K., & Lindon, J. C. (2008). Systems biology: metabonomics. Nature, 455, 1054–1056. https://doi.org/10.1038/4551054a.
Ogawa, T., Washio, J., Takahashi, T., Echigo, S., & Takahashi, N. (2014). Glucose and glutamine metabolism in oral squamous cell carcinoma: insight from a quantitative metabolomic approach. Oral Surgery, Oral Medicine, Oral Pathology, Oral Radiology, 118, 218–225. https://doi.org/10.1016/j.oooo.2014.04.003.
Ohshima, M., Sugahara, K., Kasahara, K., & Katakura, A. (2017). Metabolomic analysis of the saliva of Japanese patients with oral squamous cell carcinoma. Oncology Reports, 37, 2727–2734. https://doi.org/10.3892/or.2017.5561.
Okamura, M., Kobayashi, M., Suzuki, F., Shimada, J., & Sakagami, H. (2007). Induction of cell death by combination treatment with cisplatin and 5-fluorouracil in a human oral squamous cell carcinoma cell line. Anticancer Research, 27, 3331–3337.
Rai, V., Mukherjee, R., Ghosh, A. K., Routray, A., & Chakraborty, C. (2018). “Omics” in oral cancer: new approaches for biomarker discovery. Archives of Oral Biology, 87, 15–34. https://doi.org/10.1016/j.archoralbio.2017.12.003.
Romano, F., et al. (2018). Analysis of salivary phenotypes of generalized aggressive and chronic periodontitis through nuclear magnetic resonance-based metabolomics. Journal of Periodontology, 89, 1452–1460. https://doi.org/10.1002/Jper.18-0097.
Roodhart, J. M., et al. (2011). Mesenchymal stem cells induce resistance to chemotherapy through the release of platinum-induced fatty acids. Cancer Cell, 20, 370–383. https://doi.org/10.1016/j.ccr.2011.08.010.
Sakanaka, A., Kuboniwa, M., Hashino, E., Bamba, T., Fukusaki, E., & Amano, A. (2017). Distinct signatures of dental plaque metabolic byproducts dictated by periodontal inflammatory status. Science Reports, 7, 42818. https://doi.org/10.1038/srep42818.
Sant’Anna-Silva, A. C. B., Santos, G. C., Campos, S. P. C., Oliveira Gomes, A. M., Perez-Valencia, J. A., & Rumjanek, F. D. (2018). Metabolic profile of oral squamous carcinoma cell lines relies on a higher demand of lipid metabolism in metastatic cells. Frontiers Oncology, 8, 13. https://doi.org/10.3389/fonc.2018.00013.
Shankar, A. A., Alex, S., & Routray, S. (2014). Incorporation of salivary metabolomics in oral cancer diagnostics. Oral Oncology, 50, e53–e54. https://doi.org/10.1016/j.oraloncology.2014.07.013.
Shin, J. M., Kamarajan, P., Fenno, J. C., Rickard, A. H., & Kapila, Y. L. (2016). Metabolomics of head and neck cancer: a mini-review. Frontiers in Physiology, 7, 526. https://doi.org/10.3389/fphys.2016.00526.
Somashekar, B. S., et al. (2011). Magic angle spinning NMR-based metabolic profiling of head and neck squamous cell carcinoma tissues. Journal of Proteome Research, 10, 5232–5241. https://doi.org/10.1021/pr200800w.
Srivastava, S., Roy, R., Gupta, V., Tiwari, A., Srivastava, A. N., & Sonkar, A. (2011). Proton HR-MAS MR spectroscopy of oral squamous cell carcinoma tissues: an ex vivo study to identify malignancy induced metabolic fingerprints. Metabolomics, 7, 278–288. https://doi.org/10.1007/s11306-010-0253-4.
Star-Lack, J. M., et al. (2000). In vivo 1H MR spectroscopy of human head and neck lymph node metastasis and comparison with oxygen tension measurements. AJNR American Journal of Neuroradiology, 21, 183–193.
Sugimoto, M., Wong, D. T., Hirayama, A., Soga, T., & Tomita, M. (2010). Capillary electrophoresis mass spectrometry-based saliva metabolomics identified oral, breast and pancreatic cancer-specific profiles. Metabolomics, 6, 78–95. https://doi.org/10.1007/s11306-009-0178-y.
Sun, L. C., Suo, C. X., Li, S. T., Zhang, H. F., & Gao, P. (2018). Metabolic reprogramming for cancer cells and their microenvironment: beyond the Warburg effect. Biochimica et Biophysica Acta, 1870, 51–66. https://doi.org/10.1016/j.bbcan.2018.06.005.
Suzuki, R., Matsuno, S., Sakagami, H., Okada, Y., & Shirataki, Y. (2014). Search of new cytotoxic crude materials against human oral squamous cell carcinoma using 1H NMR-based metabolomics. Anticancer Research, 34, 4117–4120.
Takayama, T., et al. (2016). Diagnostic approach to breast cancer patients based on target metabolomics in saliva by liquid chromatography with tandem mass spectrometry. Clinica Chimica Acta, 452, 18–26. https://doi.org/10.1016/j.cca.2015.10.032.
Takeda, I., et al. (2009). Understanding the human salivary metabolome. NMR in Biomedicine, 22, 577–584. https://doi.org/10.1002/nbm.1369.
Tan, Y., et al. (2012). Metabolomics study of stepwise hepatocarcinogenesis from the model rats to patients: potential biomarkers effective for small hepatocellular carcinoma diagnosis. Molecular and Cell Proteomics, 11, M111 010694. https://doi.org/10.1074/mcp.M111.010694.
Tanaka, S., Machino, M., Akita, S., Yokote, Y., & Sakagami, H. (2010). Changes in salivary amino acid composition during aging. In Vivo, 24, 853–856.
Tiziani, S., Lopes, V., & Gunther, U. L. (2009). Early stage diagnosis of oral cancer using 1H NMR-based metabolomics. Neoplasia, 11, 269–276, 4p following 269.
Tomita, A., et al. (2018). Effect of storage conditions on salivary polyamines quantified via liquid chromatography-mass spectrometry. Science Reports, 8, 12075. https://doi.org/10.1038/s41598-018-30482-x.
Tripathi, P., et al. (2012). Delineating metabolic signatures of head and neck squamous cell carcinoma: phospholipase A2, a potential therapeutic target. International Journal of Biochemistry and Cell Biology, 44, 1852–1861. https://doi.org/10.1016/j.biocel.2012.06.025.
Urakami, K., Zangiacomi, V., Yamaguchi, K., & Kusuhara, M. (2013). Impact of 2-deoxy-D-glucose on the target metabolome profile of a human endometrial cancer cell line. Biomedical Research, 34, 221–229.
Wang, H., et al. (2015). (1)H nuclear magnetic resonance-based extracellular metabolomic analysis of multidrug resistant Tca8113 oral squamous carcinoma cells. Oncology Letters, 9, 2551–2559. https://doi.org/10.3892/ol.2015.3128.
Wang, J., et al. (2014a). Metabolomic profiling of anionic metabolites in head and neck cancer cells by capillary ion chromatography with Orbitrap mass spectrometry. Analytical Chemistry, 86, 5116–5124. https://doi.org/10.1021/ac500951v.
Wang, Q., Gao, P., Wang, X., & Duan, Y. (2014b). The early diagnosis and monitoring of squamous cell carcinoma via saliva metabolomics. Science Reports, 4, 6802. https://doi.org/10.1038/srep06802.
Wang, Q., Gao, P., Wang, X., & Duan, Y. (2014c). Investigation and identification of potential biomarkers in human saliva for the early diagnosis of oral squamous cell carcinoma. Clinica Chimica Acta, 427, 79–85. https://doi.org/10.1016/j.cca.2013.10.004.
Wang, X., et al. (2018). Taurine, glutamic acid and ethylmalonic acid as important metabolites for detecting human breast cancer based on the targeted metabolomics. Cancer Biomarkers, 23, 255–268. https://doi.org/10.3233/CBM-181500.
Wang, X., Kaczor-Urbanowicz, K. E., & Wong, D. T. (2017). Salivary biomarkers in cancer detection. Medical Oncology, 34, 7. https://doi.org/10.1007/s12032-016-0863-4.
Warburg, O. (1956). On the origin of cancer cells. Science, 123, 309–314.
Weaver, Z., et al. (2012). Temporal molecular and biological assessment of an erlotinib-resistant lung adenocarcinoma model reveals markers of tumor progression and treatment response. Cancer Research, 72, 5921–5933. https://doi.org/10.1158/0008-5472.CAN-12-0736.
Wei, J., et al. (2011). Salivary metabolite signatures of oral cancer and leukoplakia. International Journal of Cancer, 129, 2207–2217. https://doi.org/10.1002/ijc.25881.
Xie, G. X., et al. (2012). Urine metabolite profiling offers potential early diagnosis of oral cancer. Metabolomics, 8, 220–231. https://doi.org/10.1007/s11306-011-0302-7.
Yakob, M., Fuentes, L., Wang, M. B., Abemayor, E., & Wong, D. T. (2014). Salivary biomarkers for detection of oral squamous cell carcinoma - current state and recent advances. Current Oral Health Reports, 1, 133–141. https://doi.org/10.1007/s40496-014-0014-y.
Yan, S. K., Wei, B. J., Lin, Z. Y., Yang, Y., Zhou, Z. T., & Zhang, W. D. (2008). A metabonomic approach to the diagnosis of oral squamous cell carcinoma, oral lichen planus and oral leukoplakia. Oral Oncology, 44, 477–483. https://doi.org/10.1016/j.oraloncology.2007.06.007.
Yang, L. F., Venneti, S., & Nagrath, D. (2017). Glutaminolysis: A hallmark of cancer metabolism. Annual Review of Biomedical Engineering, 19, 163–194. https://doi.org/10.1146/annurev-bioeng-071516044546.
Ye, G., et al. (2012). Analysis of urinary metabolic signatures of early hepatocellular carcinoma recurrence after surgical removal using gas chromatography-mass spectrometry. Journal of Proteome Research, 11, 4361–4372. https://doi.org/10.1021/pr300502v.
Ye, G., et al. (2014). Study of induction chemotherapy efficacy in oral squamous cell carcinoma using pseudotargeted metabolomics. Journal of Proteome Research, 13, 1994–2004. https://doi.org/10.1021/pr4011298.
Yonezawa, K., et al. (2013). Serum and tissue metabolomics of head and neck cancer. Cancer Genomics & Proteomics, 10, 233–238.
Yu, L., Chen, X., Sun, X., Wang, L., & Chen, S. (2017). The glycolytic switch in tumors: How many players are involved? Journal of Cancer, 8, 3430–3440. https://doi.org/10.7150/jca.21125.
Yuvaraj, M., et al. (2014). Fluorescence spectroscopic characterization of salivary metabolites of oral cancer patients. Journal of Photochemistry and Photobiology B, 130, 153–160. https://doi.org/10.1016/j.jphotobiol.2013.11.006.
Zaal, E. A., Wu, W., Jansen, G., Zweegman, S., Cloos, J., & Berkers, C. R. (2017). Bortezomib resistance in multiple myeloma is associated with increased serine synthesis. Cancer & Metabolism, 5, 7. https://doi.org/10.1186/s40170-017-0169-9.
Zhang, R. X., Zhuang, X. Y., Zong, L., Liu, S., Liu, Z. Q., & Song, F. R. (2016). Investigations on the cell metabolomics basis of multidrug resistance from tumor cells by ultra-performance liquid chromatography-mass spectrometry. Analytical and Bioanalytical Chemistry, 408, 5843–5854. https://doi.org/10.1007/s00216-016-9696-4.
Zhong, L. P., Cheng, F., Lu, X. Y., Duan, Y. X., & Wang, X. D. (2016). Untargeted saliva metabonomics study of breast cancer based on ultra performance liquid chromatography coupled to mass spectrometry with HILIC and RPLC separations. Talanta, 158, 351–360. https://doi.org/10.1016/j.talanta.2016.04.049.
Zhou, J., et al. (2009). 1H NMR-based metabonomic and pattern recognition analysis for detection of oral squamous cell carcinoma. Clinica Chimica Acta, 401, 8–13. https://doi.org/10.1016/j.cca.2008.10.030.
This study was funded by the National Natural Science Foundation of China (No. 81873711 and No. 31670788) and Open Fund of Guangdong Key Laboratory of Pharmaceutical Functional Genes (No.2014B030301028 and No.2017B030314021).
Conflict of interest
The authors confirm that there are no conflicts of interest.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Chen, X., Yu, D. Metabolomics study of oral cancers. Metabolomics 15, 22 (2019). https://doi.org/10.1007/s11306-019-1483-8
- Oral cancer
- Oral squamous cell carcinoma