|Year : 2017 | Volume
| Issue : 3 | Page : 556-561
Serum metabolomics in oral leukoplakia and oral squamous cell carcinoma
Gokul Sridharan1, Pratibha Ramani2, Sangeeta Patankar1
1 Department of Oral Pathology and Microbiology, YMT Dental College and Hospital, Navi Mumbai, Maharashtra, India
2 Department of Oral Pathology and Microbiology, Saveetha Dental College and Hospitals, Saveetha University, Chennai, Tamil Nadu, India
|Date of Web Publication||31-Aug-2017|
YMT Dental College and Hospital, Kharghar, Navi Mumbai - 410 210, Maharashtra
Source of Support: None, Conflict of Interest: None
Context: Metabolomics is a core discipline of system biology focusing on the study of low molecular weight compounds in biological system. Analysis of human metabolome, which is composed of diverse group of metabolites, can aid in diagnosis and prognosis of oral squamous cell carcinoma (OSCC).
Aim: The aim of the present study is to analyze and identify serum metabolites in oral leukoplakia and OSCC as a potential diagnostic biomarker and a predictor for malignant transformation of oral leukoplakia.
Subjects and Methods: Serum metabolomic profile of patients diagnosed with oral leukoplakia (n = 21) and OSCC (n = 22) was compared with normal controls (n = 18) using quadrupole time of flight-liquid chromatography–mass spectrometry. MassHunter profile software was used for metabolite identification, and statistical analysis to assess the variation of the metabolites was performed using Mass Profiler Professional software. Statistical significance between the three groups was expressed using ANOVA (P < 0.05), and intergroup comparison was done using Student's t-test (P < 0.05).
Results: Significant upregulation of estradiol-17-beta-3-sulfate, L-carnitine, 5-methylthioadenosine (MTA), 8-hydroxyadenine, 2-methylcitric acid, putrescine, and estrone-3-sulfate was seen in oral leukoplakia and OSCC than in normal controls. Furthermore, significant upregulation of 5,6-dihydrouridine, 4-hydroxypenbutolol glucuronide, 8-hydroxyadenine, and putrescine was evident in OSCC group than in oral leukoplakia.
Conclusion: Upregulation of L-carnitine, lysine, 2-methylcitric acid, putrescine; 8-hydroxyadenine; 17-estradiol; 5,6-dihydrouridine; and MTA suggests their diagnostic potential in oral leukoplakia and OSCC. Further, a significant upregulation of putrescine, 8-hydroxyadenine, and 5,6-dihydrouridine in OSCC than in oral leukoplakia indicates their potential role in predicting the malignant transformation of oral leukoplakia.
Keywords: Metabolomics, oral leukoplakia, oral squamous cell carcinoma, serum diagnostics
|How to cite this article:|
Sridharan G, Ramani P, Patankar S. Serum metabolomics in oral leukoplakia and oral squamous cell carcinoma. J Can Res Ther 2017;13:556-61
| > Introduction|| |
Oral squamous cell carcinoma (OSCC) is the major form of oral cancer and the sixth common malignancy in the world. The burden is increasing worldwide with an estimated incidence of around 275,000 cases and with two-third of these cases occurring in developing countries. Data obtained from the different cancer registries in India showed age-adjusted incidence rates of OSCC per 100,000 population to be in the range of 3.3–10.7 in males and between 2.2 and 8.9 in females. While OSCC may arise de novo, most of them are preceded by the presence of clinically visible changes of oral mucosa which have a potential for malignant transformation. These lesions are together categorized as potentially malignant disorders. Leukoplakia is the most commonly encountered potentially malignant disorder of the oral cavity with a malignancy transformation rate ranging from 0.1% to 17.5%.
Despite diagnostic and therapeutic advances over the decades, the disease remains a challenge for medical professionals with the 5-year survival rate being 30%–50%. The mortality rate associated with OSCC is high because it is routinely discovered late, commonly after metastasis to lymph nodes or distant sites has already occurred. Hence, early detection and prompt diagnosis can lead to better prognosis and help in the implementation of successful clinical treatment.
It is well known that the tumor cell during its course of development undergoes molecular alterations in several cellular molecules including DNA, RNA, and proteins which could be attributed to the inherent biological properties of the cancer cell. Based on several studies conducted, it can be inferred that these alterations play a significant role in tumor progression as well as the overall survival of the malignant cells. Furthermore, these markers can assist in early diagnosis and prediction of prognosis. The rapid advancements in the identification of these molecular targets in the cancer cell have led to the revolution of the “omics” group in cancer diagnostics. Omics-based tests are assays composed of or derived from many molecular measurements and include proteomics, genomics, epigenomics, transcriptomics, microbiomics, and metabolomics.,
An important hallmark of cancer is the reprogramming of energy metabolism, which although was identified long back assumed significance recently in the light of technologies available for its identification. The field of metabolomics is defined as the study of the metabolome, which describes the repertoire of small molecules present in cells, tissues, organs, and biological fluids. The concentration and fluxes of these compounds result from a multifaceted interplay among gene expression, protein expression, and the environment. Metabolites are generated by the processes of metabolism in cells, tissues, or organs. The human body contains approximately 38,000 (exactly 37,166, until now, as per a very recent report on the HMDB Version 3.6) detectable metabolites that are very diverse chemical compounds such as volatile, polar, and more polar metabolites.,
The identification of metabolites using mass spectrometry (MS) has been performed in various solid tumors with successful results. Identification of biomarkers using metabolomic profiling is reported in pancreatic cancer, colorectal cancer, gastrointestinal cancer, and lung cancer. With respect to the identification of serum metabolomics in head and neck cancer, few studies were reported on the basis that biochemical changes are evident in these groups of cancer which can be identified as potential markers and these studies have compared the metabolite profile of head and neck cancer with normal controls. Thus, the aim of the current study was to evaluate the serum metabolomics in oral leukoplakia and OSCC to identify the presence of metabolites which can be used as reliable biomarkers in tumor diagnostics.
| > Subjects and Methods|| |
The study involved analysis of metabolomic profile in serum of patients clinically diagnosed with oral leukoplakia and histopathologically confirmed OSCC. A total of 62 participants were included in the study and were divided into three groups. Group I (n = 18) was normal individuals without any oral lesions, tobacco habits, and systemic illnesses; Group II (n = 21) included clinically diagnosed cases of oral leukoplakia, and Group III (n = 22) consisted of clinically and histopathologically diagnosed cases of OSCC. The patients with known history of systemic illness and medications were not considered for the study; patients with a history of therapy for oral leukoplakia and OSCC (surgery, chemotherapy, and radiotherapy); and patients with recurrent oral lesions were excluded from the study. Institutional ethical committee clearance was obtained before the commencement of the study. The study details were explained to the patient and written informed consent was obtained.
Five milliliters of blood was collected by venipuncture from forearm region under aseptic precautions and transferred into plain vials. The obtained samples were centrifuged at 3000 rpm for 15 min. One hundred microliters of the supernatant was mixed with chilled methanol (stored at −20°C) in 1:4 ratio (sample:methanol). The mixture was gently shaken and incubated overnight at −20°C. Following overnight refrigeration, the sample was further centrifuged at 4000 rpm for 10 min. The supernatant thus obtained was collected in a new 1.5 ml microcentrifuge tube and analyzed using ultra-performance liquid chromatography (LC) coupled with quadrupole time of flight MS (Agilent 6550 iFunnel Q-TOF LC/MS).
The components are separated by passing the pressurized liquid solvent through a C18 column of pore size 80–120 A° and particle size 1.8 μm, 2.1 mm internal diameter, the sample injection volume was 2 μl, and the mobile phase was composed of water/formic acid and methanol with solid absorption material where all components adsorb at different rates causing different flow rates for various components, thus leading to separation of the compounds as they flow out. Ions are generated using an electrospray ion source where the analyte is simultaneously analyzed and desolvated from the liquid matrix. Following the conversion of sample molecules to ions, the next step is to resolve these ions, and this is done based on the mass to the charge ratio (m/z ratio).
Raw data of HPLC/MS were preprocessed as follows. First, the whole spectral data were divided into bins and then extracted ion chromatograms were calculated. Then, data filtration and peak detection were performed at a specified range of m/z ratio which was between 50 and 1000. Retention time alignment and peak matching algorithm were applied for all data sets, and the results were then exported to a comma-separated value file which included information on mass to charge ratio, retention times, and area of peaks across all samples. The above procedure was carried out using XCMS toolbox and software tool MassHunter Qualitative Analysis B.05.00 (Agilent Technologies). After preprocessing, the LC-MS raw data are summarized by a peak list. METLIN database (which was a part of the software) was used to compare and identify the metabolites from the serum samples. The molecules having molecular weights within a specified tolerance range to the query molecular weight are retrieved from the database as putative identifications.
Statistical analysis was performed using the Agilent G3835AA MassHunter Mass Profiler Professional (MPP) software. Once the multiple data files are imported into the MPP software, experiment grouping of the samples was done into normal, leukoplakia, and OSCC. After grouping, principal component analysis (PCA) was performed using three-dimensional (3D) PCA grouping which showed a trend of intergroup separation on the scores plot. In the next step, univariate analysis involving ANOVA along with post hoc test was done to determine the statistical significance between the three groups followed by t-test to identify the results between two individual groups at confidence interval of 95%.
| > Results|| |
The serum samples collected from the study participants were analyzed for detection of untargeted metabolites. PCA was performed to show the intergroup comparison on a 3D score plot [Figure 1]. ANOVA analysis between the three groups displayed a total of 190 statistically significant (P< 0.05) metabolites that were either upregulated or downregulated in oral leukoplakia and OSCC as compared to normal controls [Table 1]. Tukey's post hoc analysis revealed a differential expression of 152 compounds in oral leukoplakia as compared with normal, 121 differentially expressed compounds between OSCC and normal, and 46 differentially expressed compounds in OSCC and oral leukoplakia [Table 2]. A comparative analysis between two groups was performed using unpaired Student's t-test. In the comparison of normal groups with oral leukoplakia, a total of 217 compounds showed statistical significance at P < 0.05 [Table 3]. Analysis between normal and OSCC revealed 190 compounds showing statistical significance at P < 0.05 [Table 4]. The comparative analysis between oral leukoplakia and OSCC group revealed 44 statistically significant metabolites at P < 0.05 [Table 5]. Some of the important compounds that were upregulated in diseased groups were estradiol-17-beta-3-sulfate, gamma-aminobutyryl-lysine, L-carnitine, N-acetyl-4-aminosalicylic acid, 5-methylthioadenosine (MTA), 8-hydroxyadenine, 2-methylcitric acid, putrescine, and estrone-3-sulfate. The compounds that were downregulated were methylthio benzoylglycine, 9,10-Dihydroxyoctadecanoic acid. Student's t-test analysis between OSCC and oral leukoplakia also showed a significant upregulation of 5,6-dihydrouridine, 4-hydroxypenbutolol glucuronide, 8-hydroxyadenine, and putrescine.
|Figure 1: Principal component analysis plot showing the intergroup comparison|
Click here to view
|Table 1: ANOVA unequal variance between normal, oral leukoplakia and OSCC|
Click here to view
|Table 2: Tukey's post hoc analysis between normal subjects, oral leukoplakia and OSCC patients|
Click here to view
|Table 3: Student t-test to compare the significant metabolites between normal and oral leukoplakia|
Click here to view
|Table 4: Student t-test to compare the significant metabolites between normal and OSCC|
Click here to view
|Table 5: Student t-test to compare the significant metabolites between oral leukoplakia and OSCC|
Click here to view
| > Discussion|| |
The study analyzed the serum metabolomic profile in oral leukoplakia and OSCC in comparison with normal controls. In the present study, L-carnitine which belongs to the class of hydroxyl fatty acid was significantly upregulated in oral leukoplakia and OSCC than in normal controls. It is an essential factor in β-oxidation of long chain fatty acids synthesized from lysine and methionine. A study by Wang et al. showed decreased levels of carnitines in saliva samples of OSCC than in normal. Increased serum carnitine levels observed in our study suggest an upregulation of fatty acid metabolism as a compensatory mechanism. The increased levels of carnitine in the diseased conditions could relate to the tricarboxylic acid cycle through lactate accumulation which again might occur in response to the higher energy demand of the tumor. The levels of carnitine could also provide for differentiation between early stage and late stage disease. The altered carnitine levels might indicate an increased membrane synthesis and cellular turnover.
Furthermore, there was a significant upregulation of phosphohydroxypyruvic acid and 2-methyl citric acid in oral leukoplakia and OSCC. 2-methyl citric acid belongs to the tricarboxylic acid derivatives which are formed by condensation of accumulated propionyl-CoA and oxaloacetate by the enzyme citrate synthase. Currently, there is no scientific documentation with respect to alteration of these compounds in any form of cancer. Their alteration along with that of L-carnitine indicates an altered amino acid metabolism in oral leukoplakia and OSCC which may hold diagnostic and prognostic significance.
Putrescine, a polyamine related to cadaverine produced by the breakdown of amino acids, was significantly upregulated in oral leukoplakia and OSCC than in normal controls. The quantitative levels of putrescine are associated with regulation of tumor growth and hence show marked variation in its levels as evident from our study. A study by Sugimoto et al. found a markedly increased level of putrescine in the saliva of OSCC patients. In another study, the putrescine levels were found to be decreased in cancer patients undergoing radiotherapy but remain higher than healthy. It can be hypothesized that increased levels of putrescine indicate the severity of the diseased state, and the levels can also be used to monitor the effect of chemotherapy on tumor cancer cells. Furthermore, on intergroup comparison between oral leukoplakia and OSCC, the study found a significant upregulation of putrescine levels in OSCC.
A significant upregulation of 8-hydroxyadenine in OLP and OSCC than in normal controls was evident from the current results. The study also found that this compound was significantly upregulated in OSCC than in oral leukoplakia, thus suggesting an increased DNA damage and induction of oxidative stress. An oxidant–antioxidant imbalance results in oxidative stress that is detrimental to cell causing lipid, protein, and DNA damage. In all living cells, misrepaired DNA can result in mutations such as base substitution, deletions, and strand fragmentation, thereby leading to carcinogenesis. Increased DNA damage has been reported in studies concerning oral premalignant lesions and OSCC and is attributed to the use of tobacco which is one of the important causes of DNA damage.,
Estradiol sulfate (E2S) or 17 β-estradiol 3-sulfate is a natural, endogenous steroid and estrone-3-sulfate is a major circulating estrogen, which are highly expressed and are involved in the progression of breast cancer. In the present study, these compounds were significantly upregulated in oral leukoplakia and OSCC than in normal controls. A study by Colella et al. showed an increased expression of estrogen receptor α in messenger RNA of OSCC tissues, thereby suggesting its involvement in OSCC. In another study by Lukits et al., an increased expression of estrogen receptors was observed in the tumor cells of tissue obtained from OSCC patients. While the exact mechanism for this observation is unconfirmed, it possibly occurs due to deteriorating liver function secondary to alcohol leading to alteration of sex hormone metabolism.
A component of nucleotide metabolism, 5,6-dihydrouridine, was found to be significantly upregulated in OSCC group than in oral leukoplakia which could be due to an increased RNA degradation in malignant lesions. An increased 5,6-dihydrouridine has been reported in various malignancies representing rapid RNA degradation due to tumor–host metabolic interactions., Elevated levels of modified nucleosides were found in breast cancer, cancer of liver, lymphoma, and lung cancers, but no studies have reported such changes in oral leukoplakia and OSCC till date. Altered 5,6-dihydrouridine can thus be considered as an important finding in OSCC as well as to predict malignant transformation of oral leukoplakia.
MTA is a naturally occurring sulfur-containing nucleoside, and ANOVA test between three groups shows a significant upregulation of this metabolite in oral leukoplakia and OSCC than in the control group. A high concentration of MTA (μM) has the following effects: interferes with cell proliferation, tumor development, invasiveness, and the regulation of apoptosis;, interferes with key cell signaling pathways; and increases intracellular cyclic adenosine monophosphate levels. While the present study shows an increased expression of MTA in serum, it is possible that it may either be underutilized or excreted from the body. This could be due to the lack of 5-methylthioadenosinephosphorylase activity that is required for recycling MTA. These findings suggest the clinical utility of MTA in OSCC and therapeutic intervention aimed at increasing the utility of 5-methyladenosine may have beneficial effects.
| > Conclusion|| |
A range of metabolites was altered in oral leukoplakia and OSCC in the present study. The major pathway demonstrating alterations was related to the amino acid metabolism, oxidative stress damage, nucleotide metabolism, and estrogen metabolism. The significant metabolites include L-carnitine, 2-methylcitric acid, polyamines such as putrescine, 8-hydroxyadenine, estrone-B-sulfate, 5,6-dihydrouridine, and 5-methyladenosine. On intergroup comparison between oral leukoplakia and OSCC, the study found significant upregulation of putrescine, 8-hydroxyadenine, and 5,6-dihydrouridine in OSCC than in oral leukoplakia.
These changes signify a modification in the body metabolism in oral leukoplakia and OSCC, and the increased expression of various metabolites in OSCC and oral leukoplakia indicates their potential to be used not only as an important diagnostic aid but also help in determining the prognosis. Further to these data, it is necessary to evaluate and analyze the diagnostic, therapeutic, and prognostic utility of the individual metabolites in oral leukoplakia and OSCC with a two-pronged benefit of preventing malignant transformation of oral leukoplakia and to decrease the morbidity and mortality of OSCC.
The authors wish to thank Dr. Sharad Kokate, Dean of YMT Dental College and Hospital, Navi Mumbai, and the management of Saveetha University, Chennai, for their academic and clinical help and encouragement. The authors acknowledge the contribution of Department of SAIF, IIT Bombay, Mumbai, for providing infrastructure and technical support.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| > References|| |
Warnakulasuriya S. Global epidemiology of oral and oropharyngeal cancer. Oral Oncol 2009;45:309-16.
Ferlay J, Pisani P, Parkin DM. Globocan. Cancer Incidence, Mortality and Prevalence Worldwide. IARC Cancer Base (2002 Estimates). Lyon: IARC Press; 2004.
Murthy NS, Mathew A. Cancer epidemiology, prevention and control. Curr Sci 2004;86:518-27.
van der Waal I. Oral potentially malignant disorders: Is malignant transformation predictable and preventable? Med Oral Patol Oral Cir Bucal 2014;19:e386-90.
Li Y, St. John MA, Zhou X, Kim Y, Sinha U, Jordan RC, et al
. Salivary transcriptome diagnostics for oral cancer detection. Clin Cancer Res 2004;10:8442-50.
Sugimoto M, Wong DT, Hirayama A, Soga T, Tomita M. Capillary electrophoresis mass spectrometry-based saliva metabolomics identified oral, breast and pancreatic cancer-specific profiles. Metabolomics 2010;6:78-95.
Sethi S, Ali S, Philip PA, Sarkar FH. Clinical advances in molecular biomarkers for cancer diagnosis and therapy. Int J Mol Sci 2013;14:14771-84.
Ali S, Almhanna K, Chen W, Philip PA, Sarkar FH. Differentially expressed miRNAs in the plasma may provide a molecular signature for aggressive pancreatic cancer. Am J Transl Res 2010;3:28-47.
Ogino S, King EE, Beck AH, Sherman ME, Milner DA, Giovannucci E. Interdisciplinary education to integrate pathology and epidemiology: Towards molecular and population-level health science. Am J Epidemiol 2012;176:659-67.
Wong DT. Salivaomics. J Am Dent Assoc 2012;143 10 Suppl: 19S-24S.
Yakob M, Fuentes L, Wang MB, Abemayor E, Wong DT. Salivary biomarkers for detection of oral squamous cell carcinoma – Current state and recent advances. Curr Oral Health Rep 2014;1:133-41.
Vermeersch KA, Styczynski MP. Applications of metabolomics in cancer research. J Carcinog 2013;12:9.
] [Full text]
Dettmer K, Hammock BD. Metabolomics – A new exciting field within the “omics” sciences. Environ Health Perspect 2004;112:A396-7.
Oskouie AA, Taheri S. Recent developments and application of metabolomics in cancer diseases. J Paramed Sci 2015;6:116-35.
Wishart DS, Jewison T, Guo AC, Wilson M, Knox C, Liu Y, et al
. HMDB 3.0 – The Human Metabolome Database in 2013. Nucleic Acids Res 2013;41:D801-7.
Sreekumar A, Poisson LM, Rajendiran TM, Khan AP, Cao Q, Yu J, et al
. Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression. Nature 2009;457:910-4.
Hirayama A, Kami K, Sugimoto M, Sugawara M, Toki N, Onozuka H, et al
. Quantitative metabolome profiling of colon and stomach cancer microenvironment by capillary electrophoresis time-of-flight mass spectrometry. Cancer Res 2009;69:4918-25.
Ikeda A, Nishiumi S, Shinohara M, Yoshie T, Hatano N, Okuno T, et al
. Serum metabolomics as a novel diagnostic approach for gastrointestinal cancer. Biomed Chromatogr 2012;26:548-58.
Hori S, Nishiumi S, Kobayashi K, Shinohara M, Hatakeyama Y, Kotani Y, et al
. Ametabolomic approach to lung cancer. Lung Cancer 2011;74:284-92.
Busquets S, Serpe R, Toledo M, Betancourt A, Marmonti E, Orpí M, et al
. L-Carnitine: An adequate supplement for a multi-targeted anti-wasting therapy in cancer. Clin Nutr 2012;31:889-95.
Wang Q, Gao P, Wang X, Duan Y. The early diagnosis and monitoring of squamous cell carcinoma via saliva metabolomics. Sci Rep 2014;4:6802.
Zhang J, Bowers J, Liu L, Wei S, Gowda GA, Hammoud Z, et al
. Esophageal cancer metabolite biomarkers detected by LC-MS and NMR methods. PLoS One 2012;7:e30181.
Tiziani S, Lopes V, Günther UL. Early stage diagnosis of oral cancer using 1H NMR-based metabolomics. Neoplasia 2009;11:269-76.
Liesenfeld DB, Habermann N, Owen RW, Scalbert A, Ulrich CM. Review of mass spectrometry-based metabolomics in cancer research. Cancer Epidemiol Biomarkers Prev 2013;22:2182-201.
Khuhawar MY, Memon AA, Jaipal PD, Bhanger MI. Capillary gas chromatographic determination of putrescine and cadaverine in serum of cancer patients using trifluoroacetylacetone as derivatizing reagent. J Chromatogr B Biomed Sci Appl 1999;723:17-24.
Okamura M, Kobayashi M, Suzuki F, Shimada J, Sakagami H. Induction of cell death by combination treatment with cisplatin and 5-fluorouracil in a human oral squamous cell carcinoma cell line. Anticancer Res 2007;27:3331-7.
Valavanidis A, Vlachogianni T, Fiotakis C. 8-hydroxy-20-deoxyguanosine (8-OHdG): A critical biomarker of oxidative stress and carcinogenesis. J Environ Sci Health C Environ Carcinog Ecotoxicol Rev 2009;27:120-39.
Bahar G, Feinmesser R, Shpitzer T, Popovtzer A, Nagler RM. Salivary analysis in oral cancer patients: DNA and protein oxidation, reactive nitrogen species, and antioxidant profile. Cancer 2007;109:54-9.
Mukherjee S, Ray JG, Chaudhuri K. Evaluation of DNA damage in oral precancerous and squamous cell carcinoma patients by single cell gel electrophoresis. Indian J Dent Res 2011;22:735-6.
] [Full text]
Nozawa T, Suzuki M, Takahashi K, Yabuuchi H, Maeda T, Tsuji A, et al
. Involvement of estrone-3-sulfate transporters in proliferation of hormone-dependent breast cancer cells. J Pharmacol Exp Ther 2004;311:1032-7.
Colella G, Izzo G, Carinci F, Campisi G, Lo Muzio L, D'Amato S, et al
. Expression of sexual hormones receptors in oral squamous cell carcinoma. Int J Immunopathol Pharmacol 2011;24 2 Suppl: 129-32.
Lukits J, Remenár E, Rásó E, Ladányi A, Kásler M, Tímár J. Molecular identification, expression and prognostic role of estrogen- and progesterone receptors in head and neck cancer. Int J Oncol 2007;30:155-60.
Seidel A, Brunner S, Seidel P, Fritz GI, Herbarth O. Modified nucleosides: An accurate tumour marker for clinical diagnosis of cancer, early detection and therapy control. Br J Cancer 2006;94:1726-33.
Borek E, Baliga BS, Gehrke CW, Kuo CW, Belman S, Troll W, et al
. High turnover rate of transfer RNA in tumor tissue. Cancer Res 1977;37:3362-6.
Zheng YF, Kong HW, Xiong JH, Lv S, Xu GW. Clinical significance and prognostic value of urinary nucleosides in breast cancer patients. Clin Biochem 2005;38:24-30.
Yang J, Xu G, Zheng Y, Kong H, Pang T, Lv S, et al
. Diagnosis of liver cancer using HPLC-based metabonomics avoiding false-positive result from hepatitis and hepatocirrhosis diseases. J Chromatogr B Analyt Technol Biomed Life Sci 2004;813:59-65.
Rasmuson T, Björk GR. Urinary excretion of pseudouridine and prognosis of patients with malignant lymphoma. Acta Oncol 1995;34:61-7.
Kato T, Daigo Y, Hayama S, Ishikawa N, Yamabuki T, Ito T, et al
. Anovel human tRNA-dihydrouridine synthase involved in pulmonary carcinogenesis. Cancer Res 2005;65:5638-46.
Stevens AP, Spangler B, Wallner S, Kreutz M, Dettmer K, Oefner PJ, et al
. Direct and tumor microenvironment mediated influences of 5'-deoxy-5'-(methylthio) adenosine on tumor progression of malignant melanoma. J Cell Biochem 2009;106:210-9.
Mato JM, Corrales FJ, Lu SC, Avila MA. S-adenosylmethionine: A control switch that regulates liver function. FASEB J 2002;16:15-26.
Maher PA. Inhibition of the tyrosine kinase activity of the fibroblast growth factor receptor by the methyltransferase inhibitor 5'-methylthioadenosine. J Biol Chem 1993;268:4244-9.
Basu I, Locker J, Cassera MB, Belbin TJ, Merino EF, Dong X, et al
. Growth and metastases of human lung cancer are inhibited in mouse xenografts by a transition state analogue of 5'-methylthioadenosine phosphorylase. J Biol Chem 2011;286:4902-11.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]