Identification of differential metabolic characteristics between tumor and normal tissue from colorectal cancer patients by gas chromatography–mass spectrometry

Wu, Ning; Li, Haijing; Meng, F.; Cheng, Jianhua; Song, Xin; Zhang, Guochao; Wang, Wenyue; Wu, Shengming; Fang, Jiaojiao; Ma, Kun; Yang, Jie; Pei, Dong-po; Dong, Fangting

doi:10.1002/bmc.3999

Cited by 7 publications

(13 citation statements)

References 31 publications

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“…28 The correlations between high catecholamine levels and stress, as well as the occurrence and development of tumors, have also received increasing attention. In related research of CRC tissue at an early stage, we found that the contents of tyrosine and 5-oxoproline were also significantly higher compared with the control group, 16 which is consistent with the current results of urine analysis (Figure 5). However, this change has not been found in other CRC studies.…”

Section: Upregulation Of Amino Acid Metabolismsupporting

confidence: 90%

“…Therefore, it is a typical feature of CRC, and glycolysis is more active than oxidative phosphorylation even under normoxic conditions. 31,32 That is, glucose uptake by cancer increases, and the glucose content in normal tissues decreases; this was confirmed by our previous analysis of CRC tissue samples 16 and other researchers. 33 Our present study revealed that urinary concentrations of glucose, glucuronic acid, and threonic acid were significantly higher in patients with CRC than in healthy controls (Figure 4).…”

Section: Upregulation Of Glycolysissupporting

confidence: 82%

“…However, due to the diversity of samples, inconsistency of instrumental analysis platforms, and incompleteness of research work, the current clinical application of metabolic biomarkers is not satisfactory. Using gas chromatography time‐of‐flight mass spectrometry (GC‐TOF/MS), we previously found that the contents of glycine, tyrosine, and hexadecanoic acid were significantly increased in the cancer tissue of CRC patients 16 . However, the tissue samples from the previous study were derived from only 20 patients undergoing CRC surgery.…”

Section: Introductionmentioning

confidence: 99%

“…Using gas chromatography time-of-flight mass spectrometry (GC-TOF/MS), we previously found that the contents of glycine, tyrosine, and hexadecanoic acid were significantly increased in the cancer tissue of CRC patients. 16 However, the tissue samples from the previous study were derived from only 20 patients undergoing CRC surgery. Therefore, to investigate the endogenous metabolic changes of patients with CRC more fully and to develop a non-invasive and convenient technical method for CRC screening in large-scale populations, here we completed the metabolomic analysis of urine samples from 163 patients with CRC.…”

mentioning

confidence: 99%

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Metabolic profiling analysis for clinical urine of colorectal cancer

Qiao

Zhang

et al. 2021

Asia-Pac J Clncl Oncology

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Aim:To demonstrate the little-known metabolic changes and pathways in patients with colorectal cancer (CRC). Methods:We used gas chromatography time-of-flight mass spectrometry (GC-TOF/MS) to perform metabolic profiling of urine samples from 163 consecutive patients with CRC and 111 healthy controls without history of gastrointestinal tumors. The metabolic profiles were assayed using multivariate statistical analysis and oneway analysis of variance, and further analyzed to identify potential marker metabolites related to CRC. The GC-TOF/MS-derived models showed clear discriminations in metabolic profiles between the CRC group and healthy control group. Results:We demonstrated that 15 metabolites contributed to the differences. Among them, eleven metabolites were significantly upregulated, while other four metabolites were downregulated in the urine samples of CRC patients compared with healthy controls. Pathway analysis revealed changes in energy metabolism of patients with CRC, which are reflected in the upregulation of glycolysis and amino acid metabolism and the downregulation of lipid metabolism. Our study revealed the metabolic profile of urine from CRC patients and indicated that GC-TOF/MS-based methods can distinguish CRC from healthy controls. Conclusion:GC-TOF/MS-based metabolomics has the potential to be developed into a novel, non-invasive, and painless clinical tool for CRC diagnosis, and may contribute to an improved understanding of disease mechanisms.

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Section: Upregulation Of Amino Acid Metabolismsupporting

confidence: 90%

Section: Upregulation Of Glycolysissupporting

confidence: 82%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Metabolic profiling analysis for clinical urine of colorectal cancer

Qiao

Zhang

et al. 2021

Asia-Pac J Clncl Oncology

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“…There are many reports describing dynamic reprogramming of metabolic pathways in CRC 12,13 . The protooncogene MYC regulates various metabolic pathways in CRC, including the glycolysis 14 and tryptophan pathways 15 .…”

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confidence: 99%

Urinary charged metabolite profiling of colorectal cancer using capillary electrophoresis-mass spectrometry

Udo

Katsumata

Kuwabara

et al. 2020

Sci Rep

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Colorectal cancer (CRC) has increasing global prevalence and poor prognostic outcomes, and the development of low- or less invasive screening tests is urgently required. Urine is an ideal biofluid that can be collected non-invasively and contains various metabolite biomarkers. To understand the metabolomic profiles of different stages of CRC, we conducted metabolomic profiling of urinary samples. Capillary electrophoresis-time-of-flight mass spectrometry was used to quantify hydrophilic metabolites in 247 subjects with stage 0 to IV CRC or polyps, and healthy controls. The 154 identified and quantified metabolites included metabolites of glycolysis, TCA cycle, amino acids, urea cycle, and polyamine pathways. The concentrations of these metabolites gradually increased with the stage, and samples of CRC stage IV especially showed a large difference compared to other stages. Polyps and CRC also showed different concentration patterns. We also assessed the differentiation ability of these metabolites. A multiple logistic regression model using three metabolites was developed with a randomly designated training dataset and validated using the remaining data to differentiate CRC and polys from healthy controls based on a panel of urinary metabolites. These data highlight the changes in metabolites from early to late stage of CRC and also the differences between CRC and polyps.

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Integration of metabolomic and transcriptomic profiles to identify biomarkers in serum of lung cancer

Sun

Zhao

Wang

et al. 2019

J of Cellular Biochemistry

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We used blood serum samples collected from 31 lung cancer (LC) patients and 29 healthy volunteers in this study. Levels of serum metabolites were qualitative quantified with gas chromatography-mass spectrometry (GC-MS), and the data were analyzed by partial least-squares discrimination analysis (PLS-DA). Based on the Kyoto Encyclopedia of Genes and Genomes database, we performed pathwaybased analysis utilizing metabolites presented at differential abundance between the LC serum samples and the normal healthy serum samples for systematical investigation on the metabolic alterations associated with LC pathogenesis. Finally, we analyzed the significantly enriched pathways as well as their relevant differentially expressed messenger RNAs, and drawn a correlation network plot to identify the serum metabolic biomarkers and the significantly altered metabolic pathways for LC. GC-MS analysis showed that 23 of the 169 metabolites identified were significantly different. PLS-DA model revealed that 13 of these metabolites were with variable importance > 1, and particularly five were with area under curve > 0.9. Pathway-based analysis demonstrated that five of eight enriched metabolic pathways were statistically significant with false discovery rate < 0.05. Lastly, the correlation networks between these pathways and their related genes suggested that 29 genes had correlation degree > 10, which were mainly engaged in the purine metabolism. In conclusion, we identified indole-3-lactate, erythritol, adenosine-5-phosphate, paracetamol and threitol as serum metabolic biomarkers for LC through metabolomics analysis. Besides, we identified the purine metabolism as the significantly altered metabolic pathway in LC with the help of transcriptomics analysis. K E Y W O R D S lung cancer, metabolomics, serum, transcriptomics | INTRODUCTIONTo date, lung cancer (LC) has become one of the most common cancer all over the world, with 1.8 million new cases of LC and 1.6 million deaths in 2012. 1 In spite of great efforts in early diagnosis of LC, it still remained the leading cause of cancer-related deaths in men and the second leading cause in women second to breast cancer. 1 Currently, common diagnostic approaches included chest radiograph, computed tomography scan, fiberoptic bronchoscopy, magnetic resonance imaging and positron emission tomography. 2 Unfortunately, these techniques hardly provide useful

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Identification of differential metabolic characteristics between tumor and normal tissue from colorectal cancer patients by gas chromatography–mass spectrometry

Cited by 7 publications

References 31 publications

Metabolic profiling analysis for clinical urine of colorectal cancer

Metabolic profiling analysis for clinical urine of colorectal cancer

Urinary charged metabolite profiling of colorectal cancer using capillary electrophoresis-mass spectrometry

Integration of metabolomic and transcriptomic profiles to identify biomarkers in serum of lung cancer

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